Table of contents The Macro Scale I: Processing for Granulation 1. High Shear Granulation (G.K. Reynolds et al .). 2. Fluidized Bed Spray Granulation (L. Morl et al .). 3. Extrusion-Spheronisation (D.I. Wilson, S.L. Rough). 4. Drum Granulation Processes (G.M. Walker). 5. Roll Pressing (P. Guigon et al .). 6. Dry Granulation (Kazuo Nishii, Masayuki Horio). 7. Coating and Encapsulation Processes in Powder Technology (Khashayar Saleh, P. Guigon). 8. Modelling of Pan-Coating Processes for Pharmaceutical Dosage Forms (Preetanshu Pandey et al .). 9. Granulation Equipment (M. Jacob). 10. Online Monitoring (Satoru Watano). 11. Process Systems Engineering Applied to Granulation (I.T. Cameron, F.Y. Wang). The Macro Scale II: Applications 12. Agglomeration of Enzymes, Micro-organisms and Flavours (G.M.H. Meesters). 13. Agglomeration of Dehydrated Consumer Foods (S. Palzer). 14. Detergent Granulation (R. Boerefijn et al .). 15. Granulation Process Control – Production of Pharmaceutical Granules: The Classical Batch Concept and the Problem of Scale-Up (H. Leuenberger, G. Betz). 16. Tabletting (K. Pitt, Csaba Sinka). 17. Direct Pelletization of Pharmaceutical Pellets in Fluid-Bed Processes (P. Kleinebudde, K. Knop). The Meso Scale: Mechanistic Description 18. Shear-Induced Dispersion of Particle Agglomerates (D.L. Feke). 19. Scale-Up of High-Shear Binder-Agglomeration Processes (P. Mort). 20. Granulation Rate Processes (K.P. Hapgood et al .). 21. Breakage in Granulation (A.D. Salman et al .). 22. Fluidisation of Cohesive Particles (J.P.K. Seville). 23. Multi-Level Computational Fluid Dynamics Models for the Description of Particle Mixing and Granulation in Fluidized Beds (M. van Sint Annaland et al .). 24. Population Balance Modelling of Granulation (T. Abberger). The Micro Scale: Granules and Smaller 25. Granule Structure (D. Barrera-Medrano et al .). 26. Morphology and Strength Development in Solid and Solidifying Interparticle Bridges in Granules of Pharmaceutical Powders (G.I. Tardos et al .). 27. Liquid Bridges in Granules (S.J.R. Simons). 28. Pendular Capillary Bridges (C.D. Willett et al .). 29. Sub-Granule Scale Modelling (F. Štěpánek).
CONTRIB U TORS
1 1 09 255, 1 3 1 7 1 1 89 705 1213 255 673 499 1 071 673 1213 815 979 255, 323 897 21 289 979, 1 1 89 897 41 7 1317 779 779 673 1 071 3 705 897 897 555 1213 21 853 3 289 591 377 21 735 3, 979, 1 1 89
Thomas Abberger Michael J. Adams Daniel Barrera-Medrano Gabriele Betz Dafni G. Bika Gururajan Bindhumadhavan Renee Boerefijn lan T. Cameron Niels G. Deen Prasanna-Rao Dontula Leon Farber Donald L. Feke lan Gabbott Pierre Guigon Karen P. Hapgood Stefan Heinrich Masayuki Horio Michael J. Hounslow Simon M. Iveson Michael Jacob Simon A. Johnson Peter Kleinebudde Klaus Knop Reinhard Kohlus Hans J.A.M. Kuipers Phung K. Le Hans Leuenberger James D. Litster Lian X. Liu Gabrie M.H. Meesters James N. Michaels Lothar Mörl Paul Mort Amol M. Nilpawar Kazuo Nishii Stefan Palzer Preetanshu Pandey Mirko Peglow Kendal Pitt Gavin K. Reynolds
ix
x
CONTRIBUTORS
Sarah L. Rough Khashayar Saleh Agba D. Salman Jonathan P.K. Seville Olivier Simon Stefaan J.R. Si mons Csaba Sinka Yongxin Song Frantisek Stepanek Hong Sing Tan Gabriel I. Tardos Richard Turton Martin van Sint Annaland Gavin M. Walker Fu Yang Wang Satoru Watano Christopher D. Willett D. lan Wilson
1 89 255, 323 979, 1 1 89 255, 1 041 , 1 3 1 7 255 1 257 735 377 1 353 979 1213 377 1 071 219 499 477 1 31 7 1 89
PREFACE Granulation as a proeess has been the subjeet of ever inereasing interest over the past deeade. We think this arises beeause it is at onee a powerful teehnique for produet engineering of solids and a very interesting topie for aeademie investigation. We have attempted in this Handbook to give emphasis to both of these perspeetives - the praetieal and the theoretieal. Our vision for understanding granulation refleets in many ways the classie Chemieal Engineering paradigm developed over 50 years aga for the deseription of ehemieal reaetors. We seek to understand behaviour at some small length seale - perhaps that of a granule, or even a primary particle within a granule, and then use that to deseribe the emergent behaviour of the proeess - perhaps some eolleetive properties of granules or some produet property of individual granules. In this way we would naturally seek to develop understanding at a sueeession of length seales - whieh we usually term miero for the granules, meso for ensembles of granules and maero for whole proeess behaviour. One ultimate goal would be to quantify the behaviour at the miero and meso seales in terms of rates laws, apply them in a eonservation statement and then produee a deseription of the maero behaviour. In this ultimate state, the present Handbook would be logieally arranged from miero to maero. Inspeetion of the Contents page reveals that we have not yet reaehed our ultimate state. Instead we do the very reverse starting from the broader view of proeesses and applieation before deseending to the meso level and finally the miere level of individual granule properties. It is our hope that the material in this Handbook will provide guidanee of immediate praetieal and theoretieal benefit and that some time in future it will have given some landmarks so that navigation of the reverse journey from miero to maero beeomes possible. The Editors are very grateful to the large number of eolleagues who have helped in the preparation of this Handbook. These include the authors - who as ean be seen, are from around the world - and the members of the Partiele Produets Group at the University of Sheffield who eontributed so mueh to the praetieal arrangements of this large joint effort. Finally, we would like to thank
xi
xii
PREFACE
Professor Gabriel Tardos of The City College of the City University of New York whose efforts were the genesis of this book. A.D. Salman and M.J. Hounslow University of Sheffield, UK J . PK Seville University of Birmingham, UK
CHAPTER 1 H i g h S hear G ranu lation Gavin K. Reynolds * , 1 Phung K. Le2 and Amol M . N i l pawar2
Pharmaceutical and Analytical Research and Oevelopment, AstraZeneca, Macciesfield, Cheshire, SK10 2NA, UK 20epartment Chemical and Process Engineering, University of Sheffield, Mappin Street, Sheffield, S 1 3JO, UK 1
Contents
1 . Introduction 2. Effect of parameters and operating conditions on granulation rates 2. 1 . Effect of operating conditions 2 . 1 . 1 . Effect of amount of binder added (liquid to solid ratio) 2 . 1 .2. Effect of method of binder addition 2 . 1 .3. Effect of agitation 2 . 1 .4. Process time 2.1 .5. Other operating conditions 2.2. Effect of feed material properties 2.2. 1 . Binder properties 2.2.2. Primary particle size 3. Powder motion in high shear mixers 3. 1 . Horizontal axis ploughshare mixers 3.2. Vertical axis high shear mixers References 1.
3 4 5 5 5 6 8 8 9 9 11 11 11 13 18
I NTRODUCTION
There are typically four main types of wet-agitated granulating equipments, clas sified by the way the material is agitated: drum granulators, pan granulators, fluidised-bed granulators and mixer granulators. Mixer granulators or high shear granulators have a wide range of applications in the pharmaceutical, agrochem ical and detergent industries. They have the following advantages over other granulators [1]: • • • •
they can process wet, sticky materials, they can spread viscous binders, they are less sensitive to operating conditions than tumbling granulators, and they can produce small «2 mm) high-density granules. *Corresponding author. E-mail:
[email protected] Granulation Edited by A.D. Sa/man, M.J. Houns/ow and J. P. K. Seville i 2007 Elsevier B.V. All rights reserved
4
Gavin K. Reynolds et al. Binding liquid through lance
+
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Binding liquid through spray
Liquid add
Whirling bed
·
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Impeller
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Fig. 1 . (a) Horizontal and (b) vertieal high-shear mixer granulators. Reprodueed with permission form 'Size Reduetion and Size Enlargement', Snow et al. Copyright © 1 997 MeGraw Hili [1].
High shear granulators in general fall into two c1asses, namely horizontal axis and vertical axis, and can be either continuously operated or batch operated. Typical configurations for horizontal- and vertical-axis batch high shear granula tors are shown in Fig. 1 . High shear granulators use an impeller to vigorously agitate the powder and produce high-density granules. They are commonly found in the pharmaceutical, agrochemical and detergent industries due to their ability to handle difficult feed formulations, including high viscosity binder fluids and fine cohesive powders. lmpellers rotate at high speed (between 1 00 and 1 500 rpm) on either a vertical or horizontal axis to create the agitation required for granulation. Typically, a seco ndary smaller impeller, called a chopper, is used. This rotates at much higher speeds (around 1 500 rpm). The role of the chopper in granulation is currently a matter of debate: it either fractures larger agglomerates or causes growth of smaller agglomerates, depending on the feed properties, operating conditions and the geometry of the mixer, impeller and chopper. Binder addition to high shear granulators can be in the form of a liquid spray or pouring. For melt gran ulation, binder can be added as a solid to a preheated high shear granulator.
2. EFFECT OF PARAMETERS AND OPERATI N G CONDITIONS O N GRANU LATION RATES
For many years and still to a certain extent currently, granulation design remains an essentially empirical process. In general, the majority of literature is concerned experimentally with the role of material properties and process conditions on the properties of the product granules. This section will present the role that a variety of material properties and operating conditions have been observed to play on the growth and properties of granules.
High Shear Granulation
5
2.1 . Effect of operating conditions
This section is concerned with the effects of process operating conditions in high shear granulators. Much of the wealth of literature concerning granulation con siders this area and as a result the experimental work encompasses a variety of types of equipments and different materials, depending upon the relative impor tance of these parameters to the industry on which they are focused. 2. 1. 1. Effect of amount of binder added (liquid to solid ratio)
Typically, granulation is induced by a liquid phase, and therefore a logical con sequence is that a larger amount of liquid results in a greater extent of gran ulation. An increased granulation rate is also observed when the liquid-solid ratio increases [2]. However if the liquid-solid ratio becomes too high, a phenomenon called overwetting may occur. In this case, granulation results in the formation of a paste [3]. Clearly this situation has to be avoided, because further processing (e.g. tableting) becomes difficult. The saturation of the granules, which can be defined as the ratio of liquid volume to granule-interstitial volume, increases when more liquid is added. A higher saturation is directly related to a larger average granule size [4,5] . Alternatively, if the saturation is too low no granule growth is observed. This implies that granules must exceed a critical saturation level in order to grow. This observation also explains the decreased period of no growth (consolidation) when the liquid content is increased, which was observed by Hoornaert et al. [6]. Owing to densification the porosity of the granules decreases resulting in an increase in saturation. If the saturation remains below the critical saturation no further growth will be observed. However, if the densification is sufficient to exceed this critical saturation growth will continue. This shift from no growth to growth will be observed at an earlier process time or higher liquid concentration. The particle size of the powder influences the effect of liquid con centration on granule growth. Keningley et al. [3] showed that the minimum amount of liquid needed for granulation increased when the size of the constit uent particles decreased. The same observation holds for the maximum amount of liquid that could be used for granulation. Fu et al. [7] presented the effect of the amount of liquid on product quality in terms of the size, binder content, porosity and appearance. In this work, the associated narrowing of the range of mecha nical properties for granules formed using an optimised procedure is exemplified by measurements of a number of parameters. 2. 1 . 2. Effect of method of binder addition
There are three main ways in which binder can be added to a high shear gran ulator: pouring, melting and spraying. The method of binder addition has been
6
Gavin K. Reynolds et 81.
found to greatly influence the properties of the resulting granular product. Holm et al. [8] found that liquid addition without atomisation gave rise to inhomoge neous liquid distribution (especially at low impeller and chopper speeds) and that atomisation of the binder led to better liquid distribution. Knight et al. [9] inves tigated all three binder-addition techniques. They found that where the binder was poured or sprayed on, the granule size distribution was initially bi modal and that the modal sizes were similar; at long granulation times the granule size distri butions were monomodel. However, the spray-on technique gave a lower pro portion of coarse granules and had a distinct tail of fine material in the granule size distribution at long times. The melt-in technique also produced a lower pro portion of coarse granules as compared with the pour-on technique, but the bimodal nature of the granule size distribution developed at long times. They conciude that, "the three methods of l iquid distribution differ in nature of the initial liquid distribution, but are fundamentally the same in that they all depend on prolonged mechanical mixing to give good uniform distribution". Knight and co workers also examined the effect of pouring on the compaction of the granules. They found that at short times, the coarse granules consist of three phases: air, liquid and solid. Also, the binder is not distributed evenly with granule size. This study is the first attempt to look at the properties of granules as a function of granule size and how these properties influence the granulation process. How ever, they did not investigate air or binder distribution with granule-size fraction for granules produced by other methods of binder addition. Another parameter confounded with the methods described above is the rate of liquid addition. Knight et al. [9] showed that the rate of liquid addition is also of importance. They observed a larger average granule size for the pour-on experiments compared to the spray-on experiments. If liquid was added very fast (i.e. pour-on) regions in the powder bed existed where the liquid concentration is high, resulting in over wetting. This led to the local formation of large granules or lumps, whereas a gradual liquid addition (i.e. spraying) led to a more uniform distribution of the binder. In this case the chance of over wetting was reduced, although the same amount of liquid was used. The general trend is that the faster the rate of addition of binder, the larger the granules become over time (e.g. Wauters et al. [1 0]). 2. 1 . 3. Effect of agitation
For a high-shear mixer, there are two ways of increasing the amount of energy input into the system, through the impeller and the chopper. The effect of both of these has been investigated. Schaefer et al. [1 1 ] found that the impeller speed produced no significant difference on the intra-granular porosity. Knight et al. [ 1 2] note that at high im peiler speeds, granule growth is limited by granule breakage. Kinget and Kemel [1 3] found that increasing the chopper speed mainly improves the homogeneity of the granulation due to the absence of fines. They do not
7
High Shear Granulation
define what is meant by homogeneity and so it is difficult to interpret what is meant; probably they are referring to the breadth of the granule size distribution. In contrast, using similar materials, Schaefer et al. [1 1 ] found that when the chopper was used the mean granule size was slightly smaller; there was no significant effect on the intra-granular porosity or the granule size distribution. Knight [2] found that the chopper aided in narrowing the granule size distribution, but the chopper was not used for the first 1 0 minof granulation and so no con clusions may be drawn about the influence of the chopper during nucleation. In addition to mixing the impeller and chopper are also responsible for the energy input in the process. The influence of the impeller and chopper speed therefore depends on how the granules respond to this energy input. If the in crease in impact energy results in more deformation of the granules, both the granule size and growth rate increase. Various authors reported this observation [2, 1 2 , 1 4]. Conversely, at high-energy inputs, where granule deformation leads to granule breakage, an increase in impeller speed leads to a decrease in granule size. This explains why sometimes a decrease in granule size is observed when the impeller speed is increased [4, 1 2, 1 5]. The influence of the energy input on granule growth was examined by Knight et al. [12]. Figure 2 indicates that for impeller speeds of 450 and 800 rpm, the growth rate is proportional with the energy input. The influence of the energy input on granule size is identical. At an impeller speed of 1 500 rpm the effect of the energy input is less pronounced. The authors argued that this was caused by an increased degree of breakage at this speed.
1.500
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15
20
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Fig. 2. Dependence of mean granule diameter on mixer energy input at impeller speeds of 450,800 and 1 500 rpm.The dashed line refers to a step change in the impeller speed from 800 to 1 500 rpm, resulting in a reduction in the granule mean diameter. Reproduced with permission. Copyright © 2000 Elsevier [ 1 2] .
8
Gavin K. Reynolds
et al.
2. 1.4. Process time
It would be expected that the general influence of a prolonged process time is increased granule size. Another influence of the process time is that the granule size distribution usually becomes narrower [9,1 2, 1 6]. However, it is not always the case that an increase in process time results in an increase in granule size. Hoornaert et al. [6] observed an initial period of no granule growth, sometimes followed by a rapid granule growth phase (Fig. 3). It was argued that during the no growth period granules become more densified (consolidation) due to the re peated impacts, while the saturation is still too low to cause granule growth. This period would last until the saturation is sufficient to promote granule coalescence. A logical consequence of the repeated impacts of the mixer arms on the granules is that the granules will densify. This densification occurs by the constituent particles within the granule becoming more closely packed, and hence reducing the interstitial volume. That is also the reason that usually a decrease in porosity is observed as a function of process time [9, 1 6, 1 7]. In particular during the initial time points the decrease in porosity is pronounced, whereas almost no change in porosity is observed at prolonged process times. 2. 1 . 5. Other operating conditions
Other operating conditions for high shear granulators can include temperature and mixer loading, Le., how much material is used for any one experiment. 1000 IlOO
i
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J
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700 600 SOG 400 300 200 100 0
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100
,
120
-17.8 wt,;. liquid -- 18.4 wt.� liquid --19.1 wt."4 liquid --19.8 wt.'lI. liquid -- 20.4 wt"4liquidl Fig. 3. Evolution of the mass-mean g ranule diameter for different amounts of binder (/1 3.9 M Pa.s for all experiments). ( 1 ) 1 7.8 wt% liquid (2) 1 8.4 wt% liquid, (3) 1 9. 1 wt% liquid, (4) 1 9.8 wt% liquid and (5) 20.4 wt% liquid. Reproduced with permission. Copyright © 1 998 Elsevier [6]. =
High Shear Granulation
9
Schaefer et al. [ 1 8] found that a decrease in the mixer load resulted in a sm aller mean granule size. They calculated the specific energy input as the time inte grated power consumption profiles normalised by the mass load, and found that the smallest granule size coincided with the largest specific energy input. They also state that the correct mixer load is crucial in obtaining a uniform and con trolled movement of mass in the mixer bowl. A low load will lead to a large amount of lumps and poor reproducibility. The effect of temperature is not discussed here as it serves to manipulate the properties of the feed materials (specifically binder viscosity). 2.2. Effect of feed material properties
Much of the granulation research work that has been carried out to date uses a variety of materials, making a generalised discussion on the relationship between feed material properties and granulation behaviour at best qualitative. However, despite this, trends have been found in the effect of feed material physical prop erties and granulation behaviour and may be of benefit if an operator or designer has some choice over the feed material properties. 2. 2. 1. Binder properties
Liquid binders exhibit a variety of properties that may affect the behaviour of the granulating system: •
• •
Viscosity. This will affect the viscous forces that can dominate in granule-gran ule interactions. This has been most widely studied as it is relatively easy to vary for a given system. Surface tension. This will affect the strength of the capillary forces. Contact angle. This will affect the wetting behaviour of the binder on the pow der. This has not been widely studied as it is difficult to change this property without changing the other properties of the material system.
Although listed separately here, surface tension and contact angle will not only depend on the binder but also on the solid phase in the system. 2.2. 1 . 1 . Binder viscosity
Schaefer and Mathiesen [ 1 9] granulated different molecular weight polyethylene glycols (pEGs) and two grades of lactose in an 8 1 high shear mixer using a melt-in technique. They found that the initial growth rate was lower for higher molecular weight PEGs but for that the subsequent growth rate was higher. They also found that lower weight PEGs gave rise to more spherical granules. Using a
10
Gavin K. Reynolds et al.
high-shear mixer, Hoornaert et al. [6] found that an increase in binder viscosity led to a larger extent of granulation in the nucleation and compaction regimes. The coalescence stage was characterised by faster growth. The time spent in each regime was also longer for higher viscosities. Overall, increased binder viscosity increased average granule size. However, the true value of the binder viscosity in the mixer could not be measured in their experiments as the binder partially dissolved some of the solid and the temperature rose over the course of the experiment, and hence the viscosity changes as weil. I n a drum granulator, Iveson and Utster [20] found that increase in binder viscosity de creased the rate at which intra-granular porosity decreases over the course of a batch granulation. Here, they pre-mixed the binder and powder to eliminate the effects of nucleation and achieve a uniform distribution of binder. However, for many granulating systems this pre-wetting cannot be used either the binder re acts with the powder (as in detergent manufacture) or because the binder so lidifies if the temperature decreases (e.g. in the production of pharmaceutical products where high molecular weight PEGs are used). This allows dissociation of nucleation from growth phenomena, but as nucleation affects the initial dis tribution of binder within the system, the pre-wetted powder would not be rep resentative of an industrial process. Johansen and SchCEfer [21 ] and Keningley et al. [3] showed that, depending on the primary particle size, a certain viscosity must be exceeded in order to obtain granule growth. When large primary particles were granulated with a low-viscosity binder, granule growth was limited. The work of Fu et al. [7] performed with different molecular weight PEGs showed that the critical viscosity to promote granule growth decreased with a decrease in primary particle size and that this observation was related to the granule strength. They explained that shear forces broke down weak granules that are obtained with a low viscosity binder and a large primary particle size. 2.2. 1 .2. Binder surface tension
Capes and Danckwerts [22] investigated the effect of binder surface tension in the drum granulation of sand. Due to the strength of the capillary bond in drum granulation, they found that there is a minimum surface tension necessary to granulate particles of a certain size. Iveson et al. [23] investigated the effect of binder surface tension on the dynamic yield strength of granules and found that decrease in the binder surface tension decreased the dynamic yield stress of granules. This result is expected from the analysis of Rumpf [24]. However, when they varied the surface tension of a more viscous binder, the binder viscosity dominated the yield-stress behaviour. Iveson et al. [23] further investigated the effect of the binder surface tension on the intra-granular porosity. They found that decrease in surface tension increase the minimum intra-granular porosity reached over the course of an experiment.
High Shear Granulation
11
2. 2. 2. Primary particle size
There is evidence to suggest that the primary particle size plays a role in de termining the amount of binder required for granulation. There is a general trend that more liquid is used when the primary particle size decreases. Schaefer et al. [1 8] also showed that less liquid is required to obtain an identical average granule size when a larger lactose size is used for granulation. The explanation that the liquid requirement is related to the primary particle size is as folIows. Granules are formed and increase in size due to the presence of liquid bridges between primary particles. More liquid is required to wet the primary particles when the size is smaller, since the surface area is larger. However, the liquid requirement is also influenced by other factors such as the porosity. As was stated earlier, the primary particle size also influences the critical viscosity that is needed to pro mote granule growth [3]. To prevent complete breakage, a higher binder viscosity is necessary when the primary particle size of the feed material is larger. 3. POWDER MOTION IN HIGH SHEAR MIXERS
Powder flow characteristics in high shear mixers are of paramount importance in understanding the mixing and collision frequency and magnitude between the powder, binder and subsequent granules. A number of studies have been made, qualitatively and quantitatively into these flow characteristics. This section will discuss measurement techniques and typical flow characteristics observed in horizontal axis and vertical axis mixer granulators, although specific flow char acteristics will inevitably vary with specific mixer geometry and material properties. Two principal techniques have been used to quantitatively measure bulk mo tion within high shear mixers, namely direct high speed optical imaging and pos itron emission particle tracking (PEPT). PEPT uses a single tracer particle that can be followed in time and space. The tracer particle is an artificial proton-rich isotope such as 1 8 F, 22 Na, 68 Ga and 64 CU. Such isotopes decay to produce a neutron, a positron and a neutrino. The emitted positron carries the energy of about 1 MeV and is annihilated in 1 ps by an inelastic collision with an electron in the surrounding medium. The collision produces two opposing collinear 'Y rays. Two detector plates placed at a specified separation detect the radiation. The direction of the y-ray emissions change rapidly and triangulation of two or more successive events enables the spatial location of the tracer to be determined. The time-averaged tracer position and velocity can be used to build up an impression of the bulk motion within the apparatus. 3.1 . Horizontal axis ploughshare mixers
Investigations into the motion of horizontal axis ploughshare mixers have been made typically using small-scale mixers. Forrest et al. [25] used PEPT to
12
Gavin K. Reynolds
et al.
Fig. 4. Radial sections of the granular bed in a ploughshare mixer: ( 1 ) 45-90°, base; (2) 90- 1 35°, bulk; (3) 1 35-1 80°, top; (4) 1 80-225°, free space. Reproduced with permission. Copyright © 2003 Elsevier [25].
investigate particle motion within 4- and 20-1 ploughshare mixers. The particles used were plate-shaped calcium hydroxy-phosphate of length 600 Jlm and width 1 00 Jlm for wet granulation and 600 Jlm resin beads for dry powder analysis. Figure 4 shows a radial cross section of a ploughshare mixer, with the different zones as defined by Forrest et al. [25]. For the case of wet granulation at a low ( 1 .3 Hz) and a high (2.5 Hz) blade speed a stationary zone of particles is observed, with some particles falling down from zone 4. The bl ade pushes particles through this stationary zone. For the case of dry particles, at a low impeller speed ( 1 Hz), the particles are pushed through the stationary zone, with little falling particles from zone 4. For a high impeller speed (2.25 Hz), there is no stationary zone, with many particles falling down from zone 4. They explain that the state of the particle bed is controlled by the ratio of the relaxation time of the system and the time between successive blades passes. If the ratio is less than one, the bed will come to rest and if it is greater than one, the bed will still be moving when the bl ade re-enters the bed. They also observed a low speed circulation zone where the material not carried by the blade falls down into the space created by the blade. Examining the axial profiles, they observed axial circulation zones caused by the co-operative action of the bl ades as each in turn enters the bed pushing material into the space created by the adjacent blade. Laurent et al. [26] performed PEPT experiments on a simplified horizontal axis mixer. Their apparatus consisted of a horizontal cylindrical shell stirred by a single long flate blade. A 600 Jlm radioactive resin tracer was used and had the same density as the powder. Figure 5 shows velocity fields for six different ranges of blade position. Figure 5(a) shows that as the blade enters into the particle bed a void is created behind the blade. Figures 5(b)-(d) show that as the blade passes through the bed, material is lifted and allowed to flow into the space between the bed surface and the agitator shaft. Figures 5(d) and (e) show a cascading flow
High Shear Granulation
�ection
����r-+----r
13 01 rotation
I- SQnm'sl d) 60•• 90°
b} 0° - 30°
e) 90° -120°
c) 30° - 60°
f) 180° - 210°
Fig. 5. Velocity fields i n cross-sectional view for six different blade positions i n a horizontal axis mixer with a level fill of 20% and a blade speed of 38 rpm. Reproduced with per mission. Copyr ight © 2000 AIChE [26].
pattern for the bed surface. When the blade is out of the bed, the free surface is left at angle of 1 5° to the horizontal, compared with the material angle of repose of 30°. 3.2. Vertical axis high shear mixers
Wellm [27] investigated the flow pattern in a 0.3 m diameter high shear mixer granulator using PEPT. The powder was found to be moving in the direction of the running blade with no exception. The powder was moving much slower than the blades, even near to the bl ades where the tip-speed was about 14.1 m/s. The velocities were calculated in a horizontal and a vertical plane. The particulate
14
Gavin K. Reynolds e t al.
mass was found to exhibit a toroidal vortex motion. The vortex motion was out ward in the lower regions of the mixer and inward in the upper regions, rising at the wall and falling near the axis of the mixer. These data were analysed with fast Fourier transform (FFT) that showed a peak at a frequency 0.9 S- 1 corresponding to a maximum tangential velocity of 0.85 m/s at the outer perimeter. With the FFT analysis it was found that the speed of the solids depends on blade speed and design, properties of the solids and level of fill. The tip speed and the speed of the powder had ratios as large as 1 00: 1 that became smaller with the smaller blade speed. For experiments done with a disc impeller at different speeds, the peaks for the horizontal motion were in an identical place. It was inferred that speed of the disc has no significant effect on the movement of the powder and so co efficient of friction is independent of the velocity difference between bl ade and powder. High-speed imaging has also been used to investigate particle motion within high shear mixers. Utster et al. [28] measured powder velocity in a 25 1 PMA Fielder mixer. The powder flow was filmed with a high-speed video camera at 500 frames/s. The camera was kept tilted at 45° centred on the spray zone. The flow pattern was measured for a batch of 6 kg dry lactose powder and wet lactose (approx. 6% moisture) at impeller speeds between 1 00 and 500 rpm. It was no ticed that the powder bed did not fluidize and its movement could be followed by using the natural bed structure, specifically lumps and cracks in the packed bed. The position of a lump of powder was followed over a number of frames and scalar velocity was calculated using image analysis. An average of all velocity results was used. They observed two distinct flow regimes. Firstly, 'bumping' flow in which the powder surface remains horizontal and the bed bumps up and down as the impeller passed underneath. Secondly 'roping' flow in which the powder from the bottom is forced up the vessel wall and then tumbles down towards the centre, similar to flow described as toroidal by Wellm [27]. The velocity in the bumping flow regime increased with increase in impeller speed, but was less sensitive to impeller speed in the roping flow regime (Fig. 6). A c1ear change in powder surface velocity was noticed in the transition from bumping to roping flow. Plank et al. [29] also used high-speed imaging to measure the surface velocity of powder beds in Aeromatic-Fielder high shear mixers of 25, 65 and 300 I vol umes fitted with plexiglass lids under numerous granulating conditions. Video clips were recorded for 5 s each. Only the tangential component of surface ve locity was calculated by tracking tangential movement of the powder frame-by frame. The frame of reference was established with the image of ruler positioned inside the mixer. The powder used contained a mixture of lactose monohydrate, microcrystalline cellulose, sucrose and pre-gelatinised starch with water used as a binder. Average surface velocity was measured as a function of impeller speed, amount of granulating liquid and fill ievel. Figure 7 shows their normalised powder surface velocity measurements. The surface velocities are normalised with
15
High Shear Granulation 1.2
�-------�--,
Bumping flow
Roping flow
1.0 Vl
l
Z. 0.8 ·0 o
�
� 0.6
�::::l
Oi 0.4 rJl
� [L
0.2 0.0 *'------,--r--"--j o 100 400 200 500 300
I mpeller speed ( rpm)
Fig. 6 . Powder surface velocities as a function of impeller speed for dry lactose i n a 25 1 vertical axis mixer. Reproduced with permission. Copyright © 2002 Elsevier [28].
:s
0.6
Z. .(3 o 0.5
---- 25 L
�
� äi 0.4 �
a.
-....
:s �
.g �
Q)
�
::::l (j)
0.3
t--I .. �
�300L
�t:::--
""'"
.....,
0.2 0.1 0.0 0.0
65 L
-+-
2.0
Lo
St, ndard/ Speed 4.0
�!-.
....
;....:> - 1.1 1
t
(a)
..' :
, .
o
50
.
.
100
.
.
.
�-'
.
250
300
350
I
Fig. 9. Powder surface velocity magnitude in the rotational frame for granules made from (a) PEG 400 and (b) glycerol binders. Reproduced with permission. Copyright © 2006 Elsevier [30].
18
Gavin K . Reynolds
et al.
In summary, high-speed imaging of high shear mixers is providing valuable information on the motion of the powder. In addition, changes to that motion can be observed due to changes in impeller speed and granule properties. In par ticular high-speed imaging coupled with PIV is able to obtain high-resolution velocity fields of the bed surface. The disadvantage to this technique is that only the powder surface can be interrogated, and at best the bulk motion within the bed can only be conjectured. PEPT provides an excellent means to interrogate the bulk motion within the bed, but it is difficult to obtain high-resolution data spatially and also the temporal averaging required makes tracking the changes in bulk motion during a granulation process very difficult. REFERENCES [1] RH. Snow, T. A llen, B.J. Ennis, J.D. Utster, Size Reduction and Size Enlargement, in: R H . P erry, D.W. Green (Eds.) , Perry's Chemical Engineers' Handbook, 1 997, McGraw-HiII, USA [2] P . C . Knight, Powder Techno! . 77 ( 1 993) 1 59-1 69. [3] S.T. Keningley, P.C. Knight, A . D. Marson, Powder Techno!. 9 1 ( 1 997) 95-1 03. [4] T. Schaefer, P. Holm, H .G . Kristensen, Drug Dev. Ind. P harm. 1 6 ( 1 990) 1 249-1277. [5] P . Holm, T. Schaefer, H .G . Kristensen, Powder Techno! . 43 ( 1 985) 2 1 3-223. [6] F. Hoornaert, P AL. Wauters, G . M . H . Meesters, S.E. P ratsinis, B. Scarlett, Powder Techno!. 96 ( 1 998) 1 1 6-1 28. [7] J.S. Fu, Y.S. Cheong, G . K. Reynolds, M.J. Adams, AD. Salman, M.J. Hounslow, Powder Techno!. 1 40 (2004) 209-2 1 6 . [8] P. Holm, O . Jungersen, T. Schaefer, H.G. Kristensen, Pharm. lnd. 46 ( 1 983) 97-1 0 1 . [9] P .C. Knight, T. Instone, J . M. K. Pearson, M.J. Hounslow, Powder Techno!. 97 ( 1 998) 246-257. [ 1 0] P A L . Wauters, R B . Jakobsen, J . D . Utster, G . M . H . Meesters, B. Scarlett, Powder Techno!. 1 23 (2002) 1 66-1 77. [1 1 ] T. Schaefer, B. Taagegaard, L.J. Thomsen, H . G . Kristensen, Eur. J. P harm. Sci . 1 ( 1 993) 1 33-1 4 1 . [ 1 2] P .C . Knight, A . Johansen, H .G . Kristensen, T. Schaefer, J . P. K. Seville, Powder Techno!. 1 1 0 (2000) 204-209. [ 1 3] R Kinget, R Kemel, Acta P harm. Techno!. 31 ( 1 985) 57-62. [ 1 4] H . Kokubo, H . Sunada, Chem. P harm. Bull. 44 ( 1 996) 1 546-1 549. [ 1 5] J . S . Ramaker, M. A lbada Jelgersma, P . Vonk, N .w.F. Kossen, I nt. J. P harm. 1 66 ( 1 998) 89-97. [ 1 6] T. Schaefer, C. Mathiesen, I nt. J. P harm . 1 39 ( 1 996) 1 39-1 48. [ 1 7] AC. Scott, M.J. Hounslow, T. Instone, Powder Techno!. 1 1 3 (2000) 205-21 3. [ 1 8] T. Schaefer, B. Taagegaard, L.J. Thomsen, H .G . Kristensen, Eur. J . Pharm. Sci. 1 ( 1 993) 1 25-1 3 1 . [ 1 9] T . Schaefer, C . Mathiesen, I nt. J . P harm. 1 39 ( 1 996) 1 25-1 38. [20] S . M . Iveson, J . D . Utster, Powder Techno!. 99 ( 1 998) 234-242. [21 ] A Johansen, T. Schaefer, Eur. J . P harm . Sci. 12 (2001 ) 297-309. [22] C . E . Capes, P .V. Danckwerts, Trans. Inst. Chem. Eng . 43 ( 1 965) T1 1 6-T1 24. [23] S.M. Iveson, J.D. Utster, B.J. Ennis, Powder Techno! . 99 ( 1 998) 243-250. [24] H. Rumpf, i n: W.A . Knepper, (Ed.), Agglomeration, A lM E , Interscience, New York, 1 962, pp. 379-4 1 8. [25] S. Forrest, J . Bridgwater, P . R Mort, J.D. Utster, D.J. Parker, Powder Techno!. 1 30 (2003) 9 1 -96.
High Shear Granulation
19
[26] B.F.C. Laurent, J. Bridgwater, D.J. Parker, AIChE J. 46 (2000) 1 723-1 734. [27] A.B. Wellm, University of Birmingham, Birmingham, U K , 1 997. [28] J . D. Litster, K.P. Hapgood, J . N . Michaels, A. Sims, M . Roberts, S . K. Kemeneni, Powder Techno!. 1 24 (2002) 272-280. [29] R. Plank, B. Diehl, H. Grinstead, J. Zega, Powder Techno! . 1 34 (2003) 223-234. [30] A.M. Nilpawar, G . K. Reynolds, A.D. Salman, M.J. Hounslow, Chem. Eng. Sei. 6 1 ( 1 3) (2006) 4 1 72-41 78.
CHAPTER 2 F l u i d ized Bed S p ray G ranu l at i on Lothar Mörl , a Stefan Heinricha. * and M i rko Peg lowb
81nstitute of Process Equipment and Environmental Technology, Otto-von-Guericke University Magdeburg, Universitätsplatz 2, 0-39106 Magdeburg, Germany blnstitute of Process Engineering, Otto-von-Guericke-University Magdeburg, Universitätsplatz 2, 0-39106 Magdeburg, Germany Contents 1 . Introduction 2. Pneumatic behaviour of fluidized beds 2. 1 . Introduction 2.2. Geldart classification 2.3. Operation area of the fluidized bed 2.3. 1 . Minimal fluidization velocity 2.3.2. Elutriation velocity 2.3.3. Porosity of the fluidized bed 2.3.4. Operation area of the fluidized bed 2.4. Height and pressure drop of the fluidized bed 2.5. Air distributor of the fluidized bed 2.5. 1 . Equilateral triangle partition 2.5.2. Square partition 2.5.3. P ressure drop of segmented perforated plates with different opening ratios 2.6. Fluidized bed channel apparatuses 2.6. 1 . Setting of a constant bed height by a weir 2.6.2. Setting of a constant bed pressure drop by regulation of the discharge equipment 2.6.3. Setting of a constant bed pressure drop by regulation of the gas throughput for fluidization 2.6.4. Setting of a constant bed pressure drop by regulation of a secondary gas throughput 2.6.5. Setting o f a constant bed pressure drop b y regulation of a heightadjustable weir 3. Solid surface area and g ranule growth 3. 1 . Continuous fluidized bed granulation with ideal classifying particle discharge 3.2. Continuous fluidized bed granulation with ideal c1assifying particle discharge and monodisperse nucleation 3.2. 1 . Granule growth 3.2.2. Total surface area of all particles
* Corresponding author. E-mail:
[email protected] Granulation Edited by A.D. Sa/man, M.J. Houns/ow and J. P. K. Sevi/le C 2007 Elsevier B.V. All riqhts reserved
23 24 24 25 26 26 29 33 34 36 40 44 45 45 46 47 49 50 51 51 53 53 59 59 59
22
4.
5. 6.
7.
L. Mörl
et al.
3.2.3. Size distribution in the fluidized bed 3.2.4. Residence time of the solid particles in the fluidized bed 3.3. Continuous fluidized bed g ranulation taking into account design parameters 3.4. Continuous f1uidized bed granulation with non-classifying particle discharge 3.5. Simplified modelling of the unsteady fluidized bed granulation 3.5. 1 . Batch process with increased bed mass 3.5.2. Semi-batch process with constant bed mass 3.6. Operation area of the fluidized bed granulation during unsteady process 3.6. 1 . Operation area of the batch process with increased bed mass 3.6.2. Operation area of the semi-batch process with constant bed mass Degree of wetting and heat and mass transfer 4. 1 . Modelling of the degree of wetting and of the transfer phenomena 4. 1 . 1 . Degree of wetting in the f1uidized bed 4 . 1 .2. Solid temperature in the f1uidized bed 4 . 1 .3. Heat and mass transfer between particles and gas f1uidized beds 4 . 1 .4. Example calculation 4.2. Influence of the mixing behaviour on the degree of wetting 4.2. 1 . Steady-state operation 4.2.2. Unsteady operation Fluidized bed granulation with superheated steam Fluidized bed spray g ranulation in closed or semi-closed systems 6. 1 . Closed systems with superheated solvent steam circulation 6.2. Closed systems with inert gas circulation 6.3. Sem i closed and self-inerting systems with gas recycle 6.4. Closed systems with heat pump 6.5. Closed systems with water vapour compression 6.6. Closed systems with rejected heat utilization for an u pstream evaporator 6.7. Concatenation of several closed systems Product examples of the university of magdeburg 7. 1 . Granulation of sticky products 7. 1 . 1 . Maize swell water 7.1 .2. Raw f1avour 7.1 .3. Cytosap 7.2. Granulation of paste-like products 7.2 . 1 . Calcium lactate 7.3. Granulation of microbiological producs 7.3. 1 . Fodder yeast 7.3.2. Rye starch 7.3.3. Lysine 7.3.4. Biosludge 7.4. Granulation of hard metals and magnets 7.4. 1 . Titanium carbides 7.4.2. Ferrite 7.5. Granulation of milk products 7.6. Granulation examples of chemical products
63 64 67 77 79 81 89 99 1 01 1 04 1 08 1 08 1 16 1 18 1 19 1 20 121 1 25 1 28 1 33 1 43 1 43 1 46 1 49 1 50 1 52 1 53 1 55 1 56 1 57 1 57 1 57 1 58 1 58 1 58 1 58 1 58 1 62 1 62 1 63 1 64 1 64 1 68 1 68 1 69
Fluidized Bed Spray Granulation 7.6. 1 . Potash 7.6.2. Activated carbon 7.6.3. Lead sulphate 7.7. Granulation of animal food 7.7. 1 . Sunflower protein 7.7.2. Swines blood 7.8. Granulation of fertilizers 7.8. 1 . Urea 7.8.2. Ammonium sulphate 7.9. Granulation of Glue sewage 8. Conclusions References
23 1 69 1 69 1 73 1 73 1 73 1 74 1 74 1 74 1 78 1 78 1 78 1 84
1 . I NTRODUCTION
Fluidized bed technology was founded in 1 922 by Winkler [1] for coal gasification, since that time the technology has been extended into many areas of applications that require different constructions of fluidized bed apparatus. Fluidized beds are used for physical processes like mixing, classifying, drying, coating, granulation, agglomeration, adsorption, pneumatic transport and heating and cooling of bulk solids. The plants for combustion, pyrolysis, gasification, gas cleaning, water pu rification, catalytic or gas-solid reactions belong to chemical fluidized bed proc esses. During the last years fluidized beds have been applied more commonly for the processes of environmental technology, for example adsorptive or absorptive gas cleaning or for the fluidization of immobilized micro-organisms in the liquid phase for the production of active substances in the cleaning of sewages. Fluidized-bed granulation in particular is very common, where atomizable liq uids (e.g. , suspensions, solutions, emulsions or melts) can be converted into free-flowing granular solids by integration of a number of processes like wetting, drying, size enlargement, shaping and homogenization or separation into a single step of the process chain by using high heat and mass transfer. This tailor-made particle design is used in a wide range of industries, including pharmaceutics, foodstuffs, fertilizers, detergents, mineral processing and specialty chemicals. Reviews on fluidized bed granulation are available in Refs. [2-6]. I n the literature, many attempts can be found to describe the particle forma tion in fluidized bed granulation in terms of population balances. Usually population balances describe the temporal change of particle property distribu tion. The influence of operating conditions on particle-size enlargement has been investigated by various authors [7,8] . For example, Watano [8] observed that the moisture content in solids is one of the most important particle prop erties to control the granulation process. For the authors interested in this re search [9-20] and especially for continuous granulation with high pro duct throughputs and possible self-sustained oscillations with external product
24
L. Mörl et al.
classification, much work is required for a complete understanding of the mech anisms involved. Alongside the granulometry and the pneumatics, the particle growth process is also strongly influenced by the thermal conditions in the flu idized bed. Our knowledge on the microprocesses of liquid injection, spreading, deposition and evaporation, as weil as the interactions with the gas-particle flow, is still limited. Nevertheless, some work was done to calculate the tem perature and humidity distributions in such liquid sprayed fluidized beds [1 5,21-24]. However, this article concerns the pneumatic behaviour, the particle growth, the heat and mass transfer as weil as different apparatus configurations regard ing the fluidized bed spray granulation by using simple analytical models. Gran ulation should be understood as layered growth of particles. Typical product examples explain the applicability of this technology for a broad range of particle processes. Using derived approximations, plant engineers are able to do rough calculations for a scale-up of the process.
2. PNEUMATIC BEHAVIOU R OF FLUIDIZED BEDS 2.1 . I ntroduction
Fluidization of granular solids (particles) occurs when the drag force exerted by the fluid (gas) on the particles exceeds the total weight of the particles. Above the minimal fluidization velocity the particles behave like a liquid, and the single solid particles start to move on stochastic streamlines. This state is characterized as fluidized bed. In particular the high heat, mass and impulse transfer in fluidized beds is offen used in a series of technical processes. It is weil known, that the heat transfer coefficient to a heating surface increases in a fluidized bed com pared with an empty tube by approximately an order of magnitude. Thus, a reduction of the dimensions of the fluidized bed apparatus is possible. Apart from the variety of fluidized beds for application in novel processes, a large number of fluidized bed apparatus designs are possible. From suit able literature searches it arises that the number of publications and patents for the area of the fluidized bed technology is already in 5-digit order of magnitude. It is no longer possible for a single expert to know all developments in this area. However, not all possibilities of the application of the fluidized bed technology are exhausted, and new applications are still arising. Morever, there is special interest in the area of fluidized bed spray granulation on which many quick developments have taken place during the last few years. Thus, from many application possibilities of the fluidized bed, this weil-chosen area is a subject of the present considerations. Therefore, the following executions refer primarily to this special application.
25
Fluidized Bed Spray Granulation
2.2. Geldart classification
In the literature, a huge number of works are available about the behaviour of disperse systems in the fluidization state, nevertheless, even today it can not be said for many complicated processes which appear with the fluidization of solid systems that they are fully understood. In particular the gas bubbles appearing in gas-solid systems provide a good mixing of the fluidized bed, but lead to un desired bypass currents of the fluidization gases, are still not accessible for an exact calculation. However, there is a huge experience with the application of the fluidized bed in the different areas that has resulted in a large number of phys ically reasonable, semi-empirical or empirical calculation methods. Such ar rangements allow the interpretation with sufficient exactness for technical purposes. Geldart [25] determined the fluidization properties of various particles through numerous experiments and classified them according to their density and diameter. He determined four groups of particles, which are described from smallest to largest particle as follows (Fig. 1 ): •
Group C (cohesive powders)
These particles are typically less than 50 )lm and are very difficult to fluidize because the interparticle adhesive forces are stronger than those, which the fluid can exert on the particle (drag force). These particles will tend to rise as a plug of solids in small-diameter beds and will not fluidize in larger diameter beds. To support the fluidization one can use mechanical stirrers, or vibration of the apparatus and pulsation of the gas, respectively. 10000
-
E Ob =. '0 a.
;;-'
§ ., u 2 1 03 from Kaskas [35] 4 2 24 4 (26) Ar = - ReeIU - + � + 0.4 Reelu v Ree1u 3 From the literature a series of other criteria are known for the Reynolds number at the elutriation point as function of the Archimedes number, from which because of its simplicity and because of its validity for all areas the following is given according to Gorosko et al. [32]
for 0.1
--" 0.9 ;;
_ _ _ _ _ _ _ _ _ _ _
,
-- - - - - - - - - - - - � - - - - - - - - - - - , - - - - - - - - - - - � - - - - - - - - - - - -
I
I
I
I
0.8
0.7
- - - - - - - - - - - � - - - - - - - - - - - -I - - - - - - - - - - - - � - - - - - - - - - - ,
,
,
,
,
0.6 +------r--�--+_--_r--� 250 300 150 200 1 00 o 50 gas ternperature [0C]
Fig. 9. Relationship of the minimal fluidization velocity at a certain temperature and at 20°C as a function of the gas temperature by variation of the particle diameter (fluidization with air at 20°C and P = 1 bar, Ps = 2500 kgjm3) .
...... Richardson and Zaki
0.9
-0-
Gorosko el al.
0.8
"0
I
I ,
_ _ _ _ _ _ _ _ L _ _ _ _ _ _ _ _ I_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
- -r -
------
-r - - - - - - - -1- I
,
---
-
-
-
-,- - - - - - - I
.. ,
------
-
�_
,
_ _ _ _ _ _ _
�
_ _ _ _ _ _ _ _
,- - - - - - - - , - - - - - - - ,
-1--=::+==+====-+----t---f-.---f.--1 o
2
3
4
5
6
7
8
gas velocity [rn/s1
Fig. 1 0. Comparison of the equations of Richardson and Zaki [37] and Gorosko et al. [32].
36
L. Mörl et al.
i--;---;---:--;-;--:I:====l ,, , I • _ _ _ ______ _ _ _ _ _ _ _____ _ _ _ _ _ _ _ _ _ _ _ _ ____ _ __ _ _ _ _ _ _ _ _ _ _ _ _ _, ____ _ 0.1 ,, , I I , , , , , , , 0.08 ,, , I , I I I , , , , 0. 1 2
�
L
I
J
L I
I
J
I I ' 1 - - - - - , - - - - - - j - - - - - , - - - - - - j - - - - - , - - - - - - r -
�
,
" '" Q:;
-..
�
I I
I I
I
I
I
J
L
- - - , - - - - - - r - - - - - ' - - - - - - r - - - - -
I I
I
I
J
_ _ _ _ _ J _ _ _ _ _ _ L _ _ _ _ _ J _ _ _ _ _ _ L _ _ _ _ _ J _ _ _ _ _ L _ _ _ _ _ J _ _ _ _ _ _ IL _ _ _ _ _ J, _ _ _ _ _ _ IL _ _ _ _ _ ,
0.06
L
L I
___
0.04
L..I
,
I I
I I
e
"
e ti_ a rea On _ -,_-.J -, _
ra lar g_o p_ _ _
,
� �1
,
,
�
I
,
,
I
I
,I
I
I I - - - - - - r - - - - - ' - - - - - - r - - - - - ' - - - - - - r - - - - -
�
a �
a
----'lu
ea ar ion er top_ 1I _ Sm _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ L-_ � �
0.02
"
,
O +---�--�----r---�--_r--r_� 0.1
10
100
1 000
10000 1 00000 100000 I E+07
Ar
[-]
I E+08
I E+09
I E+ I O
Fig. 1 1 . Representation of the operation area of the fluidized bed by the relationship as a function of the Archimedes number.
fmax
The operation area of the fluidized bed can also be shown with the relative voidage as a parameter with direct dependence of the Archimedes number on the Reynolds number as shown in Fig. 1 2. The representations above are valid for monodisperse particle mixtures. In practice this case does not seem practical and for all particle mixtures with wide size distribution it must be taken into consideration that the sm all solid particles may not be elutriated, while the big particles should still be fluidized and may not remain Iying on the air distributor. In addition, their density must also be taken into consideration as another particle property. For such a case it is suitable to cal culate the minimal fluidization velocity and the elutriation velocity, in each case for smallest and the biggest particles present in the particle mixture. Figure 1 3 shows for an example (wooden particles and sand particles in each case with a minimal diameter of 1 mm and a maximal diameter of 3 mm ) , the dependency of minimal fluidization and elutriation velocities for a particle mixture with light small and large heavy particles. The operation area of such a fluidized bed is between the minimal fluidization velocity of the smalI, light particles and the elutriation velocity of the large, heavy particles. In this case it is possible to reach a stable fluidized bed for the entire particle spectrum. 2.4. Height and pressure d rop of the fluidized bed
The height of the fluidized bed determines the pressure drop that the gas suffers while flowing through the bed. The expansion behaviour of the bed is usually calculated with empirical correlations. In general, between the superficial velocity
Fluidized Bed Spray Granulation
37
l . E+ I O
I .E+09 I .E+08
,
,
,
"
I " , I 1 1
!
_ _ _ _ _ _ _ L _ _ _ a _ _ a _ � _ � _ L I , , I I I ' I I I I , I - - - - - -T r T r ' '
,
I
'
I
, I
I I
I
I
J � � _ _ _ _ _ _ _' _ _ _ _ L _ _ � _ L _ L � _ L L J _ _ _ _ _ _ � _ _ _ � _ _ � _
I
I I I I I
I , I I I
I ' I I I r I
I I I I I I I t I ' I I I I - -r l �' � - r -r ' -r r T - - - - I I I I I I I I "
I
' '
I
I
I
1
1
I
I
I
I
I
, , ,
I .E+07 I .E+06
�
, �
I .E+05 l .E+04 I .E+03 I .E+02
I .E+O I l . E+OO
I , t - - - - - - I r -- -T
I
I
- --
+-
-- -
I I I I I I I I I I I I I I I I - Ir I 1 1 - - - - - - - - - - - r t I - - i - � - - - I I
I I
, .. - - - -+" - - • - ...
I I
�
I I
I
I
__
10
I ' I 1 1 I I I 1 1
I ,
,
1
1
I
I
I I
I I
I I
... - � ... -'4 - - - - - - - ,- - - - '"" - - - - .. - .... ... -I- .. 1- -
���:�� : :�_L ' '� ' I
__ __ __
-
I , I I I r - r � -r r i
1 ��
1
,
t
,
l
I
1 1
I
�
__ __ __
100
�� I
__
I
-t:r-
=0.6
--0-
=0. 8
I I
I
I
I
I I I I ,
I I - _ 1_ ..... _ j,. ..... _1_
-D- E =0.4
I
I
I " I I I
- -,- -, - i "i -,-
I I I I , - -1- -1 - ... .... -1 -
��_L��========������� I
I
I
I
I
I
--
= 1 .0
__
1 000
1 0000
Re [-] Fig.
12. Operation area of the fluidized bed as dependency Ar = f(Re).
10 -0- minimal
9 -tr-
tluidization velocity of small and light partic1es
minimal tluidization velocity of large and heavy particles
� elutriation
8
�
7
- -� - - - - - - - � - - - - - - - - - -
velocity of small and light particles
elutriation velocity of large and heavy particles
00
�
6
0 ·ü 5 0 �
I
;> '"
co bl)
I I , t I - - - - - y - - - - - - - -r - - - - - - - T - - - - - - - - - - - - - - - - T - - - - - - - - - I
4 3 2
o
I
( I - - - - -� - - - - - - - T - - - - - - - - - - - - - - - - T - - - - - - - - - I ,
,
,
- -, - - - - - - - j - - - - - - - - - -
- � -------� � ---- � - � -- g - -tt:--� operation area
of the fluidized bed
-
o
�
0.5
:
- - - - - - - _ -
-
1 .5
,
,
- -r - - - - - - - T - - - - - - - - - -
- - - - - -r
2
2.5
3
-
-- -- �
-
3.5
- - - - - -
4
partic1e diameter [mm]
1 3. Operation area of a fluidized bed with a particle mixture of light-small particles (wood spheres with a diameter of 1 mm) and large-heavy particles (sand spheres with a diameter of 3 mm) with air at room temperature as f1uidization medium. Fig.
38
L. Mörl et 81.
VG = Veff the corresponding bed height Hbed and bed porosity s and the same quantities at the minimal fluidization point exists an relationship - Smf Hbed Hbed.mf With this the dependence of the bed height at any operating velocities vG can be calculated
1
(35)
1 -S
(36) with
(37)
or
Hbed (Ar, Re) = Hbed,mf
1-C
Smf 8Re+2/6Re2 ) 0.21
1-
(38)
The dimensionless bed height Hbed can be written as (Re, Ar) L.ft (Ar, Re Hbed nbed Hbed,mf or Smf Hbed (Ar, Re) = Hbed,mf 0 21 - 8Re+2;36Re2 ) . C With this representation it must be pointed out to the fact that the dimenionless bed height is valid only in the operation area of the fluidized bed from = to In Fig. the dimensionless bed height is shown as a function of the Reynolds number with the Archimedes number as a parameter. It is recognizable that the dimensionless bed height rises to a non-finite value for certain values of Reynolds number. Then, these are the Reynolds numbers with a void fraction of related to the corresponding elutriation velocity. The pressure drop of a fixed bed increases with the gas velocity up to the minimal fluidization point. The pressure drop at this point can be given with as follows ( IX =
)
(39)
_
_
1-
1
1.0.
(40)
S 0.4
14
1,
38°):
[27]
(1 - s) 1 [ 150 (1 - S) + 1.75] S
d �Pbed = HbedPG VG --- 2 3 p Re cos IXst With further increase of the gas velocity after the minimal fluidization velocity has reached, the bed pressure drop of a monodiperse particle bed remains con stant. However, it is only valid for an open and non-limited bed height (Fig. If the fluidized bed has a weir as shown in Fig. the bed height can grow only up to limited height corresponding to the height of the weir. With further increase in .2
16,
(41)
15).
39
Fluidized Bed Spray Granulation
16 TT---'�----�---' 14
I . I -�--- - - - � - - - :- - - - - - - - � - - � , , .. , , : 1 - - - - t - - - :- - - - - - - - -: - : - - - - - - - � - - - - -
12
..: 01) 'ä}
,g
.c:: '0
I •
I
- - - • < •
_ _ _ _
c:
2
-
Ar = I000
- -
- - -
Ar = 10000
, , , ,
, ,
_ _ _ _ _ _ _ _ _ _ _ _ ..J _ _ _
: Ar = 100000 , : - - - -:. r - - - - - . - � - . - - - -- Ar = 1 000000 I I . I I I ' , .: , I I " I 1_ - - - - - - - - -I ': --------, -----I I I I, I I I , , , , I I ,IJ I I II I - - - 1 - - - -:- - - - - - - - -:�: - - - - - - - - - � - - - - - - - - - r - - - - - - - - - � - - - - - - - - - :- - - - - - - -: - I , I I I I : : : : I ;" : :I I , I I I -� --------�---------�---_ _: _ _ -1 _ _ _ _ _ : _ _ _ _ _ _ I •
8
4
•
-
I
.�c: 6 CI)
a '6
I
-
10
'" '" � '"
, '
.
•
I - : I I
1
•
I I I
•
- . - - - - •
- -1-
I - - - - - - - -i -
11
. - - - - - - - - - �
I
I
- - - - - - - - 1-
I
-
I
•
I
•
•
I
/� I' _ _
I
_
_ _ _ _ _ _ _ _
.J'.
I
_
'
,
� _" _'_" _ _ _ _ _ _ _','_ _ _ _ _ _ _ _ _ -: _ _ : I
_ _ _ _ _ �, _ ,. � _ '
-
I
I
_
-
I
-
_
_ _ _
I --------�---� - - - - - - - - - I� - - - - - - - - -II I :
: I
0 +------+--4--�--+_� 1400 1 200 800 1 000 200 600 400 o Re [-)
Fig. 14. Dimensionless bed height as a function of the Reynolds number by variation of the Archimedes number.
Fig. 1 5.
Bed behaviour with unlimited bed height.
the gas velocity solid particles are discharged over the weir, the relative voidage increases further and thus, the bed pressure drop decreases up to a value of zero until the elutriation velocity is reached. The bed behaviour is shown as an example in Figs. 1 7 and 1 8 for an unlimited bed height. In Fig. 1 7 the bed pressure drop and the bed height are illustrated as a function of the gas velocity for a fluidized bed with an unlimited bed height and Fig. 1 8 plots the bed porosity as function of the gas velocity.
40
L Mörl et al.
�1
'"";:: E >
t
J
Va,3 > Va.2 > Vmf
Fig.
1 6. Bed behaviour with limited bed height
If the fluidized bed is limited by its height by using a weir as is the case with most fluidized bed channels (horizontal fluidized beds), it extends after reaching the minimal fluidization velocity, firstly in the same way as the bed with unlimited height. This process goes on until the bed height is equal to the weir height. With further increase of the gas velocity solid particles are discharged over the weir, and the mass of the particles in the fluidized bed decreases, while the bed po rosity is increased. This process continues until the elutriation velocity is reached with which the bed pressure drop reaches the value of zero. In this limiting case only few particles are in the bed. As an example the dependency of bed pressure drop and bed height from the gas velocity is shown in Fig. 1 9 and Fig, il lustrates the dependency of bed porosity and bed mass from the gas velocity.
20
2.5. Air d istributor of the fl uidized bed
The air distributor of a fluidized bed strongly determines the functional behaviour of the bed. In particular with fluidized beds of large dimensions and with fluidized
41
Fluidized Bed Spray Granulation 15
3500 , - - - - - t - - - - - - - � - - - - - - -
3000
� 2500 e:.
_ _ _ _ _ _ _
0-
e "0 2000
� a '" 1 500 �
0"0 ., �
0
,
_ _ _ _ _ _ _
__ . _ _ __ I
_ _
- -
_ 1 I I
_
_
, ,
;
_ _ _
bed pressure drop bed height
---
I
_ _ _ _
_, __ .&..
, ,
_ _ _ _ _ .1 _ _ _ _ _
I
I
1
.!
_ _ _ .1 _ _ _ _ _ _ _ .1 _ _ _ _ _ _ _ . . _ _ _ _ _ _ _ !.. _ _ _ _ _ _ _ 1. _ _ _ _ _ _ _ _ _ _ _ I t I I I I I I
,
I
----
1000 500
:
, ,
- - - - - - - r - - - - - - - � - - - - -
,
I
I
I
I
I
, , ,
I
_ _ _ _ _ L _ _ _ _ _ _ _ � _ '
I
_
I
,
I
I
,
,
_
I
6
3
2
4
"E � ..c
I
_ _ _ _ � _ _ _ _ _ _ _ I
gas velocity [mls]
� ·0
- - ---
3
.-
��'�±=�==i'==1'��-J--J o
I Oll
---
I
I , I I I r - - - - - - I- - - - - - - - r - - - - - - - T - - - - - - - � -
_ _ _ _ _ � _ _ _ _ _ _ _ _ _ _ _ I
9
_ _
I
I
I
I
,
12
_
I
- - - r - - - - - - - 1 - - - - - - - , - - - - - - - -� - - - - - - - r - - - - - - - r - - - - - - - T - - I I I I - - - - r - - - - - - - , - - - - - - - � -
-
7
6
5
8
0
Fig. 1 7 . Dependency of the bed height and of the bed pressure drop from the gas veloci � with unlimited bed height (Aapp 1 m2 , = 300 kg , dp 2 mm , Ps = 1 500 kg/m , 9G = 20°C).
A4ed
=
€ �
0.8
0. 6
e
� .., o
.0
0.4
=
_
I I I I I I
- - - - - - - -
Fig.
I I I I I I
I I I I I I
�
- - - - - - - - -
�
- - - - - - - -
I I I I I I I I I I - - - - - - - - ,I - - - - - - - - - Ir - - - - - - - I I I I I I I I I I I I
I I I I I I
- - - - -� - - - - - - - - � - - - - - -
0
I I I I
_ _ _ _ _ _ _ _ �_ _ _ _ _ _ _ _ _ L _ _ _ _ _ _ _ _
I I I I I - - - - - _ 1_ - - _ _ _ _ _ _ 1 _ _ _ _ _ I I I I I I I I I I I I I I - - - - - - - -� - - - - - - - - t - - - - - - - -
.l- ----"
I I
-� - - - - - -
�
- - - - - - - - - � - - -- - - - -
I I I I I I I I I I I-I -1 ----+ 1 ----+-----4 ---� ----�------� --
�---�-o
I I I I I
I I I I I
2
3
4
gas velocity [mls]
5
6
7
8
1 8. De�endency of the bed porosity from the gas velocity with unlimited bed height 1m , = 300 kg, dp = 2 mm , Ps 1 500 kg/m 3 , 9G = 20°C).
(Aapp
=
A4ed
=
bed channels, the right construction of the distributor is very important. The sim plest (and often sufficient) constructions are perforated plates (sieve plates). The pressure drop of perforated plates can be calculated according to Hunt et al. [39] and McAllister et al. [40]. There are a series of other distributor designs, for example jet plates, CONIDUR@ plates that provide a directional airflow and bubble trays. The application of gas distributors with different opening ratios
42
L. Mörl
et 81.
3000 i--;::::;:====::;::==r----;---;---:---, 0.7 0.6 2500 0.5 ..:... 2000 ! 0.4 -:::6': � 1500 0.3 ; - bed pressure drop ]0. 1000 0.2 bedheight : � 500 � 0.1 , - - , - - - - - - - - r - - - - - - - " - - - - - - - -� - - - - - - -
, ,
, ,
• I I - - - - - - - - r - - - - - - - T - - - - - - - ,- - - - - - - - r
� �
I
,
I
, ,
-
,
_____
_ _ - - - - - -
_ - - - - - -
�
',;
I
- - - r - - - - - - -
-
..c: Oll
I - - - - - - , - - - - - - - -r - - - - - - -
�
- - - - - - - - - _ - - - - - -
- - - - - - -
, , ,
,
'" .0
- - - - - - - -r - - - - - - -
�
,
- - - - - _ _
I
O �--�r---�----_r--�--+--_+ O 0
2
3
4
gas velocity [m/s]
5
6
7
8
1 9. Dependency of the bed height and of the bed pressure drop from the gas velocity 2 limited bed height (Hweir 0.6 m, Aapp = 1 m , 300 kg, dp = 2 mm, 3 Ps = 1 500 kg/m , 9G 20°C). Fig.
with
A4ed
=
=
0.8 - - - - - - � - - - - - - -� � 0.6 :: ]R 0.4 + - ...-
(ddPp,out)3 MMp
P,out
,
59
Fluidized Bed Spray Granulation
3.2. Contin uous fluidized bed g ranulation with ideal classifying particle discharge and monodisperse n ucleation
In some eases (e. g . granulation of inorganie praduets) the internal formation of nuclei in the fluidized bed due to attritio n, spray dried liquid droplets (the so ealled overspray) or breakage of particles (see assumption 6) is not negligible. Henee, the following seetion derives an analytieal model for this formation of internal granules (nueleation) in the fluidized bed taking into aeeount the assumptions 1-5 and 7-9 of Seetion 3 . 1 [43]. 3. 2. 1. Granule growth
Aeeording to equations (62) and (64) the following expression is valid i n general terms for the volumetrie inerease of a particle in the fluidized bed (where y is the fraetion of the solid that is deposited onto the sphere) d �p = �6 [Cdp + d dp)3 cß.p] ML(1l:-Apx)ypsndp dt (96) With equation (66), a linear differential inerease of the di ameter of the granules with time is found x) dt d dp = 2ML(1 (97) p l: A ps Two separate eases must be eonsidered: Particles whieh arise fram the monodi sperse feed nuclei flowrate Mp , Particles whieh arise fram the newly-formed nuclei with the mass flow Md 1 x) .
_
2
=
-
•
•
(1 -y) .
-
If dp,Q is the diameter of the feed nuclei at the time of their addition, and dP,nuc is the diameter of the newly formed nuclei at the tim e of their orig in, then the dia meters, surfaee areas, and vol u mes ofthe granules (Table 1 ) ean be obtained as a funetion of the time fram equation (97). 3. 2. 2. Total surfaee area of all partieles
In equations (98-1 03), the total surfaee area of all granules is stil unknown, but ean be determined with equation (71 ) , whereby the total number of all particles in the fluidized bed is eomputable with (85). Thus, it is finally found that ( 1 04)
Cl o
Table 1 . Granule g rowth under consideration of monodisperse nucleation
Diameter
Feed nuclei
ML(1 - x)y 2 t d (t) = dP O + p
,
(98)
" L.. A P Ps
Surface area of a partic\e Volume of a partieie
\I,fed (f)
=� 6
[
]
(100)
ML(1 - x)y 3 2 t (102) dP,O + I: App s
Newly-formed nuc\ei M 2 L(1 - x)y t dnuc ( f) = dnuc + " A P Ps A nuc(f)
L..
(99)
]2 ] (103)
- X)y t = n: dnuc + 2ML(1 (101) I: A pPS
[ [
.
2ML(1 - X)y
t Vnuc (t) = 6 dnuc + I: A p ps n:
.
3
61
Fluidized Bed Spray Granulation
The mean surfaee area and the mean vol u me per particle for the two types of particles are as folIows: -
-
-
-
Ap Afednfed ++ Anucnnuc nfed nnuc V + Vnucnnuc Vp = fednfed nfed + nnuc
(1 05)
=
( 1 06 )
The assumption that all the solid particles leave the apparatus exaetly when they have reaehed the dia meter dp t gives the expressions for Ap and Vp for the two types of particles (Table 2). The residenee times of the solid partieles are then readily found fram equations (98) and (99) for the feed and newly-formed nuclei ,ou
� dp,o) L A pps t�ed = (dp,out2ML(1 - x)y
(1 1 1)
-:- dnuc) L Apps t�UC (dp,out2ML(1 - x)y
(1 1 2)
=
When equations ( 1 00-1 03) are introdueed, and allowanee is made for equation (1 07-1 1 0) , it follows fram equati o n (1 1 1-1 1 2) that Tabl e 3 ean be shown. The total number of nuclei i n the fluidized bed ean readily be obtained from the two fluxes of nuclei and the residenee time of a particle (Table 4). The mean surfaee area and the mean volume of a particle in the fluidized bed ean now be determined fram equations (1 05-1 1 0) together with equation (1 1 8) and equation ( 1 20). (1 2 1 ) Table 2. Integrals
Mean surfaee area of a particle Mean volume of a particle
Feed nuclei
1 A fed = f"" tved Jor v A fed (t)dt tled
Newly-formed nucl ei uc _
(1 08)
(1 07)
Vfed t Jor v Vfed (t)dt v 1
=
tled
ted
(1 09)
r�
A nuc = t�1UC Jo A nuc(t)dt V
nuc tv Jor v Vnuc(t)dt 1 = nuc
tnuc
(1 1 0)
62
L. Mörl et al.
Table 3. Solution of the integrals
Mean surface area of a particle
A-fed -
Mean volume of a particle
(
) ,0 )
Feed nuclei - �3
_
n Vfed = 24
)
d A- nuc - � �,out - �uc 3 dp,out - dnuc ( 1 1 4)
ifp,out - ifp,o dp,out - dp,o (1 1 3)
('
(
Newly-formed nuclei _
cfp out - cfp dp,out - dp,o (1 1 5)
v: - nuc
_
(
� cfp,out - �uc
- 24
)
dp,out - dnuc ( 1 1 6)
Table 4. Number of nuciei in the fluidized bed
Feed nuclei
nfed
fed ,tCi;ed
= 3n·
( 1 1 7)
Newly-formed nuclei nnuc
_
-
( 1 1 9)
3 (dp,out - dnuc) ( 1 - Y) ( 1 20) 3 n dnucY
( 1 22)
Hence, and with equation (1 04) the total surface area of all particles in the flu idized bed can be calculated. ( 1 23)
It should be noted at this point that another constrai nt on the quantities .o , dnuc and dp,oul stil exists, so that only two of these quantities can be freely seldpected at a given feed rate of nuclei and a given liquid flow rate. This gives ( 1 24)
63
Fluidized Bed Spray Granulation
-1 �jnLnn
60 .-----�--�----.--_.
� g
50
6.5
- - - - - - -.'� -. ,,: ... "f : : � .' , ,, , �, .,
_ _ 0
'" u
� 3 '" 40
�
'"
,
ü
.�0.. B
;.
.-
öl 30
7
- -
, , ' f ..
- - - - - - -
,,
...
-
-
- - - - - - -
6 - - -
5.5
5
- - - - - - -
4 4
I.... *
a .5 :a ti dpout - , t
.
71
Fluidized Bed Spray Granulation
,
10 8 --------------
,, �,
_ _ _ _ _ _ _ _ _ _ _ J. _
- - - - - - t- -
�
- - - - - - - - -
- - - - - -
-f:r-0O �======�==���--��� 4
- - - - - - - - - - - - - - - - - - - -
-0-
2
vG = 7.62 mls vG = 6.74
- -
vp = 0. 1 4 m/s
-t
m/s -t
vG = 6.08 m/s
vp = 0.087 mls vp = 0.026 mls
-t
0. 1
Fig. 37. Experimental results of Jännert [46] for the fictive particle velocity at a fluidized bed plant with Dapp 0.4 m and Dsep 0.07 m. =
=
and solution of the integral
-,
n p in n p �dp.ou'
- '- =
np t ) exp (- --np�dp.ou'
(1 56)
With equations (1 52) and ( 1 56) the number of particles in the diameter range dp � dp,out can be written as np (2 Hbed + Dapp ) (1 57) n p �dp.ou' vpln ( 1 - �) =
A Aapp
_
By feeding of spherical and monodisperse nuclei of same density into the flu idized bed follows with equation (81 ) 6Mp (2Hbed + Dapp ) (1 58) n p �dp.ou' = ( A) ndp o Ps Vp In 1 - Asep where Mp is the feed particle flow, dp, is the diameter of the monodisperse particles and Ps is the particle density . Theo mass-based density distribution of the particles by using the apparatus configuration of Fig. 35 is shown in Fig. 38, whereby q't characterizes the number of particles at a certai n diameter related to the mass of 1 kg particles/m. 3
_
,
app
72
Fig.
L. Mörl et al.
38. Mass-based number density distribution and particle diameter as function of time.
At time tv all solid particles achieves the diameter dp,out and begin to fall out off the fluidized bed. For a better mathematical description the time 0 is introduced 0 = t - tv (159) corresponds to the time t in equation (152) and to the time t, which is past since the entry of a nucleus with the diameter dp,o into the fluidized bed. The function qr1(0) can be calculated with t7p0 ) qo (0) = exp ( - -(160) p n ?:dp,out with q� as mean mass-based number density distribution of the particles per kg and meter which is constant in the dia meter range dp, ut � dp � dp,o, because the absolute particle number is constant. Nevertheless,othe particles grow linearly from the diameter dp,o up to the diameter dp,out. Taking into consideration equa tion (157), we obtai n : ) 0vp I n ( 1 - AAsep app (161) q�(0) = q� exp o
M
%
-M
[
_
2 Hbed + Dapp
]
With the assumption of linear particle growth, we get: 0 = -tv and dp dp,o 0 and thus dp = dp,out =
=}
=}
o
dp - dp,out tv = dp ,out - dp,o
=
0
(valid for dp
2:
dp,out)
(162)
Fluidized Bed Spray Granulation
73
Now the density distribution as function of the diameter can be written as qo (1 63) q� Cdp) exp (Kwdp y expCKwdp) ,out This function is only valid for the range dp dp,out, whereas Kw summarizes some quantities: tvvp I n ( 1 �sep ) app Kw - ( (1 64) dp,out - dp,o ) (2Hbed + Dapp) The quantities q� and tv are stil unknown. With the assumptions the density distribution q� in the diameter range dp,o- dp,out and the total-residence time of a nuclei tv is calculable. If the number of particles in the fluidized bed in the diameter range dp,o-dp,out is much larger than the number of particles with a bigger dia meter than dp,out, the following equation can be written -M
=
�
_
_
(1 65)
Thus, with the total mass of the fluidized bed
M�ed
with
results
(1 66)
(1 67)
The mean particle volume Vp can be calculated by using the assumption np,dp o . dp,out » np.dP,out and equation (79). Now, q� i n the di a meter range dp dp,o ut can be calculated with 24 (1 68) qo (dp,out - dp,o) by using the residence time of a nucleus in the fluidized bed according to equa tion (88) 24 ex p (Kwdp) M(dp ) (1 69) (dp,out - dp,o) exp (Kwdp,out) �
-M
=
4
n
%
_
nps
4
4
Ps
4
(1 70)
L. Mörl
74 E
�
g-
600000 -r---,----,---..,---,---r--.--. - - - - - - :- - - f - - - ,- - - - - - - ,- - - - - - -,- - - - - - - - - - - - - - - - - - j, - - - - - - j - - - - - - j - - - - I I r ,
bI)
500000
I
'" o ';:J
B 400000
E::l
,' , ,I - - - - - I,,
I I
,
I - - - - - - r- -
300000
-
I
I
I I
200000 1 00000
.0 '" '" '"
E
o
I I
- - - - --r
I
-
:
I - r -
,
,
I
- - - - - -1 -
I I
I I
,
�
I
-
, -t---�' o
dp'o
0.002
_ _ _ _ _
,
- - - - -1 - -
, ,
I I
,
,
I I
,
I J_
f-+' 0.004
I I
I
-
,
,
I
,
�------�
- - - - - -
- - - - - -
,
�
- - - - - -
- -
,
,,
, - - - - - - , - - - - - - , - - - - - - T - - - - - -
_ _ _ _ _
--+----1 0.008 0.0 1
t--
-
--
I
_ _ _ _ _ _L _ _ _ _ _ 1_ _ _ _ _ _ _ 1_ _ _ _ _ _ _' _ _ _ _ _ _ , I I
I
, ,
,
i
,
I
l
, ,
-
I ( I - - I- - - - - - - , - - - - - - -,- - - - - - , - - I I i I I
.. - - - t- t
'"
1
�
I
"
I
'Ö
1l
I
I I _ _ _ _ _ _ � _ _ L _ _ _ � _ _ _ _ _ _ I_ _ _ _ _ _ _ _ _ _ _ _ _ �
.�
.� '" ., "0
et al.
- -
-
, �- --
- - -
-
- -
,
� -
- - - -
,
f-- --
,
I
0.0 1 6
0.0 1 8
-
-
0.006
0.0 1 2
0.0 1 4
0.02
particle diameter [ml Fig. 39. Mass-based number density distribution of the particies in the fluidized bed as function of the diameter for an example (!fbed = 0.8 m, Dapp 0.8 m, Dsep 0.08 m, vp 0.05 m/s, dp.o 3 mm, dp,out = 10 mm, ML 50 k9/h, x 80 mass%). =
=
=
=
=
=
This is the mass-based density distribution of the number of particles in the diameter range dp,out :::;; dp which is iI ustrated in Fig. 39 for an example. Fi g ure shows the influence of the diameter of the c1assifying tube on the number density distribution of the fluidized bed particles. Now, with the number density distribution the number of particles in the fluidized bed and the cumulative density distri bution can be calculated for both diameter ranges
dp - ,out
ldp,oP q�ddp d
q�(dp - �p,o)
+ J::'out eXP(K�dp,out)
=
=
q�(dp -dp,o )
exp(Kwdp)ddp
x
1 00
(1 71 ) (%)
1dp,out exp (Kwqo dp,out) exp(Kwdp)d d KwexprKwdp,out) [exp(Kwdp) -exp (Kwdp,out)]
(1 72)
00
-M
00
p
-M
(1 73)
75
Fluidized Bed Spray Granulation E
600000 .---�--�----.---�--'---�
� 500000 oJ)
-- - - - -...., I
,
c::
] 400000 .S2
'S :.c Vl
:> c::
]
- -
- - _
.... -
1
- - - - - - - - I
,
-
, ,
---
Dscp = 40 mm
-0-
= 60 mm
200000 . 1 00000 -
.... -
- -
- -
- - -1 - - - "1-
I
-
- -
-
I
- - - -
- -1I
- - - -
- -1 - - - - ,
- -
,
_ _ _ _ _ _ I... _ _ _ _ _ _ L. _ _ _ _ _ . 1... _ _ _ _ _ . . _ _ _ _ _ . I I I I ,
.� 300000 c:: ""Q.)
�
- - - - - _
- -
- - -
- - - - - - - - - - - - -:- - - - -
-
- ,,- - - - - - -,. - - - - - - -
= 80 mm
-
= 1 00 mm - -
-+--
= 1 20 mm
-0-
= 1 40 mm
o +-��==�==��--�--��� o 0. 002 0 .004 0 .006 0. 008 0 .0 1 0 .0 1 2 0.014 0.0 1 6 0.0 1 8 0.02 particle
diameter [m]
Fig. 40. Influence of the diameter of the ciassifying tube on the mass-based number density distribution of the particles in the fluidized bed for an example (Hbed = 0.8 m, Dapp 0.8 m, vp 0.05 m/s, 30 kg, dp.o 3 mm, dp.out 10 mm, flA 50 k9/h, x 80 mass%, Ps 1 500 kg/m ) . =
=
=
=
0-
Atff.e. d
=
=
=
(K d [exp(Kwdp ) - exp(Kwdp,out)] Kwexp w P,out)
=
-M
1 00 (%) - J:P,pou O t q�ddp + J:P,out exp(Kq�dP,out) exp(Kwdp )ddp X
W
(K d [exp(Kwdp ) - exp(Kwdp,out)] Kwexp w P,out) q- oM ( dp - dP,in ) - Ker� -M
=
X
1 00 (%)
( 1 74)
The resulting cumulative density distributions of the example in Fig. 40 are plotted in Fig. 41 . It is recognizable that the apparatus geometry has an important influence on the density distribution during granulation. Analogous, the density distributions for surface area, volume and mass can be written: 1. Range: dp, Q :( dp :( dp .out
qÖ(dp ) # f(dp) = q� q� (dp ) = q� n d� q�v (dp ) = q� � d� q�(dp ) = q� � d�ps
76
L. Mörl et al.
�
80
.tj
60
c o ';::l
E
:a o 'Vi
�
- - - - - - - - - - - � - - - - - - - - - ,
_ _ _ _ _ _ _ _ _ _ _ L _ _ _ _ _ _ _ ,
c
.�
öl :; E E
40
- - - - - - - -
,
�
- - - - - - - - - - -
T '
- - -
-0-
,
= 60 mm = 80 mm = 1 00 mm
20
= 1 20 mm
:::l U
O ����----�--��==�====� -4-
o
0.005
0.0 1
0.0 1 5 parlicle diameter [m)
0.02
= 1 40 mm
0.025
0.03
�ed
Fig. 41 . Influence of the diameter of the discharge tube on the cumulative mass-based number density distribution = 0.8 m, Dapp = 0.8 m, \lp = 0.05 m/s, = 30 kg, dp , o = 3 mm, dp,o ul = 1 0 mm, ML = 50 kg/h, x = 80 mass%, Ps = 1 500 kg/m ) .
(!:fbed
2. Range : dp ,oul � dp �
00
equation (169)
q�(dp ) = q�(dp) = q�(dp)d� q�v (dp) = q�(dp) � ifp q�(dp) = q� (dp) � ifpps
The above-mentioned equations are valid for the condition (175) The total number of all particles per kg in the diameter range from dp,oul to is (176) Taking into account equation (163), we get (177) np-> dP,out exp (:0 ) }{d ,out exp(Kwdp)ddp 00
=
d w P,OUI
-M
00
p
77
Fluidized Bed Spray Granulation
and the solution of the integral delivers
q�
ML (1 - x) (cfp,out - cfp,O) (2 Hbed + Dapp) np:o:dp,OU! = - Kw = - q-Mo 4/Vfred Asepp ) P (d3P,out _ d3P,O ) vp ln ( 1 _ Aa p *
(1 78)
For the total mass of all particles i n the diameter range dp,out to we obtain with equation (1 58), equations (1 68) and (1 78), 00 ,
np _ - * :O: dp,ou! MP :O: dp,ou! _ nP :O: dp,ou!
_
M. p ( cß,P,out - d3p,o) ed tv1?. d3P,O ML (1 - x) P
and with
(1 79)
(1 80) Mp>-dP,ou!
=
( 1 + d3 '
P,O ML
(1 -�)
(181 )
)
Mp (cfp,OU! - dp,o)
These assumptions yields the total number of all particles for both ranges dP, in < dp < dp ,out and dp ,out < dp < 00
(1 82)
and (1 83)
Analogous, the total surface area, volume and the mass of the particles in the ranges can be determi n ed. 3.4. Continuous fluidized bed g ranulation with non-classifying particle discharge
Basis for the calculation is the one-dimensional population balance for the conti n uous granulation aqÜ,bed L np aGqÜ,bed L np = qO,in n p,in - qO,outnp,out + at adp qü bed 'Lnp np,i n np,out *
.
*
.
(184)
describes the number density distri bution of the particles in the where fluidized bed related to the particle number, respectively include all
78
L. Mörl et al.
fluxes of the particles entering or leaving the granulator. The growth rate G is assumed as equal for all particles and independent from the di ameter, which means that a big particle gets more solid material per unit time than a smaller one (see equation), whereby the total surface area of all particles results from equation (71 ) with ( 1 85)
The assumption of constant bed mass leads to the fact that the sum of the feed and discharged mass flows is equal. This means, analogous to equation (80) that the discharged mass flow Mp,out is equal to the sum of i njected mass flow Ms and feed nuclei mass flow Mp . Taking into consideration a non-classifyi ng discharge of particles, the discharged particle flow np,out results from its dependency from the particle density distribution and the bed mass Ms Mp . " np,out = +ed qO,bed � np r-.j;.p *
(1 86)
Hence, from the population balance equation (1 84) follows under neglect of the ti me derivation " + Mp G 8qü,bed L np - np, m Ms .bed QO,bed � np 8dp IWp [dp,i; dp,i+1 ] Ip Qü bed n _
'
*
.
-
•
(1 87)
of the particle size, the number By integration over an interval can be substituted by the particle number np in the density distribution accordant interval . Ms + Mp G 8np = nP , in .bed np 8dp /VIp
( 1 88)
+ MP n P, . G np,i - np,i-1 - nP,m,1 Ms .bed I I1 dp IWp
(1 89 )
-
•
To determine the steady-state particle size distri bution, equation (1 88) must be solved. A possibility is the transfer of the partial differential equation by using the method of differences into a system of coupled ordinary differential equations .
. _
-
•
By transformation, we get the particle number in class I np,i =
,Gd np'i-1 + np ,in,i G + Ms +Mp
L}. p
8dp
(1 90)
M;ed p
The calculation of the particle number in a certain class occurs gradual starti n g with 1 to I. An explicit calculation of these expressions is not possi ble, because the surface-proportional growth rate G depends di rectly on the particle surface area. Nevertheless, equation (1 90) can be solved by a simple iteration (Fig. 42). i=
79
Fluidized Bed Spray Granulation
I I I I
estimate value I Ap
calculation
l
G
calculation np"
1
I I I
calculation I Ap,",w
end
Fig. 42. Computational sequence diagram of the continuous fluidized bed granulation with non-classifying particle discharge.
A selected calculation is shown in Fig. 44. A Gaussian normal distribution with a mean diameter dmean = 1 mm and standard deviation (J = 0.2 mm has been applied for the number density distribution of the nucieL The size distributions of the nuclei are il ustrated in Fig. 43. The resulting normalized number and mass density distributions of the bed material can be found in Fig. 44. By increasing the mass flow on the nuclei from 0.5 to 2 kgjh, Fig. 45 results. It is recognizable that the increase of the fraction + rlAp)/ M�ed leads to narrower particle size distributions. These ratio is equivalent to the mean residence time tv of the particles. For the limiting case tv 0, the particle diameter is constant. This means that the particle size distribution at the outlet of the system (product) is identical with the nuclei size distribution. (rIAs
-+
3.5. Simplified modelling of the u nsteady fluidized bed g ranulation
An advantage of the fl uidized bed spray granulation with a classifying discharge tube is the continuous processing with high product throughput and the possibi lity of process automation. Nevertheless, the unsteady behaviour is of interest for special cases, e.g., for the 1 coati n g of particles or production of spherical granul e s by si n gle-stage or multi stage batch processes,
80
L. Mörl 2.5
..;
E
�
iN -------i--b;j---
�-
2
e..
et al.
1 .5
1
------
-
- - -- - ----
-
-
-- ---- -- ----- - --- --
.
r- --
:
+
- - - - - - - - - - - - - -
-
-�----r---�--,
- - -
------ ------- ------ -----
e..
•
0; 0-
0.5
------ -------
- - - - - - - - - - - - -
- - - - - - -
o +---�--����--�--o 0.2 0.4 0.6 0.81 1 .2 1 .4 1 .6 1 .8 2 particle diameter [mm]
Fig.
Mp
43. Particle size distributions of the nuclei for the example calculation (Ms 0.5 kg/h, tvfped = 30 kg , Ps 1 500 kg/m3).
=
=
20 k9/h,
=
0.6
E .§ .
�
E .§
0-
�
- -- -- -�- -- --- � - -- --- �- -- --- �- ----- �- ----- r- -- - -- r- -- - --
0.5
I
I
I
I
I
I
q�.bcd
I
, �------�------�------�- -----�------+---- - - +------ ------�------
0.4
I
•
I
I
- - �- - - - - } - - - - - - � - - - - + -
0.3
-
-
-
I
0.2
I
-
-
- -
--�---- -+---
I
- - -
I
f-- --- ------�------
I
_ _ _ I.. _ _ _ _ _ _ L _ _ _ _ _ _ I.. _ _ _ _ _ _ 1. _ _ _ _ _ _ .I. _ _ _ _ _ _ .I. _ _ _ _ _ _ I I I I I I
,
_ _ _ _ _ _ .1 _ _ _ _ _ _ I
0-
0. 1
0 0
2
4
6
8
10
14
12
16
18
20
particle diameter [mm]
Fig. 44. Pa�icle size distriputions of the particles in the fluidized bed for the example calculation (Ms = 20 k9/h , Mp 0.5 k9/h, tvfped 30 kg, Ps 1 500 kg/m3). =
=
=
start-up phase during granulation of a fluidized bed consisti ng of particles of different material as the feed seeds or internal monodisperse nuclei with small particle diameters, and 3 transition period between cycle changes duri n g granul ation at conti n uous processi ng. 2
81
Fluidized Bed Spray Granulation
0.8 .---�----�--. 0.7
E 0.6
E :::; ." ß .-; * 0"
E E --
:g
o ·x· 0"
-
.. I
I
, , ,
-
--
- - -
... I
- - - - - -
I
_
-
I
I
- - - - -1- _ _ _ _ _ _ I
I
, , ,
_ _ _ _ _ _ _ l _ _ _ _ _ _ J _ _ _ _ _ _J . _ _ _ _ _ _ _ _ _ _ _ _ _
,
- - - - - - 1I - - - - - - �I - - - - - - - I- - - - - - I
0.5
-.
0.4
- - - - - ----- -,----
0.3
�
- -
--
I
T
- - - '-
, ,
- -
, , , -
, -
- - - - - -
- - - - -
, , ,
- - - - - � - - - - - - � - - - - - - -I- - - - - - -
0.2 - - - - - - -,. - - - - - - -
0. 1
2
4
6
8 10 12 particle diameter [mm)
14
16
18
Nfped
20
Fig. 45. Particle size distributions of the particles in the f1uidized bed for the example calculation with a quadruple nuclei mass flow (Ms 3 Ps 1 500 kgjm ).
=
20 kgjh, Mp = 2 kgjh,
=
=
30 kg,
In the following section, some modell i n g aspects based on investigations of Sachse as weil as Mörl et al. [45,47-49] wi l be explained regarding these 3 cases. 3. 5. 1. Batch process with increased bed mass
The batch process with increased bed mass for the coati n g of particles is very important for example for the production of pharmaceutical granules with retarded release of active i n gredients by using different coated layers of spherical form and an outer shell (Fig . 46) or of fertilizers with a long-term effect due to this alternating layering or for pelleted vegetable seeds. Fi gure 47 shows photos of coated landfil leachate granules of the University of Magdeburg with a cohesive shell of the coated layer. Figure 48 presents a schematic of the discontin uous coating process of particles. For the modelling the following assumptions are introduced: 1 . The total number of al l particles i n the fl u i d i z ed bed i s constant. 2. All granul e s are spheres. 3. Al l granules have the same di a meter, i. e ., the granul e s are monodi s perse. 4. There is no internal nuclei formation by attritio n, overspray or breakage and no elutriation of particles as weil as no agglomeration of particles.
82
L. Mörl et 8/. shell(coat)
layer I
core
coated granulate
spherical layered granulate
Fig. 46. Structure of a coated, respectively, spherical-Iayered granulate.
13
14
Fig. 47. Photos of coated landfill leachate granules.
The fluidized bed is ideal mixed. Thus, all particles are uniformly wetted with the liquid . 6. The amount and the concentration of the i njected l i q ui d is constant; and 7. The sol i d densities are constant. With the assumptions 1-6 follows for the time-dependent increase of the mass of a particle 5.
(191 )
where Mp time t = 0
=
Mp ,o
is the mass of a particle and dp
=
dp, o
is the particle diameter at (1 92)
83
Fluidized Bed Spray Granulation
l ,r M,
•
-
�
--
,-
..
� CI 1
�
-, -
-,�7/�!\.:S\
u \....
\ ,
<j
lf lf -
-
�/ !
-(
-
i
I
... '- '
-
1-
Cl
_
'_I
:S !I ü
� -
'-.) C... -
("'J .....
_
:-
_
C
fluidized bed bed Mp
gas distributor
\
M.
Fig. 48. Schematic of the discontinuous fluidized bed granulation with constant number of particles.
After integration the linear time-dependent solid mass growth can be written Mp (f)
=
MP,O
+
ML (1 x) f " L np -
(1 93)
In general, the total mass of all particles in the fluidized bed ��g is known. So, we get with P,O � "'"' n � p - Mp - d 3 ,o � p,op p,o _
M bed
_
M bed
[
bed MP,O
bed MP,O
]
(1 94)
the functional dependency of the particle mass from the ti m e Mp (t) = (3 dp,o Ps 1 + J[
3
ML(1 x) bed f MP,O -
(1 95)
With the spherical geometry according to Fig. 49 follows (1 96)
84
L. Mörl et al. dp ( l ) d�.o
P,,"oat
Ps Fig.
49. Structure of a granule.
By introducing the partie/es mass
(197) and a dimensionless ti me
[ML(1 - X)] _t
tvl;.,ed P,O
(198)
r
follows with equation (193) the dimensionless equation for the growth of the partie/e mass Mp(r) =
1
+r
( 199)
The dependency of the di mensionless partie/e mass fram the di mensionless time is drawn in Fig. 50. A bed mass of Mp = 3 Mp,o at the dimensionless time of r = 3 is i n a non-realistic order of magnitude. Normally, fluidized beds for coating operates in the range of Mp = (0. 1 . . · 2) Mp,o , Nevertheless, the dia gram il ustrates the sensitivity of the model. The dependency of the granulation from the pneumatic conditions and the l i m its of the disconti nuous process are explained i n Section 3. 6 .1, respectively. If equation (196) is inserted into equation (195) and if we consider that the core and the shell of the partie/e have a different solid density, we get x
x
(ddp,po)3 [1 ML(1 :;o x) PcoatPs ] Mt, =
+
t
(200)
85
Fluidized Bed Spray Granulation 4 .----------------,, ------------------------------� ,, ,
3.5
----------
� "
- ------ - -- -
� ,
- ----- - - ---
�
-----------
�
I
,, I
I
,
I I
I I
I I
I I
-----------
: , , ,
-----------
- - - - - - - - - - - T - - - - - - - - - - - t - --- - - - - - - -t - - - - - - - - - - -: - - - - -
3
., u 't; � 2 .5
,
-----------�-----------� , , ,
,,
2
,
, , , , , , , , ,, , , , , , - - - - - - - - - - - r, - - - - - - - - - - - T, - - - - - - - - - - -----r , ,
-----------�--------- -- I - --------
1 .5
-
T
-
-----
, , ,
l �------+---+_--+_--�--�
o
0 .5
1 .5
2
dimensionless time
2.5
3
[-]
Fig. 50. Dependency of the dimensionless particle mass from the dimensionless time during batch coating according to equation ( 1 99).
] 1 /3
Thus, we receive the dependency of the partide di ameter from the ti m e ML(1.bed x) Ps t dP ( t) dP,O 1 (201) IV/r,o Pcoal A dimensionless partide diameter can be written as (202) (:;J ifp Hence, the dependency of the di mensionless partide diameter from the di mensionless ti me duri n g the unsteady coatin g of partides with the ratio of the density of the core to the density of the shell Ps (203) Pp Peoal as dimensionless parameter occurs as folIows: (204) ifp('!) = ( 1 + P�'!) Figure 51 shows these dependency considering a constant number of partides and a complete evaporation of the total mass of the injected l i q ui d . For the calculation of the heat and mass transfer i n the flu i dized bed the total surface area of all particles in the bed is requi red (see Section 4.1). Assumi n g a constant partide number 'Lnp , the change of the total surface area of all partides =
[ . +
-
•
=
--- =
*
1 /3
86
L. Mörl et al.
2 .6 --
--0, " " E'" �
2.2
'ö " ü
.�on on
1 .8
p� = 5
=4
-.-
=3
-lr-
=2
--+-
=
1
-0-
=
0.5
--
= 0. 1
" t:
.�c
E 'ö "
2
1 .5
0.5
dimen ionle
s
2.5
time l-J
Fig. 5 1 . Dependency of the dimensionless particle diameter from the dimensionless time during batch coating according to equation (204) by variation of the dimensionless particle density according to equation (203).
in the bed during the particle growth reads as folIows:
(205) LAp(t) L npAp (t) = L np1td� (t) the derivations for 'Lnp and dp(t) into the equations above, we can =
Insertin g rewrite the time-dependency of these total surface areas 6M bed L Ap(t) = � dp,oPs
[ M' LM(1b: Ps ] 1
x)
+
p
0
Pcoat
t
2/3
By using a specific surface area which is based on the surface area at tim e and the di mensionless time, we obtain
(206) t
=0
(207)
Figure 52 shows the trajectories of this function with the di mensionless density ratio PS/Pcoat as parameter. The thickness of the shell respectively of the coated layer is Scoat dp -2 dp,o (208) _
-
87
Fluidized Bed Spray Granulation
7 1.=====��--�-----;--1 p;, = 5 -
=4 =
o
3
- -
----
-
- - - - - - - - - - -
-
- - - -
-
-
- - - -
1 .5
0.5
dimensionle
time [-]
r
, ,
- - - - - - - - - -
2
- ---
2.5
3
Fig. 52. Dependency of the dimensionless total particle surface area from the dimen sionless time during batch coating according to equation (207) by variation of the dimen sionless particle density according to equation (203).
We can rewrite equation (208) as dp 2scoat + dp,o (209) and insert these equation into equation (201) to get the time-dependent layer thickness Ps t) - 1 ] scoat(f) d2p,o [ (1 MLM(1bed x) Pcoat (210) Thus, a time-dependent dimensionless layer thickness, which is based on the initial diameter is calculable Scoatp,o = 21 [( 1 + Ppr - 1 (211) scoat(r = d Analogous to Fig . 51 , this dependency is drawn in Fig . 53. Contrarily equation (210) can be used to determine the ti m e which i s necessary to reach a certai n layer thickness scoat =
=
+
P,O
)
*
1 /3
-
*
) 1 /3 ]
3 d 2 ) [( Scoat tcoat(scoat) _ 1 ] M�� Pcoat M (1 Ps =
+ dP•o
dp,o
.
L - x)
(212)
88 1 .8 Ir===�==;---;' : P" = 5
-
-
-0-
�
]u
1 .6 -
:s
--
=4 =3 =2 =I = 0.5
I :I
----
-
i
:I :I :I
�--
-----
�:_
:I :I
-;-
-
,-
L. Mörl et al. ,
-
�
-
i.- ------ -:I
II I
II II
� _ _ _ _ _ _ _ _ _ _ _L __________ _
___
o
1 .5
0.5
2
3
2.5
dimensionJess time [-]
Fig. 53. Dependency of the dimensionless layer thickness from the dimensionless time during batch coating according to equation (2 1 1 ) by variation of the dimensionless particle density according to equation (203).
The mean particle density duri n g coating reads as folIows:
Pp = MVpp
(21 3)
-
(21 4)
_
-
Pp = (dp,dpo) 3Ps + [1 (dpdp,o) 3] PCt:Jat
With equation ( 1 96) and Vp = (1t/6)ifp, we receive a mean particle density _
whereby by considering of equation (202) stands Pp
= (opr3Ps + [1 (opr3] PCt:Jat -
(21 5)
and in dimensionless form
[ [ 1 (opr3] = 1 + (op ) -3 �- 1 ] = Pcoat = (opr3 �+ PCt:Jat Pcoat
P� Pp
_
Finally, we obtain with equation (203)
1
Pp(op 31 PP = +-) -*
-
(21 6)
(21 7)
89
Fluidized Bed Spray Granulation 10
- - - - - -- -- -- - - -f-- - - - - - - - - - : = = = : : : : : : : ::r- : : : : : : : : : : : 'rr : : : : : : : : : : : : : _ : : _ : : : : : : � - � -- - - - - - - - - - - . - - - - - - - - - - - - - - - - - - - { - - - - - - - - - - - - - - - - - - - - - - - t - - - - - - - - - - t - - - - - - - - - - - - - - - - - -- - - - - - - - - - - - - - - - t - - - - - - - - - - - - - - - - - - - - -( - - - - - - - - - - - t - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - { - - - - - - - - - - - - - - - - - - - - - - -t - - - - - - - - - - - } - - - - - - - - - - - - - - - - - - - - - - - - - - - - + - - -- -- - - --- ------ --- - - -:- --- - ----- --t-I - - - -
.� 5
- - - - - - -
- - - 1 - - -
- - - - - - - - - -
- - -
-
I , [: :: =�:�: =:=:=J:�t_:_=_ ==::�=�:::=�:: ==�: : :�E
T I
_
-
=
:=:
I
: ,
,
�
,
0. 1
-0-
=
- - - - - � - - -.-
- - - - - - - , - - - - - - - - - - - - :- - �- - - - - - - - - - - -� - -
-----------t: : - .. - - - - - - - - -t - - - - - - - - - - - :- - - -
e
c
:
- - - -==-=�====- ==- I_ -
----------t -----------�-- -
� § . Vj
=========
�
I
=
-4 :�:�::�:�j:�=�:�: _;=�::�_�::J� 3
2 0.5
I
---A-...:r-
=
'
-+-
= 1
�
=
:
I
- - - - - - - - - - - -
- - - - - - - -
- -
- - - -::=�:���:�� �_���- -�:�;t���-5�3 , I
I '
"0
- - - - - - -
= O. J
---
-,--- ---------
- - - - - -+ - - - - - - - - - - - -
-----i-- - - - - i - -_ _- - - - - - - - - : - -- -- - - - - i- - - - - :
__ _ __ .1 _
��-__+_---+__ ' ---J---== --: =:=::t===------i---.j 3 2. 5 o
0. 5
- 10:: l)\ V �I?�
/
1/
I'
/
�
/
r0 � .�/x V , '-I> N)< K /r\bX/D< �::Xx 1"-""
,Q'
•
/
- -;; Vv l""" V j
://' V V-
/'
R< "V
01
V
/'
x x
V' 1= V/v �
40
- :0; .:0;
0 01
�
/ / /IX / /V l>< v
V 7 /1717 / jV
I?
1/ � �
V 1/
IX
I� ./
rI
IX
>-)
e?< J
,
, ,. ,
.0
0.6
,
- - - - - - - - - - -
- - - - - - - - - - - - I-- - - - - - - - - - - - " - - - - - - - - - - - -1- - - - - - - - - - - - .. - - - - - - - - - - -
,
" I
I
: ,
p"
� " -= 0
E '6 ...
c
0.4
- � - - - - - - - - - - - � - - - - - - - - - - - -I- - - - - - - - - - - - � - - - - - - - - - - I I I I
,
,
,
"
0.2 O +-------�--�--�r_--� o
0.5
1.5
dimensionless time [-)
2
2.5
3
Fig. 60. Decrease of the total particle number in the fluidized bed during the discontinuous start-up phase according to equation (232).
96
L. Mörl et al.
1 .8 ::!:: 1:l
-t :J
�
---
p;
1--:---�--�----;--;===::::;::==::;-� -0-
1.5
=5
=4 =3 =2
1 .2
u
.€ '"
Li
Q.,
0.9
B
'"
� -a .o
0.6
;;; " .
�
�
Vl
C o ' iji
0.8
� Q)
E 0.4 '0
o l&�a��t=:= ==� o
3
2
dimensionless time [-]
F ig. 62. Dependency of the dimensionless layer thickness from the dimensionless time during the discontinuous start-up phase according to equation (237) by variation of the dimensionless particle density according to equation (203).
dp,out
The substitution of equation (238) leads to the time fend which is required for a start-up phase of the discontinuous semi-batch process and which predicts the duration until the first particles will be discharged with the diameter fend
=
ML�: x) { In [1 - P;:at (1 - �f�t) 1 }
(dp,--out) ]
(239)
An equal density of the core and of the shell yields fend
-
_
-
[
3�ed . In dp,o ML(1 x)
(240)
Based on equation (240), we developed a nomogram, which is shown in Fig. 63. By inserting the dimensionless quantities, we get
and respectively for
PcoaJPs = 1
rend
= 3 In (
cfp,out)
(242)
�.: Peoat
Figure 67 shows the minimal fluidization velocity and the particle diameter as function of the dimensionless time for the case that the density of the shell material is higher than the density of the core material. At the beginning, the minimal fluidization velocity decreases, while further granulation causes a rise in the progression. For example, using an effective operation velocity of 1 m/s, the fluidized bed is stable only until the dimensionless time r 9.9. After this time, the granulation must be stopped. Figure 68 iIIustrates for the same example the time-dependency of the mean particle density and of the particle diameter. It is obvious that a maximal particle
=
1 03
Fluidized Bed Spray Granulation 3.5 i.= ====:::::;:----:--;--i
....... p�
= 10 2 � =1 'g 2.5 -
.......
- - - r - - - - - - - - - - - - - - r - - - - - - - - - -
, ,
t;: �
§c 1 . 5 'E '" '" "
,
- - - - - - - - - - -
j, - - - - - - - - - - - - - - r, - - - - - - - - - - - - - ,
, ,
,
_ _ _ _ _ _ _ _ _ _ _ _ _ L _ _ _ _ _ _ _ _ _ _ _ _ _ _ L _ _ _ _ _ _
"2
o .� c
E
"
'Ö
0.5
- - - - - - - - - - - - - -
, �---,
, "
- - - - - - - � - - - - - - - - - - - - - - � - - - - - - - - - - - - - - � - - - - - - - - - - - - - -
O +-------�--�--r_--� o
2
4
dimensionJess
6 time [-]
8
10
Fig. 66. Dependency of the dimensionless minimal fluidization velocity fram the dimen sionless time according to equation (255) by variation of the dimensionless particie density during the batch pracess for an example (AA = 1 00 kgjh, x = 70 mass%, dp,o = 2 mm, 2 Ps = 2500 kgjm3 , 9G,in = 20°C, VG,in = 1 5 X 1 0-6 m js, PG ,in = 1 .2 kgjm3) . 1 . 2 -r------,---,---r- 0.008
1
i
.q �
g
.�
,
- - - -� - - - - - - - - - - - - r - - - - - - - - - - -
0.6
N
E '2 E
. :
0.006
I .... öl Eos "
_ _ _ _ _ _
�_
_ _ _ _ _ _ _ _ _ _ _ _
: , ,
'Ö ':;
�
,
,
0.8
c
t;:
0.007
• • • • • • • • • • • •• • • • •: • • • • • • • • • • • • • • • • •: • • • • • • •• • • • • • • • ••:•••••••••••••••• .J
- - -
�
,
_ _ _ _ _ _ _ _ _ _ _ _
:
L
:
_ _ _ _ _ _ _ _ _ _ _•
, � - - - - - - - - - - - - � - - - - - - - - - - - - - � - - - - - - - - - - - - � - - - - - - - - - - - :. " , , .
-0-
minimal fluidization velocity
-0-
particle diameter
- - -, - - - - - - - - - - - - r - - - - - - - - - - - .
, ,
, ,
0.005
: : .
. .
'Ö
�., "
0.004
a.
0.003
0 �------+---4---�--�--_+ 0.OO2 8 10 4 6 o 2
dimensionJess time [-]
Fig. 67. Dependency of the minimal fluidization velocity according to equation (253) and of the particle diameter according to equation (20 1 ) �rom the dimensionless time at Ps > Pcoat during the batch process for an example (ML = 1 00 kgjh, x 70 mass%, dp 0 = 2 mm, 2 Ps = 2500 kgjm3, Pcoat = 500 kgjm3, 9G•in = 20°C, VG,in = 15 X 1 0- 6 m js, PG in = 1 .2 kgjm3). , =
1 04
L. Mörl et al.
0.008�------�--. 3� 0.007 2500 :§: 0.006 2000 .� particle diameter � 0.005 1500 mean particle density .� 0.004 1000 e::0. E 0.003 -500 0.002�--o 2 4 6 8 10---�---r--� 0 dimensionless time [-) ................ ,. ............... ........... . . ,,. ............... , .......... . , , , - -- - -- -- -- - -� -- --- ------- �- --- -- --- -- -�- -- -- - -, , I
I �
.
... " "
'Ö " Ü
.
I
.
, .. - - - - . - - - - - - - - - - - - .. - - - - - - - - - - .... .. , , , , :
"'s 00 =.
-0-
" " ü .€ '"
- - :-
�
I
I
I
I
I
I
I
I
•
- - - � - - - - - - - - - - - - � - - - - - - - - - - - - 7 - - - - - - - - - - - - + - - - - - - - - - _ ..:..
0.
---------� , ,
- - - - - - - - - - -
�
- - -
---------�-----,
- - - - - -
:
- - - - - - - - - - -
e::
"0
'" "
� . :
Fig. 68, Dependency of the particle diameter according to equation (201 ) and of the mean
particle density according to equation (21 5) from the dimensionless time at Ps > Pcoat during the batch process for an example (ML = 1 00 kg/h, x = 70 mass%, dp 0 = 2 mm, 2 3 3 3 Ps = 2500 kg/m , Pcoat = 500 kg/m , 9G,in = 20°C, VG.in = 1 5 x 1 0- 6 m /s, PG ,in = 1 .2 kg/m ) .
diameter of 7.4 mm can be reached corresponding to a mean particle density of 540 kg/m 3 . •
Case 2:
Ps
c 0 'z:j oS
'S !;:: � E 'e 'E .!;:l
.......
10
-
p;
= 10 =5 =
1
:
-(r-
= 0.2
--
= 0. 1 '
,
-e
�
-
.�c
�,
- - - - - - - - - - - - -
� ,
- - - - - - - - - - - - - -
�
- - - - - - - - - - - - - -
E '6 "
O. l +-------�--_r--_+--�--� 4 o 2 6 8 10 dimensionless time [-)
Fig. 71 . Dependency of the dimensionless minimal-fluidization velocity from the dimension less time according to equation (262) by variation of the dimensionless-particle density during the semi-batch process for an example (M� = 1 00 kg/h, x 70 mass%, dp,o = 2 mm, 2 3 15 x 1 0- m /s, PG,in = 1 .2 kg/m3). P s = 2500 kg/m , .9G.in = 20°C, VG.in =
=
minimal fluidization veloeity deereases, while further granulation eauses a rise in the progression. By using an effeetive operation velocity of 1 m/s, the fluidized bed is stable only until the dimensionless time 2.4. That means, the gran ulation must be stopped earlier in eomparison to the example from the previous seetion. The reason is the higher partiele growth rate due to permanent deerease of the number of particles at eonstant bed mass. For fortifieation, Fig. 73 illustrates for the same example the time-dependeney of the mean particle density and of the particle diameter. The maximal particle diameter of 7.4 mm at a mean particle density of 540 kg/m 3 ean be reaehed after = 2.4 instead of 9.9 in eomparision to the example of Seetion 3.6. 1 . r
r
•
r
=
=
Gase 2 : P s < P eoal
In agreement with Gase 2 of the previous seetion, no deerease of the minimal fluidization velocity oeeurs for low dimensionless times when the shell density is higher than the core density. Instead, the minimal fluidization veloeity, the particle diameter as weil as the granule density rises permanently, expressed in Figs. 74 and 75. Hereby, the eritical time where the unstable area begins is = 2.35 cor responding to a granule diameter of 2.85 mm and to a mean granule density of 1 780 kg/m3. r
1 08
L. Mörl et al. 4 .-------r---.,...---.---� 0. 102 3.5
--
minimal fluidization velocity
-0-
particJe diameter
--------
,
" "
_ _ _ _ _ _ _ _ _ _ _ _ � _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.":'
�
� �
c:
� :a
� .§c: ·s
-------
2.5 2
-
-
- - -
-
_ _ _ _ _ _ _ _ _ _ _ _ J_ _ _
- - - - - " - - - - - - - - - - - -,,- - - - - - - - - - - - -
- - - - - -
, , , ,
- - - - - - - - - - - - �- - - - - - - - - -
_
-
0.082 _ _ _
_ _ _ _
-
� :
- - - - -
" E'" :a " v 0.042 'a ;;
- - - - -� - - - - - - - - - -
- -
'
-
g
0.062 �
-
1 .5
Ol
c..
0.022 0.5 o
����:;:J�--�---�---___+ 0.002 0
2
6 4 dimensionless time [-]
8
10
Fig. 72. Dependency of the minimal fluidization velocity according to equation (259) and of the particle diameter according to equation (229) from the dimensionless time at Ps > Peoal during the semi-batch process for an example (ML = 1 00 kg/h, x = 70 mass%, 2 dp•o 2 mm, P� = 2500 kg/m3 , Peoal = 500 kg/m3 , .9G,in = 20°C , VG.in = 1 5 X 1 0-6 m /s, P G ,in = 1 .2 kg/m ). =
4. DEGREE O F WETTIN G AND HEAT AND MASS TRANSFER 4.1 . Modelling of the degree of wetting and of the transfer phenomena
At fluidized bed spray granulation a permanent wetting of the particle surface and simultaneous evaporation and drying of the deposited liquid occurs. If we assume a laminar film on the particle surface, we can derive expressions for the ca Icu lation of the heat and mass transfer, drawn in Fig. 76. For the modelling we assume the following: 1 . All granules are spheres. 2. All granules have the same diameter, Le. the granules are monodisperse. 3. There is no internal nuclei formation by attrition, overspray or breakage and no elutriation of particles as weil as no agglomeration of particles. 4. The fluidized bed is ideal mixed (CSTR behaviour) . Thus, all particles are uniform wetted with the liquid proportional to their surface areas.
1 09
Fluidized Bed Spray Granulation 0. 1 02 _---�----r--___,-__r_---___r 3000 -0-0-
0.082
particJe diameter mean particle density r:
_ _ _ _ _ _ _ _ _ _ _ _ � - - - - - - -
I ö:i E�
� 0.062
I
, ,, ,, ..
,
- - - - - - - - - - - -
r I
- - - - - - - - - - - -
,
, :
- - - - - - - - -
2500
2000
_ _ _ _ _ _ _ _ _ _ _ _ 1- _ _ _ _ _ _ _ _ _ _ _ _ 1- _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ I
" 0.042 '"
:a
�
_
I
,
:
1 500
,,
_ _ _ _ _ _ _ _ _ _ � _ _ _ _ _ _ _ _ _ _ _ _ L _ _ _ _ _ _ _ _ _ _ _ _ � _ _ _ _ _ _ _ _ _
0.
0.022
1 000
1. _ _ _ _ _ _ _ _
:
500
:
�
-'" .� " " 'Ü,:'" "E
bl)
e
"0
0. e �
1:�������!:::=--_L---�r__ ---_L8 ---___l100 6 · ·· ·· · ·· ·· · · · ·
0.002
- - - -
I
o
2
4
dimensionless time [-)
73. Dependency of the particle diameter according to equation (229) and of the mean particle density according to equation (244) from the di!Tlensionless time at Ps> Peoat during the semi-batch process for an example (ML = 1 00 kg/h, x = 70 mass%, 2 3 3 dp,o = 2 mm, P � = 2500 kg/m , P coat = 500 kg/m , 9G,in = 20°C, vG, in = 1 5 X 1 0- 6 m /s, PG i 1 .2 kg/m ) .
Fig.
,n
5. 6. 7. 8. 9. 1 0. 11. 1 2. 1 3. 14.
=
The fluidized bed has a constant porosity. The amount and the concentration of the injected liquid is constant. The injected liquid is totally deposited onto the particles. The solid densities are constant. The gas flows as ideal plug through the fluidized bed (PFTR behaviour). The secondary (classifying) gas flow fram the classifying tube is immediately mixed with the fluidization gas flow after passing the distributor plate. The process operates under steady-state and adiabatic conditions. There are no diffusion phenomena in the particles. The sensible heat of the injected liquid and of the solid is much smaller than the heat of evaporation. The water content of the feed nuclei and of the discharged granules is neg ligible.
Expressing the mass flux of vapour or water in an infinitesimal volume element as a function of pressures, we get with A = LA p d Mv = Ma d Y = P�Mv In RT
(PP _- PP�V) d � Ap '"
(263)
1 10
.-------,r--.,---r---..---r , --- --- - , - --- --- ------ -- --
L. Mörl et al.
6
-0-
5
� .� 4 öl
5 � 3 >
'ö 'S I;:: N
-
-
- - - -0-
-
0.037
minimal fluidizatiOll velocity
particle diameter
- -
-
- - - - - - - - - - - -
- - - - - - -
�
- -
_ _ _ _ _ _ _ _ _ _ _ _ _ L _ _ _ _ _
"
- -
- -
- - -
'
�
0.032 0.027
- - - -
- - - - - - - - - - - -
,,
-;; 2 E
'e
' ;:
i - - - - - - - - - - - - - r - - - - - - - - -
0.01 7 � 'ö
0.0 1 2 -
� § ...
0.022
1
0,007
o �ooo Pcoat during the semi-batch process for an example (AA = 1 00 kgjh, x = 70 mass%, 2 3 3 1 5 x 1 0- 6 m js, dp,o = 2 mm, P � = 500 kgjm , Pcoat = 2500 kgjm , 9G,in = 20°C, VG ,in P G, in = 1 .2 kgjm ) . =
(M(Y*v/Ma) (�v/Mv/�Maa Y*)
with a humidity-dependent Stefan correction factor
cPSY
=
-
In
Y)
+ +Y
(267)
A degree of wetting or wetting efficiency marks the ratio of wetted particle surface area to total particle surface area Awetted - Awetted (268) � Ap Atotal Thus, the effective surface area (Fig. 77) can be calculated by using the wetted part of the particles
ep -
_
_
A eff = Awetted
=
The unwetted part of the surface area is Aunwetted
=
(1
-
ep L Ap
(269)
ep) L Ap
(270)
Using a specific surface area (271 )
1 12
L. Mörl et 81. Ma
= M a,l + M a ,2
u
D �
YOUl ' 'ÖOUl
Y: _ _
_
o M p
•
• o
u D 'cf
Fig. 76. Schematic of the f1uidized bed granulation and drying model. and a dimensionless bed height
we obtain with
dL
Z
= Hbed
(272)
Ap = aAappqJdz
(273)
�bed
-
and with a specific gas mass flow or a gas mass flux
ma = AMappa ,
-
(274)
1 13
Fluidized Bed Spray Granulation
werted surface
unwerted surface
Fig. 77. Model of the degree of wetting.
from equation (266) dY CP sy{ Y'
-
Y)
_
-
ß
RT
MaP cpaHbed Y d rha �bed
(275)
If equation (275) is integrated into the boundaries z=
0:
z = z:
�bed = 0 and Y = Yin �bed = �bed and Y = Yin
results the dependency of the air humidity from the height of the fluidized bed. The following two cases should be distinguished •
•
Gase 1 : The partial pressure of the water vapour in the gas is negligible com pared to the total system pressure: P v < < P (e.g. at one time flow of ambient air through the fluidized bed). Then, a linear correlation between air humidity and particle vapour pressure according to equation (264) can be formulated with Y = (Mv / Ma )pv. Gase 2: It is essential that P v < P, but P v is not negligible compared to the total system pressure P (e.g. at recirculation of air).
For Case 1 , the Stefan correction factor CPSy, which is caused by the back flow of the gas from the phase interface (boundary layer), can be set to CPSy = 1 . Thus, after separation of the variables results (276) We can define a number of transfer units NTU (277)
1 14
L. Mörl et al.
so, after integration the equation (276) can be written in explicit form (278) This equation describes the dependency of the air humidity from the dimen sionless bed height. By introducing a modified drying potential of the gas or rather a modified drying efficiency (compare with the drying efficiency of equation (31 7)) Yf*
= Y*Y*-- YinY
(279)
a dependency of the modified drying efficiency of the gas from the dimensionless bed height can be transformed to (280) Figures 78 and 79 show these dependencies according to equation (280) at different degree of wetting. We can write for the gas outlet at (bed = 1 in dimensionless form (281 ) Yf�ut = exp (-NTUcp) Considering equations (277) and (278) we can also express for case P v < < P the gas outlet humidity with real dimensions Yout at a certain bed height a be (282) Yout = Y* - ( Y* - Yin) exp - ßPa cp H d rha The mean modified drying efficiency of the gas in the fluidized bed stand with ij*
=
1(';bebde=d=O1
(
exp(-NT UCP(bed ) d(bed
)
= NTU1 cp [1 - exp(-NTUcp)]
(283)
Again, we get in real dimensions Y* - Yin [1 - exp(-NTUcp)] Y = Y* NTUcp
(284)
where the quantities ß, a and cp are still unknown. Before we calculate these quantities we want to give some remarks concerning Case 2. Here, the Stefan correction factor is between 0 and 1 and not negligible, depending on the value of y* and Y. Starting with equation (266) and using the introduced quantities, we get analogous to equation (276) (285)
115
Fluidized Bed Spray Granulation
- -----��------- ; +......
,
-
0.8
>, 40 min to reduce the spore
L. Mörl et al.
1 64
Table 1 3. Rye starch - parameters and results of fluidized bed spray granulation
Apparatus configuration Circulation Atomization Gas distributor Seeds supply Waste gas purification
Discharge Parameters Superficial gas velocity Gas inlet temperature Gas outlet temperature Specific evaporation Specific granulate throughput Mean residence time Granulate Particle size and form Flowability Stability Moisture content Solid density Bulk density
Open One two-fluid nozzle, lateral Opening ratio decreasing from the outside inwards External seeds supply, top down (star feeder) Cyclone with recycle of the separated dust into the fluidized bed Classifying tube 4.6-5.3 mjs 65-126 °C 38-47 °C 1 30-350 kgj(cross section area x hour), 0.8-2. 1 kgj (kg bed mass x hour) 23-60 kgj(cross section area x hour) 2.8-7.2 h 1 000-5000 Jlm; spherical, light blackberry-like Good Medium, dust-free 5-1 0 mass% 1 050 kgjm 3 640 kgjm 3
forming anaerobic and aerobic bacteria. The used granulation parameters can be found in Table 1 5. 7.4. G ranulation of hard metals and magnets 7.4. 1. Titanium carbides
For the sintering of hard metals, strength and compact as weil as free flowing carbide granules with a diameter between 0. 1 and 1 mm are necessary. To get a very high bulk density, a broad particle size distribution was useful. Fluidized bed granulation experiments were carried out with an aqueous suspension (solid content of 50 mass%) by using an additional binder [72]. Granulation parameters are summarized in Table 1 6. A spray-dried product was used as hold-up material. Figure 1 1 9 draws pictures of the titanium carbide particles.
1 65
Fluidized Bed Spray Granulation Table 1 4. Lysine - parameters and results of f1uidized bed spray granulation
Apparatus configuration Circulation Atomization Gas distributor Seeds supply Waste gas purification
Discharge Parameters Superficial gas velocity Gas inlet temperature Gas outlet temperature Specific evaporation
Open One single-fluid nozzle, top down Opening ratio decreasing from the outside inwards External seeds supply, top down (star feeder) Cyclone with recycle of the separated dust into the fluidized bed Classifying tube 6.4 m/s 1 45-149 °C 1 20-1 30 °C 1 20-300 k9/(cross section area hour), 0.7-1 .8 k9/ (kg bed mass hour) 26-1 06 k9/(cross section area hour) x
x
Specific granulate throughput Mean residence time Granulate Particle size and form Flowability Stability Moisture content Solid density Bulk density
x
1 .5-6.3 h 3000-8000 11m; spherical , light blackberry-like Good Medium, dust-free 5-1 0 mass% 1 1 90 kg/m3 7 1 5 kg/m 3
Fig. 1 1 7. Lysine - form and surface of granulates.
1 66
L. Mörl et al.
Fig. 1 1 8. Biosludge - form and surface of granulates.
Table 1 5. Biosludge - parameters and results of fluidized bed spray granulation
Apparatus configuration Circulation Atomization Gas distributor Seeds supply Waste gas purification
Discharge Parameters Superficial gas velocity Gas inlet temperature Gas outlet temperature Specific evaporation Specific granulate throughput Mean residence time Granulate Particle size and form Flowability Stability Moisture content Solid density Bulk density
Open One two-fluid nozzle, lateral Opening ratio decreasing from the outside inwards External seeds supply, top down (star feeder) Cyclone with recycle of the separated dust into the fluidized bed Classifying tube 6-1 0 mjs (depending on particle size) 1 40-1 50 °C 60-70 °C 1 000 kgj(cross section area x hour), 6-7 kgj(kg bed mass x hour) 90-140 kgj(cross section area x hour) 1 . 1-1 .8 h 3000-1 0000 flm, almost monodisperse; almost spherical, smooth surface Very good Stiff, dust-free 4-1 0 mass% 1 050 kgjm 3 630 kgjm3
1 67
Fluidized Bed Spray Granulation
Table 1 6. Titanim carbide - parameters and results of fluidized bed spray granulation
Apparatus configuration Circulation Atomization Gas distributor Seeds supply Waste gas purification
Discharge Parameters Superficial gas velocity Gas inlet temperature Gas outlet temperature Specific evaporation
Open One two-fluid nozzle, lateral Constant opening ratio External seeds supply, top down (batchwise) Cyclone with recycle of the separated dust into the f1uidized bed Classifying tube 7.2 mjs 1 56 °C 60-90 °C 540 kgj(cross section area hour), 0.65 kgj(kg bed mass hour) 550 kgj(cross section area x hour) x
x
Specific granulate throughput Mean residence time Granulate Particle size and form Flowability Stability Moisture content Solid density Bulk density
1 .5 h 1 00-1 500 11m, almost monodisperse; spherical Very good Stift, dust-free < 1 mass% 6000 kgjm 3 3600 kgjm 3
Fig. 1 1 9. Titanium carbide - form and surface of granulates.
1 68
L. Mörl et 81.
lable 1 7. Ferrite - parameters and results of fluidized bed spray granulation
Apparatus configuration Circulation Atomization Gas distributor Seeds supply Waste gas purification:
Discharge Parameters Superficial gas velocity Gas inlet temperature Gas outlet temperature Specific evaporation
Open One two-fluid nozzle, top down Opening ratio decreasing from the outside inwards External seeds supply, top down (star feeder) Cyclone with recycle of the separated dust into the fluidized bed Classifying tube 3.5-4.5 mjs 1 30 °C 60-70 °C 240-300 kgj(cross section area hour), 0:45-0.6 kgj(kg bed mass hour) 1 30-1 80 kgj( cross section area hour) x
x
Specific granulate throughput Mean residence time Granulate Particle size and form Flowability Stability Moisture content Solid density Bulk density
x
3-4 h 200-2500 /lm, almost monodisperse; spherical, smooth Very good Stift, dust-free 0.1-0.4 mass% 381 0 kg/m 3 1 800 kgjm 3
7.4. 2. Ferrite
Analogous to the production of carbides, for the production of magnets it is essential to design particles with a very low porosity and a very high-bulk density. The fluidized bed granulation of ferrite suspensions (solid content: 35.5 mass%) was able to produce such granules. The granulated preforms have very good magnetic properties (high-electric field strength) [73]. Table 1 7 and Fig. 1 20 summarize the results. 7.5. Granulation of milk products
Milk contains 85-91 mass% water, 3.4-6.1 mass% fat, 2.8-3.7 mass% proteins, 4.5-5 mass% lactose and 0.68-0.77 mass% minerals and many trace elements.
Fluidized Bed Spray Granulation
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Fig. 1 20. Ferrite - form and surface of granulates.
The fluidized-bed granulation of skim milk (solid content: 50 mass%) was realized to produce a free flowing, hydrophobie and storable (many years) anima I feed [74,75] . As hold-up material during the start-up, hackled milk granulates or casein particles with a diameter between 1 and 3 mm were used. Table 1 8 presents the parameters and Fig. 1 2 1 shows granule pictures.
7.6. Granulation examples of chemical products 7. 6. 1. Potash
Potash or potassium carbonate (K2 C0 3) is an important material for the glass industry. To prevent a demixing of the raw materials, a narrow particle size distribution is essential. Potash was atomized into a fluidized bed as aqueous solution with a solid content of 30-45 mass% [76-78]. The produced granules are monodisperse, attrition-resistant, free flowing and dust-free (Fig. 1 22). Again, Table 19 summarizes the parameters.
7. 6. 2. Activated carbon
The production of activated carbon from bones, wood or other renewable ma terials yields a fine activated carbon dust. We granulated this dust together with a binder suspension (solid content: 1 0-20 mass%) to get particles in a size range of 1-6 mm [79,80]. Table 20 explains the parameters, Fig. 1 23 shows the form of the granules. Subsequently, the activation of the granules was carried out by exclusion of air at temperatures between 600 and 1 000 °C.
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Table 1 8. Skim milk concentrate - parameters and results of fluidized bed spray granulation
Apparatus configuration Circulation Atomization Gas distributor Seeds supply Waste gas purification
Discharge Parameters Superficial gas velocity: Gas inlet temperature Gas outlet temperature Specific evaporation Specific granulate throughput Mean residence time Granulate Particle size and form Flowability Stability Moisture content Solid density Bulk density
Open One two-fluid nozzle, lateral Opening ratio decreasing from the outside inwards External seeds supply, top down (star feeder) Cyclone with recycle of the separated dust into the fluidized bed Classifying tube 2.8--3. 1 m/s (depending on particle size) 1 02-1 35 °C (due to the low thermal resistance of the product) 48-72 °C 1 00-1 1 0 kg/(cross section area x hour), 0.55-0.65 k9/(kg bed mass x hour) 1 00-1 1 0 kg/( cross section area x hour) 1 .6-1 .8 h 3000-8000 11m, almost monodisperse; spherical, light Blackberry-like Very good Stift, dust-free 1 .5 mass% 1 263 kg/m3 758 kg/m3
Fig. 1 2 1 . Skimmed milk concentrate - form and surface of granulates.
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Fig. 1 22. Potash - form and surface of granulates.
Table 1 9. Potash
_.
parameters and results of fluidized bed spray granulation
Apparatus configuration Circulation Atomization Gas distributor Seeds supply Waste gas purification
Discharge Parameters Superficial gas velocity Gas inlet temperature Gas outlet temperature Specific evaporation
Open One two-fluid nozzle, top down Opening ratio decreasing from the outside inwards External seeds supply, top down (star feeder) Cyclone with recycle of the separated dust into the fluidized bed Classifying tube 3.3 m/s 1 65 °C 80-90 °C 1 1 0-380 kg/(cross section area hour), OA-1 A kg/ (kg bed mass hour) 60-250 k9/(cross section area x hour) x
x
Specific granulate throughput Mean residence time Granulate Particle size and form Flowability Stability Moisture content Solid density Bulk density
1 . 1 -4.5 h 1 000-31 50 Jlm, almost monodisperse; spherical Good Stift, dust-free < 1 mass% 1 990 kg/m 3 1 1 94 kg/m 3
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Table 20. Actibated carbon - parameters and results of fluidized bed spray granulation
Apparatus configuration Circulation Atomization Gas distributor Seeds supply Waste gas purification
Discharge Parameters Superficial gas velocity Gas inlet temperature Gas outlet temperature Specific evaporation Specific granulate throughput Mean residence time Granulate Particle size and form Flowability Stability Moisture content Solid density Bulk density
Open One two-fluid nozzle, lateral Opening ratio decreasing from the outside inwards External seeds supply, top down (star feeder) Cyclone with recycle of the separated dust into the fluidized bed Classifying tube 4.4 m/s 1 50-200 °C 60-90 °C 380-570 kg/(cross section area hour), 2.5-3.7 k9/ (kg bed mass x hour) 50-1 30 kg/( cross section area hour) x
x
1 .2-3.2 h 1 000-6000 J.lm, almost spherical Good Good, dust-free < 1 mass% 1 1 00 kg/m 3 660 kg/m3
Fig. 1 23. Activated carbon - form and surface of granulates.
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Fluidized Bed Spray Granulation
7. 6. 3. Lead sulphate
Lead sulphate is a stabilizer during the production of polyvinyl chloride. An aqueous suspension with a solid content of 50 mass% was injected into a flu idized bed granulator [81 ] to produce dust-free, free flowing and very strength granules. Table 21 contains the parameters and Fig. 1 24 shows the nearly ideal spherical particles with a narrow-size distribution. In a second step, a coating with stearate is possible.
7.7. Granulation of animal food 7. 7. 1. Sunflower protein
The fluidized bed granulation of a suspension of proteins from a sunflowers sus pension (solid content: 1 0-20 mass%) was realized in Refs. [44,49,82-84]. The large granules (2-20 mm) are spherical, storable (many decades) and water Table 21 . Lead sulphate - parameters and results of fluidized bed spray granulation
Apparatus configuration Circulation Atomization Gas distributor
Seeds supply Waste gas purification Discharge Parameters Superficial gas velocity Gas inlet temperature Gas outlet temperature Specific evaporation Specific granulate throughput Mean residence time Granulate Particle size and form Flowability Stability Moisture content Solid density Bulk density
Open One two-fluid nozzle, top down Opening ratio decreasing from the outside inwards Without seeds supply, dust discharge, 50% dust production Cycione and filter with recycle of the separated dust into the fluidized bed Classifying tube 3-5 mjs (depending on particie size) 1 40-1 50 °C 90-1 00 °C 250-400 kgj(cross section area hour), 0.5-0.8 kgj(kg bed mass hour) 250-400 kgj(cross section area hour) 1 . 1-1 .9 h x
x
x
1 00-3000 Jlm, almost monodisperse; spherical, smooth Very good Stift, dust-free < 1 mass% 3900 kgjm3 2260 kgjm3
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Fig. 1 24. Lead sulphate - form and surface of granulates.
resistant. Spray dried proteins are water soluble and only few weeks storable. The granulation parameters can be found in Table 22. Photos are iIIustrated in Fig. 1 25.
7. 7.2. Swines blood
In slaughterhouses, large masses of swine's blood accumulate with a high con tent of proteins and minerals. This blood is only storable for a few hours. For an application as animal food, a blood suspension with a solid content of 1 0-1 5 mass% was granulated in a fluidized bed [85]. Salmonella as weil as pathogen sprouts was deadened. Table 23 and Fig. 1 26 show experimental pa rameters as weil as granule photos.
7.8. Granulation of fertilizers 7.8. 1 . Urea
Urea is an important nitrogen fertilizer and finds also application as animal food. The traditional use of prill towers (height: 40 m) for the solidification of urea melts (melting point 1 32.7 0c) produces only particles with 2 mm diameter. For fertilization by using an airplane, particles with a diameter of 4 mm are more suitable. The fluidized bed granulation of urea melts (95°C) with a solid content of 90-95 mass% was successfully realized [5,50,86-91], (see Table 24, Fig. 1 27). To influence the solubility, the granules were coated with c1ay in a second step.
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Fluidized Bed Spray Granulation
Table 22. Sunflowers protein - parameters and results of fluidized bed spray granulation
Apparatus configuration Circulation Atomization Gas distributor
Seeds supply Waste gas purification Discharge Parameters Superficial gas velocity Gas inlet temperature Gas outlet temperature Specific evaporation Specific granulate throughput Mean residence time Granulate Particle size and form Flowability Stability Moisture content Solid density Bulk density
Fig.
Open One two-fluid nozzle, top down Opening ratio decreasing from the outside inwards (1 8.45%, 8.33%, 5.33%) External seeds supply, top down (star feeder) Cyclone with recycle of the separated dust into the fluidized bed Classifying tube 2--1 0 m/s (depending on particle size) 1 00-1 80 °C (due to the low thermal resistance of the product) 60-90 °C 400-1 000 kg/(cross section area hour), 0.5-3 k9/ (kg bed mass hour) 50-200 k9/(cross section area hour) x
x
x
1-4. 1 h 2000-20000 Jlm, almost monodisperse; spherical, smooth Good Stift, dust-free 4-1 0 mass% 1 500 kg/m 3 900 kg/m 3
1 25. Sunflowers protein - form and surface of granulates.
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Table 23. Swines blood- parameters and results of fluidized bed spray granulation
Apparatus configuration Circulation Atomization Gas distributor
Seeds supply Waste gas purification Discharge Parameters Superficial gas velocity Gas inlet temperature Gas outlet temperature Specific evaporation
Open One two-fluid nozzle, top down Opening ratio decreasing from the outside inwards (25%, 1 3%, 9.5%) Without seeds supply Cyclone with recycle of the separated dust into the fluidized bed Classifying tube 5-1 0 m/s (depending on particle size) 1 40-1 60 °C (due to the low thermal resistance of the product) 1 00-1 30 °C 500-1 000 kg/(cross section area hour), 2-4 k9/ (kg bed mass hour) 50-1 50 kg/(cross section area x hour) x
x
Specific granulate throughput Mean residence time Granulate Particle size and form Flowability Stability Moisture content Solid density Bulk density
1 .3-4. 1 h 1 000-8000 �m; spherical, blackberry-like Good Medium, dust-free 1-3 mass% 1 1 00 kg/m 3 600 kg/m3
Fig. 1 26. Swines blood - form and surface of granulates.
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Fluidized Bed Spray Granulation Table 24. Urea- parameters and results of fluidized bed spray granulation
Apparatus configuration Circulation Atomization Gas distributor
Seeds supply Waste gas purification Discharge Parameters Superficial gas velocity Gas inlet temperature Gas outlet temperature Specific evaporation
Open One single-fluid nozzle Opening ratio decreasing from the outside inwards External seeds supply, top down Cyclone with recycle of the separated dust into the fluidized bed Classifying tube 4.4 mjs 35-60 °C 40-55 °C 1 5-55 kgj(cross section area hour), 0.08-0.3 kgj(kg bed mass hour) 290-530 kgj(cross section area hour) 0.4-0.7 h x
x
Specific granulate throughput Mean residence time Granulate Particle size and form Flowability Stability Moisture content Solid density Bulk density
x
1 500-7000 J.lm, almost monodisperse; spherical, smooth Very good Stiff, dust-free < 0.5 mass% 1 500 kgjm 3 900 kgjm 3
Fig. 1 27. Urea - form and surface of granulates.
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Fig. 1 28. Ammonium sulphate - form and surface of granulates.
7. 8. 2. Ammonium sulphate
Ammonium sulphate is also a nitrogen fertilizer, but more inactive than urea and will therefore be deployed before drilling. Ammonium sulphate was granulated in a fluidized bed by using an aqueous solution (solid content: 42 mass%) [92]. Figure 1 28 shows the form of the free flowing and dust-free granules, in Table 25 the parameters are summarized. The throughput could be increased when using higher temperatures. 7.9. Granulation of Glue sewage
Industrial glue sewages (solid content: 42 mass%) contain different ingredients, which may be obtained in concentrated form as dry substance due to fluidized bed granulation [93]. The produced particles are very stiff. The hold-up material was dry glue sewages powder as weil sand spheres. Table 26 presents the parameters, and Fig. 1 29 illustrates photos of the granules.
8. CONCLUSIONS
Normally, the granulation of particles in fluidized beds involves different kinetics such as formation of seeds, growth, breakage and agglomeration. The equations of these kinetics are usually non-linear, and this property in combination with continuous product classification and recycling of particle fractions can lead to
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Fluidized Bed Spray Granulation
Table 25. Ammonium sulphate - parameters and results of fluidized bed spray granu lation
Apparatus configuration Circulation Atomization Gas distributor
Seeds supply Waste gas purification Discharge Parameters Superficial gas velocity Gas inlet temperature Gas outlet temperature Specific evaporation
Open One two-fluid nozzle, top spray Opening ratio decreasing from the outside inwards External seeds supply, top down (star feeder) Cyclone with recycle of the separated dust into the fluidized bed Classifying tube 6 m/s 1 45 °C (higher temperatures would be useful) 90-1 00 °C 1 60-250 kg/(cross section area hour), 0.5-0.9 k9/(kg bed mass hour) 1 30-1 80 kg/( cross section area hour) x
x
Specific granulate throughput Mean residence time Granulate Particle size and form Flowability Stability Moisture content Solid density Bulk density
x
1 .5-2.5 h 2000-6000 Jlm, almost monodisperse; spherical, smooth Very good Stiff, dust-free 0.1-0.4 mass% 1 770 kg/m 3 1 060 kg/m 3
self-sustained oscillations of particle size distributions and temperature and con centration progressions of the gas and solid phase. However, the focus of this article is to analyze simple approximations for the pneumatic behaviour, partic/e growth, particle wetting and their influence on the operation area of fluidized-bed granulation The aim is to show simple calculation procedures for scale-up of these types of granulator. The approximations are able to estimate particle residence times, partic/e surface areas, particle and gas temperatures, or time-dependent partic/e diameters, as weil as pneumatic operation areas for both operation modes: dis continuous and continuous granulation. So we introduced a surface proportional granule growth kinetic as weil as a surface proportional degree of wetting model.
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Table 26. Glue sewage - parameters and results of f1uidized bed spray granulation
Apparatus configuration Circulation Atomization Gas distributor
Seeds supply Waste gas purification Discharge Parameters Superficial gas velocity Gas inlet temperature Gas outlet temperature Specific evaporation Specific granulate throughput Mean residence time Granulate Particle size and form Flowability Stability Moisture content Solid density Bulk density
Open One two-fluid nozzle, lateral Opening ratio decreasing from the outside inwards External seeds supply, top down (star feeder) Cyclone with recycle of the separated dust into the fluidized bed Classifying tube 5.6 m/s 1 48 °C (higher temperatures would be useful) 80 °C 400 k9/(cross section area x hour), 1 .8 k9/(kg bed mass x hour) 80 k9/(cross section area x hour) 3.5 h 1 000-4000 )lm; spherical, light blackberry-like Very good Very stiff, dust-free < 1 mass% 2000 kg/m 3 1 200 kg/m 3
Fig. 1 29. Glue sewage - form and surface of granulates.
Fluidized Bed Spray Granulation
1 81
For continuous granulation, models for the ideal c1assifying particle discharge as weil as for the non-c1assifying particle discharge were derived. For the first case, a discharge probability into a classifying tube was presented, using design parameters of the plant. The discontinuous granulation is described by case studies for the batch and semi-batch process, which are weil applicable to the coating of particles, for the start-up phase as weil as for the transition period between cycle process parameter changes. The time-dependent calculation of the layer thickness can help pharmacists to evaluate the quality of the coated layers. The mixing behaviour has an important influence onto the effectiveness of drying and thus on the granulation. Additionally, a model for the application of fluidized bed granulation with superheated steam has been developed. For the evaluation of operation modes, different c10sed or semi-c1osed systems were discussed. Notation
A A LAp �A� Ap Ar cp d, D dp
� F
9 G h H H* Ahv Ahvü K L
Le
M Mp
�
rh
M M* M n
specific particle surface (m2jm3 ) surface area (m2 ) total surface area of all particles (m 2 ) dimensionless total surface area of all particles related to t = 0 s mean surface area of a particle (m2 ) Archimedes number (m2 ) specific heat capacity at constant pressure (Jj(kg K)) diameter (m) mean surface based diameter of a particle (m) dimensionless particle diameter force (N) acceleration of gravity (m/s2 ) growth rate (mjs) specific enthalpy (Jjkg) height (m) normalized height specific heat of evaporation of the water (Jjkg) specific heat of evaporation of the water at O°C (Jjkg) flow coefficient of the air distributor length (m) Lewis number mass (kg) mean mass of a particle (kg) dimensionless particle mass mass flux (kgj(s m 2 )) mass flow rate (kgjs) dimensionless mass flow rate molar mass (kgjmol) particle number
1 82 NTU
ncirc 'L; np 'L; np np qo
q� %
-M
qü 'L; np -M q2 q3 q� M q3,V q3 'L; np p p
Pv P� LlP R
RRe
s Sc Sh S8 S�oat t T T tv v V
v v* Vp
V
x y
y Y* z
L. Mörl et al.
number of transfer units number of particle circulations total number of all particles dimensionless total number of all particles related to t = 0 s particle flow (1js) number density distribution ( 1 jm) mass-based number density distribution (1j(kg m» mass-based number density distribution in range d p , o ::::;; d p < dp,out ( 1 /(kg m» number density distribution related to the particle number ( 1 jm) mass-based surface area density distribution (m 2j(kg m» mass density distribution (k9/ (kg m» mass-based mass density distribution (kgj(kg m» mass-based volume density distribution (m 3j(kg m» mass density distribution related to the particle number ( 1 jm) collision probability system pressure (Pa) vapour pressure (Pa) saturation vapour pressure (Pa) pressure drop (Pa) specific gas constant (kgj(kg K» universal gas constant (Jj(mol K» Reynolds number thickness (m) Schmidt number Sherwood number spacing (m) dimensionless thickness of the coated layer time (s) hit temperature (K) residence time (s) velocity (m/s) volume (m 3) mean velocity (mjs) dimensionless velocity related to t = 0 s mean volume of a particle (m3) volume flow (m 3jh) water content (mass%) fraction of the sprayed solid which deposits on the granules (mass%) humidity (kg waterjkg dry air) saturation humidity (kg waterjkg dry air) length coordinate (m)
Fluidized Bed Spray Granulation
Greek symbols �
iXst
ß (j
� �h F E
I]
1]*
9
�o 9
o o o v
P Pp Pp Pp v
� �bed
(J r
cp CPs
CPSy Ij;
heat transfer coefficient (W/(m 2 K)) statistical fixed bed flow angle (0) mass transfer coefficient (m/s) diffusion coefficient (m2/s) difference liquid film thickness (m) porosity of the fluidized bed or void volume (m 3/m 3) drying efficiency modified drying efficiency temperature (0C) wet bulb temperature CC) mean temperature (0C) time function (s) dimensionless temperature mean dimensionless temperature kinematic viscosity (m2 /s) density (kg/m 3 ) mean particle density (kg/m 3) dimensionless mean particle density dimensionless particle density bypass fraction drag coefficient dimensionless bed height standard deviation (mm) dimensionless time degree of wetting shape factor of spheric form Stefan correction factor opening ration of the sieve boUom
Subscripts
a Ac app b B bed coat core CSTR
air acceleration apparatus bubbles width fluidized bed coated particle layer core of particle continuous stirred tank reactor o drag distributor sieve boUom resp. air distributor
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eff elu fed G Gr in
L
Li max mf min nuc out p
PFTR
S
Sat sep St tot v W 0
effective elutriation added gas gravity at inlet or input liquid litt maximal minimal fluidization minimal nuclei at outlet or discharge particle plug flow tubular reactor solid saturation classifying tube (separator) steam total vapour water state at time t = 0 or entry state
S uperseripts
fluidized bed added nuclei or seed
bed fed nuc
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J . F . Richardson, W.N. Zaki, Trans. Inst. Chem. Eng. 32 ( 1 954) 35-53. D. Sathiyamoorthy, C.S. Rao, Powder Technol. 30 ( 1 98 1 ) 1 39-1 4 1 . C .D'A Hunt, D . N . Hanson, C.R. Wilke, AIChE j. 1 (4) ( 1 955) 441-45 1 . RA McAllister, P.H. McGinnis Jr. , CA Plank, Chem. Eng. Sci. 9 ( 1 958) 25-35. L. Mörl, M. Mittelstraß, J. Sachse, Chem. Technol. 29 ( 1 0) ( 1 977) 540-541 . L. Mörl, J . Sachse, L. Schuart, M . Mittelstraß, Chem. Technol. 3 1 (6) ( 1 979) 295-297. L. Mörl, Wiss. Z. Technol. Hochsch. Magdeburg 24 (6) ( 1 980) 1 3-1 9. L . Mörl, M . Mittelstraß, J . Sachse, Chem. Technol. 30 (5) ( 1 978) 242-245. L. Mörl, Anwendungsmöglichkeiten und Berechnung von Wirbelschichtgranulation strocknungsanlagen, Doctoral thesis B, TH Magdeburg, 1 980. I. Jännert, Ingenieurbeleg 77/24, Technische Hochschule Otto-von-Guericke Ma gdeburg, Sektion Apparate- und Anlagenbau, 1 977. L. Mörl, H.-J . Künne, Wiss. Z. Technol. Hochsch. Magdeburg 26 ( 1 ) ( 1 982) 5-8. J . Sachse, L. Mörl, R. Schmidt, M. Mittelstrass, Diskontinuierlich arbeitender Wirbelschichttrockner für die Trocknung von Lösungen oder Suspensionen, Chem. Technol. 31 ( 1 1 ) ( 1 979) 560. J . Sachse, Wirbelschichtgranulationstrocknung von Proteiinsuspensionen, Doctoral thesis A, Technische Hochschule Otto von Guericke Magdeburg, 1 980. N A Schachova, A I . Ritschkov, Chimitscheskoje Promischlennost 1 1 ( 1 963), Soviet Union, pp. 856-859. NA Schachova, A I . Ritschkov, Chimitscheskoje Promischlennost 6 (1 967), Soviet Union, 459-462. V. Gnielinski, Wärme- und Stoffübertragung in Festbetten, VDI-Wärmeatlas, 9. Au flage, Gf1-Gf3, VDI-Verlag, Düsseldorf, ISBN 3-540-4 1 20 1 -8, 1 980. R. Schirmer, Die Diffusionszahl von Wasserdampf-Luftgemischen und die Verdamp fungsgeschwindigkeit, VDI Beiheft Verfahrenstechnik 1 70, 1 938. W. Göhler, Höhere Mathematik - Formeln und Hinweise, Verlag Harri Deutsch Thun Frankfurt, ISBN 3-8 1 71 - 1 0 1 8-9, 1 2 . Auflage, ( 1 990) 63. S. Heinrich, M . I hlow, M . Henneberg, L. Mörl, E. Machnow, Drying Technol. 20 ( 1 ) (2002) 1 74-194. L. Mörl, H .-J . Künne, L. Krell , J . Sachse, Powder Technol. 30 ( 1 98 1 ) 99-1 04. L. Mörl, L. Krell , H .-J. Künne, J . Sachse, J . Kliefoth , Studie zur Granuliertrocknung von Mais-Quellwasser in der Wirbelschicht, Forschungsbericht an der Sektion Apparate- und Anlagenbau, Technische Hochschule Otto von Guericke Magdeburg, 1 98 1 . L . Mörl, L . Krell, H .-J . Künne, J . Sachse, J . Kliefoth, Studie zur Granuliertrocknung von Rohwürze in der Wirbelschicht, Forschungsbericht an der Sektion Apparate- und Anlagenbau, Technische Hochschule Otto von Guericke Magdeburg, 1 98 1 . H .-J. Künne, L . Krell , L . Mörl, Wirbelschichtgranulationstrocknung von Zellsaft mit und ohne Zugabe von Futterkalk, Forschungsbericht an der Sektion Apparate- und An lagenbau, Technische Hochschule Otto von Guericke Magdeburg, 1 980. M. Mittelstraß, H .-J . Künne, L . Mörl, J. Sachse, L. Krell , Studie zur Trocknung und Granulierung von Kalziumlaktat-Schmelzen in der Wirbelschicht, Forschungsbericht an der Sektion Apparate- und Anlagenbau, Technische Hochschule Otto von Gue ricke Magdeburg, 1 979. H. Berg mann, P. Löwe, P. Heinemann, A Piehier, J. Grünzel, K. Leuschner, L. Mörl, L. Krell, Chem. Techn. 39 ( 1 0) ( 1 987) 432-435. H .-J . Künne, L. Krell, G . Krüger, J . Kliefoth, G . Grünzel, L. Mörl, Neurervereinbarung zur Granulationstrocknung von Hefesahne in der Wirbelschicht, Bericht VEB Gärungschemie Dessau, 1 975. H .-J. Künne, L. Krell , G . Krüger, J . Kliefoth , G. Grünzel, L. Mörl, Studie zur Gran ulationstrocknung von Gärhaushefe in der Wirbelschicht, Forschungsbericht an der Sektion Apparate- und Anlagenbau, Technische Hochschule Otto von Guericke Magdeburg, 1 984.
[46] [47] [48] [49] [50] [51 ] [52] [53] [54] [55] [56] [57]
[58] [59] [60]
[61 ] [62] [63]
Fluidized Bed Spray Granulation
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[64] H .-J . Künne, L. Krell, L. Mörl, G. Krüger, J. Kliefoth, G. Grünzel, L. Mörl, Auslegung einer Anlage zur Granulationstrocknung von Futterhefe in der Wirbelschicht, Forschungsbericht an der Sektion Apparate- u nd Anlagenbau, Technische Ho chschule Otto von Guericke Magdeburg, 1 979. [65] L. Mörl, L. Krell, H .-J . Künne, J. Kliefoth, Granulationstrocknung von Roggenstärkefu gat i n der Wirbelschicht, Forschungsbericht an der Sektion Apparate- und An lagenbau, Technische Hochschule Otto von Guericke Magdeburg, 1 984. [66] M. M ittelstraß, L. Mörl, L. Krell , H .-J . Künne, J. Sachse, Zur Granulationstrocknung von Lysinkonzentrat in der Wirbelschicht, Forschungsbericht an der Sektion Apparate- und Anlagenbau, Technische Hochschule Otto von Guericke Magdeburg, 1 979. [67] A. Höfler, H. Alt, C. Klasen, F. Heinz, U. Hertz, L. Mörl, R. Schütte, Verfahren zur Herstellung eines Tierfuttermittelzusatzes auf Fermentationsbrühe-Basis, German Patent - DE 1 9 621 930 C1 , DEGUSSA AG, Frankfurt/Main, 1 996. [68] L. Mörl, L. Krell, H .-J. Künne, G. Krüger, J . Kliefoth, H. Grau, W. Behns, B . Ebenau, Verfahren zur kontinuierlichen Herstellung von L-Lysinfutterkonzentrat in granulierter Form, GDR Patent DD - WP A23K/262 8 1 3 1 , Forschungszentrum Biotechnologie Berlin, 1 984. [69] H .-J . Künne, L. Krell, L. Mörl, J. Sachse, Bericht zur Trocknung und Granulierung von Bioschlamm in der Wirbelschicht, Forschungsbericht an der Sektion Apparate- und Anlagenbau, Technische Hochschule Otto von Guericke Magdeburg, 1 979. [70] M. Mittelstraß, H .-J . Künne, L. Krell, L. Mörl, H. Koriath, K. Ebert, Trocknung, Granu lierung und Hygienisierung von Bioschlamm nach dem Wirbelschichtverfahren, Gem einsamer Forschungsbericht der Sektion Apparate- und Anlagenbau, Technische Hochschule Otto von Guericke Magdeburg, dem Institut für Düngungsforschung der Akademie der Landwirtschaftswisenschaften der DDR, Potsdam und dem Be zirksinstitut für Veterinärwesen Potsdam, 1 979. [71 ] K. Ebert, H .-J . Künne, L. Mörl, G.J. Grünzel, R. Bergmann, R. EIspaß, M. Mittelstraß, J. Sachse, L. Krell, Verfahren zur Trocknung und Hygienisierung eiweißhaitiger Sus pensionen, GDR Patent DD - WP F26B/2 1 6 251 , Akademie der Land wirtschaftswissenschaften der DDR, 1 979. [72] L. Mörl, L. Krell, H .-J . Künne, J. Kliefoth , J. Schmidt, Studie zur Wirbelschichtgranu lierung von Titancarbid und Wolframcarbid, Forschungsbericht an der Sektion Apparate- und Anlagenbau, Technische Hochschule Otto von Guericke Magdeburg, 1 986. [73] M. Mittelstraß, H .-J . Künne, L. Mörl, J . Sachse, L. Krell, Studie zur Trocknung und Granulierung von Ferritsuspensionen in der Wirbelschicht, Forschungsbericht an der Sektion Apparate- und Anlagenbau, Technische Hochschule Otto von Guericke Ma gdeburg, 1 976. [74] L. Krell, H .-J. Künne, L. Mörl, J. Sachse, S. Schmidt, Granulationstrocknung von Ma germilchkonzentrat i n der Wirbelschicht, Forschungsbericht an der Sektion Apparate und Anlagenbau, Technische Hochschule Otto von Guericke Magdeburg, 1 982. [75] J. Schmidt, L. Krell, L. Mörl, H .-J. Künne, U. Wendler, L. Hartmann, Verfahren zur Herstellung und Verwendung granuliergetrockneter Magermilch, GDR Patent DD WP A23C/2729 474, VEB Schwermaschinenbaukombinat Magdeburg, 1 985. [76] R. Kohlschmidt, Inbetriebnahme einer großtechnischen Wirbelschichtanlage zur Granulation von Pottasche, Sektion Apparate- u nd Anlagenbau der Otto von Gue ricke-Universität Magdeburg, I ngenieurbeleg, 1 983. [77] H .-J. Künne, L. Mörl, J . Sachse, L. Krell, Studie zur Granulierung von Pottasche in der Wirbelschicht, Forschungsbericht an der Sektion Apparate- und Anlagenbau, Tech nische Hochschule Otto von Guericke Magdeburg, 1 980. [78] H .-J . Künne, L. Krell, L. Mörl, J . Sachse, Wirbelschichtverfahren zur Herstellung kalzinierter und staubfreier Pottaschegranulate, GDR Patent D D - WP C01 D/2407 802, Technische U niversität Magdeburg, 1 982.
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[79] H .-J. Künne, L. Krell , L. Mörl, A. Lehnert, K. Radecke, Verfahren zur Herstellung konditionierter Adsorbentien, GDR Patent D D - WP C01 B/3 1 48 864, VEB Leuna Werke, 1 988. [80] A. Lehnert, Granulierung von Aktivkohlepulvern in der Wirbelschicht, Diplomarbeit, TH OUo von Guericke Magdeburg, 1 984. [81 ] M. MiUelstraß, H .-J. Künne, L. Mörl, L. Krell, Studie zur Trocknung und Granulierung von Bleisulfatsuspensionen in der Wirbelschicht, Forschungsbericht an der Sektion Appa rate- und Anlagenbau, Technische Hochschule Otto von Guericke Magdeburg, 1 978. [82] L. Krell, H .-J. Künne, J. KIiefoth, L. Mörl, Verfahren zur Granuliertrocknung von Pro teinhydrolysaten und Fleischaromakonzentraten, G DR Patent DD - WP A23L/2460 1 81 1 6, I nstitut für Getreideverarbeitung der Akademie für Landwirschaftswissenschaf ten der DDR Potsdam-Bomim, 1 982. [83] H .-J . Künne, Zur E ntwicklung und volkswirtschaftlichen Nutzung der Wirbelschicht technik, Doctoral thesis B, Technische Hochschule OUo von Guericke Magdeburg, 1 986. [84] J . Sachse, R. EIspaß, L. Mörl, Trocknung von Proteinsuspensionen, Forschungsbe richt an der Sektion Apparate- und Anlagenbau, Technische Hochschule OUo von Guericke Magdeburg, 1 972. [85] M. MiUelstraß, H .-J . Künne, L. Mörl, D. Schneider, J. Sachse, Trocknung von Blut in einem Wirbelschichtapparat, Forschungsbericht an der Sektion Apparate- und An lagenba u , Technische Hochschule OUo von Guericke Magdeburg, 1 976. [86] S.M. Danov, Trocknung und Granulierung von Harnstofflösungen in der Wir belschicht, Chimitscheskoje Promischlennost 6, Soviet Union, 1 966, 453-456. [87] H .-J . Künne, M. MiUelstrass, L. Mörl, J. Baruizki, D. Braumann, M. H uth, Chem. Techn. Rundschau 1 2 (2) ( 1 980) 1 3-23. [88] M. M iUelstraß, H .-J. Künne, L. Mörl, J. Sachse, Studie zur Granulierung von Harnstoff i n der Wirbelschicht, Forschungsbericht an der Sektion Apparate- und Anlagenba u , Technische Hochschule OUo von Guericke Magdeburg, 1 977. [89] M. MiUelstraß, H .-J. Künne, L. Mörl, J. Sachse, L. Krell , Studie zur Granulierung von Harnstoffschmelzen in der Wirbelschicht, Forschungsbericht an der Sektion Appa rate- und Anlagenbau, Technische Hochschule OUo von Guericke Magdeburg, 1 978. [90] M. MiUelstraß, H .-J. Künne, L. Mörl, J . Sachse, L. Krell, Studie zur Granulierung von FuUerharnstoff, Forschungsbericht an der Sektion Apparate- und Anlagenbau, Tech nische Hochschule OUo von Guericke Magdeburg, 1 979. [91 ] M. MiUelstraß, H .-J. Künne, L. Mörl, J. Sachse, L. Krell , Studie zur Granulierung von Harnstoff mit Wirkstoffzusatz in der Wirbelschicht, Forschungsbericht an der Sektion Apparate- und Anlagenbau, Technische Hochschule OUo von Guericke Magdeburg, 1 979. [92] H .-J . Künne, L. Mörl, J. Sachse, L. Krell , Studie zur Granulierung von Ammonium sulfat in der Wirbelschicht, Forschungsbericht an der Sektion Apparate- und An lagenba u , Technische Hochschule OUo von Guericke Magdeburg, 1 980. [93] L. Mörl, L. Krell, H .-J. Künne, J . Kliefoth, J . Schmidt, Studie zur Wirbelschichtgran ulation von Abwasser, Forschungsbericht an der Sektion Apparate- u nd Anlagenbau, Technische Hochschule OUo von Guericke Magdeburg, 1 986.
CHAPTER 3 Extrus ion-Sp he ronisation D . l a n Wilso n , * and Sarah L Rou g h
Department o f Chemical Engineering, University o f Cambridge, New Museums Site, Pembroke Street, Cambridge CB2 3RA, UK C ontents
1 . Scope and introduction 2. Equipment 2. 1 . Combination 2.2. Extrusion 2.3. Spheronisation 2.4. Drying and finishing 3. Mechanics and mechanisms 3. 1 . Rheology 3.2. Liquid-phase effects in extrusion 3.3. Extrusion-spheronisation interactions 3.4. Spheronisation 4. Formulation 5. Control 5. 1 . Combination 5.2. Extrusion 5.3. Spheronisation 6. Challenges and future developments Acknowledgments References
1 89 191 191 1 92 1 96 1 99 200 200 204 205 207 209 213 213 213 214 214 214 215
1 . SCOPE AND I NTRODU CTION
Extrusion-spheronisation (E-S) is used to manufacture spherical or cylindrical pellets by extruding a semi-solid wet powder mass through a single die, a series of dies or a screen featuring many holes, then breaking up and rounding the extrudate on a rotating friction plate. E-S is also known as extrusion-marumeri sation, where a Marumeriser is the name for the spheroniser originating from the Japanese for 'pellet', which appeared on the original Fuji-Paudal patent for their device. When optimised, the process yields a dense and quite spherical product with good integrity. These properties can be tailored via coating, which is *Corresponding author. E-mail: diw1 1 @cam.ac.uk
Granulation Edited by A.D. Salman. M.J. Hounslow and J. P. K. Seville ( 2007 Elsevier B.v. All rights reserved
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amenable to the spherical shape of the granules [1]. E-S is used widely in the manufacture of controlled release pharmaceuticals, polymers, detergents, ferti lisers and herbicides (particularly water dispersible granule forms). The spher onisation step is often omitted when cylindrical pellets are the desired product form, as in fertiliser and herbicide manufacture where the extrudates can be broken up in a fluidised bed drier to give products with the required size. This chapter will focus on the use of E-S in pharmaceutical granulation and related applications, where the material extruded is a wet powder mass and extrudate diameters are in the range of 500-1 500 flm. In practice, the largest particle sizes achievable are 5 mm. The free-flowing granules obtained by E-S are used in tabletting or in filling capsules for oral dosage forms. This particular process is favoured by the pharmaceutical industry since pellets formed with a small amount of active ingredient show a slower release profile compared to those made by other techniques. The closely related topic of pelletising, which employs similar devices to extrude drier materials to give generally larger gran ules, is not covered. The E-S process involves four steps, as iIIustrated in Fig. 1 : �
(i) Combination. The wet mass is prepared by combining particulate solids with a liquid binder. This is often termed 'granulation' in the E-S literature and employs standard granulation equipment, but the aim is to generate a well mixed material rather than a specific particle size distribution. (ii) Extrusion. The wet mass is compacted to a density approaching its saturation density (expelling entrapped air) and shaped into cylindrical extrudates by forcing it through circular dies or multi-holed screens. Non-circular dies are rarely used. The combination and extrusion steps can be combined in twin screw extruders. (iii) Spheronisation (or marumerisation). The extrudate is broken up into smaller rods and rounded by the action of a horizontal rotating friction plate, with typical operating speeds of 1 000 rpm. (iv) Drying and finishing. The pellets are then dried and coated as required. The pellets formed after spheronisation are quite firm and can be conventionally handled in this 'wet' stage; hence fluidised-bed drying is suitable for the removal of the granulation liquid. �
The influence of extrusion on the final granules is currently difficult to quantify: with many formulations one cannot form spheres from the wet powder mass directly - it first needs to be compacted and formed. The correct formulation will give spheres that are stable on the spheroniser plate for up to 30 min [1], and quality - quantified by granule shape and size distribution - will be relatively insensitive to variations in operating parameters. It is also difficult to predict
191
Extrusion- Spheronisation powders and liquid
wet mass
extrusion
extrudate
spheronisation
[
spheroid
'�I"g ao' "",,h'",
•
Fig.
granule or pellet
1 . Schematic of steps during E-S.
spheronisation performance simply from monitoring the extrudate quality, as not all smooth and well-compacted extrudates give good spheres [2].
2. EQUIPMENT 2.1 . Combination
Most types of powder mixers have been reported for preparing wet masses, including planetary, Z-blade, high-shear and paddle mixers [3]. The need to achieve homogeneous distribution of the liquid phase and a wet mass of uniform consistency applies, as for other granulation processes. The mode of combina tion can also affect the properties of the extruded material and spheroids as the packing and wetting of particles are sensitive to the extent of shearing applied.
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D. I . Wilson and S . L. Rough
Schmidt and Kleinebudde [4] experimented with four types of granulator prior to extrusion (using a rotary ring die press), namely a planetary mixer, high-shear mixer, twin-screw with kneading elements, and twin-screw without kneading. They reported that higher liquid contents were required for successful E-S of material prepared in the high-shear devices. This water content requirement also affected the properties of the spheroids during and after drying. It is also nec essary to control the evaporation of liquid, especially in high-shear devices, where the viscous dissipation rate is high and may result in a noticeable tem perature rise, as liquid content is a key parameter controlling the rheology of the wet mass. Screw extruders, and particularly twin-screw extruders, are often used in con tinuous E-S applications since the combination step is performed alongside the extrusion operation. The extruder can be configured in separate zones, such as powder mixing, liquid addition, kneading then forming. 2.2. Extrusion
Extrusion of the wet mass represents an important densifying stage [5], as weil as a forming operation. Vervaet et al. [3] proposed that E-S devices can be clas sified as either ram or gravity fed, on the basis of the feed mechanism of the wet powder mass, but here we classify the extruders in terms of the mode of ex trusion, as this allows one to relate formulation and mechanisms more readily (Fig. 2). (a) Pumping action: ram, axial single and twin-screw. Here, the material is com pacted and conveyed in its dense form before being forced through a die plate or screen . The material is therefore held at a high pressure over some period of time and thus yields a dense product, but is subject to phenomena such as liquid phase migration owing to the extended duration of applied stress. The extruding pressure is generated by the auger or ram, and die land lengths can be large. Gear extruders, where the material is drawn into the gaps between intermeshing teeth, represent pumping action machines with a short contact time. (b) Wiping action: sieve and basket, roll, radial screen. In this mode, the material is compacted to its extrusion density and forced through a die or screen via a wiping action as a blade passes over the die entry. The screen usually flexes in response to the high stresses involved: this is a shorter time-scale process, where elastic effects are important and the operation is usually less sensitive to shear rate, except in a conveying section. The wiping action can be pro vided by a number of rotating parts. Little attention has been paid to the design and arrangement of the blades, with the noticeable exception of
1 93
Extrusion- Spheronisation (a) Pumping action (in a single screw extruder)
(b) Wiping action (in a screen extruder)
material densified -----� during approach to nip region
��III����I-
perforated screen W iPing blade
Fig. 2. Extrusion modes.
Vervaet and Remon [6], who modified the impeller design of a Niea E-1 40 (Aromatie Felder) radial basket extruder. They developed a new high-effi eieney bl ade design, with a longer eompression surfaee via a eonieal inner edge - this improved the feed eompression and evened out the pressure aeross the sereen. Several novel blade eonfigurations have also been pat ented (e.g. [7]). The use of sereens means the die hole lengths tend to be short (diameter 500-1 500 j1m, lengths O.5-2 mm). These deviees usually run at lower average pressures (but high stresses oeeur at the nip) and allow a greater throughput. The type of extruder will mainly influenee the density of the granules formed: frontal extruders (end-on, high pressure) produee relatively hard and dense granules; radial extruders produee medium density granules, with an 'overflow'; and dome extruders produee the lowest density and temperature rise [8]. Figure 3 illustrates the action of different deviees and Table 1 lists some of the manu faeturers of E-S equipment.
1 94
D. I. Wilson and S. L. Rough (a)
rotary pelJeLiser
(b) basket extruder (plan view) /
\:\
/
,
screen rotation
fixed / internal rollers ,,/
"
"
-- - ----
,,
- - - - - .. ...
,
,
,
,
,
\
\
\
I
\
I I I I
, "
/ , .. ... _ - -- - -
(cl rarn extrusion
(e)
/
I I I I I I \ \ \ \
", ,. ,,
(dl
/
I
,,/
gear extruder (end viewl
GO
radial screen extruder . _
.
�._ -
Fig. 3. Action of different extruders.
It is important to note that formulations which operate satisfactorily in one extruder type do not readily transfer to different machines [9]. For example, Fiel den et al. [1 0] reported that two microcrystalline cellulose (MCC)-Iactose formu lations (differing in lactose size) were both successfully spheronised after ram extrusion through long dies, but one failed to spheronise appropriately. Screen extruders are relatively insensitive to the solids particle size distribution in achieving good E-S, since they provide low average shear rates followed by a rapid deformation, and hence the material is close to its yield stress during its processing history. In ram extruders, low shear rates can lead to liquid phase migration. These two examples outline the fundamental differences in wet pow der mass handling, and Vervaet et al. [3] further rationalised the problem by relating the type of feed mechanism of the plastic mass, i.e. screws vs. gravity, to
1 95
Extrusion- Spheronisation
Table 1 . Manufacturers of pharmaceutical extrusion-spheronisation equipment (2005)
Spheronisation{ Marumerisation
Address
Manufacturer
Extrusion
Alekanderwerk
Cylinder Screen
Caleva
Screen Gear Mini-screw
Batch Twin Continuous M icro
www.caleva.co.uk Dorset, U K
Fuji-Paudal (Luwa in US)
Screen Screw Dome
Bench-top and floor standing
www.fujipaudal.co.jp Osaka, Japan
GEA Aeromatic Fielder (Nica)
Basket
Batch
www.aeromatic-fielder.com Switzerland, U K
Rotary pelletiser Pelletiser cascades
www.glatt.de Binzen, Germany{ Leicester, UK
Glatt
Hosokawa Bepex
Roll compactor Screen Screw Gear
Schlüter Machinefabrik GmbH
Screen{ring
www.alexanderwerk.com Remschiei, Germany
www. hosokawa.co.uk Osaka, Japan{ Cheshire, U K Batch
www.schlueter-neustadt.de Neustadt, Germany
the effeet on pre-eompaetion. They add that an axial serew feed produees a more den se material than a radial sereen, a lower throughput, and that the eorre sponding pellets differ in sphericity and size distribution (although different die land length to diameter ratios, LID, were used). A theoretieal framework for ex plaining sueh observations is not yet eomplete (see Seetion 3 - Meehanies and Meehanisms). For example, Raines [1 1 ] used the Benbow-Bridgwater ram ex trusion analysis [1 2] to identify formulations that produeed good-quality extru dates and those that did not. However, it was not possible to relate the rheologieal parameters direetly to the tendeney to form good spherieal granules. The movement of water during extrusion is eritieally important for ram extrud ers, and less so for eontinuously operating units Iike serew extruders. This being said, Newton [1] reeommends that if extrusion is to be earried out using a sereen system, then the water should be dispersed by a high-intensity mixing proeess. Preparations extruded with low-pressure systems ean be more suseeptible to water distribution problems sinee the extrusion stage will not eonsolidate and distribute the liquid, and henee require intensive mixing to ensure eonsisteney. The water aets as a glidant during extrusion [1 3], and is also related to the
1 96
D. I . Wilson and S. L. Rough
plasticity of the extrudates formed. With screen extruders, there is little internal moisture loss or movement of water within the extrudate. For example, a Nica™ radial screen extruder (basket type) as used by Hileman et al. [14], where the feeder and agitator rotate in opposite directions, affords a shorter compression zone, and thus the wet mass has a shorter exposure to high-shear gradients, with corresponding low heat (and thus negligible liquid evaporation) and product build up. A key parameter that does affect the extrudate quality is the thickness of the screen or die land length L compared to the die diameter D. Vervaet et al. [3] reported that a low LID, of "-'1 , produced rough, loosely bound extrudates due to the low extrusion pressure incurred. A higher LID can produce smoother extru dates and better densification [6], as weil as an increase in temperature. Vervaet et al. [3] reported that a gravity-fed system with LID = 2 allowed for a wider operability zone in forming decent quality spheres than that of a screw-fed system with LID = 0.9. Any alteration to the diameter of the perforations, either due to manufacturing methods or wear/abrasion, is thus an important consideration, as weil as the pre compaction stress. The longitudinal shape can be an issue with the holes in screen extruders, which are usually punched, drilled or laser drilled. These rep resent short dies, and rough hole finish, excessive taper or abrasion can promote surface fracture. Vervaet and Remon [6] investigated the influence of the method of screen perforation and perforation geometry on E-S. The perforation method affected the maximum amount of drug that could be processed (67% for punched screen, compared with 70% for drilled and profiled holes), whereas the profiled screen also led to a smaller amount of surface fracture. Examples of extrudates with and without surface fracture are shown in Fig. 4, and it is clear that the occurrence and extent of fracture for a given material depend on die geometry and extrusion velocity. The material used to make the screen or die can also affect the likelihood of fracture. Extrudates exhibiting gross fracture yield fines readily, while very dense extrudates can be resistant to breakage on the spheroniser plate. The presence of smalI, regular cracks has been demonstrated by Rough and Wilson [15] to aid the formation of regular sized granules since this can promote regular breakage. 2.3. Spheronisation
Figure 5 shows a typical spheroniser, which features a friction plate rotating at a controlled speed so that extrudate cylinders are broken up into short rods with lengths approximately equal to their diameters. Over time, following collision with the plate, walls and other particles, the pellet edges are rounded off and their overall shape changes from rounded rods to du mb-beils to ellipsoids to spheres
1 97
Extrusion- Spheronisation
(a)
(c)
LID = 48/3,
LID = 3/3.
V = 140 DUn s-J
V = 690 mm s- J
(b)
(d )
1 2/3, V = 690 (top), 1 40 (bottom) mm s- J
LID =
LID = 6/3, V = 690 mm s- J
4. Shape and fracture of extrudates from ram extrusion of 55 wt% water-MCC paste at various die land geometries (LID) and mean extrusion velocities ( V). Scale intervals O.5 mm.
Fig.
[3] (Figs. 6 and 7). Other workers report a twisting mechanism. The finished granules are designed to be greater than 0.5 mm in diameter, since extrusion holes less than this are difficult to manufacture, and spheronisation of granules greater than 5 mm is not straightforward due to the chopping and rounding proc esses [1]. In general, spheronisation is less dependent on equipment type, although plate design is important. Schmidt and Kleinebudde [1 6] reported that a rougher spheroniser plate applied more energy, thus reducing the water content required for spheronisation. The plates can be smooth, or grooved with radial- or cross hatching. Typical laboratory spheronisers feature a 1 20-225 mm diameter plate, operating at 1 200-400 rpm, and spheronisation usually takes 2-1 0 min; larger production units are available, up to 1 m diameter, and scale-up is often reported in terms of edge or peripheral velocity [3, 1 7]. Most spheronising equipment is manufactured from hygienic materials, such as 3 1 6 stainless steel. There is often an optimal spheroniser load and speed. Too low a load does not provide enough contact between the particles, and too high a load does not allow for enough interaction between the plate and the extrudate. Similarly, low speed
D. I. Wilson and S. L. Rough
1 98
lid
spindie
� I
chute with door
rotating friction plate
housing for variable speed motor
Fig. 5. Schematic of spheroniser.
Ca)
CA)
(h)
0 0 Ce)
( d)
o Ce)
� C=0 0 0 0 0 (B)
CC)
(D)
(E)
Fig. 6. Spheronisation mechanisms according to Rowe [58]: (a) cylinder, (b) round-edged cylinder, (c) dumb-bell, (cf) ellipse, (e) sphere; Baert and Remon [59]: (A) cylinder, (8) rope, (C) twisted dumb-bell, (D) spheres with cavity, (E) spheres.
changes rod shape slowly, while high speed can result in particle size reduction via unwanted breakage. The spheroniser process variables have been shown to determine the packing properties of the granules. Hellen et al. [ 1 3] showed that bulk and tapped densities increased with increasing spheroniser load, residence time and speed. Increasing the plate speed and residence time increases the granule density and roundness, or can produce more agglomerated pellets [16]. A system in which there has been insufficient consolidation during extrusion, or in which the extrudate has a high degree of surface impairment, will be more
1 99
Extrusion- Spheronisation
(a)
(e)
LID =
LID
=
1 2/3,
48/3,
V=
V=
140 mm S- I
350 mm S- I
(h)
L ID = 24/3, V =
140 mm S- I
(d)
LID = 48/3, V =
350 nun
s-I
7. Examples of pellet shapes obtained from ram E-S: water-MCC paste spheronised at 1 600 rpm for 2 min. (a-c) 55 wt%, (d) 50 wt%. (a) shows spheres, (b) ellipses, dumb beils and fines, (c) dimpled spheres, (d) dumb-bells and rounded rods.
Fig.
sensitive to the operating conditions in the spheroniser [1]. Thus screen extru dates are more sensitive to the spheronisation stage. Agglomeration of a slightly overwetted extrudate can be avoided by the use of a smoother friction plate andj or a lower velocity. 2.4. Drying and finishing
Fluidised-bed drying is widely practised for E-S granules. The degree of shrink age observed will vary with water content, and the common pharmaceutical ex cipient MCC gives pronounced shrinkage at higher water content. Bashaiwoldu et al. [ 1 8] demonstrated that the microstructural characteristics were strongly influenced by mode of drying, with freeze-drying yielding stronger pellets than fluidised-bed or dessicant drying. The drying stage is critical in controlling bac teria or other micro-organisms: Kouimtzi et al. [ 1 9] demonstrated that probiotic bacteria largely survived E-S before drying.
200
D. I. Wilson and S. L. Rough
3. MEC HANICS AND MEC HANISMS
E-S involves three distinct processing stages before drying, namely: (a) consolidation of the wet mass to a state which will allow it to be formed; (b) extrusion of the consolidated mass through the die(s) or screen; and (c) rupture and rounding of the compacted and shaped material. The level of detailed understanding and ability to perform quantitative predic tions of each stage varies, with the first stage being notably better established than the second and particularly the third. This is because the materials used in E-S, namely high solids volume fraction wetted granular pastes (as defined by Coussot and Ancey [20]), are complex systems whose rheological behaviour is determined both by the large number of particle-particle contacts and liquid phase phenomena. Without the liquid, the particle assemblies would be highly frictional and prone to locking in the extruder, require high stresses to deform and give brittle extrudates. The liquid phase provides interparticle cohesion, lubricates particle contacts, promotes wall slip and can also bear some of the stress. The rheology of these materials is relatively poorly understood compared to polymers or less dense suspensions. 3.1 . Rheology
An important feature of E-S materials that complicates their understanding is that they are not necessarily saturated, i.e. the voids between particles may contain gas (usually air) as weil as liquid. In the related field of ceramics manufacture, extensive degassing is employed to eliminate entrapped air, which promotes weaknesses and defects in extrudates, but this is rarely practised in E-S as it is seldom necessary. There are many similarities between the wet masses used in E-S and soils, particularly after the consolidation stage where the material will be close to its saturated state. The uniaxial compaction profiles in Fig. 8 show how the porosity of two materials - a microcrystalline cellulose powder commonly used in E-S, with and without the liquid phase - changes as they are com pressed. The initial decrease in porosity does not require large stresses as the particles rearrange. Above a joining pressure, larger stresses are required to change the porosity and in an extruder the material will often choose to flow instead. In the presence of the liquid phase the joining pressure occurs at a lower stress and is followed by a flatter profile as the system is now saturated and the liquid phase must be compressed in order to change its volume - the material will then prefer to flow rather than to consolidate further. This behaviour can be interpreted in terms of plastic flow, and the stress re quired to make the material flow is described as a yield stress as found in the O"J,
201
Extrusion- Spheronisation 0.8 r-------� ,
,
0.7
· · · ··
� '00 e 0.6 o Cl..
{jJ
{jJ
f
·. . ·· · · . . .
(dry MCC)
.
... . .. . .. . .
.-
�
. .. . . . .. . ... . . . . . . . . .
(wet MCC)
0.5
0.4 '-------'--'---' 3 4 7 8 5 6 o 2 Compaction stress I MPa
Fig. 8. Compaction behaviour of MCC: dotted line - compaction of dry powder; solid lines - compaction and relaxation behaviour of 4 5 wt% water-MCC paste. {}J indicates joining pressure.
metal-forming and soil mechanics literature. The yield stress is a measure of the work required to change the material's shape, and its relationship to the joining pressure observed in compaction testing is not straightforward (the description above is a simple one to communicate ideas). Nevertheless, many workers have used the techniques devised for measuring the yield strength of soils, metals and other plastics, such as cone penetrometers, to characterise the rheology of E-S materials, and this provides a useful quantitative tool for comparing formulations and assessing whether they will give cohesive masses suitable for extrusion (e.g. , Li et al., [21]). The plasticity approach is the basis of the characterisation method described by Benbow and Bridgwater (1 2), where the wet mass is compacted and then extruded by a ram at constant velocity through a cylindrical square-ended cap illary die as shown in Fig. 9. The force on the ram during extrusion, F, is reported as an extrusion pressure, Pe , which is related to the geometry and material by (1 )
where A ra m is the area of the ram in contact with the wet mass. Here, the die entry contribution P1 is described in terms of a simple plastic deformation model, which affords a yield strength parameter 0'0 and a rate dependent term (rxV m). The P2
202
D. I . Wilson and S. L. Rough
Extrudate
o
v
Fig. 9. Terms used in the Benbow-Bridgwater analysis of ram extrusion.
term accounts for shear in the die land and assumes that this is dominated by wall slip, characterised by a yield stress and rate term (ra and ß Vn , respectively) which are not necessarily the same as those involved in the extensional flow at the die entry. Newton and co-workers have made extensive use of ram extrusion to study E-S systems since it provides quantitative parameters for comparison of different formulations and also indicates conditions under which surface defect and liquid phase maldistribution phenomena can arise [1 0,22,23]. For example, Fig. 1 0 shows how the yield strength parameters i n equation ( 1 ) varied with water con tent for mixtures of MCC and water. The figure shows the range of water contents which could be reliably extruded and a marked reduction in strength with de creasing solids content, which is a well-established result in the soils literature. Table 2 lists sets of Benbow-Bridgwater characterisation parameters reported for some E-S materials. These strength parameters can be manipulated by the use of additives, particle size distribution, etc. A priori prediction of these parameters is not currently possible, even for the simplest systems, and leads to extensive empiricism in formulating E-S materials. The difficulty in predicting whether E-S materials will extrude and the forces involved is compounded by the fact that many extruders feature complex defor mation patterns which have yet to be modelIed in detail. The Benbow-Bridgwater approach, for example, provides parameters which can be applied readily to ram extrusion and other pumping mode devices such as single-screw extruders [24], but not to the feed section of twin-screw extruders and, in particular, wiping action devices. The latter have received Iittle attention apart from the work by Martin [8], with the result that the key deformation modes have not been identified and therefore the most appropriate rheological parameter(s) that need to be meas ured have not been established. E-S materials have also been studied using fluid constitutive models, but without modelling to link the parameters and extruder performance the data are effectively quantitative handles within an empirical framework. Delalonde et al. [25] used a compresso-rheometer to study the rheology of Avicel™ MCC pastes at different water contents, and reported simple power-Iaw shear thinn ing behaviour (r = Kr)")' with the lower water content formulation of 50 wt%
203
Extrusion- Spheronisation
1 0 ,-----,
-
.,0
"
0.1
'"
.
'00
. .. . ..
0.01 0.00 1 L�
Ii> : --� ____'_:-
__ _'_ _ _ � _ _ _ � _
�
�
�
W � Water content I wt%
-:!
_ _
m
Fig. 10. Benbow-Bridgwater yield parameters for extrusion of MCC pastes with varying water content. (Data from Rough et al. [32), reproduced with permission from Elsevier.)
Table 2. Benbow-Bridgwater characterisation parameters (equation pastes
Formulation
(jo
(all % wet basis) Water-MCC [32] 45 wt% 50 wt% 55 wt% 60 wt% 65 wt% Tale (vol. fraetion 0.49) Water + 39 wt% Surfaetants [56] 40 wt% water - potato starehes [57]
MPa
MPa (m/s) -m
1 .4 0.61 0.19 0.027 0.008 0. 1 5
5.8 4.7 2.7 0.40 0.057 1 .0
0. 1 1
1 .3
Cf.
(1 )) reported for E-S
ß
n
MPa
MPa (m/s) - n
0.21 0.28 0.34 0.37 0.26 0.23
0.39 0.080 0.051 0.01 1 0.00 1 2 0
2.0 0.61 0.42 0.076 0.0 1 6 0.22
0.59 0.29 0.37 0.42 0.37 0.26
0.33
0
0.30
0.36
m
TO
321 9 Pa SO. 38 , ; = 0.38) being more 'viseous' than the upper water content limit of 61 .54 wt% ( K = 453 Pa SO. 32 , ; = 0.32). MaeRitehie et al. [26] performed eontrolled stress rheometry of MCC/laetose formulations and related the results to ram E-S. They analysed their data using a viseo-elastie model. The apparent viseosity of mixtures deereased as the water eontent inereased, and they re ported that the range of water levels over which the elastic modulus GI and viscous (Ioss) modulus GI! were uniform corresponded to water levels which produeed the best extrudates. The ranges of GI, GI! and apparent viscosity re ported were of the order 3 1 07, 7 1 06 and 1 09_1 0 1 0 Pa s, respeetively. (K =
,
,
x
X
204
D. I . Wilson and S. L. Rough
3.2. Liquid-phase effects in extrusion
Galland et al. [27] studied E-S of MCC-water pastes in a simple axial screw extruder and identified 'hydric domains' for the extrudability regime, wh ich for their material lay between a 'hygroscopic limit' of 65% liquid (dry basis) and a 'fluidity limit' of 1 65%. They measured the porosity of the wet mass before and after extrusion at various rotational speeds and demonstrated that the level of unsaturation, i.e. the air content, of the wet mass generated in the combination stage was large at low liquid contents. The air content was almost completely removed in extrusion (Fig. 1 1 ). Above a threshold, corresponding to the capillary regime described by Newitt and Conway-Jones [28], the wet mass obtained after combination was close to saturation and this level did not change much on ex trusion. This study illustrated how, depending on the liquid content, extrusion can be simply a shaping process, or serve as a compacting process as weil. The wet powder mass fed to an extruder does not necessarily have to be saturated for extrusion, but for unsaturated feeds, the process must have sufficient time to compact the material. The threshold for saturated behaviour is strongly affected by the packing characteristics of the particulates - Heng and Koo [29] found a significant correlation between the void volumes in different MCC powders and their packing properties, and the water requirements for good E-S and pellet qualities (although this study used hand pressing through a mesh rather than mechanical extrusion). If the wet powder mass is consolidated and saturated, extended processing time can lead to liquid-phase migration, where the pressure on the liquid causes it to flow relative to the solids, leading to regions of high solids content, non-uniform extrudate composition, wet extrudate surfaces and, in the worst case, wholesale
1 .0 o
� (j)
o
e
o c..
0.5 50
1 50 1 00 Water content, wt% dry basis
Fig. 1 1 . Saturated (line) and measured porosity of wet masses (cireles), extrudates (squares) and pellets (triangles) during E-S via an axial screw extruder. (After Galland et al. [27], reproduced with permission from lehemE.)
Extrusion- Spheronisation
205
drainage. Boutell et al. [30] investigated the influence of liquid binder on the liquid mobility and preparation of spherical MCC/barium sulphate/surfactant granules by E-S, and they found that liquid phase migration was influenced more by the amount of liquid and the rate of extrusion than by the solids composition. Low liquid levels led to elongated pellets, whereas wet formulations produced larger, agglomerated pellets with a wide particle size distribution and a high porosity. Liquid-phase migration is exacerbated by slow extrusion speeds, so that the liquid has time to redistribute, and narrow particle size distributions that have a high permeability and therefore poor resistance to liquid-phase motion [31 ,32]. MCC does not dewater as readily as other non-absorbing solids: its water-binding behaviour has been described in terms of a gel and a super-molecular sponge by different groups. Various methods have been reported for studying liquid-phase migration, such as centrifugation [33], magnetic reSOnance imaging [34] and sectioning and drying of paste extrudates [32J, but this effect cannot yet be predicted without supporting experiments. 3.3. Extrusion- spheronisation i nteractions
Tomer et al. [35] reported that successful spheronisation requires extrudates that: (i) possess enough mechanical strength to retain their structure, but be brittle enough to break into short rods on the spheroniser plate; (ii) have enough plasticity in order to enable rods to roll into spheres; and (iii) be non-adhesive so that spheres do not agglomerate or stick to the spher onising equipment. The extrusion process therefore has direct impact on the subsequent spher onisation stage since extrusion defects, liquid-phase migration and extrudate ho mogeneity all affect spheronisation. Many workers have reported optimal combinations of geometry and operating conditions in order to extrude and spheronise a particular formulation. Figure 12 illustrates some of the factors in ram extrusion: short dies (small LID) require lower extrusion pressures but promote surface fracture, particularly at high extrusion velocities. Large LID values offen yield smooth extrudates, but these feature lower voidage owing to the higher extrusion pressures, and thus do not tend to break up readily and are prone to form dumb-bells during spheronisation. Low extrusion velocities can promote liq uid-phase migration, while high velocities can promote surface fracture owing to the uneven release of strains within the extrudate upon exiting the die land. It should be noted that surface fracture is not necessarily an undesirable phe nomenOn for spheronisation, unless it generates many fines. Rough and Wilson [1 5] have shown that evenly spaced circumferential fracture with small rupture
206
D. I . Wilson and S. L. Rough Quality
Knuckle-bones
.'
L .
Smooth and rigid
• • • • •
• •
. .
.
.
•. • •. . • .
• • • . .••• .. • .. .
.'
..
.'
.'
V ..
.. ••
• •• •
••
•
Gross fractures
�
.
Fig. 1 2. Schematic iIIustrating optimal operating conditions for extrusion prior to spher onisation.
depth (e. g. Fig. 4b) can promote regular break-up on the spheroniser plate. Domanti and Bridgwater [36] noted that these cracks often arise at a spacing of 012, giving the following relationship between final granule diameter dp and ext rudate diameter (ignoring compressibility effects): (2) This resonates with the observation by Harrison et al. [37] for an MCC-Iactose system that the diameter of the spheres was approximately equal to that of the extrudate diameter, although they did state that a smooth extrudate was required for good spheronisation. Figure 1 3 shows pellet size distributions obtained by sieving granules generated from ram extrusion of MCC-water masses and the link between the modal value of dp and 0 is evident. The generation of fines at smaller values of LID owing to fracture is also apparent. These sieving data do not, however, give an accurate account of granule shape as a significant pro portion of granules formed at larger LID are dumb-bells, but the minor axis allows them to pass through the '0' sieve and therefore count as pseudo-spheres. The strength of extrudates is determined by their degree of compaction, and cohesion
207
Extrusion- Spheronisation Dumb-bells 0.6
c 0
·ü
�
'" '" 4.00
Upper sieve diameter / mn (a) D = 3 mm, V = 1 40 mm s-J 0.6
c
.2 Ü
� '" '" t1 giving the equilibrium granule distribution for coalescence in the non-inertial regime only.
Drum Granulation Processes
241
4.5. Solution of the population balance and estimation of the coalescence kernel
Various numerical solutions to known analytical solutions of the general popu lation balance equation, equation ( 1 3), have been established. Hounslow's sec tional model solution [61 ] equation (14), was found to accurately describe the behaviour of granulation processes. For given values of k1 and k2 , equation ( 1 5) is solved with the coalescence kernel given by equation (22) [1 2]. In a typical study [2], 1 8 size intervals were used with the first top size being 0.32 mm. Thus, a total size range of 0.32-1 7.46 mm was covered ensuring there is always at least one empty size interval at the top of the size range, so as to avoid finite domain error [68]. Equation (14) is a series of 1 8 ordinary differential equations (ODE), which can be solved using the Fehlberg fourth-fifth order Runge-Kutta method for a range of residence times [74]. The predicted size distributions at varying residence times can be compared to the measured ones and the best values of k1 and k2 , for a given set of data are estimated by non-linear regression. Adetayo et al. [1 2] used the Marquardt compromise method [75]. This routine combines the steepest descent and the Iinearization methods, and has the advantage of fast convergence as weil as being relatively robust. The best parameters are estimated by minimising the sum of squares error between the simulated and experimental cumulative size distributions [1 2]. 5. DRUM GRANU LATION OF NPK FERTILISERS (including own contribution) 5.1 . Fertiliser granulation
Granulation is an important process in the fertiliser industry. However, prior to 1 950 most fertiliser manufactured was produced in a non-granular form. In such form, the material caked when stored and was extremely dusty when applied in the field. About this time, a wide interest developed in the fertiliser industry for the manufacture of a granular, high-analysis fertiliser of improved physical properties [79]. Since this time various granulation processes have been developed. A schematic diagram of a typical granulation process is shown in Fig. 8. Recycle seed granules are fed to the granulator. New feed, which is in the solid or liquid phase depending on the process being used, is added to the seed granules, and granule growth occurs. Granules leaving the granulator are first dried and then screened to separate out the product size. Product size is normally very strict, e.g., 90% -4 mm + 2 mm [80]. Oversize granules are crushed and recycled with undersize granules.
242
G . M . Walker New Fecd
We! Granules
GRANULATION DRUM
Dry Granules
DRIER SCREENS
' '
Oversize
.;:: -0 -+-'---;;:::-...::.
-
Undersize
-+-
-
---..
-
Produc!
CRUSHER
Ree eIe Seed Granules
Fig. 8. Schematic diagram of a fertiliser granulation plant.
The operation of granulation plants is difficult because of two major problems. Firstly, often only a small fraction of the granules leaving the granulation drum are in the specified product size range. The recycle ratio, that is the ratio of the amount of material returned to the process, to that of the product, may be as high as 1 0-1 5, in high-recycle processes, and anywhere between 0.5 and 2 in low recycle processes. Processes using no recycle are practically non-existent, be cause there is always an undersize or oversize fraction of the product that has to be returned to the process [81 ]. Secondly, problems of non-uniform mass flow (surging) and non-uniform particle size (drifting) exiting the granulator coupled with the large dead time make it difficult to control the granulation plant at a steady state. In extreme cases these problems can result in plant shutdown [1 1]. Fundamentally, fertiliser granulation is similar to agglomeration in other sys tems such as pelletisation, flocculation, crystallisation and aerosols. Of these, the closest is pelletisation. However, because fertilisers are soluble, chemical com position of the particles significantly affects the agglomeration process. Com pared to soft and plastic pellets, recycled fertiliser granules are hard and cannot easily be deformed. These recycled particles have a very broad size distribution, which overlaps the distribution of product granules [3]. The following section describes the effect of process parameters on the drum granulation of NPK fertiliser in bench-scale batch systems. Although these data are specific for the
243
Drum Granulation Processes
fertiliser grade (27:6:6 in this case), many of the conclusions can be applied to general fertiliser granulation and indeed to other drum granulation processes. 5.2. Effect of solution to solid-phase ratio
The effect of solution to solid-phase ratio on NPK drum granulation is iIIustrated in Figs. 9 and 10 as a plot of solution-phase ratio vs. the mass-median diameter (d50) of the granulate at the end of each experiment. As with all fertiliser materials an increase in solution-phase ratio results in an increase in median granule size. The results also show a similar trend to those of other researchers in that gran ulation is weak, with a small increase in d 50, at low solution-phase ratios. At higher solution-phase ratios, depending on granulation time, d 50 increases sig nificantly, indicating a high degree of granulation [50,80]. Figure 1 1 i1lustrates the frequency size distributions for NPK fertiliser with in creasing moisture content. At all moisture contents (4-8% mOisture), almost all the fine material from the initial distribution was removed up to a critical size with this fine material agglomerated into granules having a broad size distribution. The relationship between moisture content and particle size distribution indicates that the finer material is removed but also gives an indication of how the granulation proceeds. At 4% moisture, the "s" curve is relatively shallow, but as the moisture content is increased to 6% the curve becomes steeper although the mass-me dian diameter remains fairly constant. At 8% moisture, the shape of the "s" curve is very similar to that of 6% except that the curve has been shifted towards the higher particle size range [50,80]. 4.5 -,-------,--,--, 4
3.5 3
� 2.5
.g.
2 1 .5
0.5
-+
--
1-
���----�i==-=�===
o �---+---�--�--� o 0.05 0.1 0. 1 5 0.2 0.25 y
Fig. 9. Effect of solution-solid-phase ratio on dso for variation i n granulation time (drum diameter 25 cm, four radial flights) [50]. =
244
G . M . Walker 7
6 f- - -.. - d
___tr_ d
�d
- 25cm
38cm 25cm (flights)
= =
5 0 4 -It)
Q.
" 3 2
:/ :1 ..11 ../ / •
�
--r
-o
0.05
o
0.1
I
0. 1 5 y
V
/
0.2
0.25
Fig. 1 0. Effect of solution-solid-phase ratio on d50 for variation i n flight arrangement and drum diameter (granulation time = 5 min) [50].
45
·
'1
35
:: ::
Ci
,
40
30 25
"if!. 20
15
·
.
·
,
rr----
-+- initial �8% '0- - 6% - 4% •
/ '\. , . '\. / , '\. }--, , / \ I ....... Li: . \ . . . / . \..'� .� .� ..... j .0 � ,
0-,
10
.
5
.
o o
2
4
6
8
10
dp (mm)
Fig. 1 1 . Effect of moisture conte nt o n particle size distribution (granulation time 25 cm drum, no flights) [50].
=
1 0 min,
5.3. Granulation kinetics
From Fig. 9, the transition in granulation occurs at a solution-phase ratio of between 0. 1 3 and 0 . 1 8 for a granulation time of 1 0 min and between 0. 1 8 and 0.24 for a granulation time of 5 min. Similar results were found by previous researchers with other fertiliser materials in that high degrees of granulation are dependent upon both solution-phase ratio and granulation time. The kinetics of fertiliser granulation have been described previously by Ennis et al. [38] in terms
245
Drum Granulation Processes
of the viscous Stokes number, which was defined as the ratio of the relative kinetic energy between colliding particles to the viscous dissipation about the pendular bond. Adetayo et al. [24] modified this original relationship (equation (8)) for drum granulation, yielding the following equation: 8p rwR Stv = g9/1 (22) where: Pg = granule density, kg m- 3 ; r = effective granule size, m; w = granulator speed, S- 1 ; R = granulator radius, m; and /1 = binder viscosity, kg m- 1 S- 1 . The three granulation regimes were defined in terms of the magnitude of Sty in comparison with St�. as before: non-inertial regime; inertial regime; coating regime. The results plotted in Figs. 1 2-14 i1lustrate these regimes quite neatly. Gran ulation with 4% moisture (Fig. 1 2) i1lustrates the non-inertial regime with similar distributions for 5 and 1 0 min indicating an equilibrium has been reached. Gran ulation with 6% moisture i1lustrates intermediate inertial regime with a narrowing of the distribution and a slight increase in particle size with time (Fig. 1 3). Granulation with 8% moisture (Fig. 1 4) shows the effect of the coating regime, with a significant increase in particle size with time caused by preferential coalescence. It was noted that in this granulation system preferential coalescence is undesirable with most of
:: ::
45 ,-
� �
0.0 1 . Using a n X-ray radiography technique, the densification i n the nip region was investigated. The results indicated that densification starts weil above the nip zone at low speed, which may indicate that high-speed conditions are too aerated for satisfactory compaction to take place. Bourseul [ 1 5] also investigated the effect of altering the friction coefficient of the powder on the rolls, by modification of the roll surface. He showed that the nip angle and hence the peak pressure both increase with an increase in the coefficient of wall friction. Perera [1 6] studied the compaction of the pharmaceutical excipients micro crystalline cellulose (Avicel PH1 0 1 , PH1 02 and PH1 05) and lactose (regular and w
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free flow). He made an extensive study of the analogy between uniaxial com paction and roll compaction, as mentioned earlier, and employed the empirical pressure-density relationships due to Heckel [32], Cooper and Eaton [33] and Kawakita [34]. Of the three, the Kawakita correlation showed the best fit to experimental data in both uniaxial compaction and roll pressing. The compact mechanical properties were studied using the three-point bend test to understand the influence of powder properties and process parameters on the compact strength. Bindhumadhavan [35] carried out further experimental investigations using pharmaceutical excipients on an instrumented roll compactor with an incorpo rated pressure transducer, particularly concerning the influence of powder prop erties on the roll-compactor performance. He showed that the particle size distribution has a strong influence on the compaction pressure applied and the final properties of the compact. An increase in the fines content can increase the peak pressure applied, and therefore the compact bulk density and compact strength. As summarised earlier, he also showed that Johanson's model is able to pro vide a reasonable basis for calculating the nip angle and pressure profiles de veloped in a roll press for a gravity-fed system. In principle, the current findings will apply to a screw-fed system but the additional complexity of a fluctuating feed pressure needs to be considered (see below). The major weakness of the model is the need to estimate the feed pressure at the nip since the complete pressure profile is very sensitive to this parameter. However, this boundary condition is likely to be a problem for any model unless a detailed analysis of the feed region is included. Such an extension might also be able to account for the entrainment of air. Briscoe et al. [36] attempted to validate the roll compaction parameters such as the roll force and roll torque predicted using Johanson's model with roll-mill experimental results. The effects of the roll-operating conditions - the roll gap, roll speed, feed material and friction ratio-on the roll force and roll torque were investigated. The model predictions were in close agreement with the experi mental results, again indicating that the simplified approach of Johanson [6] can be used to provide a quantitative prediction of the extent of the roll compaction performance and may be used to design optimal roll geometries and operating conditions. 6.2. Roll compaction using a screw feeder
When fine powders (Iess than about 50 Jlm) are compacted, press feeding is often a problem. As indicated earlier, this is the case firstly because fine powders de-aerate slowly, and secondly because fine powders often exhibit poor flowability
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so that gravity feeding is problematic. Screw feeders are therefore employed. In this case, the roll-press parameters include not only the roll speed and the roll gap but also the screw feeder parameters. Moreover the screw feeder interacts with the compaction process. These aspects have been extensively investigated by Guigon and co-workers [37-40], using the commercially available screw-fed lab oratory roll press (Komarek(K)B 1 OOQC) described in Section 5. Simon and Guigon [39] carried out experimental work to understand the influence of the operating parameters on the roll pressing of lactose and the interactions between the feed ing conditions and compaction. The measured stress applied to the powder was found to fluctuate significantly with time and position. The heterogeneity of the compact was correlated with the heterogeneity of the feeding pressure caused by the operation of the screw feeder. These aspects are considered further below. 6.3. Rol l-press throughput
The throughput of a roll press is principally limited not only by the rate of powder de-aeration, as noted above, but also by the elastic properties of the particles, which limit the compaction speed. In general, there is a limiting speed, above which poor-quality compaction takes place, for one or both of the reasons given above [4]. If the screw feeder is operated at a constant speed and the roll speed is varied, three conditions can be observed: •
•
•
sub-feeding, where the amount of powder that is provided by the screw feeder is too smalI. In this case, the particulate material is not compacted and no strip is formed. over-feeding, where the amount of powder provided by the screw feeder is too large. The compact is then extruded between the rolls and the roll gap in creases. In this case, the compacted material is of poor quality and a proportion of the powder is lost in non-compacted form . good compaction rate, which is an operating range between sub- and over feeding, corresponding to the production of a strip of compacted material that exhibits acceptable cohesion and mechanical strength.
Figure 1 9 shows the results of a series of such experiments, each at a fixed screw speed, where measured throughput is plotted as a function of roll speed, for conditions leading to good compacts. For a constant screw speed, the roll press throughput is approximately constant. Figure 20 presents the throughput against screw speed for all roll speeds, demonstrating a universal linear rela tionship. It should be noted, however, that the throughput resulting from the combination of screw feeder and roll press is considerably smaller than the
279
Roll Pressing 700 600 '";-
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16
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45 rpm
1 9. Compactor throughput vs. roll speed for different screw speeds.
800
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600
'E 500 � 400 Cl. ci>
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.' •
.r:.
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0 5. 9
.& 6. 9 x 9.8
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20. Compactor throughput vs. screw speed for different roll speeds and comparison with throughput delivered by the screw when not coupled with the roll .
Fig.
throughput of the screw alone, which is also shown. This is because the coun terpressure created by the rolls modifies the friction between the powder and the screw barrel . Similar results were obtained subsequently by Lecompte [41 ] on a laboratory roll press of roll diameter 240 mm.
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6.4. Rol l-gap variation
If the upper roll can move vertically, the roll gap increases from its initial value to an equilibrium value when the powder is compacted. This equilibrium value, S, is a function of the mean stress applied by the rolls on the compacted material. It is also a function of the roll speed Vn the roll-press throughput Qe, the density of the compacted material Ps, the roll width L, and the extent of slip of the compacted material on the roll surface � [28]: (8)
If the roll gap is measured for many working points (sets of screw speeds, Vs, and roll speeds, Vr) then iso-gap curves can be computed, as shown in Fig. 21 . Depending on the powder being compacted, the curves are more or less straight; for alumina they are not perfectly straight, but curve slightly upwards. The local slope of the curve is the inverse of the working coefficient Cw, where 1 /Cw = VsfVr [42]. Lecompte [41 ] found a linear relationship between the gap and what he termed the predensification parameter R, defined as the ratio of the mass throughput to the product of the roll peripheral speed and the width of the roll. By
60
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!: �
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10 o
5
10 Roll speed / rpm
15
Fig. 21 . Calculated iso-gap curves (mm) vs. roll and screw speed. Initial gap 0 . 8 mm. (alumina S H 1 00)
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0.8 0.6 -l----,.---,---,..----,.-,---,.---j 200 o 250 350 300 50 1 00 1 50 / Maximal normal stress MPa Fig. 22. Maximum normal stress measured with the piezoelectric transducers vs. roll gap. I nitial gap 0.8 mm. Solids:alumina (SH 1 00), salt, lactose.
taking the peripheral speed instead of the angular roll speed, he was able to take into account the roll size. In Fig. 22, the roll gap is plotted as a function of the maximum normal stress measured with the piezoelectric transducer embedded in one roll. The relation ship thus obtained is linear, which means that the iso-gap curves can be assim ilated to iso-maximum normal stress curves. Therefore for a given powder, the working range can be obtained in terms of the maximum stress. The working roll gap defines, of course, the thickness of the product strip and also the product properties or 'quality'. In order to obtain the same quality when varying the throughput, the operator must vary the screw and the roll speeds to remain on the same iso-gap curve. Some powders present straight iso-gap curves. In that case, using the same working coefficient leads to the same quality of compact.
6.5. Motion of the particles in the nip zone
Various investigators have attempted to follow the trajectories of individual particles within a press. One method is to observe the motion visually through a transparent cheek plate [28,42]. Markers added to the powder can be located and tracked on video using video analysis software. The position of a marker particle as a function of time (trajectory) represents a flow line. The speed of the particle can also be calculated along the trajectory in the x and y directions. Figure 23 represents the trajectories of 1 3 markers (the dotted lines show the roll surfaces). As expected, the dominant motion of the particles is in the x di rection. However, in the left part of the graphie (for x < 1 5 mm) the trajectories show discontinuities. The motion of the particles in this region is not continuous because of cyclic perturbations produced by the screw feeder. At every turn of the
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10 8 6 4 2 E E 0 >-2 -4 -6 -8 -10 -33
Upper roll
Lower roll
30 -27 -24
-2 1
-
-18 -15 -12
-9
-6
-3
0
3
x l mm Fig. 23. Trajectories of 1 3 traced particles with initial different positions (lactose mono hydrate + 0. 5% Mg stearate + 4% coal as marker [200-400 )lm], Vs 22. 7 rpm, Vr = 6.6 rpm, hydraulic pressure: 80 bar) [28,43]. =
':"C/l
E E 2.g �
8 7 6 5 4 3 2 1 0
00
0
Screw period
2
3
Time / s
4
5
6
7
8
Fig. 24. Axial velocity vs. time for traced particles ( Vx), measured for particles having a
position -33 < x < -28 and -2.5 1 5 mm). The flow here is steady, determined principally by the friction on the rolls. Careful observation of the motion of traced partie/es e/ose to the cheek plate showed that their velocities varied periodically with time in a sinusoidal way, as shown in Fig. 24. These fluetuations have the same period as the feed serew and are in fact eaused by the motion of the last serew flight (Fig. 25). The
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Feeding plane Stationary powder
ls e inside the ro___I�
_ _
Moving powder Fig. 25. Sketch of the feeding zone with screw feeder flights.
pressure at the exit of the screw is not uniform in the plane perpendicular to the direction of motion. This pressure is a function of the geometry and surface properties of the screw and of the compressibility of the powder. When the wall of the last screw flight is far from the feeding plane (the position corresponding to the top part of Fig. 25), the powder between the flight and the feeding plane is not compacted and the local pressure at the feeding plane is low. When the flight at this location moves forward, the powder first compacts without moving sig nificantly, progressively increasing its density and the local pressure at the feed ing plane. This is the cause of the discontinuous motion shown in Fig. 23. If the powder is less compressible, as is the case for sodium chloride, for example, the magnitude of these fluctuations is less pronounced. 6.6. Distribution of the compact heterogeneity
Most of the properties of the compacted strip depend on its density, so it is of interest to determine this as a function of position. This is particularly impor tant if a screw feeder is used, because this can, as shown above, impose a time dependent variation on the applied stress and can therefore be expected to influence the density in a time-dependent way. Various methods for measuring strip properties have been aUempted. Bourseul [1 5] made extensive use of three-point bend tests on pieces of the strip, as weil as measuring density. Lecompte [41] used the force needed to indent the slab and also measured the local density and porosity. Bindhumadhavan [35] obtained microstructural information on the cross-section of the compacts using X-ray microtomography. Simon [28] has used visualisation techniques to obtain qualitative indications of the stress variation, by incorporating either comminuted coal or sodium chloride into the feed powder. The former comminutes in high-stress regions and makes them look darker, while the laUer results in crystal orientation in high-stress
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I
160mm 50
Wicompact dth45mm
x / mm
Fig. 26. (top) Light transmitted through a sodium chloride compact (sodium chloride d50: 74 ).lm); (bottom) iso-grey-Ievels of the light transmitted through a sodium chloride compact [28].
regions, leading to greater light transmission. 80th methods have been used to study the oscillation in strip properties due to the feed screw. Figure 26 shows an example of the output of the latter method, with iso-contours of light transmission. 6.7. Novel techniques and improvements
Gaete-Garreton et al. [44] investigated the advantages of applying ultrasonic fields in the nip zone of a roll press. The presence of an ultrasonic field resulted in the reduction of the shaft torque required compared with the same operation without ultrasonic energy. It was also shown that the abrasive wear was reduced significantly using the ultrasonic field. Hirohata et al. [45] carried out experiments on metal powder compaction by differential speed rolling. There are two methods: using the same roll diameters but operating at different speeds, and using different roll diameters at the same speed. In this study, a compacted strip was fabricated from electrolytic copper powder by applying differential speed rolling with the same roll diameters under a carefully regulated powder feed volume. The roll diameter was 50 mm. The speed ratios were varied from 1 (conventional) to 1 .33. The effect of the roll speed ratio, initial roll gap, powder feed volume and strip speed at the roll exit on the rolling load, relative density and strip thickness were examined. The relative density was found to increase with differential speed rolling compared to conventional rolling for the same rolling load. It was found that the density of the strip was about 1 5% larger than that from conventional rolling. The difference in density between conventional and differential rolling becomes smaller as the rolling load is
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reduced. It was also found that a strip can be made with a small powder feed volume when a large roll speed ratio is used. The strip thickness increased with increasing rolling load and was directly related to the rolling load regardless of the roll speed ratio. Much remains to be done on the characterisation of roll-press products in response to different processing routes. Bultmann [46] investigated the effect of repeated compaction on the compact properties. Compacts were produced using microcrystalline cellulose and the sampies were recompacted by up to 1 0 passes. The amount of fines was found to reduce with the number of compactions. The powder flow properties were improved and the mean granule size was increased. However, the tensile strength of the resulting tablets was found to decrease with the number of passes, indicating the need to identify the optimum number of compactions in a particular case. Until recently, the extent of instrumentation applied to roll pressing was limited to pressure and torque sensors. Acoustic monitoring is a non-invasive technique widely used in powder metallurgy. Hakanen and Laine [47] used this technique to characterise the roll pressing process. It was found that the over-compaction of microcrystalline cellulose could be detected using this method, since it was ac companied by enhancement of acoustic emission in the region of about 1 7-23 kHz. In a later study, Salonen et al. [48] showed that acoustic relaxation emission (ARE) is a function of the compressive stress applied and is a char acteristic of the compacted powder. They compared microcrystalline cellulose with maize starch and suggested a possible relationship between the ARE and the mechanical properties of the powders. 7. FORWARD LOOK
The advantages of roll compaction compared with other granulation routes are likely to ensure its continued use in the pharmaceutical industry and new uses are emerging. Laboratory-scale test methods are now available to enable fea sibility studies to be carried out and scale up of industrial processes can be achieved. Future studies are likely to focus on the complex interactions between powder properties, process variables and product properties, especially in cases where the feed powder contains a mixture of components. Several new ideas have been proposed for enhancing the effectiveness of roll pressing, including the use of ultrasound and differential speed rolls, and these can be expected to be investigated further in the future. The direct measurement of stress in the nip region has been very important in understanding the process; further enhance ments in instrumentation can be expected. From a modelling perspective, several studies have shown the applicability of Johanson's model. To make further advances and, in particular, to model both
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the feed and the nip region will require 3D computational models. A promising approach here is the combination of DEM and FEM, allowing individual particle motion to be studied even in cases where extensive deformation is taking place. ACKNOWLEDGEMENTS
The authors thank the Region Picardie and the French Ministere de I'Education Nationale de la Recherche et de la Technologie for their financial support through the Pole Regional Genie des Procedes; and the industrial research organi sations of Rhodia, Pfizer, and Merck Sharp and Dohme. Nomenclature
roll diameter (m) roll gap (m) roll width (m) roll press throughput (kg S- 1 ) roll speed (rad S- 1 ) Vr screw feeder speed (rad S- 1 ) Vs velocity in x direction (mm S - 1 ) Vx main direction of motion of the powder X vertical direction perpendicular to x y horizontal direction perpendicular to y z nip angle (deg) rx density of the compacted material (kg m- 3) Ps max maximum of the normal stress profile (Pa) extent of slippage of the compacted material on the roll surface � entry angle (deg) e er release angle (deg) neutral angle (deg) D S L Qe
an Yn
REFERENCES [ 1 ] R. Miller, Roller compaction technology, in: D . M . Parikh, (Ed.), Handbook of Pharmaceutical Granulation Technology, Marcel Dekker, New York, 1 997, pp. 99-1 50. [2] R.W. Miller, P.J. Sheskey, Am. Pharm. Rev. 4 ( 1 ) (200 1 ) 24-35. [3] P. Kleinbudde, Eur. J. Pharm. Biopharm. 58 (2004) 31 7-326. [4] W. Pietsch, Size Enlargement by Agglomeration, Wiley, New York, 1 991 . [5] S. Wennerstrum, Ten things you need to consider when choosing and installing a roller press system, Powder and Bulk Engineering, 1 4(2) (2000) 37-50. [6] J . R. Johanson, ASME, J. Appl. Mech. 32 ( 1 965) 842-848. [7] J . M . Bultmann, http://www.jmbnet.de/brc/compare.htm. 2002.
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[8] B. Michel, Compactage en presse a rouleaux de poudres minerales, PhD thesis, Universite de Compiegne, 1 994. [9] B. Michel, J.P.K. Seville, P. Guigon, C. Sidawy, Experimental study of the roll compaction of powders, Proc. 6th Int. Symp. Agglomeration, (1 993) 790-795. [ 1 0] J . P.K. Seville, U. Tüzün, R Clift, Processing of particulate solids, Chapman & Hall, London, 1 997. [1 1 ] R Dec, Problems with processing of fine powders in roll press, 25th Biennial Conference, International Briquet. Assoe. , Philadelphia, 1 995. [ 1 2] R Mansa, Using intelligent software to predict the effects of formulation and process ing parameters on roll compaction, PhD thesis, University of Birmingham, 2006. [ 1 3] AW. Jenike, RT. Shield, J. Appl. Mech . 26 (1 959) 599-602. [ 1 4] G. Bindhumadhavan, J . P.K. Seville, M.J. Adams, RW Greenwood, S. Fitzpatrick, Chem. Eng. Sei. 60 ( 1 4) (2005) 389 1-3897. [ 1 5] F. Bourseul, Investigation on roll pressing as a forming operation, PhD Thesis, Uni versity of Birmingham, 200 1 . [ 1 6] L.N. Perera, Roll compaction of pharmaceutical excipients, PhD Thesis, University of Birmingham, 2004. [1 7] K. Kawakita, K.H. Ludde, Powder Technol . 4 (1 970/1 971 ) 6 1 -68. [ 1 8] RT. Dec, A Zavaliangos, J.C. Cunningham, Powder Technol. 1 30 (2003) 265-27 1 . [ 1 9] P A Cundall, O. D.L. Strack, Geotechnique 29 ( 1 ) ( 1 979) 47-65. [20] Y. Tsuji, 1. Kawaguchi, T. Tanaka, Powder Technol. 77 (1 993) 79-87. [2 1 ] K. Odagi, T. Tanaka, Y. Tsuji, J. Soc. Powder Technol. Jpn. 38 (2001 ) 1 50-1 59. [22] Y. Tsuji, T. Tanaka, T. Ishida, Powder Technol. 71 ( 1 992) 239-250. [23] RC. Rowe, RJ. Roberts, Intelligent Software for Product Formulation, Taylor & Francis, London, 1 998. [24] J.S.R Jang, C.T. Sun, E. Mizutani, Neuro-Fuzzy and Soft Computing, Englewood Cliffs, Prentice-Hall, NJ, 1 997. [25] S. Inghelbrecht, J.P. Remon, P. Fernandes de Aguiar, B. Walczak, D. Massart, F. Van De Velde, P. De Baets, H . Vermeerseh, P. De Backer, Int. J. Pharm. 1 48 (1 997) 1 03-1 1 5 . [26] M . Turkoglu, I. Aydin, M. Murray, A Sakr, Eur. J. Pharm. Biopharm. 48 (1 999) 239-245. [27] R Mansa, R Bridson, RW Greenwood, J . P.K. Seville, H . Barker, Int. Conf. Particle Technol. (PARTEC), Nuremburg, Germany, 2004, conference CD. [28] O. Simon , Etude experimentale de I'interaction alimentation-compaction dans une presse a rouleaux lisses alimentee par une vis horizontale, PhD Thesis, Universite de Technologie de Compiegne (2000). [29] AV. Zinchuk, M.P. Mullarney, B.C. Hancock, Int. J . Pharm. 263 (2004) 403-4 1 5 . [30] G.W Gereg, M.L. Cappola, Pharm. Technol. 26 (2002) 1 4-23. [3 1 ] Y. Loginov, S.P. Bourkine, NA Babailov, J. Mater. Process. Technol. 1 1 8 (200 1 ) 1 5 1-1 57. [32] RW. Heckei , Density-pressure relationships in powder compaction, Trans. Metall . Soc. A l M E 221 ( 1 96 1 ) 67 1-675. [33] AR Cooper, L.E. Eaton, J. Am. Ceram. Soc. 45 (1 962) 97-1 01 . [34] K. Kawakita, J. Soc. Mater. Sei. Jpn. 1 3 ( 1 964) 42-428. [35] G. Bindhumadhavan, Roll compaction of pharmaceutical powders, PhD Thesis, University of Birmingham, 2005. [36] B.J. Briseoe, AC. Smith, YA Yusof, Chem. Eng. Sei. 60 ( 1 4) (2004) 391 9-3931 . [37] A Petit-Renaud, C. Laroche, P. Guigon , Experimental study of the roll compaction of powders, World Cong. Particle Technol. 3, Brighton, U . K . , 1 998. [38] O. Simon, P. Guigon, Interaction between feeding and compaction during lactose compaction in a laboratory roll press, Kona Powder Part. 1 8 (2000) 1 34-1 38. [39] P. Guigon , O. Simon, Roll press design - influence of force feed systems on com paction , Powder Technol. 1 30 (2003) 41-48. [40] O. Simon, P. Guigon, Powder Technol. 1 30 (2003) 257-264.
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[4 1 ] T. Lecompte, Etude experimentale et numerique de la compression de poudre or ganique en presse a rouleaux, alimentee par une vis sans fin, PhD Thesis, Institut National Polytechnique de Grenoble, 2005. [42] E. Goidin-Jeröme, A. Delacourte, J.C. Guyot, F. Dehont, P. Hervieu, S.T.P. Pharma Sciences 2 (4) (1 992) 320-324. [43] O. Simon, G. Turini, P. Guigon, Determination of velocity of powder in the nip region of a laboratory roll press using video analysis, IBA Proceedings, 26, San Diego, California, USA ( 1 999) 67-77. [44] L Gaete-Garreton, Y. Vargas-Hernandez, A. Chamayou, JA Dodds, W. Valderama Reyes, F. Montoya-Vitini, Chem. Eng. Sei. 58 ( 1 9) (2003) 431 7-4322. [45] T. Hirohata, S. Masaki, S. Shima, J. Mater. Process. TechnoL 1 1 1 ( 1 -3) (200 1 ) 1 1 3-1 1 7. [46] J . M . Bultmann, Eur. J. Pharm. Biopharm. 54 (2002) 59-64. [47] A. Hakanen, E. Laine, Drug Dev. Ind. Pharm. 1 9 ( 1 993) 2539-2560. [48] J . Salonen, K. Salmi, A. Hakanen, E. Laine, K. Linsaari, Int. J . Pharm. 1 53 (1 997) 257-26 1 .
CHAPTER 6 Dry G ra n u latio n Kazuo Nishii,a, * and Masayuki Horio b
aNishii Gijutsushi Jimusho (Nishii Professional Engineers' Firm), Japan bGraduate School of Bio-Applications and Systems Engineering, Tokyo University of Agriculture and Technology, Tokyo, Japan Contents 1 . I ntraduction 2. Grawth Pracess and Mechanism 3. Operating Variables 3. 1 . Total granulation time 3.2. Superficial fluidizing gas velocity 3.3. Back pressure for downward gas flow 3.4. Durations of fluidization and downward gas flow periods 4. Material Properties 4. 1 . PSG from a single powder 4.2. PSG from hard-metal powder mixture 4.3. Co-granulation fram mixtures of pharmaceutical powders 5. Scale-up Considerations 5. 1 . Scale-up testing with a lactose powder 5.2. Scale-up testing with a hardmetal powder 6. Applications 6. 1 . Application to powder metallurgy industry 6 . 1 . 1 . Hard-metal materials of WC-Co with a lubricant 6 . 1 .2. Hard-metal materials fram WC-Co without lubricants 6.2. Application to pharmaceutical industry 6.2. 1 . A drug mixture with an excipient for dry powder inhalation 6.2.2. Powder coating of drug particles o n excipient granules for dry powder inhalation 7. Theory 8 . Summary References
289 291 294 294 294 297 297 298 299 300 301 303 306 306 307 308 308 310 312 313 314 319 32 1 322
1 . INTRODUCTION
Fine particles with sizes of less than several microns are mostly cohesive and are readily agglomerated by exerting pressure on them. Dry granulation utilizes their *Corresponding author. E-mail: vzy0451
[email protected] Granulation
Edited by A.D. Salman, M.J. Houns/ow and J. P.K. Seville B.v. t) 2007
Elsevier
All rights reserved
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gas flow
Pressing
Extruding
Tumbling
Fluidizing
F i g . 1 . Typical dry granulation methods.
cohesive characteristics to form larger granules without using any binders but with pressure by extruding, tumbling and fluidizing powders as shown in Fig. 1 . 'Pressing' is performed mechanically or pneumatically. Roll compaction is the typical mechanical pressing method as described in a previous chapter. As a novel pneumatic method, Akiyama etat. [1] granulated superfine silica anhydride and diatomaceous earth by liberating air out of a pressurized chamber into a chamber containing the powders but evacuated initially. They reported that this method is applicable to powders whose bulk volume can be reduced by more than 40% by air compaction. 'Extruding' is conducted by scraping fine powders through a sieve or a per forated plate. It is an old-fashioned granulation method but is still used to some extent in industries as a simple and easy method. However, such equipments are difficult to automate. Another difficultiy is that the improvement in flowability is small because of the wide size distribution and rod Iike shape of the product granules. 'Tumbling' has also been applied over sixty years [2]. Meissner et at. [3, 4] investigated the agglomeration behavior of fine ZnO powders in a tumbling bottle. They reported that steady-state granules were obtained after revolutions between 40000 and 635000 at the speed of 1 1 0 rpm. Claussen et at. investigated the spheronization behavior with WC-1 0%Co powders of 1-2 f-lm in diameter for 1 2 hours and proposed a model for granule growth [5]. However, such granulation times are too long for commercial production. It is also difficult to obtain spherical and small granules of less than 1 mm because tumbling does not work effectively for small granules. 'Fluidizing' of fine cohesive particles has been recognized as a difficult process but known to form agglomerates as weil. The first report of the agglomerating tendency was made, as far as the authors' knowledge is concerned, by Sugihara [6] and Bearns [7] independently in 1 966. Sugihara investigated fluidization with fine particles of O.9�35 f-lm in diameter. He reported that the measured minimum fluidization velocity umfincreased with decreasing particle diameter in comparison with the Umf of primary particles calculated from the Kozeny-Carman equation.
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He concluded that fine powders were fluidized in the form of agglomerates and estimated the agglomerate size. Bearns investigated the effect of cohesiveness of fine particies ranging from 2 to 200 flm in diameter on fluidization conditions. He defined a fluidizability index (FI) as a ratio of the calculated Umf and the measured Umf' However, such agglomerating behavior remained unnoticed until Chaouki etat. [8] of 1 985. They investigated the bed pressure drop and bed expansion of extremely light aerogels of CuOjAI 20 3 and CujAI 2 0 3 (bulk density: 66 kgjm 3) fluidized with gases of H 2 and N 2 in the temperature range from room temper ature to 473 K. They reported that the bed was changed from a packed state to a fluidized state at a gas velocity much higher than the calculated Umf of primary particles. An overall agglomerate size determined from photographs of approx imately 1 mm in diameter was observed. In many cases, the target of granulation is to produce free-flowing granules with a mean particie size of less than 1 mm in diameter. Granulation by fluid ization as a whole can produce smaller spherical granules within a shorter gran ulation time than tumbling. However, the reproducibility of product properties is difficult to achieve because of its insufficient capability to cope with the wide property distribution in the initial bed. In 1 989, Nishii et al. [9] reached the idea that this self-agglomerating tendency can be utilized for dry binderless granulation, while the attention of many workers was focused solely on the phenomenology. In 1 993 the idea was developed further into a novel granulation system named Pressure Swing Granulation (PSG) [10] . The advantage of PSG is the reproducibility of product properties that can be obtained by repeated fluidization and reverse pressure action for filter cieanup while maintaining the simplicity and functionality of fluidized bed granulation. The growth behaviors of dry granulations by extruding and tumbling are similar to those of the wet granulations that are described in other chapters. However, the growth behavior of dry granulation by fluidization is different from that of the wet granulation, which has never been discussed precisely in the literature. In this chapter, the dry granulation by fluidization is discussed on the basis of PSG results.
2. GROWTH PROCESS AND MECHANISM
In PSG, the periodic and sudden introduction of downward gas flow into the column of the normal fluidization operation unifies the quality of agglomerates as illustrated in Fig. 2. When gas is introduced upward into the bed of a fine cohesive powder, chan nels are formed in the bed or the bed is lifted up as a plug in the beginning. Then,
292
K. Nishii and M. Horio B reakage
t t t Upward gas f10w
Downward gas f10w
.! .! � Upward gas flow F l u i d izatlon
Com pactlon
Fig. 2. Principle of Pressure Swing Granulation.
the bed is partially fluidized with frag mental agglomerates of various sizes. If the gas velocity is further increased to improve the fluidization quality, the entrainment of fine particles also increases and the bed may still remains in the abnormal state. At this moment, if the fluidizing gas is shut down and downward gas flow is applied to the bed, the bed is compacted and the channels and large fragments formed during the fluidization period are collapsed by the downward gas pressure. At the same time, the fine particles accumulated on bag filters installed in the freeboard are recycled back to the bed. This period of downward gas flow is followed by the upward gas flow whose volume is more than that of the fluidizing gas flow and there the compacted bed is braken into smaller fragments. In the course of re peated fluidization, the fluidization quality is gradually impraved, fines are captured by larger agglomerates and agglomerates of irregular shapes andjor too large sizes are made more spherical and smaller through attrition. Eventually, after several hundreds cycles, the generation of elutriated fines decreases significantly and spherical granules of a narraw equilibrium size dis tribution with smooth surface morphology are obtained as shown in Fig. 3. The granules produced with this method have two kinds of internal structure as shown in Fig. 4; A core-shell structure (a). The core part has the same structure as the initial porous bed but is surrounded by a denser shell layer. These gran ules graw from cores composed fram the initial small fragments by the subse quent impaction and layering of fine particles. The second type is a uniform structure (Fig. 4(b)). In this case the whole granule's meso-structure is presum ably the same as the initial bed. Granules with the laUer structure are supposed to be obtained fram the large fragments broken in the early stage of granulation.
293
Dry Granulation
Fig. 3. Optical micrographs of ZnO powder during PSG granulation. (a), as received powder; (b), after 4 cycles; (c), after 8 cycies; (d), after 1 6 cycies; (e), after 32 cycies; (f), after 64 cycies; (g), after 1 28 cycies; (h), after 256 cycies.
(a)
(b) ----- 500 l!m
Fig. 4. Scanning electron micrographs of ZnO granules split with a needle. (a), core-shell structure; (b), nonnucieated structure.
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K. Nishii and M. Horio
3. OPERATING VARIABLES
The characteristics of binderless granules are influenced by operating variables and material properties. In PSG systems, the major operating variables are durations of fluidization and downward gas flow periods and the chamber pres sure for the downward gas flow in addition to the total granulation time and superficial fluidizing gas velocity UD, which are common variables of conventional fluidization. In this section, these effects are discussed with the results of PSG experiments [1 1 ] . A fluidized-bed column of 1 00 mm in diameter, dehumidified compressed air, and ZnO powder (Miyazawa Chemicals), of which the median diameter dp,50 is 0.57 ).lm, were used for the experiments unless otherwise stated. 3. 1 . Total granulation time
As described in Section 2, the granule sizes tend to converge at a certain size through time. From the scientificjengineering point of view it is important to know the time required for it. The granulation experiment was performed using a small column of 44 mm in diameter with nitrogen gas (purity: 99.997%) to prevent the effect of moisture for 450 cycles, Le. approximately 2 h and the granules sampled out of the bed during granulation were evaluated. Figure 5 shows the size distribution change during granulation. A similar growth process has also been obtained by using a larger column with dehumidified compressed air as shown in Fig. 3. After 32 granulation cycles, the size distribution of agglomerates was still rather wide with a peak in the size fraction at 300 ).lm. As the granulation cycles were increased further, the peak progressively shifted and the PSD narrowed to near equilibrium ones. The size fraction between 350 and 500 ).lm reached approx imately 80 wt% after 450 cycles. This was achieved in a very short time in com parison with that of more than 6 h for the tumbling method. In addition, free flowing granules can be obtained after a hundred cycles, Le. approximately 30 minutes, when granules are not completely spherical. Such granules are already valuable since spherical granules with a uniform size are desirable but they are not always required, especially for intermediate products. 3.2. Superficial fluidizing gas velocity
Granule growth occurs mainly during the fluidization period. Therefore, the op erating velocity of the bed is supposed to have an important impact on this condition. Figure 6 shows the effect of the fluidizing gas velocity Uo on the median granule diameter obtained at 1 0 various velocities ranging from 0.354 to 1 .46 m/s
Dry Granulation
1 00 80
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:c
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Granule diameter b1m] Fig. 5. Size distribution change of ZnO granules with granulation cycles. 0 . 7 r-------, c:
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Fluidizing air velocity [m/s]
Fig. 6. Effect of fluidizing air velocity on mean granule diameter.
for a total granulation time of 900 cycies for each test [12]. The lower limit of the above range was determined based on visual observations. Below 0.354 m/s, fluidization quality was poor. The upper limit was simply determined by the ca pacity of the air compressor used.
K. Nishii and M . Horio
296
In the previous works on the growth rate of granules by fluidized-bed spray granulation [1 3] or attrition rates of particles in a fluidized bed [14] granule sizes were reported to reduce with increasing Ua. However, with the PSG system, the size of granules increased with increasing fluidizing gas velocity. Granules larger than 5 mm in diameter have been obtained from the circulating fluidized bed configuration with Ua of 2.71 mjs in the riser although their size distribution is rather wide [1 5]. This is because the higher gas velocity accelerates attrition of large size fractions and enhances the deposition of smaller particles. Figure 7 shows the effect of fluidizing velocity on the granule density. The granule density is determined based on the weight of 1 00 granules sieved be tween 0.5 and 0.71 mm in diameter with a mean diameter of 0.605 mm.The granule density is also found to increase as Ua is increased. This is considered to be the combined results of the attrition of core that had a density lower than the deposited layer, and the densification of deposited layer by increased and in tensified collisions. Note here that each core should have originated from the porous agglomerates formed in the early stage of granulation. The minimum fluidization velocity Umf and the terminal velocity Ut of granules were calculated using the size and density of the converged granules obtained at two values of the fluidizing gas velocity. For calculation of Umf, the Wen-Yu equation [1 6] was used and for Ut the Allen equation is used because of their Reynolds number of between 5.76 and 5 1 7. The granules produced at superficial velocity of 0.5 and 1 mjs had umf of 0.084 and 0.202 mjs and Ut of 2.50 and 4.06 mjs, respectively. From these results it is quite clear that attrition, deposition and collision mechanisms are essential in PSG process. 5000 E --
4000
. E
u c 0 u CI> "0
(/) CI> ::> C '" �
50
'E Cl 2 5 '" N C CI> .s=
W
1 00 75 50 25 Ethenzamide concentration of starting powder mixtures (mass%]
Fig. 1 7. Content uniformity of ethenzamide in individual granules fram powders E-1 and L-9.
306
K. Nishii and M. Horio
5. 1 . Scale-up testing with a lactose powder
An experiment was performed with a jet-milled lactose powder with dp,50 of 2.6 11m in three PSG granulators with column diameters of 1 00, 230 and 350 mm, respectively. All granulators are made of stainless steel. Oehumidified com pressed air was used for downward flow. In the case of the 1 00 mm granulator, dehumidified compressed air was used for fluidization. However, ambient air was used in the other two cases. The granulation conditions were all the same as shown in Table 5. As shown in Fig. 1 8, granules of fairly similar characteristics were obtained for the three PSG granulators of different diameters. The median diameters of the granules from 1 00, 230 and 350 mm 1 . 0. granulators were 0.45, 0.43 and 0.44 mm, and the bulk densities were 420, 340, and 350 kg/m 3 , respectively. The granule size seems to be converged within 1 20 minutes of the total granulation time. The bulk density of granules from 1 00 mm 1 . 0. granulator was slightly higher than from 230 and 350 mm granulators presumably due to the wall effect. Incidentally, the powder deposition was not observed on the stainless steel chamber wall during the tests. This is an advantage of stainless steel wall to satisfy the essential requirement of no deposition especially from the pharma ceutical industry. 5.2. Scale-up testing with a hardmetal powder.
Experimental tests were performed with a hard-metal powder of 1 .5 11m WC6wt. %Co-1 .8wt. % paraffin wax using the same PSG granulators as described in Section 5. 1 . The mixed dry material was provided from a hard-metal tool man ufacturer. The fluidizing air was heated at 70°C, which is above the melting point of paraffin wax (56°C), to reduce the fine particles generated at filling process to a die. The granulation conditions are shown in Table 6. Figure 19 shows the granules obtained in the testing. The bulk densities of product granules from granulators of 1 00, 230 and 350 mm I. O. were 371 0, 3800 and 3760 kg/m 3 , and the angles of repose were 34, 33 and 35°, respectively. In this case the similar overall bulk density of the granules was obtained for all Table 5. Scale-up testing conditions for a lactose powder
Bed height (mm) Superficial fluidizing gas velocity (m/s) Initial pressure of downward gas flow(MPaG) Ouration of fluidization period (s) Ouration of downward gas flow period (s) Total granulation time (min)
60 0.42 0.03 15 1 .0 1 20
307
Dry Granulation
(a)
(c) -
1 mm
Fig. 1 8 . Micrographs of lactose granules using three kinds of PSG granulators with the column diameters of (a), 1 00 mm; (b), 230 mm; (c); 350 mm.
Ta ble 6. Scale-up testing conditions for a hard-metal powder
Bed height (mm) Superficial fluidizing gas velocity (mjs) Initial pressure of downward gas flow (MPaG) Duration of fluidization period (s) Duration of downward gas flow period (s) Total granulation time (min)
1 00 0.64 0.03 15 1 .5 30
because the density of the hard-metal material was extremely high. The granule size was not evaluated since it is not so important for the evaluation of free flowing. However, as can be seen the mean diameters of granules were similar. The size distributions of hard-metal granules were wider than those of lactose granules. With a longer total granulation time this should be improved but will lead to an increase in costs. In the present case, the production cost was given priority over that of a narrower size distribution for the granules. In summary, the simple scale-up procedure of maintaining the same fluidizing air velocity and bed height successfully was applied to PSG granulators with column diameters from 1 00 to 500 mm. 6. APPLICATIONS
The granules obtained with dry fluidized-bed granulation are porous and their strength is approximately one or two orders of magnitude smaller than that of
308
(a)
K. Nishii and M. Horio
(b)
(c) -
O.5 mm
Fig. 1 9. Micrographs of hardmetal granules using PSG granulators with the column di ameters of; (a), 1 00 mm; (b), 230 mm; (c); 350 mm.
granules with wet binders because the wet binders once dried produce much stronger solid bridges while in dry granulation particles are agglomerated by only interparticle forces. It is thus inappropriate for us to build a large stockpile with granules from dry granulation or to handle them violently before use. Accordingly, this method seems to suit to small production andjor to intermediate process for products that require high purity, good compressibility, and good dispersibility into air and liquids.
6.1 . Application to powder metallurgy industry
In the powder metallurgy industry, binder granulation of fine powders is per formed before pressing to obtain free-flowing granules. For granulation of hard metal powders, spray drying has also been performed exclusively after wet mixing in a solvent such as ethanol and acetone. Accordingly, in spray drying the system becomes more complicated by introducing nitrogen gas circulation sys tem to prevent both oxidization of materials and solvent explosion. Combined with a vacuum dryer PSG systems can be much more cost-effective than spray drying systems, especially for small production volumes.
6.1.1. Hard-metal materials of WC-Co with a lubricant
In the formulation of WC-Co materials, mainly WC particle size and Co content are determined in accordance with the intended use of a tool. The WC size is
309
Dry Granulation
commonly selected from 0.5 to 1 0 )lm, and the Co content fram 6 to 25 wt.%. Paraffin wax of 0.5-3 wt. % is added as a lubricant for die pressing. Generally speaking, materials with coarser WC particles, larger Co and paraffin wax content tend to be more difficult to granulate. For materials with WC particles of sizes less than 1 .5 )lm, Co content less than 1 0 wt. % and paraffin wax content less than 3 wt. % can be successfully granulated by dry granulation as described in Section 4. Most of the materials have been smoothly granulated by supplying hot fluidizing air to utilize paraffin wax in a melt condition [1 9, 21]. Hot fluidizing air was applied to a PSG system for the conventional die pressing/sintering process (see Table 7) and found to be beneficial since it eliminates the generation of fine particles that causes pressing problems such as high friction between die and punches. Figure 20 shows scanning electron micrographs of PSG granules with various formulations of WC-Co materials. The angle of re pose of the product granules was significantly improved compared with those of the original powders as shown in Fig. 21 . Sintered bodies of 4 8 24 mm were prepared by die-pressing of granules at 1 00 MPa and were then sintered at 1 673 K in vacuum for 1 h. The density of the sintered bodies obtained from the granules were higher than 99% of the theoretical one. Figures 22 and 23 show RockweIl hardness and transverse rupture strength of the sintered bodies, respectively. They satisfy the cemented carbide industrial standard of Japan Carbide Tool Manufacturers' Association (CIS 01 9C-1 990). The PSG system has been employed so far by 16 manufacturers in four countries for granulation of har-dmetal materials not only for WC-Co-paraffin wax systems but also for other cermets-paraffin wax systems. PSG is applicable to other materials with the aid of melting additives such as paraffin wax. Further investigation is, however, needed to clarify its limitation. For instance, in the case of WC-Co systems granules are difficult to obtain when paraffin wax is added more than 3 wt. % even with hot air. If the surface of pow ders is completely covered with wax, the surface energy of powder is decreased and the granulation tendency is reduced. Even though the wettability of paraffin wax is low, it seems to be the reason for the difficulty we have experienced. Likewise, dry fluidized-bed granulation cannot be successfully performed in high moisture circumstances. x
x
Table 7. Compositions of hardmetal powders
Powder W-4 W-5 W-6
WC [wt.%]
93.0 (dp.50 = 1 .5 )lm) 85.0 (dp,50 = 1 6.0 )lm) 77.0 (dp,50 = 9.0 )lm)
Co [wt.%] 7.0 1 5.0 23.0
Paraffin wax [wt.%] 0.5 0.5 0.5
310
K . Nishii and M . Horio
(c)
- 0. 1 mm
Fig. 20. Scanning electron micrographs of PSG granules of WC-Co materials (uo 0.548 m/s, total granulation time: 1 6 min). =
70 .-----� o :Original powders
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---
--
2 � 5--� 30
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Fig. 2 1 . Angle repose of the granules of WC-Co materials.
6.1.2. Hard-metal materials tram WC-Co without lubricants.
Spark Plasma Sintering (SPS) is a new technology in powder metallurgy industry. The sintered bodies with higher hardness and transverse rupture strength can be obtained at lower temperature and pressure in a rather shorter time than those in the conventional methods. In this technique, the material without any lubricants is preferred since pressing and sintering is performed simultaneously if no de-wax ing stage is needed. Accordingly, products with high purity can be obtained.
31 1
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�
95
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0
5
10
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Co content
20
25
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[wt.%]
Fig. 22. RockweIl hardness of sintered bodies from the granules of WC-Co materials.
3500 �------� Granules :PSG al 348K Compacling: 1 tf/cm2 3000 Sinlering : 1 673K.l h Ä 2500 2000
.------ �
•
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1 500
•
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Co content [wt.%] Fig. 23. Transverse rupture strength of sintered bodies from the granules of WC-Co ma terials.
The authors [22] granulated 0.5 j.LmWC-6wt%Co mixture with PSG method using ambient air. The initial material was mixed in a wet ball-mill of ethanol with an agitator for 5 h and then dried in a vacuum mixer with an agitator before granulation. The methods of the upstream pracess were selected as an optimum for PSG. Figure 24 shows a micragraph of the granules. The yield of the granules bet ween 0 . 1 5 and 0.84 mm in diameter was 89%. Table 8 shows the properties of the granules in comparison with those made by spray drying. The hall flow of spray-dried granules was unable to be determined as da,5o was approximately 50 j.Lm and the granules did not flow out of a funnel with an orifice of 1 0 mm in diameter. The Fe and 0 contents for PSG granules are slightly higher than the spray dried granules but oxidization by the fluidizing air and Fe contamination fram the
312
K. Nishii a n d M . Horio
-
1 mm
Fig. 24. Micrograph of PSG granules of 0.5 IlmWC-6wt%Co (uo = 0.43 m/s, total granu lation time: 60 min).
Table 8. Properties of granules obtained
Bulk density (kg/m 3) Angle of repose (deg.) Hall flow (s/200 g) Fe content (wt.%) o content (wt.%)
Spray-dried 2000 50 No flow out 0.0020 0.34
PSG 2660 27 2.6 0.0028 0.36
stainless-steel container are tolerable in commercial production. Since in spray drying a binder shall be required, PSG can provide better process concepts. As far as the authors knowledge is concerned, two PSG systems have been employed for granulation of hard-metal materials not only for WC-Co but also only for WC in the manufacturer of SPS systems. For other advanced materials such as AIN and rare earth-based magnetic materials, granulation testing was also successfully performed but the system has not been employed in the industry yet. Some breakthrough is required for each process under consideration of its upstream and downstream. 6.2. Application to pharmaceutical industry
Dry granulation is finding new applications in drug designs as an alternative delivering method for systemic medications, e.9. peptides and proteins to avoid
Dry Granulation
313
the "first-pass effect", i.e. drug metabolism in the liver and unwanted systemic side effects. So far, there are three major delivery systems available, namely, (1 ) nebulizer, (2) metered dose inhalation (MDI) and (3) dry powder inhalation (DPI). In DPI system, dry drug particles have to be aerosolized and inhaled by the aspiratory effort of the patient and deposited on the target region of the lungs. DPI is now recognized to be in an advantageous position over the other meth ods; nebulizers are expensive and unsuitable for portable use and MOl requires chlorofluorocarbon propellant whose utilization has to be stopped due to their ozone depleting effect. In DPI, controlling particle cohesiveness is a key factor in its implementation because powders need to de-agglomerate into aerosol particles having a size range of 1 to 7 ).lm that can reach bronchi or alveoli in the lung. The applicability of dry fluidized-bed granulation to pharmaceutical powders has already been dem onstrated in Section 4, its product granules are suitable for DPI. This is because they are sufficiently weak for easy disintegration and dispersion but sufficiently strong to maintain their shape in the container until its use under practical conditions.
6.2.1. A drug mixture with an excipient for dry powder inhalation
The major formulation of DPI medication includes coarse excipient particles such as lactose with a diameter of approximately 60 ).lm that acts firstly to dilute the drug ingredient and secondly to obtain the free-flowing mixture. In this section, the effects of lactose particle size and its content on the di spersibility of PSG granules from mixtures of lactose and ethenzamide powders shown in Section 4 are discussed based on the work by Takano, Nishii and Horio [20]. The inhalation properties of the granules were evaluated with a cascade impactor (Tokyo Dylec, AN-200), a vacuum pump and a ball mill-like inhaler for Intal:IT, (Fujisawa Pharmaceutical, E-haler}') as shown in Fig. 25. 20 mg of the product granules (size range: 0.35-0.50 mm) was fed into a NO.2 HPMC capsule (Shionogi Qualicaps), inserted into the E-haler,j{ and then suctioned at an op erating airflow rate of 28.3L/min for 5 s. Afterwards, the capsule, the inside of the inhaler, throat, and each stage of the cascade impactor were rinsed with ethanol and analyzed with the spectrophotometer to determine the quantity of ethenz amide in each section. The respiratory fraction was calculated from the amount of ethenzamide collected in each section as a percentage of the amount loaded into the capsule. Figure 26 shows the results of the dispersion experiments, where the mass fraction of ethenzamide deposited on each stage is indicated. In addition, the total percentages of the deposition on stages of respirable size range from stage
314
K. Nishii and M. Horio
stageO:> 1 1 �l m f1='I' :l! "I': "" __ stag e 1 :7 ·1 1 �lm 1L=or ,.JI �___,.JI stag e2:4 . 7·7flm _ stage 3:3.3.4. 7j.l m � :l! stage4:2.1 .3.3j.l m f1='I' """I'::l! stage5: 1 .1 ·2.1 j.lm f1='I' :l! _ _ _ _
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No
J
I
Fig. 6. Monte Carlo algorithm used in the current work to determine the coating weight gain of each tablet in the pan.
in order to predict the coating variability. The projected surface area values were randomly chosen from experimentally obtained projected surface area distribution. The movement was simulated for all the tablets in the bed for a coating time of 30 min and the weight gain of each tablet was calculated using equation (7). The coating weight variability between the tablets was calculated using equation (8). mi =
n
L L AexpSflux�t 1
Pass
cv = (Jm
Pm
X
1 00
(7) (8)
390
P. Pandey et al.
where mi (g) is the coating weight gained by tablet 't, Aexp (mm2) is the projected surface area at each sighting of the tablet in the spray zone, Sflux (gjmm2js) is the spray flux at the centroid location of the tablet, CV is the weight gain coating variability, (jm is the standard deviation of the coating weight gain distribution, 11m is the average of the coating weight gain distribution, and n is the total number of passes taken by each tablet through the spray zone. Each 'pass' is defined by the appearance of the tablet in the spray zone before 'disappearing' into the bulk of the tablet bed. 2. 3.4. Results
The operating variables studied in this work in the experimental matrix include pan speed (6, 9, and 1 2 rpm), tablet size (6.4, 7.9, and 1 0.4 mm), pan loading (2 levels), spray shape, spray area, and spray flux (uniform, non-uniform) inside spray zone. The pan loading was quantified by using the fractional fill volume ( v) , defined as the ratio of volume occupied by the bed to the total pan volume, given by equation (9). It was varied at two levels (v = 0. 1 0 and 0 . 1 7), which covers the range of typical pan loadings used in the industry. volume of bed v = (9) pan volume The video-imaging data were used to generate distributions of circulation time, surface time (time spent in the spray zone per pass), projected surface area per pass and velocities in two directions for these conditions. These distributions are shown in Figs. 7(A)-(C), for 1 0.4 mm tablets at a pan speed of 9 rpm and a fractional fill volume of 0.1 0. It is c1ear from the figures that the distributions are non-normal in nature. However, the velocity distributions in 2 directions were found to be normal, as shown in Figs. 8(A) and (8) for 1 0.4 mm tablets at a pan speed of 9 rpm and a fractional fill volume of 0.1 0. The effects of average circulation time, surface time, projected surface area, and velocity as a function of tablet size, pan speed, and pan loading have been discussed in detail elsewhere [1 6, 1 7]. The main reason for the observed weight gain variability in the coating process is that all of the tablets in the bed do not behave in an identical manner over a given time period. For example, the number of passes each tablet makes through the spray zone is not the same. This is captured by Monte Carlo simulation and a typical result is shown in Fig. 9 for 1 0.4 mm placebo standard round tablets in a 30 min coating run at a pan speed of 9 rpm. It is desirable to have a 'narrow' distribution of circulation frequency between different tablets. This can be achieved by using mixing aidsjbaffles in the system [1 9]. --
--
2.3.4. 1 . Effect of coating time
The effect of coating time on CV was also studied. It was found that the CV decreases with increasing coating time, as shown in Fig. 1 0(A), for 1 0.4 mm
Modelling of Pan-Coating Processes
391
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250
Fig. 7. Distributions of (A) circulation time, (8) surface time, and (C) projected surface area per pass, for 1 OA mm tablets at a pan speed of 9 rpm and a fractional fill volume of 0 . 1 0.
392
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393
Modelling of Pan-Coating Processes
tablets rotating at a pan speed 1 2 rpm at a fractional volume fill of 0 . 1 0. It was also found that the CV is inversely proportional to the square root of coating time, as shown in Fig. 1 0(8) (equation (1 0)). 1 CV cx - (1 0) ,Jtcoal where tcoal is the total coating time. 2.3.4.2. Effect of spray shape and spray area
The effect of spray shape (eilipsoidal and circular) on CV was investigated. Initiaily, the spray area was maintained the same for both the cases. This meant that the entire pan width was not covered for the circular spray shape and ailowed 'bypassing' of tablets without getting sprayed/coated, as shown in Fig. 1 1 (A). This resulted in significantly higher CV values for circular spray shape, which, not surprisingly, shows that it is critical that the spray covers the entire pan width and ailows no or minimal bypassing [4]. In order to study the effect of spray shape alone, the spray area for the circular and eiliptical spray shapes was kept the same, and the entire pan width was covered. This was achieved by comparing two circular shaped spray regions with one eiliptical spray region, as shown in Fig. 1 1 (8) and (C). The ratio of the minor axis of the ellipse to the major axis was kept at 0.5, to maintain the same total
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2 circular spray zones
•
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394
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Modelling of Pan-Coating Processes
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Fig. 1 6. Normalized spray flux as a function of the location of the tablet i nside the spray zone, as measured by the linear patternator at an atomizing air pressure of 40 psi and a gun-to-bed distance of 1 0.2 cm (4 in.). 2 . 3 .4.4. Effect of spray flux variation inside the spray zone
The spray flux variation inside the spray zone was measured using the pat ternator shown in Fig. 5. The spray gun used was a two-fluid air atomizing nozzle (model 1 /8JAC + SU 1 1 ) fram Spraying Systems (Wheaton, IL). The normalized spray flux variation data obtained fram the paUernator as a function of distance (r1) fram the centre of spray zone is shown in Fig. 1 6. The atomizing air pressure used for this experiment was 40 psi with a gun-to-bed distance of 1 0.2 cm (4 in.). Figure 1 7 shows the results for 1 0.4 mm tablets, at a fractional fill volume of 0. 1 0 and at 3 different pan speeds. The uniform spray flux (no variation within the spray zone) was found to give a lower CV in comparison to the case where spray flux va ries with respect to the location (non-uniform flux) inside the spray zone. It should also be noted that the value of CV decreased with an increase in pan speed, as shown in Fig. 1 7. Setter mixing is obtained at higher pan speeds, which results in lower weight gain variability during coating. 2.4. D iscrete element modelling (DEM) and computational fluid dynamics (CFD)
As described in the previous sections, renewal, compartmental, and Monte Carlo techniques can be used to predict the mass coating variability. However, some model parameters should be either determined a priori experimentally or adjusted to obtain good agreement between simulation and experimental results. In prin ciple, this limitation does not exist for the application of the discrete element
398
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modelling (DEM) and computational fluid dynamics (CFD) methods. Much work has been done on DEM and CFD modelling and although exact predictions using these methods is still not possible without some parameter adjustments, these techniques provide a powerfuI and rigorous modelling framework to compare the effect of key operating variables on system performance. Most of the previous work using CFD methods has focused on the modelling of fluidized bed equipment. In CFD, equations describing the momentum and cont inuity of gas and solids flow in the equipment are solved numerically. In order to predict CV by using CFD methods, the spray plume from the spray nozzle should be combined simultaneously with the governing equations for gas and solids flow. Then the mass deposition of coating material can be calculated based on the interaction of the solids with the droplets from the spray nozzle. Rajabi-Siahboomi [38] used CFD to investigate critical process parameters for aqueous film coating in side-vented coating pans. Although this approach is capable of predicting CV using the current commercial CFD codes, much work must still be done to com bine the movement of gas and solids and their interactions with spray droplet for the application of CFD to model successfully the mass coating variability. The Discrete Element Modelling method is another useful tool to study granular flow in fluidized bed coaters and coating pans. Unlike CFD simulation, particles are tracked individually rather than as a continuum flow. Newton's equations of motion are solved numerically for each particle in the DEM method. In order to obtain accurate results, the time step should be kept very smalI. Therefore, the DEM method is a time-consuming approach, especially for a coating pan process in which, even for lab scale equipment, in excess of ten thousand particles are used. As computers continue to become more powerful and the contact algorithms for non-spherical particles become more efficient, this limitation will be eased.
399
Modelling of Pan-Coating Processes
2. 4. 1. Spherical-particle DEM simulation
As discussed in the Monte Carlo section, the coating process has two main components, namely the particle movement in the pan and the spray dynamics. Although there is not much work on modelling mass coating variability by DEM, particle movement inside the fluidized beds has been investigated by several researchers [39-41]. In addition, the DEM method has been used widely to study granular flow in rotating drums. Yamane et al. [42] used the DEM method to predict the distributions of circulation time, surface time, and the particle area exposed to the spray in a rotating drum. Mass coating variability can be estimated based on these distributions. Recently, Wassgren et al. [43] used the DEM ap proach to simulate the coating process for spherical particles and tablets in a pan coater. The effect of pan speed, pan loading, pan size and particle properties on the particle movement inside the coating pans can be obtained using DEM methods. This information can then be combined with that from the spray pattern analysis to predict mass coating variability. An introduction to the DEM method and the application of DEM to particle movement in rotating drums is discussed in the subsequent sections. 2. 4. 2. DEM method
Newton's equations of motion are used to track the translation and orientation of each particle in the DEM method. The basic equations for translational and rota tional motion of each particle are: cfr =v _
dt
dcö dt
r
1
( 1 6) ( 1 7)
where v is the velocity vector of the particle, r is the position vector of the par ticle's centre, F is the total surface force acting on the particle which includes the total normal forces and total tangential forces, 9 is the gravitational accel eration, m is the mass of the particle, cö is the angular velocity, r is the total torque acting on the particle, 1 is the moment of inertia of the particle, where 1 = 2/5 mr 2 for a spherical particle, and r is the radius of the particle. For non-spherical particles, the moment of inertia can be determined based on the geometry of particles. It should be noted that vectors are defined in the traditional global Cartesian coordinates. It is assumed that the values of the right hand side terms of the above two equations are constant over a very small time step, M. By integrating equations ( 1 6) and ( 1 7) over the time step M, equations ( 1 8) and ( 1 9)
400
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are obtained.
v vo + (g Fo) -
=
-
-
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m
( 1 8)
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(1 9) I where suffix 0 refers to the value from the previous time step. In order to solve these equations, the contact forces between interacting par ticles should be known. The solution yields the trajectory of each particle in the DEM simulation. Soth normal and tangential force models are required. There are several models that have been proposed to predict contact forces between in teracting particles [44-47]. A MATLAS™-based DEM code was developed (by IETek™ , Tacoma, WA) to simulate the spherical particle movement in a rotating drum [37]. Figure 1 8, shows a snapshot of the graphical user interface (GUI), which provides a picto rial representation of the simulation process. From Fig. 1 8, it is shown that it is very straightforward to change the particle size, pan size, operating conditions, and physical properties for the DEM simulation. The effect of these parameters on the dynamic angle of repose and average cascading velocity on the inclined surface have been investigated and compared with experiments using a video imaging technique, described in Section 2.3.2. The experimental conditions are �oecIlOI"I
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as foliows: •
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• • •
The diameter of the spherical polystyrene balls used in the experiment is 9 mm with a particle density of 0.99 gjcm3 . Young's modulus and Poisson ratio of the polystyrene balls are 1 28 1 09 Njm2 and 0.3, respectively. The coefficient of friction is 0.5. The thickness and diameter of the coating pan are 1 0.5 and 58 cm, respectively. Three levels of pan speed are used in the experiments (6, 9, 1 2 rpm). Pan loading is represented by using a fractional fill volume (v), which is defined as the ratio of volume occupied by the particle bed to the total pan volume (equation (9)). Two levels of pan loadings are used, v 0. 1 0 and 0. 1 7. .
x
=
2. 4. 3. Dynamie angle of repose
The dynamic angle of repose is the angle formed by the inclined cascading surface and the horizontal and is illustrated in Fig. 1 9. A visual comparison of the dynamic angle between the experiments and simulations is shown in Fig. 1 9. Figure 20 shows the comparison of the dynamic angle obtained fram DEM sim ulation and experiments for two pan loadings and three pan speeds. Although the trends predicted by DEM were consistent with the experimental observations, the dynamic angle was found to be higher for the experiments. A possible reason for this difference is the 'wavy' shape of the cascading bed SUrface, which was observed to be more pranounced in experiments compared to simulations. 2. 4. 4. Average easeading ve/ocity of partie/es in the spray zone
The average cascading velocity of particles in the spray zone can be determined by using video-imaging methods as explained in Section 2.3.2. For the DEM
Fig. 1 9 . Comparison of simulation (A) and experiment (8) for 9 mm polystyrene balls in a 29 cm diameter pan. Parallel lines are shown in both figures to compare dynamic angles (slope) in both cases [37].
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at a higher cascading velocity than spheres with the same volume equivalent diameter. Therefore, it is important to model the shape of the partie/es in a more realistic way to improve the predictions of the DEM simulation. In order to simulate tablets in DEM, a contact algorithm is required to determine which partie/es are in contact with each other in multi-partie/e simulations. Since contact criteria are straightforward for spherical partie/es, multi-sphere represen tations of non-spherical partie/es are often used in tOO simulation. EI/iott et al. [49] used these methods to predict packing characteristics of non-spherical partie/es. The resufts showed that these methods are successful in determining the packing density of non-sphericaJ particJes. However, Song et al. [50] found that for the dynamic behaviour, there were large errors for single collisions of two tablets by
406
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using multi-sphere representations compared with experiments. Therefore, for sim ulating particle velocities the representation of tablet shape should be realistic, and yet the contact algorithms must not be too complicated otherwise simulation times become excessive. A method to represent the shape of standard round tablets, and the contact algorithm for these tablets was recently developed by Song et al. [50]. 2. 4. 7. Representation of tabtet shape and contact atgorithm
The intersection of three spheres is used to represent the shape of a typical round tablet, as shown in Fig. 25. From Fig. 25, the radii of the top and bottom surfaces (referred to Surfaces 2) are R2 and the radius of the side surface (referred to as Surface 1 ) is R1 . Other parameters used to define the geometry of the round tablet are shown in Fig. 25. On the basis of the above representation, there are three possible contact forms between the tablet and a flat surface, which are Surface 1 - Flat Surface, Surlace 2 - Flat Surface and Rim - Flat Surface as shown in Figs. 26(A) and (8). The corresponding contact criteria are also included in Fig. 26. In Fig. 26(C), S is the point on the rim of the tablet in contact with the flat surface. The location of .
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407
Modelling of Pan-Coating Processes p
Contact criteria for Surface Surface are:
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-
(8) p
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ß < y 90 - a
•
Axo + Byo + CZo + D $;
0
---------"'........ ... '-.. --- F1at Surface (C)
Fig. 26. (A) Schematic diagram of surface 2-flat surface contact, (B) schematic diagram of surface 1 -flat surface contact, and (C) schematic diagram of rim-flat surface contact [50].
point S is S(xo , Yo, zo) and the equation of the flat surface is Ax + By + Cz + D = O. In addition, there are three contact forms, which are Surface 1 - Surface 1 , Surface 1 - Surface 2 and Surface 2 - Surface 2 for the Tablet - Tablet contact shown in Fig. 27. Considering the Rim contact with the tablet, there are three more contacts, namely Rim - Surface 1 , Rim - Surface 2 and Rim - Rim for Tablet - Tablet contact shown in Fig. 28 (since Rim - Rim contact is not frequent,
408
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Contact criteria for Surface Surface I are:
(A)
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y, � 90 - 0:
•
y, � 90 - 0:
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0,0, < 2R,
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1', � 90 - 0(
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-
(e)
Fig. 27. (A) Schematic diagram of surface 1 -surface 1 contact, (8) schematic diagram of surface 2-surface 2 contact, and (C) schematic diagram of surface 1 -surface 2 contact [50].
it is not shown in Fig. 28). All contact criteria are shown in the related contact forms in Figs. 27 and 28. 2. 4. 8. Implementation of contact algorithm for tablet- tablet collision simulation
The contact criteria for tablet-shaped bodies were implemented in MATLAS™ code to model a collision between a moving tablet and a stationary tablet fixed to
409
Modelling of Pan-Coating Processes
Contact criteria for Rim Surface I are:
p
(A)
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Fig. 27. Basic properties of gas distribution plates.
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In accordance with processing requirements and size or design of the fluidized bed unit the pressure drop has to be specified correctly to guarantee the desired gas velocity distribution across the whole cross section. Moreover, the stress resistance must be high enough to avoid vibrations or breakage of the gas dis tributor. At the industrial scale the gas distributor plate itself has to be equipped with a support structure. Porous plate gas distributors are widely used in research and development to study the bubbling behaviour of gas-solid fluidized-bed hydrodynamics. Simple perforated plates are commonly used for many kinds of fluidized-bed applica tions. The main advantages are the low price, easy manufacture, the variety of specifications and the possibility of tailoring the plates to fit special demands (for instance, segmented design). In Fig. 28, two examples of perforated plates are shown. On the left side in Fig. 28 an example of a typical perforated plate is shown. This kind of plate is commercially available with relatively low thickness, for ex ample, 1-3 mm. Owing to the method of manufacturing the openings the min imum size of holes is of the same order as the plate thickness. That means small holes, which are needed to avoid passage of particles, can only be achieved with thin plates. In that case, an additional supporting frame below the hole-plate is needed for the structure to have sufficient stiffness and strength. To get more stress-resistant gas distributors the wedge-wire plates were in troduced in fluidized-bed processing (Fig. 29). This type of plate consists of profiles, which are welded direct on supporting profiles. The gap between the individual profiles determines the maximum size of openings. The advantage of such gas distributors is the very high stress resistance in combination with sm all opening sizes. Additionally these plates are also easy to clean. Standard perforated plates and wedge-wire plates are designed to create up wards gas flows (vertical to surface of gas distributor). That means the particles in
441
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fIWWl
special version without transport effect
Fig. 29. Examples of wedge-wire type gas distributors.
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a)
b)
Fig. 30. Examples of plates with transport effect.
the fluidized bed are not blown or conveyed in a certain direction. To have ( outlet gas
external solid feed q -------,
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Fig. 47. Principle of external seed production - conveying of seeds.
to the granulator as seeds. The oversized fraction also can be used if they are milled or crushed to a smaller size and returned to process. The fraction between the two sieve decks is defined as final product. External seeds are produced in additional processes. Typically powders can be used for further size enlargement in granulation plant. As an example, fine par ticles produced in spray dryers can be fed to a granulation plant where they will be enlarged by agglomeration, spray granulation or coating. The product flow and conveying of seeds can be done using typical solid transport principles like pneumatic transport, gravity, belts or screw conveyors. In Fig. 47, the discharged particles are fed to sieve and mill by gravity. This principle requires a certain minimum height below the fluidized-bed unit. The seeds are blown back to the granulator by pneumatic conveying. The conveying air is han dled by a blower, which produces enough overpressure for transportation. This principle is called dilute phase conveying. The conveying gas (mainly air) enters the fluidized-bed granulator. The filter system of this apparatus is used to handle this gas stream. The disadvantage of seed conveying by overpressure is the risk of dust for mation or contamination in case of a leak in the transport line. An alternative philosophy is to convey all discharged product upwards and then design the classification and millingjcrushing based on gravity. In Fig. 48, this principle is shown. The advantage of this setup is, in principle, easier conveying of discharged material due to its good flowing behaviour. Moreover less height below the gran ulator is needed. All downstream processing to handle final product and seed material can be based on flow by gravity. Because of this fine particle and dust conveying by pneumatic transport can be avoided. A disadvantage is the sig nificant increase in size of the conveying system. Here the total discharge stream
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Fig. 48. Principle of external seed production - conveying of discharged product.
has to be transported in contrast to only seeds conveying. Depending on process conditions, a smaller amount of discharge grains has to be recycled in a number of industrial applications. But there are also processes installed where the ma jority of discharge is recycled (in that case mainly undersized particles) and only a small percentage is the final product. This ratio varies from process to process and should be optimized during process development. 2.11 Liquid handling and spray systems
In most fluidized-bed processes for granulation and coating one or more liquids have to be added depending on the process. To have good process conditions for particle growth by coalescence of (smaller) particles, layering by spray granu lation, powder layering or coating in nearly all cases very small droplets are needed. Different types and sizes of spray nozzles are in use to transform the continuous liquid stream(s) into disperse drops. For atomization, in general, two basic types of spray nozzles are in use. These are pneumatic (binary) and hy draulic (pressure) nozzles as shown in Fig. 49. If spray nozzles have to be selected or designed for fluidized-bed applications, some general parameters have to be taken into account. These factors include: • • • •
drop size distribution or average drop size (e.g. Sauter-diameter); spray pattern (full cone, hollow cone, flat jet); spray angle; liquid feed rate (minimum, operation, maximum);
456
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pneumatic (binary) nozzle
gas cap
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.f..I--W-- spray liquid --M-I" ring gab L---- liquid outlel -----' Fig. 49. Nozzle types. • • •
drop velocity distribution or average drop velocity; feed pressure of the liquid; and atomization gas feed pressure and flow rate in case of pneumatic (binary) nozzles.
In Fig. 50 the different spray patterns are sketched. The spray pattern has an influence on the particle wetting and on the local liquid distribution in the fluidized bed. Owing to this the spray pattern and all the nozzle parameters have an effect on particle growth kinetics, type of particle size enlargement (e.g. layering or coalescence) and product properties (e.g. porosity, surface roughness, size, particle density). In fluidized-bed applications in the fine chemical, pharmaceutical or food in dustries, pneumatic nozzles are typically used. This type is also called a binary nozzle. This nozzle atomizes the liquid flow using a high velocity gas flow. As shown in Fig. 49 left, a liquid nozzle with relatively big bore is covered by gas cap. Between the gas cap and the liquid nozzle is a ring gap where the atomization gas is led to the nozzle tip. On the nozzle tip the relatively slow flowing liquid comes in contact with the very high velocity gas stream. Owing to the high shearing forces the liquid stream is atomized, producing a very fine mist. In Fig. 51 two basic gas-Iiquid-mixing principles are explained. The standard case is shown on the left where the liquid to gas contact takes place just in front of the nozzle tip. This kind of pneumatic nozzle design is ca lied external mixing. In case of internal mixing (Fig. 51 right) the tip of the liquid nozzle is inside the gas cap and liquid and gas are mixed before the mixture leaves the circular arranged spray bores (Figs. 52 and 53). In contrast to pneumatic (binary) nozzles, hydraulic nozzles atomize the liquid stream due to high feed pressure. The drops are formed because of the very high
457
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external mixing
1--1-......;. ---- liquid ------ftI..-tt-l Ho!lf---- atomization gas ---Mf'
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". "T i_ _
:'i : '.\ / : :, \, \, I
'I� \((
, ,
I I
' I
I I
I,
\
\ \
,:
mixing zone
spray cone --...:-,..
\ \ \ \ \ \ \
,
'
Fig. 51 . Basic gas-liquid-mixing principles of pneumatic (binary) nozzles. (Adapted fram Schlick [ 1 6].)
velocity inside the bore. In Fig. 54 an example of such a spray nozzle is shown. The simple design and the mechanical robustness are some of their advantages. In a lot of applications ceramic liquid inserts are in use due to the very high flow velocity inside the bore. Especially if suspensions or other abrasive liquids are to be sprayed, special construction materials are needed. Depending on the liquid feed pressure different drop size distributions and spray rates are achieved. Owing to the direct dependency between spray rate
458
M. Jacob
Fig. 52. Pneumatic (binary) nozzles with external mixing - left single nozzlejright multi head nozzle (SchlickjGermany) [ 1 6] .
F i g . 53. Pneumatic (binary) nozzle modified for internal mixing (SchlickjGermany) [ 1 6] .
Fig. 54. Pressure (hydraulic) nozzle (SchlickjGermany) [ 1 6] .
and drop size pressure nozzles have to be designed for a weil defined operation point. For a good spray pattern a certain minimum spray rate is required and has to be considered in start-up procedures of spray systems. In Fig. 55, two photos of spray pattern produced by pressure (hydraulic) noz zles are shown. On the lett is a standard nozzle type with a very uniform spray and the right photo explains a special nozzle with multiple holes, which are arra nged in a circular pattern.
459
Granulation Equipment
Fig. 55. Examples of pressure (hydraulic) nozzle spray pattern (Spraying Systems Co./US).
!height diameter
nozzle array
Fig. 56. Nozzle arrangements.
multi head nozzle
center nozzle
In pilot and industrial scale fluidized-bed processing several spray nozzles are typically installed in one granulation or coating unit. In Fig. 56, different options of nozzle arrangements are shown. In the simple case one single nozzle is installed in the centre of a fluidized-bed unit. Depending on the process the spray rate of this nozzle can be very high and large differences in the local moisture distribution in the bed can be the result, especially in large-scale processes. A way of im proving the wetting properties across the bed surface is the use of multi-head nozzles. Here the simple liquid feed system can be combined with a more uniform distribution of the spray.
460
M. Jacob (a)
(c) 1+--1::'o:r-+ nozz[e open/e1ose
f-------i::' ------, drying gas inlet =>
->I r-�--+---'----,
-
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)- gas distributor
drying chamber exhaust
CD E :@ 300 c ts
{
{
k, constant; ts , switching time k, w < w* ß= O , w > w* W - (u+v)a (uvt k, a, b, constants ß = ßo ( 1 l u + 1 Iv) 1 /2 (u1 /3 + V1 /3) 2 ß = ßO (U-1 /3 + V- 1 / 3) (U1 / 3 + V1 /3) ß1 Types l and 1 1 without permanent deformation ß lu,v = ß2 Type 1 1 with permanent deformation rebound o
References Kapur and Fuerstenau [45] Kapur [46] Sastry [47] Golovin [48] Golovin [48] Adetayo et al. [49] Adetayo and Ennis [50]
_
{
Friedlander [44] Uu and Utster [42]
the application. The authors have reviewed a number of model order reduction techniques applicable to granulation processes [6]. These include reduced order models using the concept of lumped regions in series, model order reduction for multi-dimensional population balances and reduced order models using the method of moments. The method of moments has been frequently used in control and optimization for crystallization processes [51 ,52]. However, it is not com monly used in granulation processes because of the difficulties involved in the computations of fractional and negative moments. In the cases where the type of size distribution is more or less known, such as the log normal distribution, the moment models are also very effective for control and optimization of granulation processes [53]. 2.1.4. Development of linear models and multiple model approach
Most industrial processes, including granulation plants, should be represented by non-linear models. However, the well-established theory and techniques for
519
Process Systems Engineering Applied to Granulation
process control and systems analysis are largely based on linear models. Non linear systems theory and methods are mathematically complicated and difficult to implement in real plants. Consequently, development of approximate linear models from non-linear models is a common practice in modelling of non-linear processes. A general non-linear process without uncertainty is described by the following differential algebraic equations: dX = fex, u) ( 1 6) dt y = h(x, u)
{
where y and u are the vectors of controlled and manipulated variables, respec tively, x is the vector of state variables, and f and h are vectors of smooth functions. Using the Taylor series expansion around certain operation points, the non-linear model described by equation ( 1 6) can be linearized as folIows: dbx bu = Abx + Bbu bx + ---r = --,= � ou d t ox (1 7) Oh bx = Cbx by = T OX
at ! X=Xo,U=Uo at ! X=Xo,U=Uo ! X=Xo,U=Uo
The symbol b in front of x, u and y is omitted for notational simplicity in most cases. The readers should keep in mind that the linear models developed from the first-order Taylor series expansion deal with deviations from operation points rather than real values. If the deviations from a specified operation point are too large, a single linear model is not sufficient In this case, a multiple model ap proach should be applied. That is, the original non-linear model is approximated by a number (say, m) of linear models, each of which is only valid in a narrow operation region i (i = 1 , . . , m) represented as foliows:
d�;= O�T ! X=Xi O,U=U,o bx + O�T ! X=Xi O,U=Ui O ,
I
bu = A;bx + B;bu
oh by = bx = C bx OXT x=xw,u=u/,o
( 1 8)
I
The multiple model approach has been applied to advanced control of non linear processes by the authors [22,23]. 2.1.5. The role of measurement
The role of measurement is summarized as follows with some brief explanations: •
Model validation with parameter identification. Steady state and dynamic data are essential for the identification of structure and parameters of respective steady state and dynamic models. Schroder and Cameron [54] developed a
520
•
•
• •
I .T. Cameron and F.Y. Wang
technique for model structure validation using non-linear and mixed-integer optimization (NLMIO) method. Parameter identification using measurement data will be explained in detail in Section 2.3 as applied to the development of multi-level control schemes. Glosed-Ioop control. 80th black-box control and model-based control require dynamic measurement data, which will be stated in Section 2.3. On-fine optimization and model modification. The control targets (set-points) should be updated using optimal control techniques based on the on-line mod ified models. The model modification is realized through the minimization of the differences between the measured and predicted data, which will be described in Section 2.3. Fault diagnosis and troubleshooting. This role will be explained in Section 2.4. Safety protection through risk assessment. It is easy to see that the abnormal measurement data provide warning signals for risk management. "
As a basis of on-line monitoring and diagnoses, reliabre on-line measurements of particle size distribution and moisture are important. The commonly used technique for on-line determination of particle size distribution in granulation is based on i mage analysis. A typical i mage analysis system consists of a GGO camera, lightning unit, telephoto lens and computer. An image probe is normally installed within the high-shear granulator to receive the image, which has been described in detail by Watano etal. [55,56]. A study of on-line size measurement based on image analysis using an OptiSizer unit [57] has been carried out at the University of Queensland for drum granulation processes [53]. The experimental set-up is shown at the URL: http://www.cheque.uq.edu.au/psdc. In contrast to the installation of a probe for the high-shear granulator, a sampling system can be developed for drum granulation processes to allow the measurement of a rel atively small sampie stream using the OptiSizer unit. In the case where the particles are wet, technical difficulties may occur due to the temporary agglom eration and reduced flowability induced by the particle stickiness. A modified strategy is to dry the particles before the measurement. However, this will lead to a further time delay. Solid moisture can be measured on-line by using near-infrared (NIR) spec troscopy [58] or microwave-based techniques. A microwave technique for the measurement of solid moisture in batch sam pies has been developed by Shah hosseini et al. [59]. Its extension to continuous sampies encounters similar diffi culties to that of OptiSizer units due to the particle stickiness. Further work is needed to develop improved sensors for both particle size and moisture meas urements. It can be seen from the literature that the direct measurement of particle char acteristics, such as particle size d istribution, moisture contents and deformability, is still a challenging research area. In order to cope with measurement difficulties,
Process Systems Engineering Applied to Granulation
521
some indirect monitoring parameters have been adopted as the indicators of particle characteristics. A commonly accepted monitoring parameter in the pharmaceutical industry is the power consumption, which has been successfully used to control the particle size in high-shear mixers at the end-point [60,61]. Based on a series of investigations carried out by Leuenberger [60], the energy dissipated per unit volume d W/d V in a high-shear mixer is related to powder porosity E , which can be used to calculate the powder saturation level S. As soon as the powder saturation level is determined, the average granule size can be estimated [62]. This indirect monitoring technique has been successfully applied to the control of high-shear mixers [60], which will be further explained in Section 2.3. 1 , which deals with black-box controller design. 2.2. Operational aspects o f granulation systems 2.2.1. Process optimization
Process optimization and open-Ioop optimal control of batch and continuous drum granulation processes are described in this section. Open-Ioop optimal control can also be denoted as dynamic optimization, which provides the set points (targets) for the lower-Ievel c1osed-loop contro!. 2.2.2. Statement of steady state and dynamic optimization problems
In process optimization, the adjustable variables are defined as "decision pa rameters", which are not time dependent. On the other hand, the goal of optimal control calculations is aimed at the determination of time-dependent "manipu lated variables" in order to reach optimal output trajectories. Both steady state and dynamic optimization studies are carried out by the authors, which consist of: (i) construction of optimization and control relevant, PBMs through the incorpo ration of moisture content, drum rotation rate and bed depth into the coalescence kerneis; (ii) investigation of optimal operational conditions using constrained op timization techniques; and (iii) development of optimal control algorithms based on discretized PBEs. The objective of steady-state optimization is to minimize the recycle rate with minimum cost for continuous processes. It has been identified that the drum rotation rate, bed depth (material charge) and moisture content of solids are practical decision (design) parameters for system optimization. The objective for the optimal control of batch granulation processes is to maximize the mass of product-sized particles with minimum time and binder consumption. The objective for the optimal control of the continuous process is to drive the process from one steady state to another in a minimum time with minimum binder consumption, which is also known as the state-driving problem. It has been known for some time that the binder spray rate is the most effective control (manipulated) variable. Although other process variables, such as feed flow rate
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I .T. Cameron and F.Y. Wang
and additional powder flow rate can also be used as manipulated variables, only the single input problem with the binder spay rate as the manipulated variable is addressed here to demonstrate the methodology. It can be shown from simu lation results that the proposed models are suitable for control and optimization studies, and the optimization algorithms connected with either steady state or dynamic models are successful for the determination of optimal operational con ditions and dynamic trajectories with good convergence properties. It should be pointed out that only open-Ioop optimal control issues for gran ulation processes without uncertainty are addressed in this section. The integra tion of open-Ioop optimal control with closed-Ioop, non-linear model predictive control (NMPC) for uncertain processes has been reported elsewhere by the authors [63] and outlined in Section 2.3.3. A typical batch drum granulation process is schematically shown in Fig. 6. There are two operational strategies: ( 1 ) pre-mix the fine particles with the proper amount of liquid binder followed by the rotating operation until the desired size distribution is achieved and (2) simultaneous mixing and granulating by spraying liquid binder (and fine powders in some cases) on the moving surface of particles inside the rotating drum. The first strategy involves system optimization without any control action. The optimization problem can be stated as: to determine the optimal moisture content, initial size distribution, rotating rate and bed depth (drum charge), such that the desired size distribution can be obtained within a minimum time tf. Optimal control techniques can be applied to the second strat egy, which can be stated as for the specified initial conditions, maximize the mass of product-sized particles in minimum time with minimum energy consumption by adjusting the manipulated variables, such as binder spray rate and drum rotation speed. We will discuss the optimal control problem with the binder spray rate as the single manipulated variable in detail. A continuous drum granulation process with an additional fine powder stream is shown in Fig. 7. The additional fine powder stream is used to improve the controllability of the process, which is not seen in the conventional design. Our studies on continuous drum granulation include the steady-state optimi zation and optimal state driving from one steady state to another. The objective for steady-state optimization is to achieve minimum recycle rate with minimum
_ _ .. .
t"'1r
Fig. 6. Schematic diagram of batch drum g ranulation.
Process Systems Engineering Applied to Granulation
523
Liquid Spray (Rw) Solid Feed (Fs)
Solid Output Fig. 7. Schematic diagram of continuous drum granulation .
cost through the determination of optimal operational conditions, such as rotat ing rate, binder spray rate, feed flow rate, bed depth and drum inclination angle. The optimal state driving attempts to drive the system from one steady state to another in a minimum time with minimum energy consumption by adjusting the time-dependent manipulated variables, such as binder spray rate, feed flow rate and optionally additional fine powder flow rate. 2.2.3. Control relevant models
A control relevant model was developed by Zhang et a/. [64], in which the co alescence kernel is a function of the moisture content. In the newly developed kernel models reported by Balliu [28] and Wang eta/. [40], in addition to moisture content, the bed depth and drum speed are also incorporated. Two kernel mod els, namely size-independent kernel and size-dependent kernei, are used in op timization and control simulations. The size-independent kernel is given by ßo = ao ' [(xw )n' e- a IXW ] . [(Bd t2 e- a2 Bd ] . ( S�3 e - a3 Sd ) ( 1 9) ßm_O = boßo where Xw is the moisture content in particles, Bd the bed depth, Sd the drum rotating rate, aO-a3 and n1-n3 are constants determined through parameter identification techniques based on the measurement data and bo the conversion factor. The size-dependent kernel is represented as [44]
(20) where ßo and ßm_o are also defined in equation (1 9). Since the main mechanism determining the growth rate G in equations (1 1 ) and (1 5) i s layering of the fine powders o n the surface of particles, it can be deduced that the growth rate is a strong function of the powder fraction and moisture content. The following correlation, which is an analogy to the well-known
524
I .T. Cameron and F.Y. Wang
[
]
Monod model in biochemical engineering [65], is used to calculate the growth rate
Mpowder . exp - a(xw - xwc)2 G = Gm '" M1. + Mpowder ' k . L.
(21 )
where Gm i s the maximum growth rate, Mpowder the mass of fine powder below the lower bound of the particle classes, Mi the mass of particles in the ith size class, Xwc the critical moisture, and k and a are the fitting parameters. Studies on powder mass balance lead to the following equation for batch processes:
L m ax i [ (Mi Mi )] � Finpowder - 23 G '"' f2 (Li - Li-1 ) --c + Li--11
dMpowder = in 3G ('XC> M(L) dL F powder dt Jo _
(22)
and the following equation for continuous processes:
L � [(L. L. ( · L L.
M ML dMpowder = in 3G (OO ( ) dL Fpowder _ powder tR dt Jo Mpowder � G Mi + Mi- 1 in � Fpowder � ) 1 1 1 tR 2 i=2 1 1- 1 _
_
_
_
)]
(23)
In equations (22) and (23), F�owder represents the inlet powder flow rate, and tR is the retention time. The inlet powder flow rate can be used as an additional manipulated variable. The liquid mass balance for batch processes is given by
d x w � Rw dt - Mt
(24)
where Mt is the total mass of solids in the drum and Rw the binder spray rate. Similarly, we can develop the liquid mass balance for the continuous process as
dxw = 1 [Fin in FM w + Rw] Tl Mt MXw - X
(25)
where F� and FM are inlet and outlet mass flow rates, respectively, and x� is the moisture content in the feed solids. In summary, the equations in the control relevant model for batch systems are discretized PBEs given by equation (1 1 ), powder dynamics described by equa tion (22) and liquid dynamics represented by equation (24). The corresponding equations for continuous processes are equations ( 1 5), (23) and (25). Both cases share the same kernel models given by equations ( 1 9) and (20), and growth rate model described by equation (21 ).
525
Process Systems Engineering Applied to Granulation
2.2.4. Objective tunctions tor system optimization and open-Ioop optimal control
The objective function for system optimization of batch granulation is (26)
S.t. equation (1 1 )
The objective function for batch granulation with the binder spray rate as the only manipulated variable is given by Min Rw
{
-Wl Mp (lr )+W2 fa/r Rwdl Ir
}
W1
S.t. equations (1 1 ), (22) and (24)
(27)
In equations (26) and (27), Mp is the mass of product-sized partie/es, and W2 are the weighting functions. The objective function for steady-state optimization of continuous granulation is Sd.Bdpn Rw
Min
{-W1Fp + W2 R } w
(28)
S.t. equations (1 5), (23) and (25) with left-hand si des replaced by zero
Fp
where is the mass flow rate of product-sized partie/es. For the state-driving study, we carry out steady-state optimizations for two different product specifications: the product range for steady state 1 (SS 1 ) is 2.0-3.2 mm, whereas that for steady state 2 (SS2) is 3.2-5.0 mm. The objective function for this optimal state-driving problem is described as 2 Mj (tf) - M?S2 + W2 I�f Rw d t + W3 tf ��n J = L: (29) S.t. equations (1 5), (23), (25) and zero derivatives at final time where M,{ tf) andM?S2 denote the mass of partie/es in the ith size interval at the final time and for SS2, respectively.
{
[wu(
)]
}
2.2.5. Dynamic optimization algorithm
It is not difficult to solve the steady-state optimization problems with constraints represented by algebraic equations by using commercial software packages. We mainly explain the dynamic optimization methods used in this work. The basic structure of the algorithm employed in this paper is shown in Fig. 8. In the dynamic optimization algorithm depicted in Fig. 8, a control parameter ization technique [66] is used to discretize the originally continuous control var iables. That is, a control (manipulated) variable u(t) is represented by a set of
526
I .T. Cameron and F.Y. Wang Set J=O and initial guess for Ui
,...---"'--=-"'---+1 J=J+1
Conslrained opllmlzatlon algorithm Aigebraic conslrainlS Objecllve function
Initial conditions
....
..... DAE-ODE solvers state values Ui
_ _
...
_
Yes
Terminate
Fig.
8. Basic structure of the dynamic optimization algorithm.
piece-wise constants, Ui, i = 1 , 2, . . . , q. These constants are treated as param eters to be determined by using dynamic optimization algorithms. Since the MATLAB software packages with Optimization Toolbox provides both effective ordinary differential equation (ODE) solvers as weil as powerful optimization algorithms, the dynamic simulations reported in this paper are car ried out by using the MATLAB Optimization Toolbox [67]. 2.2.6. Selected simulation results and discussion
Simulations for both batch and continuous granulation processes are based on a pilot plant drum granulator with the following parameters: length 2 m, diameter 0.3 m , nominal hold-up 40 kg, rotation rate 25-40 rpm, retention time range 6-1 0 min. The particles are classified into 20-size classes specified as: [0.250, 0.31 5, 0.397, 0.500, 0.630, 0.794, 1 .000, 1 .260, 1 .587, 2.000, 2.520, 3 . 1 75, 4.000, 5.040, 6.350, 8.000, 1 0.079, 1 2.700, 1 6.000, 20.1 60] with units of mm. Other process parameters are available in a recent paper by the authors [40]. The simulated optimal profiles for the batch processes are shown in Figs. 9(a-c) with two datasets with and without constraints on control action. The control con straints restrict lower and upper bounds on the control variables (Iower bound
Process Systems Engineering Applied to Granulation
40 �----�----�
527
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a: Constrained Trajectories
c: Cummulative Mass: Constrained t=O
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0 0
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9. Optimal Control of Batch Drum Granulation.
o kg S-1 ,
upper bound 0.015 kg S-1 ) , as weil as the gradient of the control actions ( I Rw / tl < 0.0003 kg S- 1 ) . It can be seen from Fig. 9(d) that if the normal con straints on the control variable are replaced by a high-upper bound of control variable (0.036 kg S-1 ) as the only constraint, very high-spray rates at the early operating stage with very short-spray time leads to the minimum objective function given by equation (27). However, if the normal constraints are activated, the control variable moves smoothly rather than suddenly with the price of a Ion ger operational time. The difference between final times in the two cases is about 1 04 s (283-1 79 s), which is quite significant. The results clearly have implications on equipment design and specifications that could allow the constraints to be moved out thus approaching the best-operating policy. Through steady state optimizations using the objective function described by equation (28), optimal binder spray rates for two different specifications on prod uct size ranges are obtained. These are: Rw = 0.050 kg S-1 for 2.0-3.2 mm as the product size range, and Rw = 0.075 kg S-1 for 3.2-5.0 mm as the product size range. Figures 1 0(a) and 1 0(b) show the profiles using an optimal control policy and a constant spray rate policy. The change of the cumulative mass between
528
I .T. Cameron and F.Y. Wang c: Optimal Cummulative Mass
a: Dynamics of Product Mass
40 ,-----, 16 o � E 14
0 30 � E
ll 20
2
o c::
t
=0
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=
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b: Dynamics of Under Sized Mass
d: Control Profiles
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500
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1 500
2000
6 �--�----�--� 1 500 2000 1 000 500 o
Time (seconds) Fig.
.� .
Time (seconds)
1 0. Optimal Control of Continuous Drum Granulation.
initial and final times under optimal control policy is shown in Fig. 1 0(c). The control profiles are depicted in Fig. 1 0(d). The optimal control policy leads to about 50% reduction on the objective function given by equation (29). The optimal spray rate policy can be stated: "Gradually increase the spray rate from the first steady state (0.005 kg S-1 ) to achieve a relatively high-spray rate (0.0084 kg S-1 ) followed by gradual reduction of the spray rate until the spray rate of the second steady-state value (0.0075 kg S-1 ) is reached, which will be maintained for the rest of the operational period". From Fig. 1 0, the significance of optimal control stud ies can be demonstrated by observing the facts that the optimal profiles approach the second steady state faster, and the optimal control strategy is easy to im plement with smooth movement. It should be pointed out that the small difference between two control policies shown in Fig. 1 0 is due to small difference between two product specifications (product ranges from 2.0-3.2 mm to 3.2-5.0 mm). It can be predicted that if the two steady states are far away, profound economic benefit can be achieved. Optimal control strategies are particularly important to plant start-up and shutdown operations. Figure 1 1 shows the dynamic profiles of optimal state driving from SS1 to SS2 with different levels of constraints. Dynamic changes of product mass,
Process Systems Engineering Applied to Granulation c: Dynamics of Moislure Conlenl
a: Dynamics of Producl Mass
16
529
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0.08
3 d: Control Profiles X 1 0. 10 ��------------------�
Dynamics of Under Sized Mass
Loose Constraints Loose Conslraints E
2 18
Cl .!: �
�
-i..
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!
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14 o
500
1000 Time (seconds)
Fig.
1
1500
2000
5 L---�----�--� o 1 500 500 1 000 2000 Time (seconds)
1 1 . Effects of Constraint Tightness on Optimal Control of Drum Granulation.
undersized mass and moisture content are shown in Figs. 1 1 (a), 1 1 (b) and 1 1 (c), respectively under two constraint levels. Figure 1 1 (d) depicts control profiles for these two cases. In addition to the constraints on control actions, the final time constraints to ensure the final steady-state status is imposed on the system. That is, the left-hand sides of equations ( 1 5), (23) and (25) should be zero at the final time. However, it is not necessary to achieve zero exactly for the derivatives at the final time. We normally impose the final time constraints as Idx(tf)jdtl < I> in which x represents general state variables, such as number of particles, mass of powder and moisture content, and 8 is a very small positive number for practical applications with the value depending on the tightness of constraints. The I> val ues are chosen as 1 0--6 and 1 0-3 for tight and loose constraints indicated in Fig. 1 1 , respectively. It can be shown in Fig. 1 1 that the control strategy with loose constraints leads to shorter operational time than that with tight constraints (1 827 s vs. 1 925 s). However, the moisture dynamics show severe offset and oscillation. In optimization simulations, only final time constraints are changed for the two cases. It is interesting to note that the programme with tight constraints leads to small and smooth controller movements even though the constraints on the control variable are not altered explicitly. It seems that the loose constraints
530
I .T. Cameron and F.Y. Wang
allow too much manipulative variation that drives the system into a region (xw 0. 1 ) where moisture variations have significant impact on the granulation per formance. A marginal benefit identified by 5% time reduction is achievable using loose constraints with a price of process oscillations. Consequently, a control strategy with tight final time constraints is superior to that with loose constraints in this particular application. Through an analysis on the simulation results, the following conclusions can be drawn: ;::::::
1 . Population balance modelling provides an important basis for optimal design and operations for both batch and continuous granulation processes. 2. The effects of liquid content, bed depth and drum rotation rate on the coa lescence behaviour can be quantified through the development of new kernel models with the structure described by equations ( 1 9) and (20). The simulation results are qualitatively consistent with industrial experience in large-scale fertilizer production. 3. An optimal control strategy and algorithm using commercial optimization soft ware packages connected to reliable DAE/ODE solvers are successful for the determination of optimal trajectories with good convergence properties. This implies that under certain conditions, the more complicated optimal control algorithms, such as that based on the well-known Pontryagin's maximum principle, could be avoided. 4. Since start-up and shutdown operations are frequently encountered in gran ulation plants with huge financial impacts, studies on optimal control strategies can lead to significant economic benefits. 2.3. Control design, analysis and performance 2.3.1. Black-box controller design
There exist a number of practical control schemes in granulation plants, which do not rely on mathematical models. These include simple feedback control with or without feed-forward compensation and fuzzy-Iogic control systems. One of the most important issues for the effective control of granulation proc esses is the development of fast and reliable measurement techniques for the characterization of particulate systems. As pointed out previously, because of the difficulties associated with the direct measurement of particle characteristics, such as particle size distribution, moisture contents and deformability, some in direct monitoring parameters have been adopted as the indicators of particle characteristics. Leuenberger [60] and Faure et al. [61 ] have adopted a technique to use power consumption as an indicator of particle properties for control of particle size in high-shear mixers. Leuenberger [60] has proposed an approx imation to correlate the energy dissipated per unit volume in a high-shear mixer,
531
Pracess Systems Engineering Applied to Granulation
d W/d V, with the powder porosity as folIows: 1 -3 dW = {l(JcK CX -(30) 3 dV where W is the power consumption, V the granulator volume, {l the apparent coefficient of friction, (Je the cohesive stress, K the dimensionless shear rate and 3 the porosity of the powder mass. It is easy to show that the power consumption is related to the saturation level S defined as folIows: S
= H(1 3- 3) p
(3 1 )
where H i s the mass ratio of Iiquids to solids and p the density of the particle relative to the density of the liquid ( p = P s/pd. Furthermore, Kristensen and Schaefer [62] pointed out that the saturation level defined by equation (31 ) could be related back to the average granule size. Consequently, the power consumption, the saturation level and the granule particle size are i nterrelated , which forms a technical basis to use power consumption as a monitoring parameter for the characterization of particles within the high-shear mixer. A detailed description of the control strategy using power consumption as the in dicator of particle properties in high-shear mixers is also provided in Leuenbe rger [60]. Mort et al. [68] pointed out that "With recent development in particle sizing technology, the agglomerate size distribution can be measured in-li ne at any number of points in the process." The main measurement technique is image analysis by mounting high-speed cameras and lighting systems in appropriate locations. Since the direct measurement data of particle sizes are available, the controller design can be based on these data without relying on the indirect indicators under the condition that the rate of binder addition is sufficiently slow to allow for image data to be collected, processed and fed back. This concept has been used for batch granulation processes in fluidized beds. The same authors [68] also proposed a feed-forward control strategy to compensate the fluctuation of the recycle rate. The simple feedback control with feed-forward compensation scheme is shown in Fig. 1 2. Recycle rate
�' c
3
CD
.....
"Tl 0 0 0. Cf>
Johari et al. [1 2] Hoseney et al. [1 3] Doescher et al. [14] Palzer & Zürcher [ 1 5] Vuataz [1 0] Aguilera et al. [ 1 6]
(J1 co --.I
598
s. Palzer
necessary to consider the mass fraction and the particle size distribution of its main components. 2.2. Hygroscopicity and hygrosensitivity of food powders
Since water or water-based binder solutions are often used in food agglomeration to increase the adhesion forces between the particles, it is required to know the hygroscopicity and the hygrosensitivity of the different food powders. Hygroscopicity describes the tendency of a material to adsorb water from the atmosphere. The sorption isotherm shows the amount of water ( w ' ) a food ma terial contains at a defined temperature and water activity 8w if it is in equilibrium with its environment. The 8w is the vapour pressure in the headspace of the product divided by the vapour pressure of pure water. In equilibrium the relative humidity (RH) of the surrounding air and the water activity of the product are equal. The sorption isotherm of a product can be modelled according to Guggenheim, Anderson and deBoer (equation (4); GAB) or Brunner, Emmet and Tellauer (equation (5); BET) using the parameter C, K and w ' m : ' CK8w w (4) w' m (1 - K8w)( 1 = (C - 1 )K8w) ' w ' wm
C8w (5) (1 - 8w)(1 = (C - 1 )8w) ' w m represents the water quantity (dry-basis) required for a monomolecular water layer on the solid surface. For C = 1 the GAB equation is transformed into the BET equation. Water-soluble crystalline substances nearly adsorb no water until they dissolve completely at a specific RH (sodium chloride at 73-75% RH; crystalline sucrose at 83-85% RH). Amorphous hydrophilic substances adsorb increasing amounts of water with increasing RH, which is stored within the amorphous matrix and no critical humidity, at which the particies might dissolve, can be defined. Accord ingly, re-crystallization of amorphous substances liberates moisture, which af fects the crystallization velocity of the remaining amorphous fraction. The liberated moisture might lead to caking of the powder. Due to crystaliization it is rather difficult to establish the sorption isotherm of amorphous substances with a low molecular weight at high humidity. Figure 2 shows the sorption isotherm of dextrose syrup (wh ich is amorphous), amorphous sucrose, crystalline sucrose and sodium chloride. In addition to the moisture inciuded in a sorption isotherm established for non-porous structures, water might be bound in smali pores. Below a specific pore diameter de, condensation can even occur spontaneously. This critical
599
Agglomeration of Dehydrated Consumer Foods 1 5 .----,--r--, .... sodium chloride • crystalline sucrose • amorphous sucrose • dextrose syrup
dextrose syrup DE 20-21
C .$ c:
8 ....
.$
C1l
3:
•
5
,, ,, ,, ,, ,,
•
,, ,, ,,
..
sodium chloride crysta lline sucrose
amorphous sucrose (Makower & Dye 1956)
,, ,,
re-crystallisation
0.1
......-, 0.4 0.6 0.5 0.3 water activity aw / - ( 22 °C) • •
0.2
0.7
0.8
0.9
Fig. 2. 22°C-sorption isotherm of different amorphous and crystalline food materials (water content determined according to Karl-Fischer).
diameter can be calculated according to equation (6). For the calculation the following parameters are needed: surface tension y of water, wetting angle e between water and solid, temperature T, Kelvin constant R (8.314 J/mol K), vapour pressure Pv , absolute pressure p and molar volume of water V ( 1 8 1 0 -6 m 3jmol). x
'}' cos(0)V dc < 2 RT ln (pfpv)
(6)
Capillary condensation is also one of the reasons for the observed hysteresis between the sorption and desorption isotherm. Changes in the physico-chemical properties of food materials linked to changing water content are referred to as hygrosensitivity. Amorphous materials are more hygrosensitive than crystalline substances. Crystalline substances preserve their texture with increasing hu midity until they dissolve at a certain critical RH of the surrounding air (see Fig. 2). The resulting solution has, in most cases, a low or medium viscosity because the molecular weight of crystallizing substances is normally smalI. Amorphous materials are hygrosensitive. Such substances, which can be re garded as super-cooled liquids, do not really dissolve. They already have a liquid like molecular structure. Amorphous substances absorb moisture depending on
600
S. Palzer
the humidity of the surrounding air. The absorbed water has a plastifying effect on the amorphous matrix. With increasing moisture content the glass transition temperature decreases. The decrease of Tg caused by an increase of moisture can be modelled using the Gordon and Taylor equation [1 7]. For calculating the Tg of a moist substance, the glass transition temperature of the water-free sub stance Tg, s , the glass transition temperature of water Tg,w , the water content w (wet-based) and the Gordon & Taylor constant k have to be known. T9
_
(1
-
w)Tg,s + kwTg,w - w) + kw
-
(7)
(1
Figure 3 shows the glass transition temperature of different food powders at varying water content. In a powder mix the water activity is the same for all com ponents although they might have different water content. Therefore, it is useful to measure the glass transition temperature of the different powder components depending on their water activity. Obviously, the powder fraction with the lowest glass transition temperature at a defined water activity is the most sensitive com ponent within the powder blend. Combining equations (4) and (7), the dependence
1 50 A
�
Cl
•
•
1 00
• •
I�
�
E
Q) c..
$
50
c 0 ."
'e;;
§ c
CfJ CfJ
5!1
0
Cl
•
0
5
• •
soft wheat flour dextrose syrup skim milk powder
•
• • • •
•
soft wheat flour ( D oescher et al. 1 987) ..
reaction flavour
-50
•
native wheat starch (Zeleznak & Hoseney 1 987)
•
��
:::J
reaction flavor wheat starch tomato powder
10 water content (wb) / %
dextrose syrup tomato powder
15
20
3. Glass transition temperature of various food powders depending on their water 1 content (Tg is defined as DSC onset at a heating rate of SOC min- ; water content ac cording to Karl-Fischer; Gordon & Taylor constant k and Tg, s as included in Table 1 ). Fig.
Agglomeration of Dehydrated Consumer Foods
601
of Tg on the water activity can be mode lied according to equation (8) [15]: (1 - Kaw )(1 + (C - 1 )Kaw ) Tg + kwm CKaw Tgw T9 (aw ) - ���������--�-=�� - (1 - Kaw)(1 + (C - 1 )Kaw) + kwmCKaw
(8)
2.3. Mechanical properties of solid food substances
For optimizing pressure agglomeration of food powders it is important to fully understand the mechanical behaviour of the powder. Liquids already deform at very low stress. The shear stress generated within liquids is proportional to the strain rate, and the factor of proportionality is the viscosity of the liquid. So me food substances deform plastically, which means a critical stress has to be exceeded before the material starts to flow. Furthermore, the achieved strain is proportional to the applied stress and after the stress is released, the strain remains. Other food substances like crystalline materials or amorphous substances in their glassy state show elastic behaviour according to Hookes law. Exposing elastic solids to a shear stress FjA leads to a proportional shear strain !J.xjy. The constant of proportionality is the shear modulus G. Alternatively, a compression or elongation of the material can be achieved by applying a normal stress FjA. The achieved strain Mjl is proportional to the stress and the constant of proportionality is the called Young modulus or modulus of elasticity E. The shear modulus G and the Young modulus E are connected via the Poisson ratio v.
Elastic behaviour
Viscous behaviour
Shearing Compression or elongation If the stress generated in such materials due to shearing or compression ex ceeds a certain limit, the particles will break. However, a number of food sub stances have viscous (Iiquid-like) and elastic (solid-like) features. Such materials, including various amorphous food substances, are called visco-elastic. In their glassy state and while exposed to a high strain rate, they behave more like elastic solids whereas in the rubbery or viscous state or while they are deformed slowly, they show liquid-like properties. Mechanical models for visco-elastic substances include a parallel or a serial combination of a spring (representing the elastic component) and a dashpot (representing the viscous component). A serial combination of the spring and the dash pot is known as the Maxwell model whereas a parallel combination is referred to as the Kelvin-Voigt model (see Fig. 4). Since these simple models are
602
S. Palzer E
E,
Tl
Kelvin-Voigt model
four-parameter model
Maxwell model
Fig. 4. Different viscoelastic models for solid food materials.
often not sufficient for describing the behaviour of complex food systems, more sophisticated models (e.g. a four-parameter model) can be obtained by combi nation of several springs and dash pots [18, 1 9]. By applying a constant stress over a defined time, a progressing deformation of the material, which is called creeping, is observed. In case of a Kelvin body no instantaneous deformation is given while exposing the system to such a constant stress (see equation (3)). Applying a Maxwell model an instantaneous strain and a linear increase of the strain with time is obtained (see equation (1 0)). er
�; set) = ( 1 - e -t�) (J (Jt (Ja (J = - + set) = + - t E 11 11
= Es + 11
::::}
So
::::}
Kelvin - Voigt Maxwell
(9) ( 1 0)
is the time dependent strain and (J is the normal stress applied. The Maxwell model cannot account for a retarded elastic response. On the other hand the Voigt model is not able to describe the observed stress relaxation of real food systems. Based on the Maxwell model, the stress relaxation can be described according to equation (1 1 ): s
-(
= (Jo eT
(1 1 ) The relaxation time T, calculated as the ratio between viscosity and Young modulus, indicates how fast the strain decreases after the stress is released. It can be calculated as the ratio between viscosity and Young modulus. For liquids, a relaxation time of 1 0 - 1 2 _ 1 0- 1 0 s is typically found. However, often the relax ation of real systems can only be described using a relaxation time distribution. The ratio between the relaxation time and the observation time is defined as Deborah number, D. If 0 is large, no relaxation is observed during the experiment and the visco-elastic material appears to be more liquid-like. If 0 is very smalI, the material seems to behave solid-like. The relaxation time is influenced by temperature. Empirically, it was found that the temperature dependence of all relaxation times follows the same pattern. According to the time-temperature superposition principle, the ratio between two relaxation times is defined to be the (J(t)
Agglomeration of Dehydrated Consumer Foods
603
shift factor Etr. Below Tg and over 1 000e above Tg this shift factor va ries with temperature according to the law of Arrhenius: aT
e Ea/ R(1 / T - 1 / To) =� Ta =
( 1 2)
where Ea is the activation energy, R the Kelvin constant, T the temperature and Ta a reference temperature. Between Tg and Tg + 1 oOGe the shift factor changes with temperature following equation ( 1 3) [20]: aT
T
-C(T - Ts )
=Ts = ---'---B + ( T - Ts)
( 1 3)
Ts is a reference temperature and e and B are constant factors. Williams, Landel and Ferry [20] found the values -1 7.4 and 51 .6 K for the parameters e and B suitable for the most polymers investigated. The WLF equation has also been applied to predict the temperature influence on viscosity of solid food materials by using Tg as a reference temperature [1 6,21]. log =
(11) = I1g
e(T - Tg) B + ( T - Tg)
(14)
Here I1 g is the viscosity in the glassy state and T the ambient temperature. Peleg found that the WLF constants depend on the substance investigated and the difference between T and Tg [22]. However, other authors obtained satisfying results with the published universal constants while predicting the state of dif ferent food powders [1 6,21]. It appears that, when approaching a certain tem perature, the relaxation time diverges against a finite value. This temperature is referred to as Vogel, Tammann and Fulcher (VTF) temperature Ts. Ts is sup posed to be 500e below the glass transition temperature. Using the VTF-tem perature Ts, the influence of temperature on viscosity can also be estimated using the law of Vogel, Fulcher and Thamann. o
( 1 5)
is a constant parameter. Since equations (14) and (1 5) include the glass transition temperature, the influence of moisture content on the viscosity is also considered in the calculation. Like the viscosity, the Young modulus depends on the time scale of the deformation, the temperature and the plasticizer (in most cases water) content [4]. Figure 5 illustrates how the Young modulus decreases with increasing temperature for amorphous, semi-amorphous and crystalline materials. As previously discussed a static stress leads to a creeping of the material. Alternatively, the food matrix can also be exposed to a dynamic stress or strain. For instance in the dynamic mechanical thermo analysis (DMTA) of materials a
604
S. Palzer
(log scale)
Young modulus
'-----+--;.-+ TemperatuTe T, Tm Fig. 5. Temperature dependence of the Young modulus for different molecular structures.
sinus-shaped strain profile y(t) is applied to test the mechanical material behaviour. I' = 1' 0 sin(wt) ( 1 6) where t is the time, w the frequency of rotation and 1'0 the amplitude of the strain. If the food matrix behaves more liquid-like, the following dynamic stress is ob tained : r = IJYo w cos(wt) ( 1 7) r is the resulting shear stress within the substance. For solids the following time/stress function is valid: = Gyo sin(wt) ( 1 8) G represents the shear modulus of the solid material. For visco-elastic solids, which show liquid- as weil as solid-like features, the shear and the normal stress can be calculated by combining equations ( 1 7) and (1 8): r = 1'0 ( G'yo sin(wt) + G" cos(wt)) withG" = IJ'Yo w or (J = 1'0 (E'1'0 sin(wt) + E" cos( wt») ( 1 9) G' is called the storage modulus and G" is referred to as the loss modulus. Thus the complex shear or Young modulus is composed of a real and an imaginary component. The storage modulus represents the elastic response on an applied stress, and thus includes the potential energy stored in the system. This energy is released when the applied stress disappears again. Large G' values are obtained r
605
Agglomeration of Dehydrated Consumer Foods
60 .-------�--�--�
9
'" Cl. -
W "5
50
8.5
o
"" Q)
'8
E Q) Cl
e!
0 u; Cl .Q
40
30 g> '"
8
7.5
RH,,".
Fig. 7. Dissolution of crystalline substance, building of liquid bridges and re-crystallization.
608
S. Palzer
the bridge after drying. (II
=
Vdiss ( 1 - 8)(Is Vagglo
(24)
-
A defined tensile strength of the solid can only be obtained for crystalline bridges. Amorphous substances are visco-elastic and thus their tensile strength depends also on the applied strain rate. 2.4.3. Sintering
Sintering is a process in which molecules or atoms move into the gap between two neighbouring particles. The process is driven by surface tension andjor an external force. While closing the gap between the particles. the free specific surface energy of the system is reduced. The required movement of the molecules into the gap depends on their mobility. which is linked to the viscosity of the material. Sintering metals or glass. the viscosity is commonly reduced by heating the particles. For water-soluble amorphous food matrixes the viscosity can be decreased according to equation (14) by increasing the moisture content andjor increasing the temperature. Sintering can happen during storage of food particles or while agglomerating powder particles containing amorphous components. Figure 8 iIIustrates the different stages of the sintering process. The different phases in sintering are: ( 1 ) Particles adhere and form bridges between each other (Fig. 9) (2) Bridge diameter and length increases while the open porosity decreases (Fig. 1 0) (3) Open pores disappear and only closed pores remain (Fig. 1 1 ). The kinetics of sintering can be calculated according to an equation pub lished by Frenkel [25] or using a similar equation from Rumpf etal. [26]. The ratio between the sinter bridge diameter x and the particle diameter a can be cal culated depending on the surface tension 'Y . the force Ft with which the particles
free-f1owing
adhering
Fig. 8. Sintering of spherical particles.
increase of bridge Ihickness and length
open pores disappear
609
Agglomeration of Dehydrated Consumer Foods
Fig. 9. Particles adhere to each other in an initial phase of the sintering process (dextrose syrup D E21 ).
Fig. 1 0 . Bridge diameter increasing during sintering (dextrose syrup DE21 ).
(�)2 a
(�l5 a + �) ! 511:a2
are pressed together, the particle diameter a, the time t and the viscosity 11 . =
11
(2 5 )
In case of non-spherical particles a is the radius of the surface curvature of the particle at the point of contact. The strength of the build sinter bridges mainly depends on the viscosity of the substance and the diameter of the bridge. According to Wallack and King [21 ] , a significant adhesion force F between particles should only be observed if the diameter ratio xja exceeds a value of 0.01 to 0. 1 .
610
S . Palzer
Fig. 1 1 . Disappearing of open pores in the final stage of the sintering process (dextrose syrup D E2 1 ).
As mentioned earlier, sintering of food substances is strongly dependent on the viscosity and, thus, on moisture and temperature. Combining the equations (14) and (25) and assuming that, due to sorption or desorption processes the humidity of the amorphous substance is changing permanently, equation (26) is obtained. X 2 4 y 2Ft -1 -C(T-Tg(t)) 1 0 B+(T-Tg (t)) dt + (26) a 1=0 5 a 5rca2 Yf9
( ) = lmox ( I
--
)
--
tmax is the time available for the sinter process. With equation (26) it is possible to predict the kinetics of sinter processes depending on temperature and moisture content. In addition, sintering might be accompanied by capillary condensation. If particles are close enough while they are compressed, a capillary condensation in the gap between the particles can occur (see equation (6)). Such a capillary condensation locally leads to an increasing moisture content at the contact point between the particles (see Fig. 1 2). Therefore, sintering at this contact point will be accelerated due to decreasing viscosity. 2.4.4. Solid bridges built by me/ting ot tat
Agglomeration of food powders containing fat can be achieved by melting the fat. To perform such a melt agglomeration, the powder has to be heated to a temperature close to the melting point of the tat. At least 50-80% of the tat material has to be in the liquid state (solid fat content less than 20%) to achieve a significant diameter of the liquid bridge between two particles. The liquid bridge constructed from melted fat is transformed later into a solid bridge due to re crystallization of the fat (Fig. 1 3).
61 1
Agglomeration of Dehydrated Consumer Foods
�
,../
H2
"
a
93
�2
/
amorphous
/ �
�z
-:;J \....;. H20
diffusion + plastification
crystalline ---...
capillary condensation
B HP _
amorphous substance sintering
_ H20
re-crystallisation
Fig. 12. Capillary condensation during compression facilitating sintering (amorphous sub stance) or dissolving the material locally (crystalline substance).
>S
-+
crystallisation of fat
melting of fat
Fig. 1 3. Solid bridges built by melting and re-crystallization of fat.
2.4.5. Increasing adhesion forces due to increasing contact area andjor distance between the partie/es
Adhesion between food particles can also be explained by increasing Van der Waals (electrostatic) forces. 8etween a sphere and a plate, these forces are approximately five times smaller than capillary forces. Knowing the diameter x of the created contact area, the distance 1 between the two particle surfaces and using the Lifshitz-Van der Waals constant hw ( 1 0- 1 8_1 0-20 J) or the Hamaker constant H ( 1 0-19_1 0-18 J) the resulting adhesion force Fad can be calculated according to the theory of Lifshitz or Hamaker [27,28]: Fvdw
=
Fvdw =
--3 X
hm 8nl H
2
2
Lifshitz
(27)
(28) 3 X Hamaker 61 80th equations are valid for distances smaller than 1 50 nm. Obviously, the Van der Waals forces strongly depend on the distance between the particles. In
612
s . Palzer
addition, they are proportional to the inter-partiele contact area. To increase the Van der Waals forces between food particles, their contact area has to be in creased andjor the distance between them has to be decreased. The required deformation of the partieIes can be plastic or visco-elastic. Plastic deformation. Particularly in pressure agglomeration of food partieles, sometimes plastie binders like fat are used. The plastie binder is either added in the form of a powder to the food partieIes or the food partieIes are eoated with fat prior to pressure agglomeration. Aeeording to Rumpf etat. [26] the adhesion force F between two spheres aehieved by plastie deformation is proportional to the force Ft with whieh the partieIes are pressed together and also proportional to the Van der Waals pressure PvdW . The Van der Waals pressure itself is proportional to the distanee t between the neighbouring surfaees. This distanee t is theoret ieally 0.4 nm for the ease where both surfaces are in eontaet with each other [26]. In addition, the adhesion forces generated by compression are depending on the yield pressure of the substanee Pp l . F
�
PvdW Ft Ppl
with
Pv dW
= nx2 = 8hwn2p Fvdw
(29)
The stability of the generated agglomerates depends on the adhesion of the deformed binder on the partieIe surfaee due to Van der Waals forces and as weil on the eohesion of the plastie binding substanee itself. Visco-etastic deformation. Some substanees deform viseo-elastieally. The viseo-elastie deformation leads to an inerease in Van der Waals forees due to a larger eontaet area and a deerease in distanee between single partieIes (see Fig. 1 4). The material partly relaxes if the stress is released. Equation (30), based on a simple Maxwell model, enables the ealeulation of the eontaet area between spherical partieIes ereated by a viseo-elastic flattening at
a:
�
...
...
t
a:
t
time �
Fig. 1 4. Visco-elastic deformation and relaxation of food partieIes.
Agglomeration of Dehydrated Consumer Foods
the contact points
[26].
2 = ( 3 :�r/3 G ir/3 G) 32 +
613
(30)
E is the Young modulus of the material.
3. AGGLOMERATION PROCESSES USED SY THE FOOD I NDUSTRY 3.1 . Agglomeration of food powders duri ng spray-drying
A number of dehydrated food products are produced by spray-drying or a com bination of spray- and belt-drying. It is desired to agglomerate such particles to improve their instant properties and the flowability of the powder. The finished powder can be agglomerated separately after the drying process in a pneumatically fluidized bed. However, the related additional handling and processing increases the manufacturing costs significantly. Alternatively or additionally, a limited ag glomeration can also be achieved during the spray-drying process. In most cases the drying droplets contain amorphous substances and depending on their tem perature and moisture content, they are in a sticky state. Sticky particles that collide with each other or with re-circulated fines adhere to form brittle agglomerates. Bhandari discussed the stickiness of powders during spray-drying. Werner et al. investigated the stickiness of maltodextrine solutions during drying by using a tack tester. A droplet of the solution was placed in a pan and a flat-headed probe was brought in contact with the solution. The whole installation was placed in a drying chamber. The force required to pull off the piston was measured at different moisture content. Both authors found a defined humidity level providing a maximum pull-off force. At low- and at high-moisture content the stickiness was significantly reduced. For spray-drying this means that at high moisture content the cohesion within the liquid bridge between two particles is low (cohesive failure). The droplets rather coalesce with each other or with dry particles than to form the desired porous agglomerate structure. Decreasing the moisture content of the droplet surface, the stickiness of the particles increases until a maximum is reached. Drying increases the viscosity, and, thus, the di ameter of the bridge between two colliding particles, which can be built within the short contact time decreases. Since inter-particle bridges are built by viscous flow, the adhesion kinetics should be predictable according to equation Further decreasing the water content, a point is reached at which adhesion is no longer possible (adhesive failure). According to these considerations re circulated fines should be brought in contact with droplets, which are within the state of maximum stickiness to achieve the best agglomeration result. However, it has to be considered that the state of maximal stickiness depends on the contact time of the particles.
[29,30] [31]
(26).
614
S. Palzer
Contact of sticky particles with the drier wall would lead to encrustation of the equipment. In addition, the majority of the particles falling into a fluid bed con nected to the drier outlet or integrated within a spray-drier should contain only a small amount of humidity to avoid a collapse of the fluid bed. ünce the temperaturejmoisture conditions for maximal stickiness are estimated according to equation (26) for a certain product composition, the region within the spray-drier where such conditions are given has to be identified by CFD modelling or by performing measurements. Agglomeration during spray-drying can be mod elled according to Blei and Sommerfeld [32] using a Langrangian approach. There are different technical approaches to achieve agglomeration in spray towers. üne possibility is to retain fine particles generated during atomization within the spray tower by using integrated bag-filters that are installed in the top part of the drier. Fine particles accumulating on the surface of the tissue of the filter bag fall back into the tower where they adhere to moist particles or droplets. Figure 1 5 shows a spray-drier equipped with integrated filter bags and a fluid bed at the boUom of the drier.
air
Feed Tanks Homogenizer Pump SSHEX LSI unit
Filter bags integrated into the drying chamber
Dehumidifi er Fig. 1 5. Integrated filter drier. (IFD-50-R/N; courtesy Gea Niro Soborg DK.)
Agglomeration of Dehydrated Consumer Foods
615
Another approach is to separate the fine particles from the exhaust air of the spray tower and the after-drier using a cyclone or an external bag filter. These fines are then re-circulated into the main drying zone of the tower. Sometimes the re cycled fine particles are also blown into the tower close to the spray nozzles [33]. A third possibility is to install an integrated fluid bed at the bottom of the drier. Agglomeration of partially dried droplets can happen due to the intensive contact between the particles in such a fluid bed. Sometimes also re-circulated fines removed from the exhaust air of the tower and the after drier are added into such a fluid bed. Figure 1 6 shows a spray-drier in which recycled fine particles are added back into the top part of the tower. In addition, this type of spray-drier is equipped with an integrated fluid bed. Such a system is referred to as multi-stage drier. The described spray-driers are mainly used for instant coffee, dairy powders like skim and whole milk powder, infant formulas, beverage powders, maltodex trines, dextrose syrup and powdered flavours. Figure 1 7 includes a picture of a whole milk powder agglomerated during spray-drying. Another system particularly suitable for spray-drying sticky or high fat powders is the so-called Filtermat-drier (Gea Niro), which is in fact a combination of spray and belt-drying (see Fig . 1 8). The liquid to be spray-dried is atomized into a short spray tower using a rotary atomizer or a spray nozzle. The particles that are often still in the sticky state fall on a moving belt where they agglomerate to a powder cake. This cake is dried by flushing it from the top with hot air. Carried by the
+-+
50
:; E
40
�
.
•
.
.
.
.
.
.
-
-
- - - - -. - - . . - .
.
- - - .. -
-
!c:
c: 0'
--- . 15
Ci; .,
;;
:0
Ü
25
. . . . . . . . . . . . . . . . .. . . . .
,.
-o- particle size at
30
1 5%
added wate r
particle size at 20% added water
10
-e- particle size at 30% added water
20
• •
10
.. . ...
• ••
water dislribution at
1 5%
added water
5
water distribution at 20% added water
water dislribution at 30% added water
O ���----,--�--r--.---�--+ O o
200
400
600
800
d
1 000
e
particle ia m ter
1 200 XSO,3 I
1 400
1 600
1800
2000
um
Fig. 1 9. Changes in particle size distribution and moisture content per particle class during the agglomeration of dextrose syrup (CPCG Glatt; top-spray system; dextrose syrup OE 21 agglomerated with a constant spray rate of 30 g waterjminjnozzle).
622
S. Palzer
Fig. 20. Scanning electron microscopic (SEM) picture of a collapsed dextrose syrup pow der bed.
o===� �
Fig. 21 . Batchwise operating top spray fluid bed.
Figure 23 shows a dextrose syrup agglomerate produced in a batch-wise op erating fluidized bed (top-spray). Obviously parts of the particle surface remain dry whereas others are clearly plastified by impacting droplets. These plastified areas provide potential adhesion points for other particles. Due to the strong adhesion forces generated by viscous bridges between the particles and the low shear forces, non-spherical agglomerates are obtained. For higher batch sizes continuous processes are applied. A continuous fluid-bed agglomerator is divided in different zones. In the first zone, the powder
Agglomeration of Dehydrated Consumer Foods
623
Fig. 22. Bottom spray (batch fluidized bed) with Wurster tube.
Fig. 23. Dextrose syrup agglomerate produced in a top-spray fluid bed (Glatt CPCG; 20% water; 60 g/min/nozzle, SEM picture).
is fluidized by using hot air and water is sprayed onto the moving particles. The particles are wetted, they stick to each other and simultaneously these agglo merates are dried. In the final section of the bed no liquid is injected and the powder is fluidized with cold air to cool it down to a temperature below its glass
624
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Drying or eooling air
Fig. 24. Continuous fluid-bed agglomerators. (Left: courtesy Glatt GmbH Binzen Weimar D; right: courtesy D M R Prozesstechnologie GmbH Kaiseraugst D.)
transition temperature. The movement of the power towards the outlet of the bed is linked to the direction of the air-jets leaving the holes in the boUom plate. Often the bed is vibrated by an exenter-motor, which helps to carry the product through the bed. At the outlet of the bed, a weir is sometimes installed to control the bed height and to adjust the residence time within the bed. In Fig. 24 two continuous fluid-bed agglomerators are shown. The agglomerator on the right side consists of an integrated system for spray-drying which can also be used for steam jet agglomeration. When operating a continuous fluid bed it is important to have an idea of the residence time distribution of the particles in the bed to be able to estimate the level of thermal degradation or crystallization of low molecular sugars during agglomeration. The residence time depends on the feeding rate, the weir height at the bed outlet, the air velocity, the orientation of the holes within the boUom plate and the vibration of the bed.
3.3.2. Mechanically f1uidized bed
In a mechanically fluidized bed the powder is fluidized by fast rotating stirrers while the binder liquid is sprayed on the moving particles. For agglomeration of powders in mechanical fluidized beds different types of equipment can be used: continuous and discontinuous paddle or ploughshare mixers (Figs. 25 and 28), vertical granulators with fast rotating blades on the boUom of the mixer (Fig. 26), mixers operating with turning drums and fast rotating blades and cont inuous mixers equipped with a flexible wall and fast rotating bl ades (see Fig. 27).
625
Agglomeration of Dehydrated Consumer Foods -'I!!!::::===> '--
binding liquid
moving particles
Fig. 25. Ploughshare mixer used for agglomeration. (Courtesy Lödige GmbH Paderborn 0.)
Fig. 26. Vertical granulator. (VG; courtesy Glatt GmbH Binzen/Weimar 0.)
Powders that are used for tabletting of confectionery, starch, bakery mixtures, proteins, sugar, instant beverages and feed products are agglomerated in mechanical fluidized beds. For agglomeration up to 1 5% water, water-based binder solution (e.g. con taining starch/sugar), lecithin, molasses or melted fat is sprayed onto the moving particles. In batch agglomeration systems, such as a high-shear paddle mixer, the process time varies between 1 0 and 1 00 min. The agglomerator is normally operated at a fill-level of 20-50% . In a first phase the liquid is injected at a high rotational speed of the mixing tools. In a second agglomeration phase usually the rotational speed of the mixer is reduced to form the agglomerates. Horizontal or vertical mixers with fast turning mixing tools (see Figs. 27 and 28) are used as continuous agglomeration systems. The residence time in such continuous agglomerators varies between 1 and 2 s and a fili level of 20-30% is applied. The
626
S. Palzer
Axis with mixer tools
Initial nn",rtA,'_
Flexible tube Pneumatic system for moving the tube system for moving the tube
•
Agglomerated powder
Fig. 27. Continuous high-shear mixer. (Sehugi Flexomix. eourtesy Hosokawa Mieron Doetinehem NL.)
BV
Fig. 2 8 . Continuous high-shear mixers. (Left: Turbulizer, eourtesy Hosokawa Mieron Doetinehem N L ; right: CB eourtesy, Gebrüder Lödige Paderborn 0.)
BV
mixing/cutting tools of a vertical agglomerator like the one shown in Fig. 27 are rotating with a speed of up to 3000 rpm in order to break lumps and distribute the liquid homogenously. So me continuous paddle mixers have a segmented mixer drum and each segment has a conical shape. Due to the reduced cross section the powder is densified towards the end of these sections, which should support the agglomeration process. After the agglomeration step the product is dried and cooled in a pneumatically fluidized bed to ensure its storage stability.
Agglomeration of Dehydrated Consumer Foods
627
The agglomerates produced in a mechanically fluidized bed typically have a diameter between 1 and 1 0 mm. They are more or less spherical, dense and mechanically more stable compared to agglomerates produced in a pneumat ically fluidized bed. 3.4. Press ure agglomeration of food powders
In steam jet or fluid-bed agglomeration, the particles adhere to each other upon collision if liquid or viscous bridges are generated between the particles. At low viscosities surface tension is the main driver responsible for developing liquid bridges. With increasing viscosity it is no Ion ger possible to build material bridges between the particles within the short contact time. However, at medium viscosities of the particles outer particle shell will still deform upon collision. The achieved deformation includes stronger Van der Waals forces due to a decreasing distance and an increasing contact area between the particles. Only if the viscosity at the point of contact is not too high, a significant and remaining deformation is obtained during collision. Increasing the pressure with which the particles are pressed together can compensate for the high resistance to de formation. Agglomeration processes in which the particles are subject to exter nal pressure are referred to as pressure agglomeration. Extrusion, tabletting and roller compaction are examples for such pressure agglomeration processes applied in the food industry. In extrusion of wet powder masses a low pressure is applied to form agglomerates. During roller compaction or tabletting the parti eies are subject to high pressure leading to dense and mechanically stable agglomerates. 3.4.1. Extrusion of wet powder masses
Extrusion is a process used for manufacturing various food products. In extru sion a paste like mass is pressed through a die with various holes. For example, for cereals and snack products extrusion is used to transform a starch- or flour-containing mix into swamp-like structures. Melt-extrusion applied in flavour encapsulation leads to a glassy structure in which the aroma droplets are em bedded. However, since the initial particles can no longer be. Such a process is by definition (see Chapter 1) not an agglomeration processes. A different case is the extrusion of wet powder masses known as "wet mass ing" or "sieve extrusion". A powder mix is wetted with 3-20% water in a kneader or powder mixer. In some equipment (as in Fig. 29) the wet mass is pressed through cylindrical holes by a piston or rotating blades. The obtained product string is then separated into individual agglomerates by cutting or due to forces like gravity or inertia (see Figs. 29 and 31).
628
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Fig. 29. Extruder for wet powder masses. (Bextruder; Courtesy Hosokawa Bepex GmbH Leingarten D . )
Fig. 3 0 . Extruder with two perforated rollers. (Courtesy Hosokawa Bepex GmbH Leingar ten D.)
Another equipment used for the extrusion of food and feed consists of two perforated rollers. The powder mass is pressed through holes in the roller wall while passing the gap between the roller pair. Cylindrical agglomerates (see Fig. 30), in which the original powder particles are still visible, are formed. Depending on the amount of added water, a subsequent drying step is required to stabilize the agglomerates. This drying can be performed either in a batch
629
Agglomeration of Dehydrated Consumer Foods
n��l' I
ROTATING PADDLES
---- ZONE 1 -----+· +-
ZONE
1 ,11 • •
2 · - - ZONE 3 - .Z0N E 4.
Fig. 31 . Extruder for wet or fatty masses. (Extrudo-mix; eourtesy Hosokawa Mieron B.V. Doetinehen NL.)
vacuum drier or a continuous or batch operating f1uidized bed. The final water content achieved after drying is normally in the range from 1 to 5%, depending on the drying temperature and the residence time within the bed. However, drying extruded agglomerates containing amorphous substances that are moisture and heat sensitive in a fluidized bed is difficult. In such a case, a low temperature and a low feeding rate has to be applied to avoid lumping or even a collapse of the bed. If fat is used as a binder, cooling (instead of drying) is required to stabilize the extrudates. Extrusion is applied for instant tea, sweet beverages, seasonings, culinary binders and various animal feed products. 3.4.2. Roller compaction
Roller compaction is a type of pressure agglomeration. A high pressure is exerted continuously on a moving powder stream while the powder particles are pressed into a gap between two synchronized counter-rotating rollers. Figure 32 includes a process scheme for roller compaction of food powders by using a vertical roller pair and a screw feeder. Figure 33 shows a roller compactor with flat rollers, whereas the compactor shown in Fig. 34 has roller surfaces with cavities forming briquettes. The powder is fed into the gap between the two rollers using a force feeder or sometimes just under gravity. The powder is then forced to pass the gap due to the pressure generated by the screw or gravity and to a great extend due to the wall friction between the powder and the roller surface. While passing the gap it is compacted into large flakes, briquettes or into an endless, dense ribbon. The two
630
s. Palzer base powder
+
coarse particles
sitter
g ri nde r lo:---� fine partie/es
Fig. 32.
Process scheme for roller compaction of powdered food materials.
Fig. 33. Roller compactor with vertical feeding. (Courtesy Hosokawa Bepex GmbH Le i ngarten 0.)
rollers turn at up to 20 rpm. Working with a flat roller surface, a thin flat ribbon sheet is obtained, whereas a roller surface with large cavities generates bri quettes. The compacting pressure is adjusted either by increasing the feed-rate or by adjusting the distance between the two rollers. According to Johanson [36], it is possible to increase the pressure generated within the roller gap by using rollers with rough surfaces.
Agglomeration of Dehydrated Consumer Foods
Fig. 34.
631
Roller compactor with teeth rollers. (Courtesy Hosokawa Bepex GmbH Leingarten 0.)
The compressed ribbons or briquettes can be grinded in a so-calied "gran ulator" which is a sieve basket in which a stirrer oscillates or rotates with 200-300 rpm (see Fig. 35). Alternatively, toothed crushers are used for crystalline materials. To optimize the particle size distribution of the final product the obtained coarse granules can be ground for a second time (see Fig. 36). The granules obtained after grinding are sifted into at least 2 fractions: the fines and the desired particle fraction. Oversize particles are normally not obtained by using the described granulator due to the installed sieve basket. The fines are added back into the feeding hopper of the compactor. In compactors, which consist of vertical roller pairs (see Figs. 32 and 36) the powder is fed from the side into the gap between the rollers. Compactors that have horizontal roller pairs (see Figs. 33 and 34) require a vertical feeding by using gravity or a vertical screw. For food materials, roller compactors with a throughput of up to 1 50 t/d are used. Food powders are typically agglomerated to a final particle size of 0.2-3 mm by applying a line pressure of up to 50 kN/cm. The resulting dense granules are sharp-edged, and compared to the porous agglomerates obtained by extrusion of wet masses their dissolution rate is lower. Several models to describe roller compaction have been published in the last 50 years. In some models, the gap between the two rollers can be divided into a slip and a nip region. In the zone outside the rollers the powder is exposed only to the minor principle stress generated by the feeder or by the weight of the powder
632
s. Palzer
g o
�
0
0 0
Fig. 35. Granulator used for grinding the ribbons into individual granules. (Courtesy Alexanderwerke, A.G. Remscheid, 0.)
Roller compactor with horizontal feeding and de-aeration funnel. (Courtesy AI exanderwerke, A.G. Remscheid, 0.)
Fig. 3 6 .
633
Agglomeration of Dehydrated Consumer Foods
-�
1
: -ir--
-
�
�7'""sl iP r�;
-
.----- Stress (J
length 1
Fig. 37.
Slip and nip region between the two rollers and resulting pressure profile.
itself. When the particles enter the gap between the two rollers a region whe the powder slips on the roller surfaee ean be identified (see Fig. 37). This regidn is ealled the slip region. For a steady state flow the yield eriterion aeeording to Jenike and Shield [ 1 8] ean be applied in order to deseribe the state of the powder in this region. While the particles move further into the gap between the two rollers they " nter the so-ealled nip region where the powder has no relative motion eompared ' the roller surfaee. The powder is eompaeted following a material-speeifie law. F lure 37 i1lustrates the nip and the slip region between the two rollers. Johanson [36] published a model for ealeulating the pressure generated in the powder depending on the position within the gap for these two regions. his model the pressure is predieted as a funetion of the flow properties of the po . der, the roller size, the width of the gap betwe�n the rollers, the surfaee propert" s of the rollers and the feeding pressure. In the slip region the powder slides on the surfaee of the roller and thE' e is signifieant movement of the particles within the powder bulk. Following the theory of Mohr/Coulomb the yielding of a bulk solid ean be approximated using a linear relation between normal stress and the resulting shear stress within the bulk [37]: • . '
'r
r
= (J tan (j + C
effeetive yield loeus
(35)
r is the shear stress, (J the normal stress within the powder and C represents the cohesivity. The slope of this straight line is given by the tangents of the so-ealled effeetive angle of internal frietion. This straight line represents normal and shear stress eombinations at whieh the powder starts yielding. Below the line the powder is not moving whereas any state above the Mohr-Coulomb line is not possible. It should be noted that eaeh powder density results in a different Mohr-Coulomb line. Beside particle movement within the powder bulk, the sliding of the powder particles on the surfaee of the rollers has to be eonsidered for modelling the
634
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system. This process can be described using the angle of wall friction ep. Multi plying the normal stress with the tangents of ep the shear stress required for sliding of particles on the roller surface is obtained: (36) r = (J tan ep wall yield locus All parameters in equations (35) and (36) describing the powder behaviour in the slip region can be determined by shear experiments using a Jenike shear tester or a ring shear cell. Considering the geometry of the gap between the two rollers and neglecting the cohesivity C, Johanson calculated the stress gradient d(Jjdx in the slip region according to the equations (37)-(39): 1 . sin ep = ep arcsln -.(37) 2 Sin D v
-
(1t
)
8h = 21t - V -
-
(38)
- e ) tan D 8( ) = � ( 1 � cos4(J (e�) (cot(A - cot(A with A � (� 8 ) and � � 4 2 2 2 d(J dx
-
+
=
+
v
-
-
+
J1 =
v
J1)
-
+ J1))
(39)
d is the diameter of the rollers, h the distance between the rollers and (J the normal stress. () is an angle describing the position of the particles within the slip region. eh, is the angle at which the particles enter the slip region. While e ap proaches 0h, the stress gradient d(J/dx decreases to O. For the nip region, in which the powder is compressed without relative move ment between the roller surface and the particles, Johanson assumed that the normal stress (pressure) within the powder mounts according to a simple tablet material law [36]:
(J2 (J1
=
(PP12) K P
(40)
K is the compressibility of the bulk solid, its density and (J the resulting stress. The indices 1 and 2 are defining different states of the powder. K has to be obtained experimentally. The powder density is depending only on the geometry of the system. Ac cordingly, the pressure within the nip region at a defined position in the gap (given by the angle can be calculated according to equation (41 ):
8)
d(J dx
- (0) = K
(J (2 cos 0 1 - �) tan e H� + ( 1 + � cos cos e) -
-
8)
(41 )
d is the roller diameter, h the distance between the two rollers and s the surface roughness of structured rollers. For = 0 or e�60° the stress gradient d(J/dx
8
635
Agglomeration of Dehydrated Consumer Foods
decreases to O. At the interface between slip and nip region both stress gradients are equal. The angle, at which the particles leave the slip region while entering the nip region, is ca lied angle of nip Thus, it is possible to identify by com bining equations (39) and (41 ). However, it has to be considered that in the slip region the density of the powder changes and thus, the effective angle of friction might change perma nently while the particles move through the slip zone. Johanson did not consider this fact. According to Dec et al. [38] the Johanson-model is useful for finding a theo retical value for the nip angle in compactors with gravity feeders. Furthermore, it enables to predict the pressure distribution in compactors with large smooth rollers (d> 500 mm). If rollers with structured sUrfaces are used, significant deviations between the model and the measurements are observed. The Johanson model leads to rea sonable results for granular materials having a high friction against the roller surface and a high compressibility K. If the powder is very compressible (small K value) or the applied compaction pressure is high, significant deviations between model and experiment can be expected [38]. Another modelling approach is the so-ca lied "slab method". This method was first applied by Katashinskii [39]. The zone between the two rollers is divided into trapezoidal slabs. Around these slabs a force balance is established. This force balance was combined with different material parameters that were obtained by shear tests or compression in an instrumented die. However, the nip angle has to be determined experimentally. According to Dec etal. [38] modelling by using the "slab-method" was in good agreement with experimental data in only a few of the investigated cases. Recently, the discrete element method has also been used to model roller compaction [38]. Knowing the pressure distribution within the roller gap and the material specific relation between pressure and the resulting compact strength, the achieved bri quette or ribbon hardness can be estimated. The obtained ribbons or briquettes should be stable enough to avoid a high amount of fines during the following grinding step but the obtained granules should also dissolve in a short time. Roller compaction is used for the agglomeration of various food products. Amongst them are sucrose, sodium chloride (bakery spread-salt), vitamins, fibres used as food ingredients, soup and seasoning powders, monosodium glutamate, encapsulated flavour powders and dairy powders. For crystalline food materials like sodium chloride a high pressure has to be applied to achieve stable agglomerates. Compacting soup and seasoning powders results in den se agglo merates with a reduced solubility. If fat is used as a binding substance, the solubi lity is good due to the lower pressure required for compaction. However, the IX .
IX
636
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dissolved product is often turbid due to a fine distribution of the fat. Compaction of spray-dried flavours is sometimes performed to encapsulate sensitive compo nents in a cost-efficient way. During compaction of flavour powders obtained by spray-drying of an emulsion, sometimes an oiling-out of the oiljaroma mix is observed. Fibres, cellulose, starches and other high molecular carbohydrates are compacted to reduce their transport volume and to improve their handling prop erties (e.g. their flowability). One of the major problems in roller compaction of food materials is de-aeration of the powder material. De-aeration of highly porous raw materials is crucial to reduce the elastic re-expansion of the compacted flakes or ribbons. Figure 38 shows a compactordesign facilitating de-aeration ofthe feed material. The airentrapped into the powder can escape via an additional funnel connected to the screw feeder. Within this funnel no high powder layer hinders the air to stream out of the system. Another major problem of roller compaction of food is the warming-up of the rollers due to friction between the particles themselves and friction between the particles and the roller surface. At increasing temperatures the fat can melt and amorphous components become sticky. Thus, the compressed powder can ad here to the roller surface after compression. By cooling the rollers (see Fig. 39) the warming up of the equipment can be minimized. The quality of the end product obtained by roller compaction depends on the homogeneity of the ribbons, since density variations within the ribbon sheet are often seen. Ribbon pieces with a low density lead to a high amount of fines Raw prod u e t
O e - d u s t i n g l ve n ting
U n d e r s i z e granule, dust l a nd overs i z e granule, addi tives)
S e p a r a t i o n of side seal leakages
Fig. 38. Roller compactor with de-aeration funnel and re-circulation of fines. (Courtesy Alexanderwerke, A.G. Remscheid, 0.)
637
Agglomeration of Dehydrated Consumer Foods [ ooUng c h onnels
[ 0 0 U n g wo f e r
i nlef
r;;;:::lt====;;;-J
Overprmure
I
[ooling w a f e r reservoi r
[ o oling water droin
Sue t i o n pump Overpressure
Fig. 39. Installation for water cooling of the rollers. (Courtesy Alexanderwerke, A.G. Remscheid, D.)
whereas dense ribbons may result in almost insoluble granules. Towards the border of the sheet the density decreases because a number of particles escape out of the roller gap. This problem is less important for compactors with long rollers than for machines with short roller pairs. Using a screw feeder, an os cillating density pattern is obtained due to the rotation of the screw's end. Some times the major amount of the powder is placed on the left side of the compactor and half a revolution later the major powder quantity is placed on the right side of the compactor gap. Installing two counter-rotating screws for feeding the powder into the gap can reduce density variations in the ribbon sheet. While compacting a food powder, which is sensitive to humidity, sticking is often observed on the roller surface. Specially structured roller surfaces tend to develop a crust if the feed is too humid. Most of such critical powders contain major amounts of amorphous substances that show glass transition. Thus, sticking in creases after running the compactor for some time due to the heating of the rollers. Adjusting the moisture content of the base powder, using rollers with a smooth surface and cooling the rollers themselves can help to avoid such problems. 3.4.3. Tabletting of food powders
Tabletting is a pressure agglomeration process which provides a pre-dose pow der quantity in a specific and easy recognizable shape. In addition, the high density achieved allows a slow dissolution of sweets and dextrose tablets within
638
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compression roller lablet
counter pressure plate
compression roller
Fig. 40. Double punch and single punch rotary tabtet presses used for food tabtets.
the mouth. Prior to tabletting the different powdered components are mixed within a typical powder mixer. In some applications this powder mix is agglomerated in a mechanical or pneumatic fluidized bed to improve the following tabletting process. Frequently, vertical granulators (see Section 3.3.2) are used for this first agglom eration step. The agglomerated moist powder is dried to avoid caking, chemical and enzymatic reactions and microbiological spoilage during the intermediate storage. The agglomerated powder is easier to compact and has an improved flowability compared to the initial powder mix. Finally, the agglomerated powder is compacted into tablets. However, sometimes the powder is also tabletted directly without any preceding fluidized-bed agglomeration to reduce costs. Tabletting is normally performed in rotary single or double-punch presses (see Fig. 40). The tabletting process can be divided in five different steps: ( 1 ) Filling of the powder into the dies (2) Pre-compression step air release and re-arrangement of particles (3) Main compression step deformation and breakage of particles; develop ment of adhesion forces (4) Pressure release elastic re-expansion of the tablet (5) Tablet ejection. -+
-+
-+
Figure 41 shows how the head of the piston is mounting on the compression roller. The resulting dwelling or loading time is dependent on the geometry of the system and the speed of the pistons.
Agglomeration of Dehydrated Consumer Foods
639
Fig. 41 . Pistons and compression roller of a rotary tablet press.
r is the radius of the compression roller and d the diameter of the punch head. The time the pressure is applied (total cycle time) is called loading or dwelling time. The loading time t depends on the rotational speed n of the press (in revolutionImin), the diameter 0 of the rotating die table, the number of dies and the geometrical distances Sx 1 and Sx2 included in Fig. 41 . It can be calculated according to equation (42): t
= (Sx 1 + Sx2) rrnD
(42)
During the compression phase, the density of the mass increases while the head of the piston is in contact with the compression roller. With increasing density the axial stress (Jy acting in vertical direction increases as weil. The relation between density and axial stress (called the tablet law) is specific for each powder mass and has to be determined empirically. This relation can be described using a simple tablet law like the one given in equation (40). Due to the applied compression stress (Jy acting in axial direction, the stress (Jr acts on the die wall. The ratio between (Jr and (Jy is calied the pressure transmission coefficient A. For liquids A is 1 and for ideal stiff solid bodies O. Assuming a constant A over the tablet height, the ratio }o can be calculated according to Klasen [40]: 1 I\.
_
(J r
(Jy
0 F A = - In -b 4HJ1. Fu
(43)
where 0 is the diameter of the die, H the height of the tablet, J1. the coefficient of wall friction between tablet and die wall Fb the force acting on the lower piston and Fu the force acting on the upper piston. The coefficient of wall friction and the pressure transmission coefficient are both a function of the die material and the powder properties.
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Knowing the stress acting on the moving piston O"b , the coefficient of wall friction and the pressure transmission coefficient, the radial stress at a given position y in the die can be calculated according to equation (44): (44)
In opposition to the assumption made for deducing equation (44), it appears that the pressure transmission coefficient is neither constant over the tablet height nor constant during the compression process. Thus, a stress and density distribution Iike the one shown in Fig. 42 is resulting within the tablet. After compression the stress is released. During stress release the tablet shows a spring-back. Values for the elastic re-expansion are calculated by using the final height of the tablet hfinal and the minimal height hmin of the tablet during the compression process according to equation (45). Elastic re-expansion =
�� hmin
hfina
(45)
mm
The elastic re-expansion reduces the tablet strength because the distance between the particles increases and material bridges between single particles built during compression are disrupted again [1 8] . After pressure release and elastic re-expansion, the radial stress does not decrease to zero. The remaining remnant radial stress component increases with increasing plastic deformation. Thus, force is needed to overcome the resulting friction forces while pushing the
2.8 MN 1m2
6.1 M N l m 2
200 MNlm2 F i g . 4 2 . Density distribution (density expressed a s the value within a cylindrical tablet a t progressive densification [41 ] .
V=
1 00%-porosity
e
in % )
Agglomeration of Dehydrated Consumer Foods
641
tablet out of the die. Pauli [42] found a non-linear relation between the compres sion pressure and the remaining remnant stress for tabletting of maltodextrin at constant tablet height. The remnant stress causes an inhomogeneous stress distribution within the tablet during expulsion. Figure 43 illustrates stress profiles caused by remnant stress within a tablet [43]. The remnant stress is related to capping, a phenom enon in which the tablets break horizontally during expulsion. According to Ritschel and Bauer-Brandl [44] capping is more likely to occur at low radial stresses during compaction and high-remnant stress after pressure release. The mechanical properties of the powder mix used for tabletting, strongly de pend on the material used as binding substance within the tablet, the temperature and in the case of amorphous water-soluble substances also on the moisture content of the powder mass. Tabletting powders containing a significant amount of solid fat as binding substance plastic deformation of the fat is responsible for the final tablet hardness. Like mentioned in Section 2.4.5 the obtained tablet hardness mainly depends on the mechanical properties of the fat (which is a function of temperature) and the tabletting pressure. However, most tabletted food products contain amorphous substances that deform visco-elastically while exposed to stress. In this case the final tablet hardness depends on the pressure level, the time the pressure is applied (Ioading or dwelling time) and the mechanical prop erties of the substance, which are a function of temperature and moisture. As discussed in Sections 2.2 and 2.3, increasing moisture, increasing temperature and decreasing strain rate lead to a more plastic behaviour. Figure 44 shows the pressure/time profiles while compressing a single tablet using a dry and a moist powder at different tabletting speed on a rotary tablet press. The pressure first increases while the piston of the press mounts on the compression roller. After reaching the maximum pressure while passing the highest point of the compres sion roller the pressure decreases again until the tablet is released. Tabletting a dry powder fast (short loading time) the pressure/time profile is fairly symmetric because the material behaves elastically. Even after the piston has passed the highest point of the compression roller, the pressure does not drop immediately to zero due to the elastic re-expansion. Compressing the same amorphous material at higher moisture content or over a longer time a lower residual pressure is --------
Fig. 43. Pressure profiles within a tablet during expulsion leading to capping [43].
642
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25
dry powder (aw 0.19)
20 ro c.. ::2 c. � ::;) '" '"
� c. c 0 'iij '"
15 moist powder (aw 0.45 )
10
� c. E 0
-&- 80.000 tablets/hour dry -.!r- 50.000 tabletslhour dry -s-20.000 tablets/hour dry -+-80.000 tablets/hour moist -50.000 tablets/hour moist --20.000 tablets/hour moist
u
5
0 0.00
0.05
0.10
0.15
0.20
loading time t Is
Fig. 44. Pressure/time profile while tabletting dextrose syrup (DE2 1 ) at different speed (output/time) and different moisture content (aw = 0. 1 9 and aw = 0.45) on a double-punch rotary tablet press.
observed after passing the highest point of the compression roller due to the plastic deformation of the particles and the reduced elasticity [45]. In addition, it has to be considered that the temperature increase during com pression due to inter-particle friction and friction between the powder and the die wall can affect the tabletting of amorphous powders. Nürnberg and Hopp [46] found a temperature increase of up to 20°C with longer running time of the press. Several other authors reported an increase of the tablet temperature during tab letting [47--49]. While the density of the tablet increases during compression the particles de form plastic or visco-elastic. Thus, the distance between single particles de creases and the contact area between them increases. In addition, the particles break. Both deformation and particle breakage lead to increasing contact points between the particles. At these contact points amorphous materials might sinter together supported by capillary condensation and increasing temperature due to interparticle friction. Figure 45 shows scanning electron microscope pictures of different food tablets. In some tablets a significant deformation of primary particles is visible. In others the primary particles show nearly no deformation and, thus, there are only a few
643
Agglomeration of Dehydrated Consumer Foods
Vitamin (ablet
tock tab let
Dextrose table!
Fig. 45. Photos of different food tablets (SEM pictures).
Pressure test
Bending test
�F Tensile strength
Fig. 46. Different ways to measure the hardness of food tablets. (Left: compression tests, middle: bending test, right: diametrical compression test.)
contact points between them. In such tablet structures sintering is likely to play a role in developing the final tablet hardness. The tablet hardness can be expressed as tensile strength, bending stability or breaking stress. The tensile strength is defined for round and homogenous tab lets with ideal brittle fracture, which have a line contact with the piston of the measurement apparatus ( see Fig. 46). The tensile strength can be calculated according to equation (46): 2F O"t = n
Dh
(46)
D is the diameter of the tablets, h their height and F the measured force required for breaking the tablets. For rectangular tablets, a crushing force is obtained while exposing the tablet to pressure or a bending stress is measured like shown in Fig. 46. The obtained value for the tablet hardness (expressed either as force or stress) depends on the geometry of the tablet and the measuring procedure.
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4. AGGLOMERATION TECHNOLOGIES FOR DIFFERENT PRO DUCT GROUPS
Various consumer foods are agglomerated. Amongst them are dairy powders, convenience foods, instant beverages, confectionery products and cereals. Ag glomeration is performed either for generating a distinctive shape or to improve application properties Iike dissolution time, flowability or shelf Iife. In the fOllowing, the technologies applied for different product groups are described. 4.1 . Dairy powders
The most important dairy powders are skim and whole milk powder. Besides these, several other powdered products are manufactured based on milk or milk powder. Infant formulas, for example, are composed of fresh milk, whole or skim milk powder, whey powder, micronutrients, carbohydrates, non-hydrogenated vegetable oil and sometimes also pro- or pre-biotic bacteria. Infant formulas are mainly manufactured by spray-drying. Another category of milk-based powders is the so-calied filled milk powder, which is used to replace pure milk powder. Filled milk powders are milk powders that are enriched with components Iike buttermilk powder, vegetable oils and micronutrients. Like other dairy powders, filled milk powder is mainly manufactured by spray-drying. Coffee creamers or whiteners are multi-component mixes made of casein, corn syrup, vegetable fat, emulsifiers and flavours. Furthermore, flow agents and col ours are added. Buttermilk, yoghurt, casein, caseinate, whey and hydrolysed whey powders are used by the food industry as ingredients. They are manufactured either by spray- or belt-drying. To improve dissolution of such dairy powders are often agglomerated. 4.1.1. Composition of dairy powders
Approximately 8 L of fresh milk are transformed into 1 kg of whole milk powder. Whole milk powder contains 38% lactose, which is amorphous or crystallized in its !X or ß form. Furthermore, whole milk powder is composed of 26% proteins, 26% fat, 7% minerals and less than 3% water. After the rapid spray-drying proc ess, the lactose is normally amorphous. Depending on moisture and temperature, it crystallizes into the !X- or ß-form. !X crystals are needles whereas ß crystals have the shape of a Tomahawk. Crystallization affects undesired and desired agglomeration processes because it Iiberates water. Furthermore, the crystalline state does not get sticky at higher temperature or moisture content. Thus, the presence of crystals on the particle surface might help to avoid caking of the powder.
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The fat eontent of whole milk powder is present as fat globules that are em bedded in the spray-dried partieles or in form of a layer on the particle surfaee. These fat deposits melt at higher temperature. The melted fat ean eontribute to agglomeration by liquid bridges, whieh solidify upon ehilling. Conversely, fat present at the particle surfaee ean also reduee the adhesion between amorphous particles under humid eonditions. Figures 47 and 48 are images of agglomerated skim and whole milk powder partieles obtained by seanning eleetron mieroseopy.
Fig. 47. Agglomerated skim milk powder (SEM picture).
Fig. 48. Agglomerated whole milk powder (SEM picture).
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As for different milk-based powders a rapid dissolution in warm or hot water is desired, they are often agglomerated. Several agglomeration processes and technologies are applied to improve dissolution and flow properties of dairy pow ders: agglomeration in spray towers, agglomeration during spray-drying, ag glomeration in combined spray-jbelt-driers (e.g. Filtermat drier) or agglomeration in batch or continuous fluid beds. 4.1.2. Agglomeration of dairy powders during spray-drying
Most milk-based powders are manufactured by spray- or roller-drying. A limi ted agglomeration can already be achieved during spray-drying. One approach is to install a so-ca lied integrated fluidized bed at the boUom of the drier. The drying particles fall into this bed where they agglomerate (see Figs. 1 5 and 1 6). The agglomerated dairy powder flows over a weir outside the drier, and in an external fluid bed the powder is dried and cooled. Fines which are separated by cyclones or bag filters from the exhaust air coming from the drying tower and the external fluid bed are added to the fine fraction coming from the sifter. These fine particles can either be blown into the space above the internal fluid bed or they can be added into the internal or external fluid bed. Some spray-driers for dairy powders have integrated bag filters directly in stalled in the upper part of the tower. Fines accumulating on the tissue surface fall back into the humid drying zone of the tower where they agglomerate with other particles (see Fig. 1 5). Agglomeration during spray-drying can also be achieved by installing a steamf powder nozzle on top of the drier through which fine particles are added back into the tower by mixing them with steam while they are leaving the orifice. Figure 49 includes a steam jet agglomeration system, which is integrated into a spray tower for dairy products. fln�5
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Fig. 49. Agglomeration of dairy powders using a steam jet agglomeration system, which is integrated into a spray tower.
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4.1.3. Agglomeration of dairy powders during spray-jbelt-drying (filtermat drying)
Furthermore, a combination of spray- and belt-drying called Filtermat drying is used for dairy powders (see Fig. 1 8). This system is especially applied for high fat dairy powders with up to 80% fat content. The concentrated milk-based liquid is atomized into a short spray tower with co-current airflow. For the atomization a high pressure nozzle is used. The hot drying air passes an air disperser gen erating the desired flow pattern within the tower. In the tower the particles are pre dried while they fall down. These pre-dried particles fall onto a perforated belt where they sinter or melt together forming a particle cake. While the particle cake is transported by the belt towards the outlet of the drier, hot air streams through the powder cake. In a second zone the dairy powder cake is cooled using cold air. The product stays on the belt for several minutes before leaving the drier. A comparably low product temperature is applied for drying. Finally, the dried dairy powder is milled to a smaller particle size or directly sifted to obtain the desired agglomerate size. Filtermat driers with a throughput of up to 6-7 t/h are used for drying and agglomeration of different dairy powders. 4.1.4. Agglomeration of dairy powders in an external fluidized bed
Sometimes the spray-dried dairy powder is agglomerated in an external contin uous fluid bed by atomising water on the moving particles. Such a spray-drierl fluidized bed system can be combined with an addition of re-circulated fines into the middle part of the spray-drier (see Fig. 50). Smaller volumes of dairy powders are often also agglomerated in batch op erating fluid beds. 4.1.5. Lactose crystallization during agglomeration
Amorphous lactose generated during the rapid spray-drying is within a meta stable state. Depending on time, temperature and moisture content these amorphous
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Fig. 50. Agglomeration of dairy powders in an external fluid bed.
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Fig. 5 1 . Agglomerated skim milk powder containing amorphous lactose (SEM picture).
lactose crystallizes more or less rapidly [1]. Upon crystallization, water is released because crystalline lactose is less hygroscopic than lactose in the amorphous form. Crystallization will increase the dissolution time of the powder. However, lactose crystals have the advantage that they are less hygroscopic compared to amorphous lactose. They also have a reduced risk of caking under higher tem perature and/or humidity and the flow properties of crystalline particles are im proved compared to an amorphous powder. Agglomerating milk powder in an external fluidized bed at higher tempera ture, and humidity provokes lactose crystallization. Lactose crystallization is also observed if the residence time of the particles within the spray-drier or in the after-drier is too long. If drying or agglomeration is performed rapidly by applying moderate temperatures, the lactose remains amorphous. Figure 51 shows an agglomerated skim milk powder particle containing lactose in the amorphous state. Figure 52 includes a scanning electron microscopic picture of a skim milk powder particle agglomerated under hot and humid conditions for a longer time. Needle-like lactose crystals are c1early visible on the particle surface.
4.2. Dehydrated convenience foods
The food industry manufactures various agglomerated dehydrated convenience foods. Amongst them is a wide range of dehydrated culinary kitchen aids Iike dehydrated sauces, stocks and seasonings. Beside these kitchen aids, there are
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Fig. 52. Agglomerated skim milk powder containing crystalline lactose (SEM picture).
also prepared dishes like instant soups, dehydrated mashed potatoes and pasta or rice containing dishes. 4.2.1. Composition of dehydrated convenience foods
Dehydrated culinary products are composed of starch, flour, vegetable- and yeast-extracts, meat powder, sodium chloride, sucrose and monosodium gluta mate, fat and oi! . In addition, such products typically contain spices, flavour powders, herbs and vegetable pieces. Crystalline ingredients like sodium chloride can be considered as inert during the agglomeration process. Only if a higher amount of water is present during agglomeration, such crystals dissolve partly and build solid bridges between each other upon drying. Spices and herbs also behave inert since they are mainly composed out of cellulose. A majority of the other ingredients are hygro-sensitive amorphous substances. Starch and flour, which are partly amorphous and partly crystalline have a high glass transition temperature (see Fig. 3). Thus, they only contribute to the adhesion forces at high humidity. Soups and sauce powders are mostly agglomerated for vending applications, to ensure an exact dosing by improving the flowability and to avoid caking of the powder within the vending machines. Sometimes seasonings are agglomerated in a fluidized bed to provide the flowability necessary for dosing out of a sprinkler. A desired side effect of such agglomeration is the increasing colour intensity due to the removal of fines. Some seasonings and stock powders are also structured by means of pressure agglomeration to provide them with a distinctive shape.
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Several agglomeration processes are used in the culinary industry. The most common processes are listed below: Growth agglomeration • •
Fluid-bed agglomeration of vending soups and seasonings Mixer agglomeration of sauce powders and seasonings Pressure agglomeration
• •
•
Tabletting of stock and seasoning tablets and cubes Roller compaction of seasonings, pure salt, glutamate and stock mixtures Extrusion of garnishes and seasonings
Growth agglomeration is used for improving the flowability and dissolution behaviour of dehydrated soups and sauces. Pressure agglomeration is mainly applied for structuring kitchen aids Iike stock or seasoning powders. Prior to agglomeration, the powdered components are blended batchwise in high-shear or ribbon mixers. These powder batches are then agglomerated batchwise in a second step. During mixing melted fat, oil, liquid flavours and for extrusion also water is added to the mix. Then the main agglomeration step is performed. Figure 53 shows the different agglomeration processes as applied to culinary powders. 4.2.2. Agglomeration of convenience food in mechanically or pneumatically fluidized beds
Culinary powders are sometimes agglomerated in fluid beds. The powder is flu idized either mechanically in powder mixers by fast rotating stirrers or pneumat ically by air flowing through the powder bed. Pure water is sprayed on the moving particles to increase the adhesion forces between them. Upon drying, such bridges are transformed into solid bridges with a high tensile strength. Droplets impinging on amorphous substances Iike meat-or yeast-extract generate a highly viscous solution on the particle surface providing adhesion points for other par ticles. However, it is essential not to exceed a critical RH of the air within the powder bed to avoid a collapse of the bed. Therefore, the glass transition tem perature and the collapse point (calculated using equation (26)) of the main ingredients within the powder mix have to be known to control the process. After water injection the powder is dried and cooled in a pneumatically fluidized bed. A number of ingredients used in dehydrated convenience foods have a very low glass transition temperature due to the presence of low molecular sugars or amino acids. These ingredients improve the strength of the agglomerates. Nevertheless, there is the risk of an increasing amount of oversize particles, encrustation of equipment and a collapse of the fluid bed since such substances get very sticky at high temperature or moisture.
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Fluid-bed agglomeration of culinary powders is either performed batchwise for small volumes or continuously for higher tonnages. Figure 54 shows a typical line for a continuous agglomeration of culinary powders. For the agglomeration step a continuous mixer is used and drying is performed in a continuous pneumatically fluidized bed. When agglomerating the powder batchwise, agglomeration, drying and cooling are done in the same vessel. Figure 55 includes a sehe me of a batchwise operating pneumatically fluidized bed used for the agglomeration of instant soups. 4.2.3. Extrusion of wet powder masses
One agglomeration process used for dehydrated convenience foods is the ex trusion of wet powder masses. For such an extrusion process several powdered ingredients are mixed together. This mix is plasticized by addition of 2-1 0% water. Afterwards, the plasticized powder mass is pressed through a die with small holes. The resulting cylindrical particles are dried in a fluid bed or in a
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Fig. 54. Continuous line for the agglomeration of culinary powders in a mechanicaily fluidized bed (mixer agglomeration).
batchwise-operating vacuum drier. After drying in a vacuum drier, the resulting cake is broken in a grinder and then sifted. The fines are recycled by adding them to the powder mass during the initial wetting step. In case the product is dried in a fluid bed drier, no grinding and only sifting into a coarse, medium and fine fraction is required. Agglomerates obtained by extrusion of wet powder masses (see Fig. 56) have a diameter corresponding to the hole diameter of the extruder die. The length of the cylindrical agglomerates can vary between 2 and 4 mm. Agglomerates man ufactured by extrusion of wet masses are porous and thus dissolve rapidly. Figure 57 shows a continuous line for agglomeration of culinary powders by extrusion of wet powder masses.
4.2.4. Roller compaction of culinary powders
Another pressure agglomeration process applied for dehydrated convenience foods is roller compaction. Stock and seasoning powders and even pure sodium chloride or monosodium glutamate are first compressed between two rollers into
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Exhaust air Base powder
Fluidisation air
Spray nozzle --- ..J.Binder solution Cleaning nozzle
Product hopper Sitter Mill for oversize Finished product
Fig. 55. Pneumatically fluidized bed for instant soups. (Courtesy Aeromatic-Fielder AG CH.)
Fig. 56. Scanning electron microscopic (SEM) picture of an extruded seasoning agglom erate.
large flakes and then grinded into dense sharp-edged granules with a diameter of 1-3 mm. Fat and amorphous substances are sometimes added as binders to improve the cohesion of the granules. Such agglomerates manufactured by roller compaction are often difficult to dissolve and might lead to a turbid solution after
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Fig. 57. Une for manufacturing of agglomerated culinary products by extrusion of wet powder masses.
re-hydration if they contain fat as binder. For roller compaction of culinary pow ders a line pressure of up to 4 kN/cm roller length is needed. 4.2.5. Tabletting of culinary powders
Tabletting is applied for structuring kitchen aids Iike seasonings or stock powders. Fat or amorphous substances are used as binding agents. By applying pressure, the fat deforms plastically. The strength of the obtained tablet is, thus, mainly dependent on the applied pressure and the solid fat content. If amorphous substances are used as binding agents, these substances deform visco-elasti cally and the resulting tablet hardness strongly depends on compression time and the moisture content of the amorphous binder (see Section 2.4.5). Tabletting is performed using single-punch rotary tablet presses with an output of 200-1 200 tablets/min. The powder is dosed in a die, which is embedded in a rotating table. The bottom of this die is build by a piston, which moves up and down during the rotation of the die. While the piston is running over a compression roller, the tablet is formed by pressing it against a rotating counter-pressure plate. This system was specially developed for tabletting of culinary powder mixes containing fat, which would stick on an upper piston while using a double punch tablet press. Some tablet presses even consist of a pre-compression step, which should de-aerate the powder before it is pressed in the main compression step to the final tablet hardness. During the compression cycie the pressure mounts up to 30-1 00 M Pa. A full compression cycie takes about 30-200 ms depending on
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the output and the press used. The produced tablets or cubes have a weight of 4-1 2 g. Figures 58 and 59 show two single-punch rotary tablet presses used for tab letting of culinary kitchen aids. Compared to agglomerates produced by fluid bed agglomeration, the manu factured culinary tablets are relatively dense. Figure 60 shows a tablet in which fat acts as a matrix binder. The powdered ingredients are embedded in the fat matrix which has been coloured black using Osmium-tetroxid. Figure 61 inciudes a scanning electron microscopic image of a culinary tablet in which big salt or sugar crystals are bound together by using fat and amorphous binding substances. feeding
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Fig. 60. Seasoning tablet with fat as matrix binder. (Light microseopie picture; fat coloured dark grey using Osmium-tetroxid.)
Fig. 6 1 . Scanning electron microseopie (SEM) picture of a seasoning tablet with low �at content.
4.3. Dehydrated beverage powders
For beverage powders, solubility is a key feature. Thus, the majority of beverage powders are agglomerated. Soluble coffee powder and different powdered coffee mixtures, coffee replacements, malted instant beverages, cocoa beverages, instant tea, isotonic beverage powders and sugar-based beverages are agglomerated to provide a beUer solubility in hot or cold water. Figure 62 shows soluble coffee particles agglomerated in a continuously operating pneumatically fluidized bed. 4.3.1. Composition of beverage powders
Soluble coffee must only contain coffee substances. No other additives are al lowed. Coffee mixes like cappuccino or milk coffee also contain milk powder,
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Fig. 62. Soluble coffee powder agglomerated in a continuous fluid bed.
flavours and sugar. Cocoa drinks are mainly composed of cocoa powder and sucrose. Malt-based beverages contain, beneath soluble malt powder, also sugar and micro-nutrients. Instant tea powders are a mix of ingredients like tea extract powder, dextrose, sucrose, maltodextrines, plant extracts, citric acid and fla vours. Sucrose, corn syrup, maltodextrine, f1avours and micro-nutrients are typi cal ingredients for various sugar-based beverage powders. Some of these sugar based beverages might also contain fruit powders, colours and citric acid. For Isotonic beverages also minerals and different salts are added. 4.3.2. Agglomeration of beverage powders during spray-drying
A limited agglomeration might already occur during the drying process. Agglom eration in a spray-drier can be achieved by adding fine particies, which have been separated from the exhaust air, back into the spray tower. These fines will stick to particies, which are still humid, and, thus, agglomeration is achieved. In addition, a limited agglomeration is observed in the after-drier, where the powder is dried to the desired final moisture content. The obtained fragile agglomerates have a medium particie diameter smaller than 1 50 �m. 4.3.3. Steam-jet agglomeration of beverage powders
For beverages, steam-jet agglomeration is the most common agglomeration process applied. The powder particies pass the agglomeration zone by free-fall or accelerated by a steam jet. While falling, the particies are subjected to saturated steam. The steam and the particles are often added through the same nozzle and the two streams mix with each other after leaving the orifice. The steam can either enter the nozzle centrally, laterally or by a combination of the two. The central steam-jet forces the powder through the agglomeration zone, whereas the
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lateral steam should support agglomeration by condensation on the particle sur face. A second possibility is to add the steam laterally through separate steam nozzles. To facilitate condensation, the beverage powder mix is cooled to a temperature below 30°C. Owing to the increasing moisture content, amorphous components become sticky while exceeding their glass transition temperature by 20-50°C. In the meantime, crystalline components partly dissolve. As a conse quence, colliding particles adhere to each other due to the formation of viscous or liquid bridges. The agglomeration process as such is rather fast and requires less than 1 s. Agglomerating a beverage powder containing also larger particles like sucrose crystals, it is advantageous to mill the powder prior to agglomeration to a smaller particle size [34]. Smaller particles adhere to each other more easily and the surface area available for steam condensation increases. Steam-jet agglom eration of beverage powders can be performed using a special steam/powder nozzle, which is integrated in a classical spray-drier (see Fig. 63). Alternatively, steam-jet agglomeration can be performed in a separate ag glomeration tower operating with co- or counter-current airflow (see Fig. 64). The agglomeration takes place in the upper part of the tower by mixing the powder with steam. While falling down through the tower, the built agglomerates undergo drying. Agglomeration towers for beverages operating with counter-current airflow tend to show a very efficient drying due to the turbulent airflow and due to the fact that the moisture and temperature gradient between the particle surface and the surrounding air is larger than in case of co-current airflow. In addition, no drying, but only cooling is required after the powder leaves the agglomeration tower. Co current airflow is suitable for heat-sensitive beverage formulations (e.g. recipes containing volatile aroma components) due to the lower temperature of the prod uct at the tower outlet. ftnes drying air
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Fig. 64. Agglomeration of beverage powders in a stand-alone steam jet agglomeration plant. (Agglomeration performed either in a pneumatically f1uidized bed or an agglomer ation tower.)
Another possibility for steam-jet agglomeration is to apply steam while the bev erage powder is falling into a fluid bed (see Fig. 64). In such a case the beverage powder is fed into a fluid bed drier using a vibrating conveyer. While the particles are falling in form of a powder curtain into the fluid bed, they are moistened with saturated steam. The obtained porous agglomerates are dried and cooled while they are passing through the different zones of the same or an additional fluid bed. Another approach is to dry the particles in a drum drier installed at the outlet of the fluid bed used for agglomeration. After steam-jet agglomeration, drying and cooling the agglomerated powder is sifted. The coarse fraction is either recycled to the grinder installed before the cooling step or it is grinded in a separate mill and then passed again through the sifter. The fines are added to the milled and cooled powder prior to agglomer ation. The final water content of the agglomerated beverage powder is between 0.5 and 2% depending on the product composition. Agglomerates produced by steam-jet agglomeration have a diameter of 1-3 mm, a high porosity and they are comparatively fragile. However, dissolution of such a beverage powder is very rapid. 4.3.4. Fluid-bed agglomeration of beverage powders
Beverage powders are sometimes also agglomerated in a continuous pneumat ically fluidized bed (see Fig. 65) which is attached to a spray-drier. The beverage powder is fluidized with air while it is Iying on a perforated plate. In the first part of
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Spray dryer counter CUlTent air flow
fluidhuld bad aaalomeration
Fig. 65. Agglomeration of spray-dried beverage powders in a continuous fluid bed.
the fluid bed, 2-1 5% of water is atomized on the moving powder particles. In the following zone, the agglomerates are dried at a temperature of 55-80°C to a moisture content below 3-5%. Finally, the agglomerated powder is cooled in a dedicated zone of the bed to a temperature of 20-25°C. A weir and the orien tation of the holes in the perforated plate on which the powder is Iying allows controlling the residence time within the bed. Compared to steam-jet agglomer ation the built agglomerates are more stable and dense. 4.4. Confectionery and sugar-based products
In the confectionery and sugar industry various products are agglomerated. Confectionery and sugar-based products are offen tabletted to give them an attractive shape and to provide them in a pre-dosed form. Some granular sugar products are agglomerated to improve their shelf life or to make them dispen sable more easily. Most of the mentioned confectionery products are manufac tured by tabletting of a powder mix in a double-punch rotary tablet press. Some of the formulations used for tabletting require a wet granulation step prior to tab letting. This accounts especially for formulations containing mainly crystalline sugars that are not easy to deform. Such sugar crystals are grinded and coated or agglomerated together with amorphous carbohydrates having a low or medium molecular weight. The resulting granules are deformable and the amorphous substances provide improved adhesion properties. 4.4.1. Composition of confectionery and sugar-based products
Compacted sweets based on sucrose are made by using dextrose and modified starches as binding substances. However, such sucrose sweets require an
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agglomeration step prior to tabletting. Some of these sucrose-based tablets are even made chewable. A wide range of confectionery tablets is mainly pro duced out of dextrose, which is directly compressible. These tablets mainly contain dextrose, dextrose syrup, citric acid, flavours and colourings. They are pressed into various shapes like hearts, Iipsticks, lollypops and round mini tablets. Pure dextrose tablets (see Fig. 45) serving as energy source are offered for sportsmen. Sugar-free confectionery tablets made to meet the consumer demand for more healthy products are based on sorbitol or isomalt, which are also directiy compressible. The confectionery industry also seils effervescing tablets that contain citric acid and calcium bicarbonate. The reaction of both generates carbon dioxide during dissolution. Sometimes food supplements like vitamins or minerals are incorporated into such effervescing tablets. Effervesc ing vitamin or mineral tablets are mainly based on dextrose, citric acid, sodium bicarbonate, flavours, sweeteners and different micro-nutrients. Sweetener tablets are made of saccharin, thaumatin, cyclamate and other sweetening substances. The amorphous low molecular carbohydrates and citric acid used in most of the mentioned products are easy to compact, but tend to stick on the surface of the piston of the tablet presses. In addition, they can increase the forces needed for the ejection of the tablets due to stickiness on the walls of the die. To avoid such problems, magnesium or calcium stearate is added as lubricants to the formu lations. The stearate is either mixed directly with the powder prior to tabletting or the dies and pistons of the tablet presses are coated with a thin stearate layer between two compression cycles. 4.4.2. Tabletting of confectionery
Tabletting of confectionery is similar to the tabletting of pharmaceutical products. For tabletting confectionery products double-punch presses (see Section 3.4.3) are used. The compression cycle in the press can be described as folIows: the bottom punch of the press descends to its lowest position by leaving a cavity. While the punches circulate in the turret of the press, cams control their vertical position. The powder is fed by gravity or by force-feeding into the dies and excess powder is scraped away while the dies are leaving the filling station. The powder is then compressed between an upper and a lower punch while both punches are moving over compression rollers. Some of the used rotary tablet presses consist of two compression stations: one pre-compression and one main compression roller. The aim of the pre-compression is to reduce the air entrapped between the particles. Air can cause problems during the main compression if it cannot es cape fast enough out of the die. During compression a pressure of up to 300 MPa is applied for up to 30-1 00 ms. After the compression phase, both punches are Iifted and the lower punch ejects the tablet out of the die. The tablet is then
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Fig. 66. Compression cycle of a double punch rotary tablet press. (Courtesy Courtoy, N .V. Halle, 8.)
knocked off the punch by a bar. Once again the emptied die moves to the filling station. Figure 66 shows a double-punch rotary tablet press. Common problems during tabletting of sugar confectionery are capping and lamination (see Section 3.4.3). In case of capping, the upper part of the tablet falls apart. Lamination results in a horizontal splitting of the tablet. Common reasons for both effects are the entrapment of air, low adhesion forces between the particles and highly elastic components within the formulation. Another common issue is the stickiness of the powder on the surface of the punches due to adhesion forces between the punch surface and the particles. Stickiness of powder on the punch surface is increasing with embossing or damage of the punch surface. Stickiness of confectionery powders on the punch surface is mostly linked to glass transition of amorphous components like dextrose or citric acid. 4.4.3. Manufacturing of compressed sucrose based sweets
Some compressed sweets are made using crystalline sucrose as the main com ponenl. Crystalline sucrose particles are not deformed easily and adhesion forces generated between single crystals during tabletting are limited. Thus, the crystal line sucrose is agglomerated before tabletting. To facilitate agglomeration, the sugar is grinded and sometimes mixed with 0.5-2% magnesium stearate that
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serves as lubricant during tabletting. While grinding the powder mix a narrow size distribution is desired. Very fine particles require a very high amount of binding substance in the following granulation step. Very coarse particles result in brittle granules, difficulties during tabletting and a poor mouth fee!. The sucrose/mag nesium stearate mix is then agglomerated by wet granulation in a high-shear mixer or kneader. For granulation, either pure water or a dextrose/starch solution is used as a binder. The obtained granules are dried to a final moisture content of 0.5-2% in ovens or continuously operating driers. The moisture content influences the flowability of the granules, which is reduced at higher water content. The hardness of the final tablet first increases with increasing moisture content before it softens again due to the plastification of amorphous substances. The dried granules are grinded and separated into different particle classes. The dried and sieved gran ules are mixed with powdered flavours and other heat-sensitive ingredients, which have to be added after the drying step to avoid aroma losses by evaporation or thermal degradation. Following this, the flavour/granules mix is tabletted in a rotary double-punch tablet press with an output of up to 4000 tabletsImin. 4.4.4. Agglomeration of sucrose-based products
Two main sugar qualities are offered by the sugar producing industry: Brown and white sugar. Brown sugar is composed of sucrose crystals which are coated with a thin molasses layer. The white sugar is composed of purified sucrose crystals in which the molasses has been removed before drying. Only molasses resulting from sugar cane processing is suitable for human consumption. Thus, brown sugar is either directly obtained by processing sugar cane or by coating of white sucrose crystals made out of sugar beet with sugar cane molasses. The mo lasses gives the brown sugar its distinctive colour and flavour. However, it con tains amino acids and carbohydrates, which are amorphous. These impurities are hygroscopic and can cause a caking of brown sugar particles. A strong caking might be observed already at a moisture content of 1 %. Both sugar types are offered to the consumer as cubes or different other shapes for application in coffee or tea. These shaped-sugar products are man ufactured by wetting the crystals with up to 5% water and pressing them into dies applying a low pressure. After this forming process the sugar cubes are dried to a moisture content below 1 %. White sugar is also compacted by roller compaction for decoration of bakery products and desserts. Brown sugar is hygroscopic and tends to cake during storage due to its molasses content. Thus, brown sugar is sometimes agglomerated in a mechan ically or pneumatically fluidized bed to increase the particle size. In addition, caking is reduced due to the decreasing amount of molasses present at the outer side of the granules. Prior to agglomeration, the brown sugar is milled to a particle diameter below 60 l1m and then agglomerated in a high-shear mixer or in an
664
S. Palzer
agglomeration tower. 4-5% of water is added to the sugar particles. The obtained granules are then dried to a water content below 1 %. Finally, the granules are sifted, the fines are recycled to the agglomeration step and the oversize particles are grinded in a mill or by using a roller refiner. Alternatively the milled sugar particles can be agglomerated by steam-jet agglomeration in an agglomeration tower. 4.5. Agg lomeration of breakfast cereals and manufacturing of cereal bars 4.5.1. Composition of cereal products
Cereals and cereal bars are composed out of various particles, which are ag glomerated together by applying a low pressure . Such bars are produced using cereal flakes, nuts, dried fruit pieces, chocolate flakes and various other ingre dients. In addition, cereal bars are often coated with chocolate or a milk powder/ fat mix. Extruded breakfast cereals, like corn flakes, are made for consumption after being mixed with milk. They are composed of a carbohydrate paste with various ingredients that are extruded to a defined shape. However, such an extrusion is often not considered as an agglomeration because the initial par ticles are no longer visible. An alternative process for manufacturing breakfast cereals is to granulate various ingredients like whole grains, extruded flakes, puffed rice and corn, dried fruits, chocolate pieces and nuts using a sugar-based binder. 4.5.2. Manufacturing of cereal bars
Cereal bars are made of cereal flakes, puffed corn and rice, dried fruit pieces, nuts and sometimes also chocolate flakes or pieces. These coarse particles are mixed with a sugar based binder solution. The binder solution is composed of various sugars like dextrose syrup, maltodextrine, invert sugar syrup, dextrose and fructose. The binder solution is cooked at 90-95°C. After cooking, flavours are added. The prepared binder solution is then mixed in a continuous mixer with the granular ingredients. After mixing, the sticky mass is compressed between two rollers into a layer of 0.5-3 cm thickness. This layer is then cooled down while it is passing a chilling tunnel. After chilling the layer is cut into strands, which are separated by a special transport band. These strands are cut into individual bars. In some processes the bar is cooled for up to 1 0-30 min with cold air of 1 0-20°C. Alternatively to the described continuous process forming, chilling and cutting can also be done manually. After cutting and cooling the bar is ready for coating with chocolate or a milk powder/fat based mixture. To solidify the coating a final chilling is applied prior to packaging.
Agglomeration of Dehydrated Consumer Foods
665
4.5.3. Extrusion of breakfast cereals
Since extrusion, starting with a paste and not with single particles, is not con sidered as an agglomeration process, this technology is only discussed briefly. Flour, fibres, sugar and other ingredients are mixed with water. Then this mix is exposed to increasing pressure and temperature in a cooking extruder. For this unit operation, often twin-screw extruders are used. Such extruders contain two screws which convey the product to the head of the extruder. Due to the specific geometry of the screws that changes towards the head of the extruder, the product gets compressed. The obtained plastified food mixture is then passed through holes with a defined shape. While leaving these holes, the product ex pands and solidifies. The resulting product string is cut into single particieE by a fast-moving rotating knife installed at the extruder outlet.
4.5.4. Granulation of breakfast cereals
Some granulated cereals are made by agglomeration of whole grain partides, cereals, nuts and dehydrated fruits. A sugar-based binder solution which some times also contains chocolate is sprayed on the granular solids which rotat0 in a drum or which are fluidized in a mixer with rotating tools. After agglomeratic the product is dried and cooled.
5. U NDESIRED AGGLOMERATION OF FOOD POWDERS
While manufacturing powdered food products, frequently undesired aggloP' �ra tion phenomena are observed: • • •
Caking of powder during storage Post-hardening of agglomerates (e.g. tablets) during storage Stickiness and lumping of powder during processing.
Undesired agglomeration of crystalline substances like salt or crystalline su crose can be explained with a partial dissolution of the crystalline material while exceeding the critical humidity. Liquid bridges are built due to the dissolution of the crystalline substance. These bridges solidify while they dry out (see Sections 2.4.1 and 2.4.2). Powder masses containing fat will show undesired agglomer ation if the powder temperature approach es the melting temperature of the fat (see Section 2.4.4). Undesired agglomeration of amorphous food powders like caking or stickiness is caused by sintering due to viscous flow of the plastified amorphous substance (see Section 2.4.3).
S. Palzer
666
5. 1 . Caking of amorphous food powders
Figure 67 shows SEM pictures of different caked amorphous food powders. Sev eral sinter bridges are clearly visible. Some of them are marked with white circles. Ca king is an undesired agglomeration of the powder during storage. In the initial stages the particles adhere to each other. Later they form brittle lumps and a powder cake is obtained. Finally, the particles lose their structure and shape and open pores disappear (see Section 2.4.3). Caking can be quantified by shear tests in combination with time consolidation experiments in a ring-shear tester or an annular-shear cell [50-52]. The degree of caking can be expressed by the unconfined yield strength of the powder cake [53]. Another possibility is to quan tify caking visually using a pre-defined scale. Each grade on this scale is linked to a specific appearance of the powder while emptying the storage container. One example for such a scale is given in Table 2. A caking grade of more than three is considered as a significant consolidation of the powder. The scale has been used for investigating the caking of dextrose syrup powder (DE 21 ) under different storage conditions [54]. Depending on the composition and the supra-molecular and microseopie structure of the food particles several mechanisms are responsible for the ob served caking during storage. In case of amorphous solids, sintering is the re sponsible mechanism. The kinetics of such undesired agglomeration processes should be predictable by applying equation (26). The measured unconfined yield strength obtained by storing powder under defined temperature/moisture conditions can be compared with the calculated theoretical diameter of the sinter bridge. In Fig. 68 the unconfined yield strength of a spray-dried tomate powder and hydrolysed whey permeate (vertical axis) is plotted against the diameter ratio (x/a)2 calculated according to equation (26). Obviously the unconfined yield strength increases significantly if the calculated ratio between the cross section of the sinter bridge and the particle exceeds a
dextrose syrup DE2 1
skim milk powder
tomato powder
Fig. 67. Caked dextrose syrup powder, skim milk powder and tomate powder. (SEM pic tures; sinter bridges are marked with a white circle.)
Agglomeration of Dehydrated Consumer Foods
667
Table 2. Scale for the visual assessment of caked powders
Caking grade 1 2 3 4 5 6 7 8 9
Observation Powder is free flowing Powder flowing out of the container with small clumps that dissipate easily upon slight vibrations Powder falls into fragile pieces when lifted Powder falls into pieces that can be dissipated applying low force Powder falls into pieces that can be dissipated applying moderate pressure Powder falls into pieces that can hardly be broken into larger hard pieces Powder particles stick together inseparably Powder particles form a sticky, rubbery mass. Surface is rough but flexible Powder particles form a sticky, rubbery mass. Surface is smooth and has little flexibility
value of 0. 1 5. This critical diameter ratio corresponds to the critical values pub lished by Wallack and King [20] and Aguilera et al. [16]. Although the measured yield strength values show a large variation, the theoretical area ratio (xja)2 seems to be suitable for predicting the intensity of time consolidation of amor phous particles. Furthermore, dextrose syrup powder (DE2 1 ) was stored at three different temperaturejmoisture combinations (30°Cj70% RH; 20°Cj65% RH; 20°Cj50% RH), which correspond to tropical, Mediterranean and Middle European climate conditions. After pre-defined time intervals the cups containing a thin powder layer were emptied and the state of the powder was judged using the scale given in Table 2. In Fig. 69 the experimental results are compared with the values obtained by calculating the diameter of the sinter bridge (expressed as the ratio (xja) 2). Owing to the ongoing water absorption during storage, the value for the glass transition temperature changes permanently. Thus, the ratio (xja)2 was obtained by numeric integration according to equation (26). Storing the dextrose syrup powder at 30°C and 70% RH, the powder starts to cake after 1 0 h (caking grade > 4). Simultaneously, the theoretical sinter bridge diameter increases dramatically. For the other two storage conditions only a minimal increase in the calculated sinter bridge diameter and the caking grade is obtained. Thus, again the kinetic of caking seems to be predictable by calculating the sinter bridge diameter applying equation (26). Consequently sintering seems to be indeed the process responsible for increasing the adhesion forces between
668
S. Palzer 50000 �------� 45000 40000
ct! c...
ß
- 35000 •
g>
30000
"0
25000
.c
� 1ii
äi '>, "0 Q) c
'E 8c
•
•
20000
,------,
• spraydried
•
1 5000
::s
1 0000
...
5000
#
.
.
:
". .
tomato powder
... dextrose syrup DE21
•
•
hydrolysed whey permeate [Teunou & Fitzp. 1 999]
O __��--�----._--,_--�--_,--_,._--,_--�--_i
0.0
0.1
0.2
0.3
0.4
0.5
0.6
calculated ratio (xla)2 / -
0.7
0.8
0.9
1 .0
Fig. 68. Measured unconfined yield strength of tomato powder, dextrose syrup DE21 and whey permeate versus calculated area ratio (x/af obtained by applying equation (26).
amorphous particles. A value for (xja)2 larger than 0.01-0 . 1 indicates the risk of caking. 5.2. Post-hardening of agglomerates
Offen the hardness of agglomerates containing amorphous components in creases significantly during storage. Thus, theoretically, equation (26) should also enable to predict the kinetics of such post-hardening. The post-hardening of rectangular dextrose syrup tablets has been investigated by Palzer [54]. Rec tangular tablets composed of 1 5% dextrose syrup powder (DE2 1 ) and 85% so dium chloride were manufactured adding 1 .7 and 2.3% water during mixing of the powder mass prior to tabletting. The tablets were packed in sealed plastic pouches and stored at 23°C. The crushing force while compressing the tablet between two flat pistons (see Fig. 46) was measured depending on the storage time and the moisture content of the tablets. Furthermore, the area ratio (xja)2 was calculated using equation (26) for each storage time and each sampie while considering any changes in the produci's moisture content during the storage time. Figure 70 shows the development of the crushing force and the calculated
669
Agglomeration of Dehydrated Consumer Foods
9 .-------�HH--�--��- 1 .0 30 °C/70% RH 0.9 8 0.8 --+-- measured caking index (20 QC/65% RH) 7 measured caking index (20 °C/SO% RH) 0.7 -Cl) '0
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0) 0) c
� CIl 0
--+-- measured caking index (30 °cnO% RH)
6
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• •0,- • calcula'ed (x/a)"2 20 'C/65%RH
;
4
..
. . . - . -. - - . • .
"0-
0.5
.. calculated (x/aY'2 30 °cnO% RH
caking ensel . - - - - . - - - - - - - - - - - - - - - - - - - - -
••••-
�
'0
-------------
3
0.4
.sl co "5
0.3
CO
..., ...= :
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679
Detergent Granulation
Some properties have multiple relevancies; for example, the bulk density of a product is an important conversion factor for use in carton packaging machines, which typically are not weight but volume controlled, whereas the packs are sold on weight. At the same time, bulk density has an important impact on the per ceived quality of a product; high density is typically associated with premium quality. Table 3 lists properties, measurements and indications of their relevance, as will be discussed in following sections. 3.1 . I n-use properties
Handwash consumers, still 75-80% of the global market, demand rapid dis solution of the product, typically within 0.5-1 .5 min. Also in markets with high automatie washing machine penetration, robust dissolution behaviour of deter gents is growing increasingly important as environmental awareness and regu lation drive washing temperatures and water consumption down. Especially relevant for users of front-Ioader automatie machines is the dispensing behaviour, which is a complex interaction between the kinetics of dissolution and hydrody namics of the dispenser drawer, as shown in Fig. 1 . In most dispensers, water between 1 0De and ambient temperature emerges in the form of narrow streams of liquid onto the powder and along the edges of the dispenser drawer. Some water, drawn in by the action of capillary forces, penetrates into the loose powder bed and displaces the air within. The rest flows either over or around the powder in streams and into the drum of the washing machine (Fig. 1 ). Several processes then occur simultaneously: granule dissolutionjdisintegra tion , surfactant swelling, viscous phase formation and dissolution, electrolyte hydration and dissolution, granule agglomeration on account of the greater "sticking potential" conferred by partial granule dissolution and the convective transport of granules. If all of the above proceed as desired (to be defined), the powder is dispersed and dispensed into the drum within 30-60 s. Powders that dispense quickly, i.e. in 1 5-20 s or less, dispense in spurts during which (re latively) dry portions of the powder bed break away, are lifted up by water and dispensed. If the powder does not dispense as desired, dispenser residues result. Dispenser residues are chiefly of two types. The first is a soggy, often slimy, paste of partially dissolved granules, surfactant and water. The second is a hard lump, progressively less wet from the outside to the inside of the lump (but dry compared with the first type) in which the individual granules do not appear to have dissolved much. Figure 1 also shows the forces acting on particles inside the powder bed and on the surface. The greatest force acting in the dispenser is that of buoyancy: on the powder bed with air trapped in it as a whole or on each particle. However, it acts only when water has penetrated the powder bed. The impact of the water jet on the powder bed and its subsequent transmission into �
Table 3. Powder properties and their relevance, mostly from Ref. [1], apparatus drawings also to be found there
Range Property
AbbreviationjUnit Lo
Hi
Brief explanation
Depends strongly on
Relevance
Formulation, process (densification), internal porosity, partieIe size distribution Bulk density, fines level, attrition
Brand image, dispensing, packaging and transport consumption
Process, formulation (LjS)
Solubility, dispensing, dustiness, f10wability
Process, formulation (LjS)
As RRd
Process, formulation (LjS) Process, formulation (LjS) Process, formulation (LjS), shape
As RRd As RRd Dispensing, pneumatic conveying, dustiness [14,65]
Bulk density, partieIe size
Rate of dissolution, especially hand wash
PartieIe size distribution (fines level), formulation (salts, surfactants), granule structure Porosity, non-solidified ingredients, e.g. non-ionic surfactants Process temperatures, residence time, source quality and age Surfactant level, fines level, shape
Front loader drawer residues
Bulk density
BDjkg m�3
300
900
Fill a calibrated volume without tapping, measure weight
Dynamic flow rate
DFRjmL S�1
80
NA
Particle size
RRdj�m
500
710
Particle size distribution width Fines level Coarse level Spouted-bed test
RRnj-
2
4
Flow from a standpipe through a conical orifice Measure particle size distribution, calculate RosinRammler distribution parameters As RRd
< 1 80 �mj%wt > 1 400 �mj%wt SBTj%wt
0 0 0
10 10 15
Solubility
190js
0
90
Dispensing
Dispenser testj%wt
0
5
Bleeding
Ongj%wt
0
5
Colour
L,a,b
NA
NA
Caking propensity (unconfined compression test) Compression
UCTjkg Cj%vol
Measure weight increase of filter paper over time Measure colour space co-ordinates Measure strength of a pre-compacted cake
NA NA
Sieve at 1 8 0 �m Sieve at 1400 �m Fluidise powder with a jet, measure fines generation Measure conductivity of metered dose in water Operate dispenser, measure residues
25
Compress a powder in a standpipe, measure volume reduction
Surfactant level
Ol co 0
Flow in transport (silos) and packaging
Cohesivity of non-ionic containing products Product quality Storage
;:0
OJ 0 CD ...,
CD
...: :
Storage, especially in bags, solubility
� � :J
681
Detergent Granulation STRt:AM FROM A JET DIREcru AI:IOVE
DEF/J'.crEO STRt:AM
57'Rt:AM OF \VATER FROM ANOTII ER JET
Buoyancy or Drag Force
Forces on an internal granule
Forces on a surface or near-Ihe-surface granule
Fig. 1 . Schematic of water flow in and around the powder bed in a dispenser.
the bed is not shown. Interparticle forces are also not shown. EP0451 894 [6] gives an example of a well-dispensing detergent. Dispensing behaviour may be measured by mimicking the dispensing process itself and measuring the remaining residue after a given time of dispensing from a standardised commercial dispenser. The chief parameters are geometry of the dispenser, flow rate and temperature of the dispensing water and dispens ing time. 3.2. Detergent powder handl i ng
Granules require special care in handling, and as the technology grew more or less organically from post-tower operations, which include spray-drying as an early unit operation, to separate systems, the layout of granulation plants is often determined by existing systems and buildings. Through various handling steps, such as belt conveying, belt-belt and belt-hopper-belt transfer, screw feeding, etc., size reductions of up to 30% may occur. Hoppers are often emptied by belts running underneath at speeds up to 1 m S - 1 , and normal loads may be consid erable. Granules may experience tens of impacts at up to 1 0 m S - 1 , shear at normal loads in excess of 30 kPa, rates above 1 00 Hz and compression at loads
682
R. Boerefijn et a/.
# Locmion
of (he
I
Exil
2
Sieve unil
3 Tcm
ranulation
rar base
rocess
wder slOmge
4 Admix eo l leelor belt 5 Drum mixer and sieve unit
6 Mass tlow hopper. feedi ng packing unilS
Fig. 2. Typical post-process handling plant layout (bars indicate transfer belts).
above 50 kPa. Screw feeding and pneumatic conveying [14] may result in size reductions of up to 25%, each accompanied by large amounts of fines generated. This is why often bucket elevators are preferred for vertical transport. Figure 2 depicts a typical handling system, starting from the exit of the base powder production process, passing through a bucket elevator and a sieve unit via transfer belts to storage hoppers and finally through a loss-in-weight feeder onto an admix collector bell. Then the powder may be transferred via a second bucket elevator into a drum mixer that includes a perfume spray, through a final quality sieve (admix components are commonly not sieved before mixing) and then into a mass-flow hopper feeding storage bins or packing units. 3.3. Stability
Typically, highly soluble materials such as detergent powders also exhibit hygroscopicity, and "powdering" or dry-Iayering (e.g. with zeolite) is common practice to prevent caking. Layering may take place at any stage after the for mation of initial granules. A tight control over the zeolite dosage is required to prevent dustiness and lack of flowability while preserving ca king protection. 4. GRANU LATION TECHNOLOGIES
Extensive layout diagrams and specific operating parameters for most of the processes described below may be found in Ref. [1].
683
Detergent Granulation
4. 1 . Base powder
We recall that base powder commonly contains surfactant and builder, and consti tutes 30-90% wt of the total product. It is commonly made via the routes indicated in Table 1 . As surfactant often forms a soft or waxy solid phase within the granules, granule strength has to be obtained by an efficient construction of a solid network throughout the granule. This requires micromixing of liquids and solids, and is commonly performed in high-shear mixers. Perhaps counter-intuitively, while mix ing is on-going, granule growth has to be delayed as much as possible in order to maximise the liquid load [1 5]. As it arose out of post-tower densification, after elimination of the spray-dried powder, the granulation process used in the detergent industry is commonly termed the "non-tower process". Typical layouts are as shown in Fig. 3, and comprise a high-shear mixer, followed by another moderate to high shear mixer and then usually followed by a conditioning step (cooling, drying), e.g. in a flu idised bed. For non-tower granulation [1 6-1 8], equipment of choice commonly comprises a Lödige Recycler (eB-type) and Ploughshare (KM-type). Appel [1 9] lists a number of equipment manufacturers commonly found in the industry. In the process depicted in Fig. 3, the anionic feed can be partly or fully neu tralised. The second stage (ploughshare) serves mainly for densification, and distribution of the layering agent. It can also be replaced by a recycler unit. Liquids can be pumped or sprayed in. Typical residence times in the recycler are of the order of tens of seconds, whereas in the ploughshare it may be above 1 min. Residence time in the fluidised bed may amount to 30 min. For plant Salids
• •
zeolite
satts
Liquids
• •
nonionics anionics
�
�
\9:! e:;'�:1> .......
l�
,-------, fluidbed
hol air
hOl air
Fig. 3. Typical layout of a non-tower detergent granulation process.
cool air
684
R Boerefijn et al.
flexibility and better control of product quality, in the early days of non tower granulation, spray-dried base powders were used as carrier materials. Nowadays, admixtures of non-tower and spray-dried base powders may be used to achieve the same. Conversion kinetics of the surfactant precursor neutralisa tion depend largely on surface renewal, which occurs in the first mixer at high tip speeds, generating a crumbly dough of up to 20 vol% porosity. In the second mixer, this dough-like material is densified and spheronised and the resulting granules have at most 1 0 vol% porosity. Throughputs of several tens of tons per hour are common. Only recently have satisfactory scaling rules for high-shear granulation of LAS granules been published [20]: tip speed and apparent viscosity, which may be grouped in the typical Ennis and Tardos' critical Stokes number to constitute the balance between break-up and sticking force [21 ] as weil as the volumetric liquid to-solid ratio are indicated to be the essential parameters. This analysis has a limited scope to systems employing highly viscous binders and fine carrier solids, as is the case with LAS and zeolites. It clearly shows how closely the process passes by the wet-mass region in the Utster map of deformation vs. saturation [22] at which the entire hold-up turns into a single paste. If spray nozzles are fitted in the fluidised bed depicted in Fig. 3, a fluidised-bed granulation system arises. This may be used to advantage to obtain a better control over the particle size distribution and the bulk density in the intermediate range between spray-drying and non-tower granulation [23, 24]. A typical layout of this system is shown in Fig. 4. The surface area of the f1uidised bed is typically 1 0-40 m 2 and residence times of the order of tens of minutes are common. Equipment of choice includes those supplied by Ventilex and Niro. The fluidised bed is commonly operated in plug flow mode by suitable choice of distributor plate (gill orientation). The premixer before the fluidised bed can be run either in batch or continuous mode. Throughputs can be as above or much lower, e.g. several tons per hour in the semi-batch mode. Two-phase nozzles are typically used here.
Fig. 4. Typical layout of a fluidised-bed granulation process.
685
Detergent Granulation
Fluidised-bed granulation is a self-limiting growth process. The operating airflow yields a superficial gas velocity in the fluidised bed, which corresponds to the minimum fluidisation velocity to be calculated using the Ergun equation [25] of the largest granules; those larger will settle and be unavailable for futher growth. At the same time, the elutriation or terminal velocity sets the limit on the smallest particles or granules; any smaller will be blown out. The elutriation velocity can be calculated using drag correlations [26]. The premixer, commonly a Lödige recycler or ploughshare, is used to extend the particle size range to smaller, normally not fluidisable particle sizes, owing to elutriation and/or co hesivity, which exhibit high liquid carrying capacity. Extensive research has resulted in the quantification of the dominant controls for stable operation of fluidised-bed granulation to prevent wet-quenching [27], and to prevent granulation in the case of a coating process [28], as depicted in Fig. 5. The flux or Akkermans number expresses the balance of the binder spray flux and the solids recirculation rate through the spray-zone. ,
(1) 0.9 -+-- Ob (FN
2) kg/hr ----.- Ob (FN 3.5) kg/hr
0.8 I..
=
=
0.7
� N
E 0.6
� CI >< :I
0.5
Li: >«I
... c.. CI) ... CI) '0 s::::
0.4 0.3
äl 0.2
0.1
� -- � - - -
o
0.2
-----1
0.4
Superficial Gas Velocity (m S·1) Fig.
5.
Typical granulation regime map for f1uidised-bed operation.
1 .2
686
R. Boerefijn et al.
The Akkermans number is also a useful tool for scale-up of fluidised-bed gran ulation systems [29]. Furthermore, the unique relation between the Akkermans number and the growth rate constant used in population balance modelling allows a priori determination of the growth rate constant [30]. Adequate description of granulation kinetics, in addition to reliable sensor technology, is the main chal lenge for online control [31 , 32], which can be in part alleviated with this approach. Fluidised-bed granulation is an intrinsically robust process with moderate shear, which allows for more controlled structure formation of granules. If the binder solidification can be boosted by chemical reaction and a fine crystal dis persion within it, strong and porous granules may arise as shown in Fig. 6, which allow a granule to break away from surface Iimited, slow shrinking core disso lution behaviour [33]. This is described further in Section 6.2. Figure 4 depicts the high-shear mixer, used to pregranulate a portion of the binder with the fine solid carrier to extend the carrying capacity, as a separate entity. The Schugi Flexomix is an example of a fluidised bed with integrated high shear impeller, as can be used to produce detergent base powders [34]. Some less common process routes for base powder production exist as weil: the Unilever VRV process [35-37], which employs a flash-drier with a thick rotor shaft and short bl ades with small wall clearance to produce granules containing weil in excess of 50 wt% anionic SUrfactant (Fig. 7) and • the Henkel Megaperls extrusion process, which employs a cooled twin screw extruder to mould a mixture of spray-dried base powder and other liquids and solids into highly spherical and uniform particles [3, 38, 39].
•
Particle Size (arb. units)
Fig. 6. Schematic influence of granule mesostructure on granule dissolution time.
687
Detergent Granulation air
PRODUCT
Fig. 7. Layout of the VRV process capable of manufacturing high surfactant-containing granules.
4.2. Adjuncts
Adjuncts are commonly defined as granules containing high levels of minor in gredients, which may individually be added at levels between 0.2 and 20 wt%. Notable examples are enzymes, anti-redeposition polymers and bleach. In order to maintain good control over the bulk density of the final mixture, a simple mixing rule may be employed if the granule size distributions of the individual compo nents are reasonably similar (which in the absence of cohesion is a prerequisite to avoid segregation):
B� . = L BX�. mix
n
I
with
L Xi = 1
(2)
n
It appears that the non-tower process in its essentials, Le. a high-shear mixer and a fluidised bed, is the new standard not only for base powders, but also for adjuncts, such as • • • • •
TAED bleach precursor [40], which is often provided with an acid coating for stability; silicone antifoam [41 ] , which is processed anhydrously with a starch carrier; builder granules [42], which are typically bound with a surfactant or polymer; perfume granules [43], which are typically encapsulated; and enzyme granulation [44, 45], which may contain cellulosic fibres or film-forming polymers for increased resilience and solubility [46, 47].
5. GRANU LES FOR TABLETTING
Designing granules consisting of a mixture of materials with a complex mechan ical response, including elasto-viscoplastic, for incorporation of tablets of a few centimetres in size is weil beyond the scope of most of the available literature,
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which typically addresses small pharmaceutical pills made of virtually pure, highly elastic substances [48] , with exception of the work of Adams and co-workers [49, 50]. Existing techniques for quantification of compaction behaviour are still useful, as summarised by Celik [5 1 ]. Providing a unit dose for laundry applications requires compacting between 30 and 1 00 9 of powder into 1 or 2 tablets, resulting in a considerable size tablet, typically 2 cm in height and �4 cm in diameter, which affects both solubility and strength. Functionality of the tablet relies on a suitable trade-off between the two. Commonly a brick-and-mortar system is employed, with the mortar providing for the integrity and bricks for rapid dissolution. Henkel and P&G rely mainly on swelling cellulosic polymers respectively inside and around the tablets [52-54], Unilever to some extent on phosphates [55]. Tablet strength is commonly ex pressed as diametral fracture strength (DFS), a so-ca lied "Brazilian test" for tablets. Tablets of powder mixtures depend in a complex way on the constituent properties, as quantified by Van Veen [56]. DFS may be related to a composite yield strength (CYS) as folIows: CYS = a - b DFS (3) where 1 ""' Xi (4) CYS - � 'O , i �
with L: Xi = 1 and 'O, i the Kawakita yield strength as determined by bulk comn pression of single component beds [57]: bed compression tests using a mould of similar diameter to the rotary press and plotting stress P vs. strain 8 allows for the determination of '0 from In P = cx 8 + In
(�)
(5)
Repeating this measurement at different starting bed heights, plotting '0 as a function of initial bed height and extrapolation to the abscissa yields 'O,i' Param eter a is proportional to the maximum compaction force and b to the compaction speed. Knowing the formulation and the target DFS for a tablet and 'O, i of the remaining components, the target 'O, i of a new granule to be incorporated may now be specified. Evidently, design rules of a granule for a specified strength are next in order as part of granule structure formation. 6. STRUCTURE OF DETERGENT POWDE RS
A detergent granule consists of three major components: the primary particles (solid), the detergent (liquid or soft solid) and porosity (gas). The amount, size
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Detergent Granulation Table 4. Relation between basic powder properties and structure
Property Bulk density Attrition Compressibility Bleeding Solubility Dispensing
Relation to structure Intra- and infra-granular porosity Shape (asperities) Phase volume ratios Liquid retention in micro-/mesopore structure Shrinking core vs. disintegration, viscous phase formation (can be suppressed by ionic strength or hydrotropes), water ingress Drag and buoyancy (size, density) vs. phase formation and dissolution
and distribution of these three phases determine the granule structure. The granule structure is generated by the process route and conditions and is a free handle to optimise product properties (Table 4), within the limitations imposed by the formulation. The term "structure" is widely used but not weil defined and therefore needs further specification for technical use. The structure of a system is related to the manner in which the system is internally built up from its basic components. As agglomerates are multiple component systems, the structure of granules or ag glomerates will be defined as "the spatial arrangement of its basic components" [58]. Typically, a structure definition is combined with length scale information such as macro-, meso- and microstructure. In the case of particulate systems, this would be the powder bed structure, the granule structure and the structure of the basic components itself, e.g. crystal structure of primary particles. The quantification of structure has several aspects as depicted in Fig. 8: the amounts of various components, their sizes and the manner of their assembly. In particulate systems, the amounts of the basic building blocks are the most im portant variables that define the internal spatial arrangement (or granule struc ture). The granule porosity is of special importance because it is not predetermined by the formulation, but a parameter affected if not controlled by the formation process. At the next level of detail, the size of the spatial phases formed is of interest. And last but not least, the distribution of the phases through the system defines the homogeneity of the structure and its composite behaviour. All these measures just quantify the structure of an isotropic system. The granule shape or its outer morphology, as weil as radial gradients, is not taken into account here. Therefore, one would additionally use shape descriptors, which are weil known [61 ] , and radial distribution functions, which give the radial depend ence of the concentrations of the various phases.
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Type/Scale Macro
Powder bed I Tablet
Meso G ranule
Amount BD / Bed porosity
Size Particle Size Distribution
Distribution Pore size: tablet I powder bed
Phase volume I Particle
Chord length / Covariance
Covariance function / distance distribution I
porosity
function
radial distribution
function
Micro
Formulation
Raw Materials / molecular level
Raw material characteristics (e.g. PSD solid)
Spacings, crystal types
181 °1 o
0
Fig. 8. Definition and overview of granule structure parameters [59, 60].
6.1 . Phases in a detergent g ranule
A detergent base granule is chemically composed of inorganic salts, surfactants and some water. The behaviours of these groups of components are distinctly different and do not necessarily mix. The salts are typically solids, the surfactants are liquid-like or soff solids. A detergent granule therefore has at least two well-defined separate phases: a solid phase and a liquid phase. The liquid phase, typically consisting of surfactants and water, binds the solids during the granulation process; thus it is offen termed the "binder phase". Besides these two distinct phases, entrapped air or porosity forms the third phase in a detergent granule. Phase volumes have the largest impact on the granule properties. This is, for example, the well-known effects of the granule porosity on dissolution and bulk density, or that of the liquid-to-solid ratio (L/S) and granulation index on the granulation process [20]. The granulation index is defined as the ratio of L/S and the LCC of the solids. In granulation science, this has been captured in the so called capillary state of the granule. The different types of granule structures are schematically depicted in Fig. 9 and can be described as (a) solids that are just bound together by some binder (pendular state); (b) well-bound solids with interconnected porosity (funicular state);
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Detergent Granulation
Fig. 9. Granules i n varying capiliary state as defined by Rumpf [62]: (a) pendular state, (b) funicular state, (c) capiliary state and (d) droplet state.
a) Dense granule
b ) Porous granule
c) Aggl omerate
d) High porosity
Fig. 1 0 . Different types of detergent granules containing surfactant [58, 60]: (a) dense granule, (b) porous granule, (c) agglomerate and (d) high porosity.
(c) liquid-filled solid assembly bound by capillary forces at the boundary (capillary state) and (d) a droplet with some solids inclusions and no porosity (droplet state). All these types can be found in detergent granules. Figure 1 0 depicts generalised structures as described above. Examples of cross-sections of detergent granules are shown below the four schematic struc tures in the figure. The dense system depicted in Fig. 1 0(a) is typical for a high shear mixer granulation process, e.g. European non-tower detergent powder (Section 4.1). Almost no porosity is found and the coarse solids are not densely packed. Figure 1 0(b) shows a sodium LAS adjunct manufactured via dry neu tralisation and containing a lot of porosity generated by carbon dioxide released during the neutralisation process. Figure 1 0(c) shows an agglomerate of prima ries. The primaries may either be pre-granulated material or relatively coarse raw material solids. Here the porosity has become the predominantly continuous phase rather than the solids or the binder phase. Binding of the primaries is the main issue in this type of structure. The given example is a granule bound by a
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melting-type binder and produced in a fluidised bed [63]. The last type of granule structure depicted (Fig. 1 0(d)) is one where the porosity is entrapped by a shell formed by bridging particles, rather than porosity being an interstitial space be tween attached primary particles. This requires some "blowing action" as often found in non-disperse systems such as polymer foams, or products manufactured by the reactive foaming process such as bakery products produced using sodium or ammonium bicarbonate, or eitric aeid [1 1 , 34, 64]. Here binding between pri maries is crucial to retain the high amount of porosity and still form a mechanically strong granule. The low bulk density of the fluidised-bed granule based on sodium sulphate generated in situ is an example of such a granule that shows a high amount of porosity and rapid dissolution [33]. Looking at the variety of granulation processes on offer, it is clear that the granule structure can be va ried even further. Figure 1 0 also schematically depicts the variation in porosity in granules produced via different processes. The properties of a granule are a direct consequence of the granule structure and the characteristic of the used raw materials. Hence an optimisation process of granule properties needs a systematic approach based on an understanding of granule structure formation. 6.2. Granule design 6. 2. 1. Maximising liquid content
Design of a granulated powder typically starts with a formulation. This formulation determines the mass fraction of the powder ingredients. The so-ca lied process aids may be used if cost and formulation space and regulations permit. One would run through the following steps and decision points when faced with the task of designing a manufacturing process. The amounts of liquid and solid components are given when a formulation is specified. The volume fraction of each component can be calculated using the densities of the components. The volumes of the liquid and solid phases then follow by summing the volumes of all liquid component and solid components, respectively. The next question to be answered is "How to create a dry granular structure with the given amount of solid particles to accommodate the required amount of liquids?" Being the first dimension of the structure space, the amount axis is fixed; the other two dimensions are the free parameters. This means that the size and distribution of the phases need to be adjusted to design the granule. The most natural way to create a dry liquid-solid system is that of a liquid-filled particle packing wherein the solids are densely packed and touch each other to form a disperse but percolating solid network - a skeleton. The free room be tween the solid particles can then be filled with liquid without changing the spatial
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Fig. 1 1 . An example of a brick-and-mortar structure.
Fig. 1 2 . Sequential packing of primary structures.
arrangement of the solids. Such a structure would appear solid-like because the mechanical properties are governed by the percolating solid network. We call this a brick-and-mortar system (Fig. 1 1 ). The phase volumes here are determined by the packing behaviour of the solids, which can be roughly predicted by particie packing theory, e.g. using the Kerner equation. Filling the porosity of the packing only partially enables higher liquid contents. This has its limit in the binding capacity of the liquid, at least when the liquid is the binding material. Higher amounts of liquid can be realised by distributing the solids and liquids in a designed way. The brick-and-mortar system shown in Fig. 1 1 is a random homogeneous distribution of the solids and liquid. A se quential packing of granules from the first process that results in brick-and-mortar primaries is a straightforward route to obtain a structure with a higher liquid content or higher liquid-to-solid ratio (Fig. 1 2). 6. 2. 2. Retaining porosity
The air content or porosity can be approached in a manner similar to that de scribed for the liquid content. However, the desired level of porosity (C:gra nule) is not a specified formulation component, but is determined by the desired physical
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rel. porosity -, 90% change 80% -+-- 5% 70% ___ 1 0 % 60% 20 % 50% 30 % 40% -lI .....J z
o
z
eZ
•
* •
+ * + fJf •
8Z 9 · .. ..+ .. ·
+
----l
_ _ _ _ _ _
(Y)
es)
In � 0')
es) csi csi
in ....:
1f) tn U")
N rri ";
CI)
N (D CS) - -N
normalized granule diameter
Fig. 1 4. Cumulative particle-size distribution of the agglomerates at a fixed normalized amount TC ( = 0.62) of granulating liquid for different ratios of the binary powder mixture consisting of lactose (L) and cornstarch (MS).
on percolation theory (Fig. 1 4), i.e., that the properties differ for compositions below or above a critical ratio Pe of components between lactose and cornstarch. This result can have a tremendous effect if, e.g., the particle-size distribution of the starting material changes and influences the exact percolation threshold Pe [57-59]. Thus, if the formulation is close to Pe concerning the ratio of the ex cipients lactose to cornstarch the resulting granule size distribution can exhibit a linear or an S-type shape (see Fig. 1 4) corresponding to a processing below or above Pe. In order to develop robust formulations it is important that the formu lation does not contain critical ratios or percolation thresholds [49-53,56], i.e., that the theory of percolation is taken into account. 5.3. The agglomeration process in the light of F DA's PAT initiative
Pharmaceutical formulations are complex systems and even nowadays are often developed empirically under a high time pressure on the basis of "trial-and-error" experiments. This procedure can easily lead to a non-robust formulation. Fur thermore, many pharmaceutical processes are poorly understood. Thus, the predictability of the manufacturing performance is low or even non-existent. The goal of FDA's PAT initiative is to achieve scientifically based decisions, i .e., to design the quality of the product and to "test-in" the quality by eliminating the bad items at the end of the production creating waste of time and money. The best solutions could be obtained if mechanistic models or even first principles in the
731
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GMPfCMC FOCUS
Process Design
Yes, Umited to the Experimental Design Space
Design quallflcatlon
MECHANISTIC U N DERSTANDING
Focused; Critical Process Control Points (PA T)
Maybe, Difficult to Assess
Fig. 1 5 . Knowledge pyramid (courtesy: Dr. A Hussain, FDA).
knowledge pyramid (see Fig. 1 5) are known. The manufacturing process of granules or granulation process is still poorly understood especially in cases where the necessary boundary conditions for an optimal granulation process are not fulfilled [63]. The power consumption method presented in this chapter rep resents an in-line process control method where a reference point is calculated at early stage. Thus, taking into account the properties of the starting material and furthermore the possibility of a predefined quality of the granules. REFERENCES [1] [2] [3] [4] [5] [6] [7] [8] [9] [1 0] [1 1] [ 1 2]
D . M . Newitt, J . M . Conway-Jones, Trans. Inst. Chem. Eng. 36 ( 1 958) 422-442. H . Rumpf, Chem. Ing. Tech. 30 (1 958) 1 44-1 58. B.J. Ennis, G.J. Tardos, R. Pfeffer, Powder Techno!. 65 ( 1 99 1 ) 257-272. H . Leuenberger, Pharm. Acta Helv. 57/3 ( 1 982) 72-82. H. Schubert, Chem. Ing. Tech. 45 (1 973) 396-401 . H . Leuenberger, Pharmacy World Congress '93, Tokyo, Proc. 53rd Int. Cong. Pharmaceut. Sci. 1 993, D.J.S. Crommelin, K.K. Midha, T. Nagai (Eds.), Medpharm Scientific Publishers, Stuttgart, 1 994, pp. 493-5 1 1 . K.V.S. Sastry, D.W. Fuerstenau, Powder Techno!. 7 (1 973) 97-1 05. S.M. Iveson, J . D . Litster, K. Hapgood, B.J. Ennis, Powder Techno!. 1 1 7 (2001 ) 3-39. CA Biggs, C. Sanders, AC. Scott, AW. Willemse, AC. Hoffmann, T. Instone, M. J . Hounslow, 7th Int. Symp. Agglomerat. , Albi, France, May 29-31 , 200 1 , Preprints, Vo!. 1 , pp. 307-3 1 6 . S. Heinrich, M. Peglow, M. Ihlow, L . Morl, 7th Int. Symp. Agglomerat. , Albi, France, May 29-3 1 , 200 1 , Preprints, Vo!. 1 , pp. 295-305. AA. Adetayo, J.D. Litster, S.E. Pratsinis, B.J. Ennis, Powder Techno!. 82 ( 1 995) 37-49. J . M . Newton, S. BouteII , J. Chatchawalsaisin, 7th Int. Symp. Agglomerat. , Albi, France, May 29-3 1 , 200 1 , Preprints, Vo!. 1 , pp. 337-342.
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[1 3] W. Pietsch, Wiley, Chichester, England, Otto Salle Verlag, Frankfurt/Main, Germany and Verlag Sauerländer Aarau, Switzerland, 1 99 1 . [14] W. Pietsch, Wiley-VCH , Weinheim, Germany, 200 1 . [1 5] M. Ziokarnik, Dimensional analysis, scale-up, i n : M . C. Flickinger, W . St. Drew (eds), Encyclopedia of Bioprocess Technology: Fermentation, Biocatalysis and Biosepaeration. [ 1 6] Dimensionless Groups, Handbook of Chemistry and Physics, 67th edition, 1 986-1987, pp. F307-324. [ 1 7] Pharmaceutical Manufacturers' Association 1 1 5 1 54th Street, N. W. Washington DC, 20005. Remington's Pharmaceutical Sciences, 1 5th edition Mack Publ. Co. , Easton PA, 1 975, p. 1 429. [ 1 8] RW. Johnstone, M W. Thring, Pilot Plants, McGraw-Hill, New York, 1 957, p. 1 2 . [ 1 9] H . Leuenberger, Bitte Hans fragen oder in der Bibliothek, Seminarraum nachschauen. Wir haben das Buch in IPL nicht. in: H. Sucker, P. Fuchs, P. Speiser (Eds.), Pharm. Technologie, G. Thieme Verlag, Stuttgart, 1 978, pp. 80-92. [20] H. Leuenberger, Acta Pharm. Technol. 29/4 ( 1 983) 274-280. [2 1 ] H. Leuenberger, Powder Technology and Pharmaceutical Processes, in: D. Chulia, M . Deleuil, Y. Pourcelot (Eds.), Handbook of Powder Technology, Vol. 9, Elsevier, Amsterdam, 1 994, pp. 377-389. [22] H. Leuenberger, Proc. 2nd World Congress Particle Technol ., Sept. 1 9-22, 1 990, Kyoto, Japan, Vol. 1 1 1 , pp. 3 1 7-328, Society of Powder Technology, Japan. [23] M. Dürrenberger, J . Werani, Proc. 4th I nt. Symp. Agglomerat. , Toronto, June 2-5, 1 985, C . E. Capes (Ed.), lron and Steel Society I nc., pp. 489-496. [24] H. Stauffer, I ntroduction to Percolation Theory, Taylor and Francis, London, 1 985. [25] H. Leuenberger, B. Luy, J . Studer, S.T.P. Pharma Sci 6 ( 1 990) 303-309. [26] J. Kristensen, T. Schaefer, P. Kleinebudde, Pharm Dev. Technol. 5 (2000) 247-256. [27] J. Kristensen, T. Schaefer, P. Kleinebudde, AAPS Pharmsci. 2/3 (2000) article 24. [28] P. Holm, T. Schaefer, H . G . Kristensen, Powder Technol. 43 (1 985) 21 3-223. [29] H.G. Kristensen, T. Schaefer, Drug Dev. Ind. Pharm. 13 ( 1 987) 803-872. [30] H.G. Kristensen, Powder Techn . 88 ( 1 996) 1 97-202. [31 ] M. Landin, P. York, M.C. Cliff, RC. Rowe, Pharm. Dev. Technol. 4 ( 1 999) 1 45-1 50. [32] A Faure, I.M. Grimsey, RC. Rowe, P. York, M.C. Cliff, Eur. J. Pharm. Sci. 8 (1 999) 85-93. [33] G.J.B. Horsthuis, J A H . Van Laarhoven, RC.B.M. von Rooij , H. Vromans, Int. J. Pharm. 92 ( 1 993) 1 43-1 50. [34] K. Terashita, S. Watano, K. Miyanami, Chem. Pharm. Bull. 38 ( 1 990) 31 20-3 1 23. [35] A Ohike, K. Ashihara, and R Ibuki, Chem. Pharm. Bull. 47 ( 1 999) 1 734-1 739. [36] H. Leuenberger, H . P. Bier, H. Sucker, Pharm. Tech. I nt. 3 (1 979) 6 1 -68. [37] H.P. Bier, H. Leuenberger, H. Sucker, Pharm. Ind. 41 ( 1 979) 375-380. [38] N.-O. Lindberg, L. Leander, L. Wenngren, H. Helgesen, R Reenstierna, Acta Pharm. Suec. 1 1 ( 1 974) 603. [39] D.N. Travers, AG. Rogerson, T. M . Jones, J. Pharm. Pharmacol. 27 (1 975) Suppl. 3P. [40] G. Betz, P. Junker Bürgin, H. Leuenberger, Int. J. Pharm. 252 (2003) 1 1 -25. [4 1 ] P. Junker, Ph.D. Thesis, Basel University, Switzerland, 1 998. [42] H . Leuenberger, A M unoz-Ruiz (Eds.), Date Acquisation and Measurement Tech niques, I nterpharm Press, Buffalo Grove, 1 998, pp. 1 4 1 -1 57. [43] A Johansen, T. Schaefer, H.G. Kristensen, I nt. J. Pharm. 1 83 ( 1 999) 1 55-164. [44] H. Rumpf, Grundlagen und Methoden des Granulierens. Chem. Ing. Tech. 30 ( 1 958) 1 44-1 58. [45] W. Pietsch, H. Rumpf, Chem. Ing. Tech. 39 ( 1 967) 885-893. [46] H. Schubert, Untersuchungen zur Ermittlung von Kapillardruck und Zugfestigkeit von feuchten Haufwerken aus körnigen Stoffen. Ph.D. Thesis, Karlsruhe University, Germany.
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[47] T. Schaefer, D. Pharm. Thesis, The Royal Danish School of Pharmacy, Copenhagen, 1 996, 98pp. [48] J . Ratanaen, O. Antikainen, J.-P. Mannermaa, J . Yliruusi, Pharm. Dev. Techno!. 5 (2000) 209-2 1 7. [49] H. Leuenberger, L. Holman, M . Usteri, S. Winzap, Pharm. Acta Helv. 64/2 (1 989) 34-39. [50] J.D. Bonny, H. Leuenberger, Pharm. Acta Helv. 68 (1 993) 25-33. [5 1 ] H. Leuenberger, Adv. Powder Techno!. 1 0 ( 1 999) 323-352. [52] H. Leuenberger, M . Usteri, G . Imanidis, S. Winzap, Bolletino Chimico Farmaceutico, Anno 1 28, 2 febbraio 1 989, pp. 54-6 1 [53] H . Leuenberger, Y. Jin, M. Kwauk, G. Jimbo, Y. Kousaka (Eds.), Powder Techno!. Proc. '96 China-Japanese Symp. Particuology, May 24/25, 1 996, Beijing, pp. 37-4 1 . [54] M . Ritala, P . Holm, 1 . Schaefer, H.G. Kristensen, Drug Dev. Ind. Pharm. 1 4 ( 1 988) 1 04 1 -1 060. [55] P. Luukkonen, T. Schaefer, L. Hellen, A.M. Juppo, J. Yliruusi, Int. J. Pharm. 1 88 (1 999) 1 8 1-1 92. [56] R. Luginbühl, H. Leuenberger, Pharm. Acta Helv. 69 (1 994) 1 27-1 34. [57] I. Caraballo, M. Millan, A.M. Rabasco, J. Contral. Release 69 (2000) 345-355. [58] I. Caraballo, M. Millan, A. Fini, L. Rodriguez, C. Cavallari, Pharm. Res. 1 3 (1 996) 387-390. [59] L.M. Melgoza, A. M . Rabasco, H. Sandoval, I. Caraballo, Eur. J. Pharm. Sci . 12 (200 1 ) 453-459. [60] H. Leuenberger, Eur. J. Pharm. Biopharm. 52 (2001 ) 279-288. [61 ] G. Betz, P. Junker Bürgin, H. Leuenberger, Int. J. Pharm. 272 (2004) 1 37-1 49. [62] G . Betz, P. Junker Bürgin, H. Leuenberger, Pharm. Dev. Technol. 8 (2003) 289-297. [63] H. Leuenberger, M . Lanz, Adv. Powder Technol. 1 6 ( 1 ) (2005) 3-25.
CHAPTER 1 6 Tabletti n g Kendal PiU * and Csaba S i n ka
Merck Sharp & Dohme, Hoddesdon, Herts, EN1 1 9BU, UK Contents
1 . Introduction 1 . 1 . Granule design 2. Compaction process 2. 1 . Granule flowjhopper 2.2. Die fill 2.3. Powder transfer 2.4. Compaction, ejection and post-compaction operations 3. Compaction mechanisms 3. 1 . Compaction background 3.2. Compaction equations 3.2. 1 . Walker equation 3.2.2. Cooper-Eaton equation 3.2.3. Kawakita equation 3.2.4. Heckel equation 3.3. General discussion of compaction equations 3.4. Work of compaction 3.5. Density distributions 3.6. Ejection and ejection profiles 3.7. The ejection stress 4. Compaction equipment 4. 1 . Single-station presses 4.2. Rotary press 4.3. Special tablet presses 4.4. Instrumentation 4.4. 1 . Production press instrumentation 4.4.2. Instrumentation for product and process design 5. Finished compact characteristics 5. 1 . Strength testing 5.2. Fracture mechanics 6. Compact problems and solutions 6. 1 . Cracking 6. 1 . 1 . Excessive elastic recovery 6 . 1 .2. Air entrapment
*Corresponding author. E-mail:
[email protected] Granulation Edited by A.D. Salman, M.J. Hounslow and J. P. K. Seville t: 2007 Elsevier B.V. All rights reserved
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736 6 . 1 .3. Tool wear 6 . 1 .4. Lubrication 6.2. Picking 6.3. Pitted or fissured surface 6.4. Chipping 6.5. Binding in the die 6.6. Low tensile strength 6.7. Uneven weight control 6.8. Mottled appearance 6.9. Disintegration and dissolution 6.9. 1 . Porosity 6.9.2. Hydrophobicity of powder 6.9.3. Presence of disintegrant 7. New technologies 7. 1 . The structure of powder compacts 7.2. Triaxial testing 7.3. Compaction modeling 7.4. Quality control and compaction PAT References
K. Pitt and C. Sinka 769 769 769 770 770 770 771 771 772 772 772 772 772 773 773 774 775 775 776
1 . I NTRODUCTION
Powder pressing is a forming process used in a wide range of industries, such as powder metallurgy, industrial ceramics, pharmaceutical tablets, food, detergents, fertilisers, batteries, magnets, nuclear and hard metals. The process is fast, economic and lends itself to high-volume production. The production rate de pends on the complexity of the powder compact. Complex parts such as auto motive gearbox components can be pressed to near net shape at a rate of a tens or hundreds per hour, while modern pharmaceutical presses produce hundreds of thousands of tablets per hour. In spite of the broad range of powder materials and applications, powder pressing has common features in various industries. The operation consists of filling a die with powder, compressing using rigid punches followed by ejection from the die. During this process, the loose powder bed is transformed into a compact of given shape and microstructure. Depending on industry and appli cation, secondary operations such as sintering may be necessary to achieve the required properties of the final product. Powder metallurgy compacts are required to have sufficient strength to withstand handling and a dense, uniform and defect-free microstructure. Compaction is fol lowed by sintering to achieve near full density and maximum strength for structural applications. Sintering is also employed in producing ceramics, hard metal and other composite materials. Dimensional control is important during compaction and sintering in order to reduce the need for other additional operations such as sizing or additional machining. In other industries (pharmaceutical, food, detergents), the
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final strength and mechanical properties of the compacts is determined during the compaction step. These products must be strong enough to withstand subsequent operations, such as coating, packaging, transport and use, but weak enough to disintegrate upon administration (medicines) or use (detergents). The properties of a powder compact depend on the characteristics of the powder and the choice of process parameters during compaction. In order to achieve the desired compact properties, the powders are mixed with other in gredients having specific functions. For example, lubricants are added to reduce friction and wear of the tooling. Steel powders may be mixed with graphite, which acts as a lubricant during compaction and alloying material during sintering. Hard metal cutting tools are compressed by embedding the hard ceramic component into a soft metal matrix. In pharmaceutical tablets, the active ingredient is mixed with excipients, such as lubricants (to control friction between powder and tool ing), glidants (to improve flow), binders (to improve strength) and disintegrants (polymers that swell in contact with water). Fine partides in the micron and submicron range (ceramics, hard metals, pharmaceuticals, household goods, food) usually require granulation to improve flow and avoid segregation during the various powder handling processes prior to compaction. Pharmaceutical powders of low-drug loading (e.g. under 1 % by weight) are also agglomerated to ensure drug-content uniformity. 1 .1 . Granule design
The ideal properties of a granule for compaction are 1 . The granule should have binding properties and should confer physical strength and form to the compacts. In addition, if the compact is subsequently designed to disintegrate in fluid, e.g. a detergent or pharmaceutical tablet, then the granule should allow ingress of liquid. 2. The granules should be free flowing and hence should be as near spherical as possible with minimal surface roughness. The aim is to have rapid, reproduc ible flow of granules so that compact weight variation is kept to a minimum even at high production rates. 3. The granules should have a uniform distribution of all the ingredients across the partide size distribution and robust enough to withstand handling without breaking down. The granules should also be relatively dust free to minimise any containment concerns. 4. Segregation and agglomeration ("caking") during handling, transport and storage should be reduced. 5. The granules should not stick to the die or to the punches. Compaction forces the granule into very dose contact with the wall of the die. Adequate lubrication is required to reduce tool wear or damage to the compact.
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Items 1-4 are usually achieved both by the formulation and by controlling the process of the granule formation. Item 5 is normally achieved by extra-granular addition of a suitable lubricant after granule formation. Typical lubricants used in the food, ceramic and pharmaceutical industries are stearic acid-based metallic stearates, such as magnesium or calcium stearate. Other stearates (lithium, zinc), graphite or polymeric waxes can be used in other sectors and a range of proprietary lubricants have been developed for various applications.
2. COMPACTION PROCESS
In this section, a brief overview of tabletting science and technology from an industrial perspective is presented. Common issues in powder pressing using specific examples from various industries are discussed. More comprehensive presentation of industry-specific issues can be found in specialised textbooks published on powder metallurgy [1 ,2], ceramics [3] and pharmaceutical powder compaction [4]. Compaction is a mechanical process, where the state of the material is changed from powder into a compact of given porosity. Powder compaction can be classified broadly as •
• •
cold compaction, which includes die compaction isostatic pressing, roller com paction, powder extrusion and forging of prefabricated powder parts; warm or hot compaction, where the above operations are carried out at ele vated temperatures; powder injection molding, where a large amount of binder is mixed with the powder before injection molding and removed before sintering.
In the following sections, cold die compaction is only discussed. The compaction process is composed of the following steps: • • • • •
delivery of powder to the die die fill compaction ejection post-compaction operations.
Understanding the compaction process requires knowledge of the flow behav iour of powders, the densification mechanisms (which depend on the contact interactions between particles), the formation of bonds that give strength to compacts and the understanding of the response of a porous compact during
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unloading, ejection and post-compaction operations. These aspects of powder behaviour are discussed in the following sections in turn. 2.1 . Granule flow/hopper
The flow properties of a powder are important for the powder handling and pressing industries because the powder manufacturing processes (such as mix ing, granulation, drying, milling), powder pressing and powder transport involve flow in hoppers, pipes and chutes. The design of processing equipment is based on the flow properties of the powder and operating environment to ensure uniform flow patterns that reduce segregation and blockages. Powders flow because of body forces (gravity, centrifugal force) or extern al loads, which include air pressure and vibrations as weil as the constraints im posed by walls of the containers in which flow is ta king place. Powder flow is associated with dilation, contraction or can occur at constant volume. In order to describe powder flow, parameters such as dimensionless shear rate [5] were proposed. From this point of view, a number of flow regimes have been distin guished. Rapid flow, such as avalanches, is dominated by collisions between particles [6] while slow flow, such as in hoppers, is controlled by interparticle friction. During a given process, the different types of flow can occur concurrently. Under the applied loads and constraints the flow behaviour of powders is de termined by the fundamental powder characteristics (such as particle size and size distribution, morphology, material composition and density), operating con ditions (Le. moisture, temperature, static charge) and the current state of the powder (Le. tapped, consolidated, aerated, free flowing, etc.), which incorporates the effect of previous processes. The flow properties result from the combination of the factors listed above, which makes it difficult to characterise flow in a universal way for all applications and all industries, which in turn led to the development of a variety of testing methods. The flow characterisation techniques focus on specific aspects, such as measuring the flow rates through orifices of different size; the angle of repose; the energy to stir a powder bed; the cohesion and internal angle of friction of the powder; the bulk and tap densities; the formation of avalanches, etc. The effect of the initial condition of powder on the flow behaviour was recognised and devices such as a series of chutes, upstream funnels or special pre-conditioning cycles are employed to pre-condition the powder before the experiment in order to obtain repeatable results. There is a vast amount of literature, patents, standards, and specialised books and monographs dedicated to detailed descriptions of powder flow measurement methods, for example [7]. In the following section, the focus is on the issues specific to the flow of powders in hoppers.
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Hopper flow is important in industries, such as chemicals, plastics, pharma ceuticals, food, powder metallurgy, ceramics, mineral processing, etc. In compact formation, the delivery of powder to the die involves hopper flow. There are two main types of hopper flow, as presented in Fig. 1 . •
•
funnel flow, where some of the material is stationary. This may present prob lems for materials which cake, segregate or degrade. The most severe flow problems include arching and the formation of so-called rat holes. mass flow, where the entire powder mass is moving during discharge.
The uniform flow regime present in the mass flow hoppers eliminates some of the drawbacks of funnel flow hoppers; however, it requires taller hoppers with steep walls. In order to ensure mass flow, a number of designs were developed for the shape and size of the discharge zone. The calculation of the slope of the hopper walls requires Mohr-Coulomb type constitutive data [8], which are derived from techniques developed in soil mechanics, such as triaxial testing or shear-cell measurements. Shear cells work can work in translation [9] or by rotational shearing of the material. The rotational shear cells can be annular or full circle [ 1 0]. Shear cells can also be used to determine the friction coefficient between powder and a metal target to assist selection of container materials and surface finish to ensure that the powder flows along the walls. High friction can change the flow pattern from mass flow to funnel flow. An important consideration for the design of hoppers is to avoid formation of arches and rat holes. Arching occurs due to particle interlocking or material co hesion. A variety of flow meters based on powder flow through an orifice have been developed to measure quantities such as critical or minimal orifice size at which flow starts to occur [1 1 , 1 2] or the flow rate through a standard orifice [2]. The flow measurement techniques discussed above are based on different principles and it has been recognised that the choice of flow characterisation
stationary material
( a)
(b)
(c )
(d)
Fig. 1 . Flow regimes through hoppers: (a) funnel flow, (b) mass flow, (c) arching, and (d) rat hole formation.
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technique should be made in relation to the process under investigation [1 3]. In the following section, the specific features of powder flow into the die are reviewed. 2.2. Die fill
The flow behaviour of powders during die fill is different from the flow regimes discussed above because the discharge occurs into a c10sed cavity. The flow properties of powders have been studied extensively in relation to handling and hopper design as discussed above. On the other hand, only a limited number of studies concentrated On powder flow in constrained cavities under regimes sim ilar to die fill. As the powder is deposited in the die, a back-pressure is created, which reduces fill efficiency. Powder flow experiments carried out using metal, hard metal, ceramic and pharmaceutical powders [1 2] showed that flow meas ures, such as the Beverloo constant, are significantly altered when the powder is delivered into a c10sed container; this effect was found more pronounced for fine powders and for powders of low-density materials. The packing density of the powder in the die depends On powder properties, system geometry and process kinematics. The density variations can be ob served and quantified using non-invasive techniques such as X-ray computed tomography (CT) [14] for dies filled with metal powders. The initial density dis tribution is important because its effects propagate through the compaction cycle and subsequent operations. The density distribution after die fill is an input parameter for process models for compaction, which have been used in recent years. However, the results published in the literature to date are based On the assumption that the initial density in the die is uniform. The die fill systems on production presses are designed specifically to given powder materials, geometric complexity and production rates. Structural powder metallurgy parts employ high-capacity single-station hydraulic presses (see Sec tion 4. 1 ) where the powder is delivered from the hopper to the feed shoe through a series of hoses. The shoe travels linearly over the die opening and deposits the powder into the die through a sequence of motions under the effect of gravity. The shoe kinematics may include a number of shakes to facilitate the filling process. Additional mechanisms, such as fluidisation or vibration, are sometimes employed to loosen the arrangement of the powders, however, in most cases the shoes are simple rectangular boxes. In practice, the details of filling process are more complex. High-speed video observations [1 5] shows that rapid flow regimes, where particles interact by short collisions similar to gas dynamics, and slow flow, where the energy is dissipated through frictional interactions, occur simultaneously during die fill. The problem is further complicated when complex die geometries or complicated shoe kinematics
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is employed. The influence of air pressure was studied systematically for a wide range of powder materials, particies size and shape by performing die fill experi ments in air and vacuum [1 6]. Understanding these mechanisms is important in promoting strategies for maximising flow efficiency and packing uniformity to im prove product quality. Higher volume components (pharmaceutical tablets, magnets, detergents) are usuaily manufactured on high-speed rotary presses, which present further effects. Figure 2 presents a schematic diagram of a rotary press, where punches are mounted on a moving turret and pass through feeding, compression and ejection stations. The operation of the rotary tablet press is described in more detail in Section 4.2. Below the powder feed system of a rotary press using a Fette P 1 000 tablet press (Fette GMBH, Schwarzenbek, Germany) is examined as an example. The feeding system consists of a hopper connected to a feed frame. The feed frame consists of a box containing three paddle wheels driven by a motor. The powder is received from the hopper over the dispensing wheel and transferred to the feeding and metering wheels, which are located imme diately above the die table. The powder is deposited in the die while the die passes the die feed area seen in Fig. 2. A range of die fiil mechanisms can be identified. • • •
gravity feed; force feed, which represents the contribution from the paddle wheels; suction feed, where the power punch moves downwards in the feed cam while the die opening is exposed to powder;
Fig. 2. Schematic diagram of the feed frame of a rotary tablet press (top view).
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weight adjustment, which involves overfill and part ejection after the die passes over the feeding wheel; centrifugal effects and vibrations.
A detailed discussion of the mechanisms involved in die fill is presented else where [1 7]. The feed frames are geometrically and kinematically complex. Di mensional analysis [1 8] can be employed for quantitative evaluation of these effects for a given powder in order to improve feed frame design and selection of process parameters on a more rational basis. 2.3. Powder transfer
Powder transfer is an intermediary step between die fill and compaction, which is particularly important for the compression of complex multi-level parts (i.e. au tomotive gearbox components), which requires the use of a number of punches. The transfer operation is discussed below using the compression of an "H" shaped axi-symmetric component as example, as presented in Fig. 3. The tooling consists of a die, a centre rod and a set of three concentric lower and upper punches. The top surface of the powder is flat after the die fill. In the following step, the powder is transferred to a shape that is proportional to the compressed part. The punches are moved in a controlled manner so that they arrive at the
Upper punch set
Powder after die fill
Powder after transfer
Powder compact
Centre rod
Fig. 3. Powder transfer for manufacturing an "H"-shaped multi-level component.
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same time at the final position at the end of the transfer stage. Transfer is nec essary to avoid crack formation and the volume occupied by the powder is maintained constant during the transfer process. The compression step is normally designed so that columns of powder at different sections are compressed at the same strain rate. Optimum press con figuration is necessary during all stages in order to obtain a high-density crack free part with and mini mise the density variations in the compacL 2.4. Compaction, ejection and post-compaction operations
Compaction is one of the most important steps because physical properties of the compacts as weil as the pressing forces are determined not only by the properties of the powders constituting the powder mix (such as particle size distribution, shape, morphology, lubrication conditions) but also by the selection of the proc ess parameter. The stages of compaction and the mechanisms involved are described in Section 3. During compaction, the axial stress is transmitted in part to the rigid die wall. The sequence of removal of the axial loads for a complex part (see Fig. 3, for example) together with friction forces between the compacts and die wall (and punches) during unloading and ejection result in complex stress states which may lead to cracks and/or failure. Experiments using metal powders [1 9] indicated that the presence of lubricant has a significant effect on the ejection forces, while the type of lubricant was found to have a secondary importance. High-stress concentrations can also develop during ejection as the die wall constraint is progressively removed while the powder is being part ejected. One of the requirements of a powder compact is to withstand handling and loading during post-compaction operations. Parts made of metal, ceramic or hard metal powders are sintered to transform the mechanical bonds into metallurgical bonds. After sintering, secondary operations such as sizing, re-sintering or forging may be applied to achieve dimensional tolerances for ferrous structural parts. Control of tolerances after sintering is particularly important for hard metal compacts as grinding of cutting tool bits, for example, is expensive. Final finishing operations such as machining, heat treatments or plating may be necessary. Coating is largely used in pharmaceutical tablet manufacturing for functional purpose. All products though must withstand the loads during packaging, transport, storage and use. 3. COMPACTION MECHANISMS
In the following sections, details are given of compaction mechanisms and dis cussion of various equations to characterise the compaction processes are re viewed.
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3.1 . Compaction background
In 1 843, William Brackendon was granted patent number 9977 in London "for the shaping of pills lozenges and black lead by pressure in a die" [20]. In 1 884, Henry Wellcome registered the trade name "Tabloid" fram the words "tablet" and "al kaloid" to describe a small compressed item and manufactured and distributed a number of compressed items in Tabloid form including tea. By 1 895, the Pharmaceutical Journal in an editorial was commenting, "Un questionably, one of the greatest evils fram which legitimate Pharmacy and Medicine suffers lies in the indiscriminate use of the compressed tablet. We believe that tablets have had their day, or have reached the zenith of their pop ularity and like every other drug preparation that has preceded them, will pass away to make raom for something else" [21]. However, by 1 900 both single and ratary tablet presses were in routine use with Burraughs and Wellcome praducing 36,000 "Tabloids" an hour. However, measurement and understanding of compaction did not really com mence until the 1 950s when the advent of load cells and strain gauging instru mentation became more readily available. The pracess of compaction can be described as the route "whereby a loose natural or prepared powder is placed in some form of die and pressed between punches to form a coherent mass" [22]. Various densification mechanisms operate during powder compaction. The application of a pressure to the powder bed within the confines of the punches and die results in a reduction of the porosity. During these processes, adjacent particles are pressed together so that at the contact areas the action of the interfacial surface forces (atomic, molecular and electrostatic) will produce a stable and durable adhesive junction to give a potentially rigid and tough compact [23]. However, if too much energy is stored elastically when under compression, the elastic recovery during removal of the load may lead to adhesive failures and a soft, crumbly compact [24]. Hence the ability of a powder mass to reduce in volume when compressed does not however ensure the formation of a coherent compact. In general, powder compression progresses by • • •
rearrangement by particle sliding; reversible deformation (elastic deformation); irreversible deformation (plastic deformation and brittle fracture).
A number of stages can be identified during powder compaction, as illustrated in Fig. 4. After die fill, the powder is in a state of loose packing. The particles are able to translate and ratate with respect to one another to reach a state of dense packing, which is considered terminated where further rearrangement cannot
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K. Pitt and C. Sinka
poured powder
dense random packing
dense material
porous material
stage I I-roc---,....j isolated contacts
stage 1 1 isolated pores
increase in density the state of the material can be described by density Fig. 4. Stages of compaction.
take place. Next, densification takes place as a result of the contact interaction between neighbouring particles. In what is generally referred to as "stage 1 compaction" the contacts are isolated in the sense that the contact zones are not interacting. Some powder materials, such as ceramics, hard metals or pharma ceutical powders are granulated; these granules may deform and break down during the early stages of the process. As densification progresses, the contact zones between particles interact, the connections between particles are c10sed and isolated pores are formed, this is referred to as "stage 2 compaction". During this process the density of the material is increased and density is often used as a variable that defines the state of the material. Compaction occurs as a result of the interactions at the contacts between neighbouring particles. The relative contribution of these mechanisms changes as compression proceeds and varies from material to material. It should also be borne in mi nd that materials have a critical particle size below which they will exhibit plastic flow and above which they will fracture [25]. The critical particle size will also be influenced by compaction speed. The faster the compaction goes the more likely that the material is likely to fracture during compaction. The response of the material during compaction depends ultimately on the details of the interactions between neighbouring particles. At sufficiently small loads the interactions are elastic (recoverable). For ductile materials, such as metal powders, densification occurs as plastic deformation at the contacts. Ce ramic powders, owing to low fracture toughness, densify by particle splitting or crushing. These effects are iIIustrated diagrammatically in Fig. 5. The normal compaction process will never produce a compact that is totally free of pores. Pores, imperfect bonds and cracks within the particles, granules and compacts act as defects that may result in brittle failure initiation. The strength of the material increases as the porosity is reduced, hence structural components are compressed to near full density. However, it is not always
747
Tabletting Response of a compact
Contact Mechanisms
8 8 ffi B
Elastic
Plastic
Splitting
Crushing
Fig. 5. Compaction mechanisms.
desirable to have a minimal percentage of pores especially when designing compacts that are required to disintegrate when in contact with water. In this case, it is crucial to have a balance between mechanical properties and disso lution characteristics, which are both related to the percentage porosity within the structure of the compact. Also, certain classes of compacts, such as sintered filters or catalysts, which are made of metallic, ceramic or composite materials, are designed to have certain porosity and pore structure rather than increased strength. The appearance of the microstructure and the development of residual stresses and density distributions are all influenced by the behaviour of the pow der and friction between powder and tooling as described in Section 7.3. In general, the lower the frictional forces the more even the pressure distribution and the more uniform the pore and density distribution within the compact. Graphic visualisation of the densification process is usually in the form of compaction curves. Compaction curves in the form of density-pressure relation ships can be used in the study of the compaction behaviour of powdered ma terials such as metals, pharmaceuticals and ceramics. Compaction curves have been used by various investigators, such as Lukasiewicz [26] and Briscoe and Rough [27], to identify the compaction mechanisms of powder masses. Figure 6 shows a representation of a compaction curve. When the density is plotted as a function of the logarithm of the compaction pressure used, the compaction curve shows a number of distinct regions. At the lower compaction pressures, as the particles rearrange, very little compaction occurs until a point is reached; in the literature this is referred to as the apparent yield point as shown in Fig. 6. The second yield pressure is referred to as the joining pressure and is interpreted as the point at which interagglomerate pores are removed. 3.2. Compaction equations
The relationship between compaction pressure and volume reduction or density increase has been extensively studied and several functions were proposed to fit
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K. Pitt and C. Sinka
"" . .
Jommg Pressure
Apparent Yield Point
Fig. 6. Schematic representation of compaction curve.
curves based on pressure and volume fraction. These equations often seek to provide an understanding of the basic mechanisms of the compaction process and also the magnitude of the resulting compact strength as weil as character ising the overall compaction process. The main equations extensively described in the literature are the Walker equation [28], the Cooper-Eaton equation [29], the Kawakita equation [30] and the Heckel equation [31 ,32]. 3. 2. 1. Walker equation
One of the earliest relationships was proposed by Walker in 1 923 [28] 1 00 V = K - Wa In PA (1 ) where V i s the volume of powder under applied pressure, K the constant, PA the applied pressure and Wa the constant equal to change in volume in percent of material volume when the pressure is increased by a factor of 1 0. Walker showed that the curves for this comparatively simple relationship fitted in a straight line for many sets of data. 3. 2. 2. Cooper- Eaton equation
Cooper and Eaton [29], when studying compaction of ceramics proposed that compaction occurs in two stages. Initially, the particles rearrange themselves and the large pores that are of similar size or larger than the particles within the powder bed are filled. In the second stage, the particles fragment or plastically or elastically deform and the smaller pores are filled. K K (2) V = a 1 exp - -1 + a2 exp - -2 P P I
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Tabletting
where V ' is the fractional volume compaction, 8 1 , 82 , K 1 , K2 are the fit constants and P the compaction pressure. The constants 8 1 and 82 indicate the fractional compaction associated with the different types of particle compaction: rearrangement (the filling of large pores) and fragmentation (the filling of smaller pores). When 8 1 + a2 = 1 , the compaction process can be completely described by the two processes, when the sum is less than one, other processes must be present. Constants K 1 and K2 indicate the pressures that correspond to the highest probability of one of the two compaction methods occurring. A Cooper-Eaton plot usually consists of two linear regions. A regression of these two lines enables the constants a 1 and a2 to be evaluated while the gra dient of the two linear regions allows the constants K 1 and K2 to be determined. The general suitability of using the Cooper-Eaton equation has been ques tioned. Studies have shown that when applied to relatively soft materials with polydispersed particles the two linear regions are not easily separated [33,34]. This could be due to the volume reduction occurring by several simultaneous compaction mechanisms. The Cooper-Eaton equation is, however, useful for understanding the mechanisms of volume reduction at initial stages of the com paction process (at low pressures) and as such information can be obtained regarding the effects of particle surface properties and shape and size of the densification of the powder columns. 3. 2. 3. Kawakita equation
Kawakita and Tsutsumi [30] showed that the relationship between compaction pressure and volume could be represented by 80 - ep e Va - V _ abP - 1 - Po _ (3) - � 1 bP Pp 1 - ep _
-
+
_
where e is the degree of volume reduction, Va the initial volume, V the volume of powder bed at pressure P, a, b the constants, P o the bulk density, Pp the apparent density at pressure P, 80 the porosity at the bulk state, 8p the porosity at pressure P and P the compaction pressure. The equation may be simply rewritten as [35] P 1 P (4) ab From a plot of Pie against the constants a (the reciprocal of the slope of the linear section of the graph) and b (obtained after evaluation of a and the value of the intercept obtained by extrapolation of the linear section) can be evaluated. Physically a is related to the initial bed porosity and b is related to the resistance force, although the meaningfulness of these parameters has been debated
C = + "8
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[35,36]. Also the value of C can differ depending on the experimental procedures. Sheikh-Salem and Fell [37] observed that both the die filling method and diameter of the die affect the value of C. The bulk and tapped density measurement technique provides information on powder flow and particle rearrangement at relatively small loads. Here, the pres sure can be replaced by the number of taps, N. 1 N N + -= (5) Ct at bt at The constant a is equal to the initial porosity and the constant b is considered to be related to the compressive resisting forces or cohesive forces of the powder particles. Alternatively N can be replaced by tapping time T. For agglomerates, Adams and McKeown [38] proposed a modified version of the Kawakita equation using a number of types of experimental agglomerates containing a fine inorganic particulate phase and a range of soft-binder phases, as their compressed sam pies. In P = In(ro' /r/) + + In(1 - e(-"'e») (6) -
r/ G
where P is the applied pressure, a' the constant related to friction, the strain and ro' the apparent single agglomerate fracture strength. G
3. 2. 4. Heckel equation
Heckel [31 ,32] examined the compaction of metal powders and developed an equation that regarded compression of metal powders as analogous to a first order kinetic process, where the pores are the reactant and the densification the product. This equation has since been applied to the compaction of pharmaceu tical and ceramic powders. 1 = kP + A In (7) 1 0 where 0 is the relative density at any given P, k and A are the constants and P the compaction pressure. A plot of In 1 /1-0 against P is usually referred to as a Heckel plot. The linear part of the plot can be fitted to a straight line. The intercept of the li ne will give the constant A. The value A can be related to the volume reduction of the powder bed by the process of die filling and particle rearrangement: 1 A In + (8) 1 00 B where 00 is the relative density of the powder bed at resting pressure and B the volume reduction caused by particle rearrangement. _
=
_
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At this stage no particle deformation has occurred. The relative density of the powder after die filling and rearrangement, DA, can be described by �=�+� 00 where Da is the relative density describing just the period of particle rearrange ment. DA can be found from 1 ( 1 0) A = In 1 DA The gradient of the Heckel plot, k, gives the plasticity of the material. The greater the slope the more plastic the material. Heckel showed experimentally for metals that the value k can also be related to the yield strength, Y, by the equation _
(1 1 ) Subsequently, the reciprocal of k has been defined as the mean yield pressure and has been used for comparison of properties between materials. The use of Heckel plots to describe the mechanism of powder compaction has been studied intensively. Heckel plots were analysed for pharmaceuticals by Hersey and Rees [39] concluded that the difference in shape of Heckel plots of a material with different initial particle sizes could be used to give information about the method of compaction for that material. Rue and Rees [40] and York [41 ] have published results on the limitations of the application. It has been noted that different particle sizes of the same material may compact with different mechanisms, which can involve transitions from brittle to ductile characteristics [25]. Other factors which should also be considered when evaluating the Heckel plots are the compaction time, die size, mode of die filling and dimension measurement techniques [42]. Die wall friction also affects the Heckel plots with Ragnarsson and Sjögren [43] concluding that parameters such as yield strength could be misinterpreted. How ever, they concluded if the mean compaction pressure of the upper and lower punches was used instead of the upper punch pressure the effect of lubrication, particle interactions and friction were minimised. 3.3. General d iscussion of compaction equations
The consensus is that Kawakita is most suited to low-compaction pressures and medium to high porosities. A mathematical analysis of the Heckel and Kawakita equations by Denny [44] has shown that when the compaction pressure is considerably lower than the yield strength of the compact, the two equations take the same form. Also when the Heckel equation is modified by introducing a
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K. Pitt and C. Sinka
pressure-dependent term into the yield strength, it is identical to the Kawakita equation over the full pressure range. It was therefore conciuded that the Kawa kita equation is a specific form of the more general Heckel equation [44]. Denny also concluded that compaction equations need further development to take into account the anisotropy in compacts made by uniaxial compression. A compli cation being that the Poisson's ratio of compacts will also increase with applied pressure that should be factored into any analysis. Hassanpour and Ghadiri [45] used the distinct element method (DEM) to sim ulate bulk deformation based on single-particie properties. They conciuded that there is a critical ratio of Young's modulus to the yield stress of individual particies above which the Heckel analysis does reflect the effect of the yield stress, but below which it in fact reflects the effects of Young's modulus. Therefore, the Heckel analysis does not have general validity and should be used with caution. Sonnergaard [46] has discussed the compression models given by Kawakita, Walker and Heckel who have suggested various interrelationships between the pressure and the density of the pressed sam pie and concluded that the simpler Walker equation [28] gave a beUer fit of the densityfpressure data in the low porosity region. An analysis specifically of agglomerates was undertaken by Niklasson and Alderborn [47] who took force and displacement data sampled during in-die compression of agglomerates to calculate compression parameters according to • • •
Heckel ((J Y) Kawakita (1fb and a) Adams (ro').
It was conciuded that 1fb and ro' may be interpreted as a measure of ag glomerate shear strength during uniaxial confined compression, and as such they may be used as indicators of the tableUing performance of the agglomerates. In summary, the best choice of pressure-volume relationship will depend on the experimental procedure and the use of bulk compression methods to infer single-particie properties should be made with caution [48]. All the main methods that have been discussed have advantages and limitations and no one relation ship is able to provide an adequate description for the whole compaction process. 3.4. Work of compaction
The three main deformation mechanisms that can occur to particies within the powder bed are elastic deformation, plastic deformation and fragmentation. Elastic deformation is reversible, Le. the work stored during loading is recovered during unloading. However, a material with time-dependent properties can store
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B /
w
DECOMPRESSION
U Q: o u. :r u z
� �
/ / / WORK OF /
WORK RECOVERED
: � COMPRESSION
i DURING
COMPACTION ,
� � �
.#1'
/
I
/
E3 1
/ I
A
o
I I
c
UPPER PUNCH DISPLACEMENT
Fig. 7. Plot of upper punch force vs. upper punch dis placement.
elastic energy and may relax only after a period of time or after ejection from the die. The energy required to cause plastic deformation or fragmentation cannot be recovered, as these are permanent changes to the structure of the particle. In order to quantitatively evaluate the work required for compaction, force displacement measurements have been conducted by various authors [43J. A typical plot of the force exerted by the upper punch against the displacement of the upper punch is shown in Fig. 7. The compaction pracess can be split into two sections. The first section involves increasing the compaction pressure to a set amount: this is shown by the curve between A and B. The area under this curve, shown by E2 + E3 in Fig. 7, represents the total work of compaction. Some of the work required to compact the tablet will be recovered in the second section: represented by the curve between points B and D. Here the set pressure has been reached and decompression occurs. The material usually expands to relax at this stage. The area under this curve (E3) corresponds to the recovered or elastic work. The deduction of the elastic work fram the total work represents the unrecoverable work: this is represented by the area E2 .
3.5. Density distributions
Density distributions are thought to evolve during the compaction stage of pracessing. Early research conducted by Train [22J investigated the pressure response of powder under compaction. Manganin wire resistance gauges were
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K. Pitt and C. Sinka
employed and a complex pressure pattern within the powder bed was obtained. Train concluded that the resulting density distribution could be explained in terms of a varying pressure pattern, which evolved during compaction. The measurement of density distribution by both the coloured layer method [49] have shown that flat-faced compacts formed by uniaxial compaction typically are non-homogenous with high-density regions in the top corners of the compact adjacent to the moving punch and in the middle bottom half [50]. These are consistent with the patterns identified by Train [22]. A more detailed review of density distribution in powder compacts together with experimental characteri sation techniques is given in Section 7. 1 . 3.6. Ejection and ejection profiles
After compaction the compact is unloaded and ejected from the die. It is at this point that the compact can suffer mechanical failure because of the release of stored energy. Including a lubricant in a formulation to reduce friction at the die wall minimises the potential for failure of the compact structure during the ejection process. Various studies have been carried out in the past to observe the ejection behaviour of different materials. A study was carried out on the ejection behaviour of uranium dioxide compacts [51 ] . A schematic ejection profile of the ejection stress as a function of time is shown in Fig. 8. In Fig. 8, point A is known as the static ejection force and corresponds to the maximum point reached corresponding to the initial movement of the compact. After this initial movement of the compact, the force can be seen to decrease to a value that remains nearly constant throughout the ejection process until part of the compact is ejected from the die; this corresponds to point B shown in Fig. 8 A Breaking of die Wall adhesions
Static Ejection Force B Compact moving through the die Dynamic Ejection Force
p
C Compact emerging from the die
Fig. 8. Schematic profile of the ejection pressure as a function of time.
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and is known as the dynamic ejection force. The ejection force then falls gradually to point C, which corresponds to the complete removal of the compact from the die. The values of A, B and C are all dependent upon the compact aspect ratio, the state of the die wali lubrication and the compaction pressure used to form the compacl. While this is a typical profile, other, rather different profile shapes have been reported. Briscoe et 81. [52] studied the effects of aspect ratio, the effects of lubricants and the effects of applied compaction pressure with ceramic powders. The in vestigators showed that when the aspect ratio was increased, so too did the ejection pressure. Using lubricants also significantly reduced the ejection stresses observed and concluded that the higher the pressure the compact was formed at, the greater the force needed to eject the compact from the die. 3.7. The ejection stress
Briscoe and Evans [53] further investigated the effects of friction during the process of ejecting agglomerated alumina compacts from a die. They concluded that the ejection stress, Pe , required to eject a compact out of the die was con trolled by the interfacial shear strength, Te , whose value was governed by the die wall area and the radial stress, (J normal to the die wall. For a constant applied compaction pressure, the ejection pressure can be given by xx
(1 2) where H and 0 are the compact height and diameter respectively, and Te is the mean interface shear stress acting on the surface in contact with the die wall. The interfacial shear was considered to be sensitive to the contact conditions such as the compaction pressure, the ejection velocity, the temperature and the state of die wall lubrication. For pharmaceutical tablets and ceramic compacts the aspect ratio is often less than one. Hence the height of the compact is small compared to the diameter of the specimen and hence radial pressure can be regarded as being constant down the height of the side wall. Also the relatively short-column height means that the opportunity for frictional losses at the die wall is much reduced. Consequently, often the ratio of the upper punch pressure and the lower punch pressure (sometimes referred to as the force transmission ratio) is close to one.
4. COMPACTION EQUIPMENT
In this section, the defining features of powder compression presses and the latest technological developments are reviewed. As summarised in Section 2,
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powder can be compacted under a variety of conditions. Here only cold die compaction equipment is focused on, which can be classified as • • •
single station multi-station (rotary) special presses.
The same powder compact can be manufactured on a number of presses; the equipment is chosen depending on the volume and complexity of the pressed part. 4.1 . Single-station presses
Single-station presses are the equipment of choice for • •
low-volume production rates of simple geometry (i.e. pharmaceutical tablets); complex multi-level parts, such as presented in Section 2.3.
For the production of simple parts the punch movements are given by eccentric mechanisms driven by an electric motor. The cycle consists of die fill, compres sion and ejection, as illustrated in Fig. 9, for a typical press used for pharma ceutical tablet manufacturing. In single-station presses, the powder is fed into the die from a hopper and a feed shoe (Fig. 9). The bottom punch is stationary during filling. The feed shoe is moved above the die opening, executes a number of shakes and is withdrawn. The mechanisms executing shoe motion and die fill are usually mechanically interlinked and the shoe kinematics is dictated by the operating speed of the press. During compaction the top punch is driven by an eccentric while the bot tom punch is maintained stationary. Ejection is carried out by a mechanism that
Die table r punch Lower punch holder Collection end filling
Compression
Fig. 9. Operating cycle of a single-station tablet press.
Ejection
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operates the lower punch via a lifting block. The parameters that are adjusted by the operator are • • •
•
fill volume (tablet weight), which is the lowest position of the lower punch; ejection point (highest position of lower punch); tablet thickness, given by the maximum penetration of the top punch ; press speed.
More modern presses allow independent adjustments of a number of param eters. For example, depending on application, the powder movement in the feed shoe may be facilitated by a feeding mechanism (i.e. helical screws or rotating paddles). The compaction forces necessary for compressing relatively small simple components are of the order of tens of kilo newtons and eccentric presses can produce up to approximately 60 tablets per minute. In order to increase productivity, multi-tip tooling can be used, where a number of compacts are compressed simultaneously. More complex parts such as multi-level structural powder metallurgy compo nents are manufactured on single-station hydraulic presses, where control of punch movement is essential to prevent defects. Hydraulic computer numerical control (CNG) presses can apply hundreds of kilonewtons force on each of the punches. Owing to complex kinematics, the production rates are considerably reduced compared to the eccentric presses and depend on the complexity of the part. 4.2. Rotary press
Rotary presses are used for high-volume production (hundreds of thousands of tablets per hour) of relatively simple powder parts and are used mostly in the pharmaceutical, magnets, food, confectionery and detergent industries. The op erating diagram of a high-speed tablet press is presented in Fig. 1 0. The die and punches are mounted on a rotating turret and pass through the filling station, pre compression and main compression rollers and ejection station in succession. The feeding system, consisting of a mass flow hopper connected to a feed frame, was described in Section 2.2 in more detail. Compaction is carried out in two stages, as the punches travel through the pre compression and main compression stations. Pre-compression is necessary to prevent some of the practical problems described in Section 6, as the compaction step itself can be as short as a few milliseconds. The vertical movement of the punches is guided by cam mechanisms. Ejection is applied using a cam. On a standard rotary press, each toolset produces one tablet per revolution. The productivity of the press depends therefore on the speed of the press, which
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Direction of Main Compression
j
Pre Compression
Rotation Material Feed
Q
from Hopper
.J
UlJ Pull
Tablet
Die
Ejection
Fill
Table! Ejection
Tablet Weight Adjustment ,-...
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Reproduce by permission ©200S Manesty Technology Training
Fig. 1 0. Diagram of high-speed tableUing press.
is limited by the die fill and compression behaviour of the material. Productivity can be increased by increasing the number of stations, which is dependent on the size of the turret and the size of the compact. On large presses it is possible to compress two tablets every revolution, by using double-sided configuration, as presented in Fig. 1 1 (a). For smaller tablets the productivity can be increased further by using multi-tip tooling. 4.3. Special tab let presses
Most rotary presses use die feed systems as described previously. An alternative centrifugal die-filling system [54] has been developed, where the powder is fed into the centre of the die table, which is connected by channels to the dies, the powder flows under the effect of centrifugal forces and enters a specially de signed die through a side opening. The die fill is facilitated by rapid separation of the punches, similar to the suction-feeding mechanism where both punches contribute to the suction effect. Then the powder is transferred to the lower, c10sed section of the die where compression takes place. The tablet is ejected at the lower opening of the die. The system is suitable for large-scale manufacturing as described by Catellani et al. [54]. The double-sided rotary presses have been adapted for the production of bi layer tablets. Here, the tablet is not ejected after the first compression step. I nstead, the die passes through the second feed-frame for filling the second layer
759
Tabletting Hopper I
Precomp I
.-----. Tabl et ej ection 2
Main comp 2 Tablet ej ection I
Precomp 2
(a)
Tablet ejection
Main comp
(b)
Precomp ( - 10-20% ofmain)
Fig. 1 1 . (a) Configuration of a double-sided rotary press and (b) configuration of a bi-Iayer press.
of the material. The fill depth of the second layer is dictated by the punch pen etration when compressing the first layer, although more modern presses allow further flexibility in terms of selecting the process parameters. A schematic di agram of a bi-Iayer press is presented in Fig. 1 1 (b). Tri-Iayer presses have also been developed using the same principles. Multi layer tablets are becoming more popular in the pharmaceutical industry, as they can be used for dosing two incompatible active compounds in one unit, or to releasing the active ingredients at different rates. Similarly, the detergent industry uses bi- and tri-Iayer compacts for dish washer and washing machine tablets. Low-volume bi-Iayer tablets can also be produced on single-station presses by increasing the number of feed shoes accordingly.
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A special case of multi-Iayer tabletting is the compression coating process, also known as dry coating or powder coating, which involves the use of a bi-Iayer press. The compression rollers of the first layer are replaced by a unit that places a smaller core tablet on the powder bed. More powder is fed as the die set passes under the second feeding station, following which pre-compression, main compression and ejection occur in a standard way. The small core tablet is usually compressed on a separate rotary press running at the same speed as the main press. Commercial products may include up to three completely enclosed tablets. Smaller parts having a flat face can be manufactured on anvil presses, where instead of using an upper punch the parts are compacted against an anvil by the upward motion of the lower punch. The powder feed system, the anvil and a pick up mechanism are part of a single unit. The anvil press is mechanically simple and inexpensive to install/run, however, the compaction forces are relatively small (a few kilonewtons), and the production rate varies from tens to a few hundreds of units per minute. The system is suitable for metal, hard metal and ceramic powder compaction.
4.4. I nstrumentation
As described in the introduction, the formulation of a powder blend as weil as the choice of process parameters during manufacturing are essential for producing quality compacts, which requires controlling the process parameters on one hand and adequate characterisation of the behaviour of the powder during compaction on the other hand.
4.4. 1. Production press instrumentation
Measurement of forces and displacements is critical for the compression of complex parts on multi-axis presses in order to setup the die fill, transfer and compaction sequences. Modern production presses are instrumented with devices to measure the force applied by the punches during pre-compression, main compression and ejection. Weight and hardness are usually measured by devices downstream from the press. 80th types of measurement data can be fed back to the press for auto matic control of weight and compression parameters as a minimum. Tablet machine instrumentation is a subject on its own and textbooks have been published since the late 1 980s [55], which discusses the operating prin ciples of devices measuring force, displacement, temperature, weight, as weil as signal conditioning and data interpretation.
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4. 4. 2. Instrumentation for product and process design
The fundamental understanding of the mechanisms of compaction can assist in the formulation of powders. Experimental characterisation is however necessary because behaviours such as compactibility and compressibility are dependent on the processing conditions. The experimental data are generated using either small-scale production presses with additional instrumentation or specially in strumented presses. The instrumentation of small production presses follows the same general principles as for the larger presses described above. The instrumented presses vary in sophistication from general-purpose material testing machines to high-speed hydraulic systems, such as the compaction sim ulators used in the pharmaceutical industry, which is described in more detail below. A compaction simulator is presented in Fig. 1 2 (a ) . It consists of a le jing frame, die table and two independent servo-hydraulic systems controlled JY a computer, which operate the upper and lower punches as presented in Fig. ', 2 ( b ) . The displacement profiles of the punches can be programmed such that they mimic the compression schedule of any single-station press or rotary press used for tablet manufacturing. It is a distinct advantage that only a small amount of powder is necessary to generate a wealth of information that can be us=: d to optimise tablet formulation and selection of process parameters. Compaction simulator data for a simple compression sequence, wher : the bottom punch is maintained stationary, is presented in Fig. 1 3. The force ar, J!ied by the top punch is increased during compaction and is transmitted to the br,'tom punch and the die wall. Measurement of die wall stress is necessc)r'1 to
Upper valloadve,celactaccumul ul, punch ator,ator, punch andy Lholder, assembl VDT
J:T.,,�.;;;r�._ Die table Lower
Lower valloadve,celactaccumul ul, punch ator, ator, holL der,assembl punch andy VDT
(a)
( b)
Fig. 1 2. Compaction simulator: (a) general view and (b) schematic diagram.
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K. Pitt and C. Sinka
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characterise the behaviour of material during compaction and measure the fric tion coefficient between powder and die wall as described elsewhere [56]. For this purpose, dies have been instrumented with radial stress sensors, a typical output is presented in Fig. 1 3. 5. FINISHED COMPACT CHARACTERISTICS In this section, the various tests which can be performed on the finished com pacts are described. 5.1 . Strength testing The strength of a compact which can be defined simply in terms of the force is required to fracture a specimen across its diameter [57]. More complex shapes can also be crushed by opposed loads. However, the breaking load does not take into account either the dimensions and shape of the compact or the mode of failure. The conversion of a fracture load to tensile strength, wh ich takes these factors into account, allows for ready comparisons to be made between sam pies of different shapes or sizes. In industrial practice, the most commonly applied strength measurement for a compact is the diametral compression test. The procedure involves applying a load to a simple plane-face compact which is subjected to two diametrically opposed point loads. The test was developed independently at the same time by
763
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Carneiro and Barcellos [58] in Brazil, and by Akazawa [59] in Japan and is referred to as the "Brazilian" or "indirect" tensile test as a tensile fracture is induced by compressive loading. The test is simple and easy to perform and has been widely used to determine the tensile strength of a variety of brittle materials such as concrete [60], coal briquettes [61 ] , Gypsum [62] and lactose tablets [63]. A complete analytical so lution exists for the stress state induced by the loads [64]. The expression for tensile stress (0"1), determination in a flat-face compact is O"I =
2P � nOt
( 1 3)
where P is the applied pressure, 0 the compact diameter and t the compact thickness. This theory has also been developed for the determination of the tensile strength of convex-faced compacts by Pitt et al. [65]. 0"1
= n01 0P2 (2.84 0t - 0.1 26 t
W
W + 3.1 5 0 + 0.01
) -1
( 14)
where W is the central cylinder thickness. The positioning of the load has a big effect on the stress distribution and hence the fracture of the tablets. This is especially a concern when applying this method to brittle materials where the compact cannot deform and correct the misalign ment by plastic flow. The ideal situation involves applying a line load so the stress distribution is uniform through the centre diameter. In reality, this is impossible to achieve and the load will always be applied over an area. If the contact area is smalI, however, the stress distribution will only be affected near the ends of the loaded diameter and hence the equations still hold for the majority of the diam eter. Peltier [66] calculated that the tensile stress can be held uniform across the majority of the load diameter provided that the width of this contact area does not exceed one-tenth of the length of the diameter. A more detailed analysis of the diametrical compression tests, where the effects of contact flattening and plastic material behaviour were considered, was presented by Procopio et al. [67]. It was shown that the stress field in a plastically deforming material results in significant changes of the magnitudes and location of maximum principal stresses and a validity map of the Hertzian solution was proposed. The Brazilian method can only be applied to sampies which fail due to tensile stress. If the elastic moduli of the sampie and loading platens are too great then the tensile stress will not be constant over the loaded diameter and the maximum shear and compressive stresses will reach very high values. For some brittle materials, padding is required between the sampie and the load to assure adequate load distribution [63] and promote failure in tension [68]. The different failure modes were detailed by Mitchell [69] as presented in Fig. 1 4.
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K. Pitt and C. Sinka
Simple tensile Failure
"TripIe eleft" Tensile failure
Compressive Failure
Fig. 1 4. Failure modes i n diametral compression test.
If the loading is satisfactory then the specimen will fail diametrically in tension to give simple tensile failure. Another fracture mode, the tri pie cleft, was also identified [68] to be failure in tension. High compressive stresses around the loaded part will result in non-tensile failure due to shattering and cracking in the loading region. Hence the validity of the diametral compression test under a given set of con ditions to determine a tensile strength from a fracture load can be easily assessed by examining the specimen fragments after failure [62]. Strain rate sensitivity while conducting the tensile test should also be con sidered. Increasing the load rate of concrete cylinders has been reported [69] to result in higher observed tensile strengths. Rees et al. [70] recorded similar ob servation for lactose tablets and concluded that discrepancies in tensile strength values determined using different testing instruments may be partially attributed to differences in the loading rate of these machines. If the compact is elongated then flexural or beam testing can be applied. However, the stress distribution in the specimen is non-uniform, varying from zero at the neutral axis to a maximum at the outer edge surface. Canti lever methods for strength testing have been developed for beam or elongated specimens. The compact in the form of a parallel beam of rectangular section is subjected to three- or four-point bending. The modulus of rupture is calculated from the load at fracture [71]. The major drawback with the method of three-point bending is that there may be a large contribution from shear stresses at the failure force [72] and as such application of this method to several geometries is inappropriate. In addition, beam testing accentuates the effects of surface conditions on the measured strength and the test can give results considerably different from the true tensile strength [61 ] . The formulae are summarised in Stanley [72]. Stanley and Newton [73] have also published approximate relationships for three-point bending derived for capsule-shaped tablets using basic trigonometry. Their approximation of the tensile stress is given by 2a ] 2d [d+ 6A + bd
3 WI
(Jt � 2.
(1 5)
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765
where W is the fracture load, 1 the distance between supports, A the area of curved segment, a the height of curved segment, b the capsule width and d the wall height. Four-point bending is generally considered the slightly superior test as it pro duces a region of constant bending moment between two inner loading points [72]. However, owing to the relatively small size of pharmaceutical compacts three-point bending is the more common choice. The size of the compact though can be quite smalI. Hancock et al. [74,75], investigated the use of three-point bending for the characterisation of very small powder compacts of approximately 20 mg. Elastic properties such as Young's modulus or Poisson's ratio of a material can be estimated from the linear regions of stress-strain curves. It has been shown, however, that the Young's modulus has no correlation with the fracture strength of materials [76], though obviously a high-fracture strength within one material would be an ideal situation. The testing methods for determining the strength and elastic properties of material are weil developed and form international standards. These behaviours are discussed in detail in materials engineering textbooks [77,78]. 5.2. F racture mechanics
The main fracture problems that affect compacts are cracking and lamination which are thought to be due to a combination of elastic strain release and die wall friction. Cracking can be induced at any stage of compaction of complex parts. For simpler geometries, cracking occurs particularly during decompression and during ejection. Early investigation concluded that compacts can fracture due to inhomogeneous density distribution creating weaker areas which can come apart [22]. Stored energy and bond strength play a major role in initiating cracking. Van der Voort Maarschalk et al. [79] showed that the amount of stored energy is the driving force for stress relaxation and hence cracking. If a material with a large amount of stored energy is coupled with low-bonding strength and low die wall friction the compact will readily expand resulting in a weak and porous structure. High-bonding strength and high die wall friction will prevent elastic relaxation and therefore the energy may be released by cracking of the compact. Research by Takeuchi et al. [80] concluded that the residual die wall force was related to the elastic and plastic properties of the material and the profile of die wall pressure for the materials they investigated was c10sely related to cracking and sticking prob lems during ejection. It has been shown with alumina compacts that the use of lubricants during the compaction process can improve the density distribution within the compacts by mducing the die wall friction [27,81 ] and can therefore help prevent fractures.
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Fractures occur by crack initiation and propagation. A crack will form when the applied stress reaches a critical value at a flaw for a given position and orien tation. Therefore, the statistical distribution of size and shape of flaws can lead to the calculation of the critical stress to cause a fracture. The original fracture mechanism postulated by Griffith [82] involved an energy balance analysis. In order for a fracture to occur, energy must be provided to create two new surfaces: if the stored elastic strain released by crack propagation exceeds the free-surface energy required to create the surfaces the material will fracture. It is assumed that the crack initiates from a defect in the material which acts as a stress concentrator. This phenomenon continues to concentrate the internal stresses and as such the crack grows. The Griffith equation is applied to brittle fractures, Le. one that occurs with little or no plastic deformation of the material. n(J2 a G 2y (16) E where G the energy release rate, (J the applied stress, a the half crack length, E Young's modulus and y the free-surface energy. When a ductile material fractures, plastic deformation will occur. This type of fracture usually corresponds to a higher tensile strength. An extension to this is the critical stress intensity factor, K,c. This value provides information about the stress distribution around the crack tip. The ratio of the maximum stress at the crack tip, (Jm , and the applied tensile stress, (Jo , is shown in the following equation: =
=
(1 7) where a is the crack length and rc the radius of crack tip. K,c is commonly used as an indication of the amount of stress required to propagate a crack, it is also an indication of the resistance of a material to cracking. Methods to determine K,c involve imposing a notch or crack into the sampie to induce a fracture in a specific position of the compact: methods include three- or four-point bending, double torsion and Vickers indentation [83]. 6. COMPACT PROBLEMS AND SOLUTIONS
In the following sections, a number of common compaction problems are iden tified and potential solutions discussed from an industrial point of view. 6. 1 . C racking
A major problem which can occur during or after compact manufacture is crack ing. This can manifest itself in a number of ways dependent upon the material
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properties of the feed material. It can range from surface cracking in metals through to "capping" in pharmaceutical tablets where the upper part of the tablet horizontally separates from the body during ejection (Fig. 1 5). Lamination can also occur which is where cracks form within the body of the compact resulting in the compact splitting apart into layers. The same factors may contribute to this problem. An example of a laminar crack through a microcrys talline cellulose tablet magnified using a scanning electron microscope (SEM) is shown in Fig. 1 6. Cracking can be caused by a number of factors. The principal material property leading to cracking is the viscoplastic-elastic behaviour of the powder materials comprising the compact. The elastic response during decompression is a major factor as non-dissipated stored elastic strain release is the source of the internal and disruptive forces. For complex shapes such as particularly compressed metals parts the effects of this strain release can be moderated by careful design and consideration of the powder flow and pressing sequence of the different regions of the component.
Fig. 15. Example of a pharmaceutical tablet that has "capped".
Fig. 1 6. SEM image showing a laminar crack developing through the centre of a tablet.
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K. PiU and C. Sinka
In addition the response is offen time dependent. As speed is increased, the relative elastic component of a given material also increases, giving rise to a higher incidence of cracking. Hence as compression speeds are further in creased, the occurrence of cracking and lamination of compacts tend to become more prevalent. Other than reducing compaction speed, a processing way of overcoming this and effectively increasing the relaxation time is to use pre-com pression prior to the main compression. Typically the pre-compression is at 1 0% of the main compression [84]. However, this is very much formulation dependent. Akande et al. [85] finding that optimal tensile strength was found by having a pre compression larger than the main one. Increasing speed will also reduce the time available for the air trapped between the granules to escape. Thereby leading to the potential for increased air pressure in the die to cause cracking and lamination particularly for high-porosity beds. Sticking of the compact to the die wall or punch components can also induce stresses resulting in failure. There are consequently a number of formulation and processing approach es, which can be used to address the causes of cracking and lamination. 6. 1. 1. Excessive elastic recovery
Elastic recovery itself will not necessarily result in lamination. Lamination will only occur if the interparticle bonding cannot accommodate this elastic recovery. Hence the formulation options are to either increase the binder level, or the type of binder in the granule. An alternative approach is to incorporate polymeric materials such as celluloses undergoing less-elastic recovery. For organic ma terial the moisture content can also be important as the level of residual moisture i n a polymer can affect its deformation properties. 6. 1 . 2. Air entrapment
The initial volume of granules may be several times that of the compact into which they are compressed particularly for low-apparent density materials such as de tergents, food and pharmaceuticals. During compression both particles and air will be compressed. The reduction in volume is due to removal of air. This air will need to escape from the compact otherwise there is the potential for this en trapped air pressure to blow apart the compact on ejection. Air removal can be facilitated by using dies that are tapered outwards towards the top of the die to allow the air to escape. Similarly, using punches with greater tolerances around the punch and die contact region will enable the air to escape [86]. Tapered dies also have the additional advantage of increasing the volume available for the tablet to expand radially into hence reducing residual die wall pressure. Pre compression is also a very important tool to reduce the effects of air entrapment.
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6. 1 . 3. Tool wear
Wear in the dies takes place usually about the point of compression, i .e. in the bore resulting in a circular depression within the die, which is usually referred to as banding in the context of high volume rotary presses. A compact compressed in this cavity has therefore to be forced out through the smaller aperture in the top of the die resulting in shear and lamination. Wear occurs an all tool surfaces in contact with the powder where sliding takes place and is accelerated when powder particles from hard materials, such as cera mies, are compressed. For a given material and compaction force, wear can be reduced by minimising friction using lubricant (see below) or coating the tool ing with wear-resistant materials. Tool wear occurs due to the contact interactions between various mechanical parts of the press, such as, for example, the contact between the compression roller and punch head on rotary presses, however, is present for all types of presses. Industries where product contamination is an issue require special measures for lubricating the mechanical parts.
6. 1.4. Lubrication
Lubricants will mini mise die wall friction and prevent the adhesion of the granules to the punch faces and hence can be manipulated to overcome cracking and lamination. Lubricants can be classified according to the way in which they are added to the granules. Internal lubricants are mixed with the dry powders prior to granulation, i.e. polyethylene glycol external lubricants are incorporated imme diately before compression by mixing in with the formed granules (e.g. stearates). An alternative approach is to spray in the lubricant into the punch and die cavity immediately before die filling and hence directly coating the surfaces of the tooling.
6.2. Picking
In some instances, a small amount of the compact material may stick to the tooling surfaces. As compacts are repeatedly made in this station of tooling, the problem gets worse as more and more material gets added to that already stuck to the punch face. The problem tends to be more prevalent on upper punches. The root cause is usually insufficient lubrication, although surface roughness of the tooling can also play a part. Sticking is more often observed for compacts with fine embossing, such as pharmaceutical tablets, where the design of such subtle geometrie details becomes important.
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6.3. Pitted or fissured surface
The most Iikely cause of a fissured surface, if it is not due to picking or sticking, is the presence of granules which are uniform in size and lack the sm aller particles to fill the voids. Generally, the problem can be resolved by broadening the particle size distribution of the granules provided that this does not lead to other problems such as cracking or segregation. High-speed compaction using tooling with deep curvatures, such as in pharmaceutical tablets, contributes to air entrapment at the top punch cavity, which is also thought to cause surface cracking. 6.4. C hi pping
Sometimes compacts after leaving the press, or during subsequent handling and coating operations, are found to have sm all chips missing from their edges. This fault is described as "chipping" and, in addition to the obvious formulation de ficiencies, may be caused by compaction conditions that make too soft or too brittle tablets. Incorrect machine settings, especially the ejection take-off plate and excessively harsh handling of compacts after they leave the press, may be the additional factors. Friability testing is employed as an indicator of an inherent tendency for a given batch of product to chip. In friability testing, the compacts are usually rotated in a defined drum at a set speed for a controlled number of revolutions. The amount of weight loss due from the compacts after the test is recorded as a percentage of their initial weight. The defects described above can be reduced by controlling the tablet micro structure. For example, by eliminating low-density regions where the local strength of the material is reduced. An understanding and control of microstruc ture evolution can be achieved using process modeling tools as described in Section 7.3. 6.5. Binding in the die
This is characterised by excessive side scraping of the die with the compact ejection forces being high with the resulting compact edges being rough and scored. The root cause results from high die wall friction. This in turn could be caused by poor lubrication or blemished and worn die or tooling. An alternative cause is too large a c1earance between the lower punch and die bore resulting in trapping of powder, which is compacted to form a hard film which hinders free movement of the lower punch. Binding is more frequent for materials with low-melting points or when tem perature sensitive lubricants are used. The plastic work during compaction is dissipated as heat, contributing to increasing compact temperature during the
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process. Selecting process parameters such as speed or using engineering methods such as cooling systems to reduce the temperature of the compaction equipment have been employed to reduce binding. 6.6. Low tensile strength
Structural engineering parts are pressed to near full density to maxi mise strength and control the microstructure better through post-compaction operations. Non structural compacts are designed for a variety of other requirements, for example a pharmaceutical tablet may be required to disintegrate as described in Section 6.8. In general, the higher the compaction pressure the denser the compact will be and hence the higher the resulting tensile strength of the compact. Conse quently, too low a compaction pressure will lead to low tensile strength or "soft" and crumbly compacts. Alternative reasons are excessive coverage of the gran ulation by a lubricant, such as a stearate, reducing the potential to form strong interparticle bonds. This can be caused by • • •
too high an initial level of the lubricant; excessive shear during the lubrication stage; excessive lubrication time.
An additional cause can be the weakening of the intergranular bonds by air entrapment, which is not sufficient though to cause capping. 6.7. Uneven weight control
Poor weight uniformity is usually due to poor die filling. This can be due to either poor flow characteristics of the granule or due to inadequate filling mechanisms on the compression machine. If it is due to poor granule flow then the addition of glidants such as silica or talc can be employed. A number of mechanisms have been proposed to account for glidant action. The flow properties of smooth, nearly spherical particles will be better than those of an irregular shape. Hence one mechanism proposed is that glidants fill the surface depressions and thereby reduce surface roughness. If the coefficient of friction of the glidant is less than that of the granules then the interparticle friction may be lowered. Alternatively the glidant may physically separate the solid particles so that the intermolecular at tractive forces such as van der Waals forces, or the capillary adhesion forces are reduced. So me particles may acquire a frictional electrostatic charge when handled and this mutual repulsion of the particles may be sufficient to impede die filling. Tale or
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sodium lauryl sulphate are approach es which have been used to reduce this charging [87]. Lubricants may or may not promote granule flow. 6.8. Mottled appearance
This is typicaily seen with coloured granules. This can be due to dye migration to either the smail or large granules during the granulation process. Alternatively, it can be an optical phenomenon due to the smailer particles providing a back ground of a slightly different hue whieh shows up the larger granules on the compaet surface. 6.9. Disintegration and d issolution
These are particularly applicable to pharmaceutical tablets although the concepts also apply to detergent tablets and food products. Disintegration is the time taken for the tablet to break apart into its primary particles in a fluid, normaily aqueous. Dissolution is a measure of the release of the active ingredient from the compact into solution. Disintegration and dissolution are dependent on a number of factors. 6. 9. 1. Porosity
Water can generaily only gain access to the inside of a compact via pores. Hence if the compact is compressed at high pressure then its porosity is likely to be too low to ailow water ingression. 6. 9. 2. Hydrophobicity of powder
Water will not readily penetrate hydrophobie powders. A potential issue therefore is the use of hydrophobic lubrieants sueh as the stearates, which in high con centrations can prevent penetration of water and ean decrease dissolution and disintegration. Addition of a wetting agent in the granule formulation ean assist in the penetration of water into the compact. 6. 9. 3. Presence of disintegrant
Disintegrants such as starches and modified ceiluloses may be included in a com paet formulation to assist disintegration. They ean act by two meehanisms. One is to act as a water- soluble path for the water to penetrate into the compaet. The other is by swelling up and applying pressure, which breaks apart the compact.
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7. NEW TECHNOLOG I ES
In this section, the latest developments in understanding powder compaction process and technology are reviewed. 7. 1 . The structure of powder compacts
Powder compacts are inherently non-homogeneous and anisotropie and present density variations, which are induced in powder compacts during die fill and compaction. Density variations affect the local properties of the compact, which in turn influence the behaviour after compaction, i .e. elastic rebound, ejection and post-compaction operations such as handling, packaging, coating, sintering, etc. The importance of density distributions in powder compacts has been recognised since the early 1 900s. Train [22] has described characterisation techniques based on differential machining, hardness tests or X-ray shadow of lead grids placed in the compaci. A less invasive technique for ceramic compacts present ing natural radioactivity was developed by Macleod and Marshall [51 ]. who related the density distribution patterns to die wall friction. More modern non-destructive techniques, such as X-ray CT, acoustic wave velocity measure ments and nuclear magnetic resonance (NMR) imaging, were summarised by Lannutti [88]. These techniques have been applied to a range of powder materials. Figure 1 7 illustrates the density variation after die fill [14] and in a pharmaceutical tablet [1 7]. The density gradients are induced during complex powder movements during powder fill and the pressing sequence and are affected by the interactions be tween the powder and tool surfaces. In most severe cases fractures occur. The tools and techniques described in the following sections can also assist in con trolling of the microstructure through fundamental understanding of material and process parameters.
Fig. 1 7. X-ray CT density variations in powder compacts: (a) after die fill with metal powder and (b) pharmaceutical tablet.
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7.2. Triaxial testing
The compression of a powder compact in a die involves uniaxial deformation, i.e. the movement of the powder in the plane normal to the compression direction is restricted. However, even for the simplest case (i.e. cylindrical compact with flat faces) the friction interaction between powder and tooling changes the strain path experienced by a small volume of material and the effects have been illustrated by Train in 1 957. In order to characterise the compaction behaviour of powder under the full range of loading conditions that occurs in practical situations, triaxial testing can be employed. Triaxial testing originates from the field of rock and soil mechanics as described in textbooks in the field [89] and has been adapted to examine the compaction behaviour of powders since the 1 970s [90]. A triaxial test specimen is presented in Fig. 1 8. The powder is placed in a rubber sleeve between two rigid platens. The specimen is introduced in a Hoek-type triaxial cell [89], where it is subjected to cell pressure and a superimposed axial load. The deformation of the specimen is measured in radial and axial direction using extensometry or other methods. Modern servo-hydraulic systems and computer control technology [91 ] allow investigating the high-pressure compaction response of powders along a variety of loading paths in stress or strain space and results for metals, hard metals and ceramics were presented in the literature [92]. Triaxial compression data are used for the development and calibration of constitutive models for powder com paction (as described in the following section) and probing of yield surfaces [93] of powder compacts in order to generate detailed information on the strength behaviour of powders.
I
Top platen Rubber jacket Radial displacement measurement canti lever device Powder specimen
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7.3. Compaction modeling
Similar to modeling any other process, compaction modeling offers insight into the complex physical phenomena occurring during compaction, and allows sensitivity ranking of the contributing factors. The potential of numerical simulation has been recognised since the 1 980s [94]; however, systematic application to industrial problems became possible only in the 1 990s with the development of advanced computing technology. Initial compaction models have been developed for the powder metallurgy [95] and ceramic pressing applications and today the approach is being implemented by the magnets, hard metals and pharmaceutical industries. Constitutive models (such as the Cam-Clay [96] or Drucker-Prager cap [97] models) have been adapted from the rock and soil mechanics literature and cal ibrated using triaxial test data as described by Trasorras [95]. These constitutive models are based on continuum mechanics principles and describe the evolution of the material in terms of density or relative density. However, models using work quantities as state variables have been proposed recently [98]. Continuum models have been extended to low relative densities (Le. 0.3) [56]; however, detailed experimental data to ca Ii brate the yield surface and flow po tential evolution in regimes corresponding to partieIe rearrangement and early stage compaction are not available. To bridge the gap, discrete element ap proaches [99] or multi-partiele finite element models where each individual par tiele is made discrete, have been developed [1 00, 1 01 ] which allows the development of constitutive models from first principles across the compaction regimes and length scales. Compaction models are used in industry to optimise the formulation of the powders, the set-up of punch motion sequences, the tool design and to control the properties of the final products [95,1 02] and the dimensional tolerances after compression and sintering [1 03, 1 04].
7.4. Quality control and compaction PAT
Monitoring and controlling of the process parameters at every stage is an im portant way to ensure final product quality. The quality requirements are industry and application specific. The pharmaceutical industry employs batch processes and quality is ensured by inspection. Recently, however, companies and industry regulators have initiated the process analytical technology (PAT) programme whereby critical quality performance attributes are monitored at every stage of the process. If the processes are understood from first principles, then robust processes can be designed and implemented. For pharmaceutical processes where a distinct endpoint can be reached (such as dispensing, granulation, dry ing, milling, blending), PAT initiatives have been developed, which involve
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matching the "signature" of the process using spectroscopy techniques or acoustic wave emissions. In terms of pharmaceutical tablet compaction, product quality is essentially en sured by inspection and systems have been developed to perform quality measure checks on-line. The measurement data are used as feed-back signal to adjust the operating parameters on presses such as adjustment of fill depth (weight) or compression force, to achieve the desired properties (size, strength, friability, dis integration, etc.). To check content uniformity, techniques such as near infrared spectroscopy or light fluorescence-based monitoring systems have been devel oped for on-line (to all tablets) or off-li ne applications (for selected units). Near Infra-Red (NIR) can also be used as non-destructive strength testing tool [1 05]. REFERENCES [1] F. Skaupy, Principles of Powder Metallurgy, Philosophical Library, New York, 1 944. [2] R M . German, Powder Metallurgy Science, 2nd edition, Metal Powder Industries Federation, Princeton New Jersey, 1 994. [3] W. D . Kingery, HK Bowen, D . K. Uhlmann, I ntroduction to Ceramics, 2nd edition, Wiley, New York, 1 976. [4] G .Alderborn, C.Nystrom (Eds.), Pharmaceutical Powder Compaction Technology, Marcel Dekker, New York, 1 996. [5] G . 1 . Tardos, S. McNamara, I. Talu, Powder Technol . 1 31 (2003) 23. [6] S.B. Savage, Adv. Appl. Mech. 24 ( 1 984) 289. [7] S.A. Howard, J .W. Lai , Encyclopedia of Pharmaceutical Technology Volume 6, J. Swarbrick, J . C. Boylan (Eds.), Marcel Dekker, New York, 1 992, p. 141 (ISBN 08247-2805-X). [8] J.C. Jaeger, N .G .W. Cook, Fundamentals of Rock Mechanics, 3rd edition, Chapman & Hall, London, 1 979. [9] AW. Jenike, Storage and Flow of Solids. Bulletin 1 23, Engineering and Experiment Station, U niversity of Utah, USA, 1 964. [1 0] I .A.S.Z. Peschi , Powder Handling Process. 1 ( 1 989) 1 35. [1 1 ] RL. Carr, Chem . Eng. 72 ( 1 965) 1 63. [ 1 2] D. Guyoncourt, J . Tweed, Measurements for powder flow. Proc. Valencia Euro PM, Valencia, Spain, 2003. [ 1 3] Y.S.L. Lee, R Poynter, F. Podczeck, J . M . Newton, AAPS Pharm. Sci . Tech. 1 (2000) 2 1 . [ 1 4] S . F. Burch, J . H . Tweed, AC.F. Cocks, I .C. Sinka, C.Y. Wu , Proc. P M , Vienna, Austria, 2004. [ 1 5] C.Y. Wu, L. Dihoru, AC.F. Cocks, Powder Technol. 1 34 (2003) 24. [ 1 6] L.C.R Schneider, A.C.F. Cocks, A. Apostolopoulos, Powder Metall . 48 (2005) 77. [ 1 7] I .C . Sinka, L.C.R Schneider, AC.F. Cocks, I nt. J. Pharm. 280 (2004) 27. [ 1 8] L.C.R Schneider, I.C. Sinka, AC.F. Cocks, Powder Techno!. in press. [ 1 9] D.T. Gethin, D. Korachkin, J . H . Tweed, D . M . M . Guyoncourt, Proc. PM Vienna, Austria, 2004. [20] W. Brockendon, Patent number 9977. For the shaping of pills, lozenges and black lead by pressure in a die, 1 843. [21 ] The Passing of the Tablet Fad, Pharmaceutical Journal Editorial. February 1 2 , 1 895. [22] D . Train, Trans. I nst. Chem. Eng. 35 ( 1 957) 258. [23] J . M . Newton, D.J.w. Grant, Powder Technol. 9 ( 1 974) 295. [24] E . N . Hiestand, J.E. Wells, C.B. Peot, J.F. Ochs, J. Pharm. Sci . 66 ( 1 977) 5 1 0.
Tabletting [25] [26] [27] [28] [29] [30] [31 ] [32] [33] [34] [35] [36] [37] [38] [39] [40] [4 1 ] [42] [43] [44] [45] [46] [47] [48] [49] [50] [51 ] [52] [53] [54] [55] [56] [57] [58] [59] [60] [61 ] [62] [63] [64] [65] [66] [67] [68] [69] [70] [71 ] [72] [73]
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RJ. Roberts, RC. Rowe, Int. J. Pharm. 36 ( 1 987) 205. S.J. Lukasiewicz, J.S. Reed, Am. Ceram. Soc. Bull. 57 ( 1 978) 798. B.J. Briscoe, S.L. Rough, Coll. Surf. 1 37 ( 1 998) 1 03. E.E. Walker, Trans. Faraday Soc. 19 ( 1 923) 73. JAR Cooper, L.E. Eaton, J . Am. Ceram. Soc. 45 ( 1 962) 97. K. Kawakita, Y. Tsutsumi, Bull. Chem. Soc. Jpn. 39 ( 1 966) 1 364. RW. Heckei, Trans. Metall. Soc. AlME 221 ( 1 96 1 ) 671 . RW. Heckei, Trans. Metall . Soc. AlME 221 ( 1 96 1 ) 1 00 1 . P. York, J . Pharm. Pharmacol. 2 5 ( 1 973) 1 P. T.RR Kurup, N . Pilpel, Powder Technol. 1 9 ( 1 978) 1 47. K. Kawakita, K.H. Ludde, Powder Technol. 4 ( 1 970/1 971 ) 6 1 . M . Yamashiro, Y . Yuasa, K . Kawakita, Powder Technol. 34 ( 1 983) 225. M. Sheikh-Salem, J.T. Fell, J. Pharm. Pharmacol. 33 ( 1 98 1 ) 491 . M.J. Adams, R McKeown, Powder Technol. 88 ( 1 996) 1 55. J A Hersey, J.E. Rees, Nature 230 ( 1 97 1 ) 96. P.J. Rue, J.E. Rees, J. Pharm. Pharmcol. 30 ( 1 978) 642. P. York, J . Pharm. Pharmacol. 31 ( 1 979) 244. F.X. Muller, L.L. Augsburger, J. Pharm. Pharmacol. 46 ( 1 994) 468. G. Ragnarsson, J. Sjögren, J. Pharm. Pharmacol. 37 ( 1 985) 1 45. P.J. Denny, Powder Technol. 1 27 (2002) 1 62. A Hassanpour, M . Ghadiri, Powder Technol. 1 41 (2002) 251 . J . M . Sonnergaard, Int. J. Pharm. 1 93 ( 1 999) 63. F. Niklasson, G. Alderborn, Pharm. Res. 17 (2000) 949. A Samimi, A Hassanpour, M. Ghadiri , Chem. Eng. Sci. 60 (2005) 3993. B. Eiliazadeh, B.J. Briscoe, K.G. Pitt, Y. Sheng , Part. Syst. Technol. 21 (2003) 303. B. Eiliazadeh, K.G. Pitt, B. Briscoe, Int. J. So lids Struct. 41 (2004) 5967. H . M . Macleod, K. MarshalI, Powder Technol. 16 ( 1 977) 1 07. B.J. Briscoe, N. ÖZkan, I. Aydin, Proc. Eighth Cimtech World Ceramics Congress, Florence, Italy, 1 994, p. 1 667. B.J. Briscoe, PD. Evans, Powder Technol. 65 ( 1 99 1 ) 7. P.L. Catellani, P. Santi, E . Gasperini, S. Ciceri , G. Dondi, P. Colombo, Int. J . Pharm. 88 ( 1 992) 285. P.R Watt, Tablet Machine Instrumentation in Pharmaceutics: Principles and Practice, Ellis Horwood Limited, Chichester, UK, 1 988. I . C . Sinka, J .C . Cunningham , A Zavaliangos, Powder Technol. 1 33 (2003) 33. J . E . Rees, E. Shotton, J . Pharm. Pharmacol. 22 ( 1 970) 1 7S. F.F.L. Carneiro, A Barcellos, R I .L.E.M. Bull. 18 ( 1 953) 99. T. Akazawa, R I .L.E.M. Bull. 16 ( 1 953) 1 1 . P.J.F. Wright, Mag. Concrete Res. 7 ( 1 955) 87. R Berenbaum, I. Brodie, Br. J. Appl. Phys. 1 0 ( 1 959) 281 . E . Addinall, P . Hackett, Civil Eng. Publ . Works Rev. 59 ( 1 964) 1 250. J .T. Fell, J . M . Newton, J . Pharm. Sci. 59 ( 1 970) 688. S. Timoshenko, J . N . Goodier, Theory of Elasticity, 2nd edition, McGraw-HiII, New York, 1 970. K.G. Pitt, J . M . Newton, R Richardson, P. Stanley, J. Pharm. Pharmacol. 41 ( 1 989) 289. R Peltier, R I .L.E.M. Bull . 1 9 ( 1 954) 33. A Procopio, A Zavaliangos, J . C. Cunningham, J. Mater. Sci. 38 (2003) 3629. A. Rudnick, AR Hunter, F.C. Holden, Mater. Res. Stand. 1 ( 1 963) 283. N . B . MitcheII, Mater. Res. Stand. 1 ( 1 96 1 ) 780s. J . E . Rees, JA Hersey, E.T. Cole, J. Pharm. Pharmacol. 22 ( 1 970) 64S. J . P . Den Hartog, Advanced Strength of Materials, MaGraw-Hill, New York, 1 952. P. Stanley, Int. J. Pharm . 227 (2001 ) 27. P. Stanley, J . M . Newton, J. Pharm. Pharmacol. 32 ( 1 980) 852.
778 [74] [75] [76] [77] [78] [79] [80] [81 ] [82] [83] [84] [85] [86] [87] [88] [89] [90] [91 ] [92] [93] [94] [95] [96] [97] [98] [99] [ 1 00] [101] [1 02] [1 03] [1 04] [1 05]
K. Pitt and C. Sinka B.C. Hancock, S.O. Clas, K. Christensen, Int. J. Pharm. 209 (2000) 27. B.C. Hancock, S.o. Clas, K. Christensen, I nt. J. Pharm. 228 (2001 ) 1 39. M.S. Church, J .w. Kennerley, J . Pharm. Pharmacol. 35 ( 1 983) 43P. M . F. Ashby, D.R.H. Jones, Engineering Materials 1 : An I ntroduction to Properties, Applications and Design, 3rd edition, Elsevier Butterworth-Heinemann, Amsterdam, Boston, 2005. M.F. Ashby, D.R.H. Jones, Engineering Materials 2: An I ntroduction to Properties, Applications and Design, 3rd edition, Elsevier Butterworth-Heinemann, Amsterdam, Boston, 2005. K. Van der Voort Maarschalk, K. Zuurman, H. Vromans, G . K. Bolhuis, C.F. Lerk, Int. J . Pharm. 1 51 ( 1 997) 27. H. Takeuchi, S. Nagira, H. Yamamoto, Y. Kawashima, I nt. J . Pharm. 274 (2004) 131. B.J. Briscoe, S.L. Rough, Powder Technol. 9 9 ( 1 998) 228. AA. Griffith, Trans. R. Soc. A 221 ( 1 920) 1 63. R.W. Hertzberg, Deformation and Fracture Mechanics of Engineering Materials, 4th edition, Wiley, New York, 1 996. F.C. Masilungan, K.F. Kraas, Drug Dev. Ind. Pharm. 1 5 ( 1 989) 1 771 . O.F. Akande, M . H . Rubinstein, P.H. Rowe, J . L. Ford, I nt. J. Pharm. 1 57 ( 1 997) 1 27. S.C. Mann, D . B. Bowen, B.M. Hunter, R.J. Roberts, R.C. Rowe, R.H.T. Tracey, J . Pharm. Pharmacol. 33 ( 1 98 1 ) 25P. R. Chopra, F. Podczek, J . M . Newton, G . Alderboran, Eur. J. Pharm. Biopharm. 53 (2002) 327. J.J. Lannutti, M RS Bull. 22 ( 1 997) 38. D . M . Wood, Soil Behaviour and Critical State Soil Mechanics, Cambridge University Press, Cambridge, 1 990. R.M. Koerner, Ceramic Bull. 52 ( 1 973) 566. I .C . Sinka, AC.F. Cocks, C.J. Morrison, A. Lightfoot, Powder Metall . 43 (2000) 253. I .C. Sinka, AC.F. Cocks, J . H . Tweed, J. Eng. Mater. Technol. 1 23 (200 1 ) 1 76. L. Schneider, A.C.F. Cocks, Powder Metall. 45 (2002) 237. I . M . AI-Khattat, S.T. AI-Hassani, Chem. Eng. Sci. 42 ( 1 987) 702. J . R.L. Trasorras, R. Parameswaran, A.C.F. Cocks, ASM Handbook, Powder Metal Technologies and Applications, ASM I nternational, Vol. 7 1 998, p., 326 A.N. Schofield, C.P. Wroth, Critical State Soil Mechanics, McGraw-HiII, London, 1 968. D.C. Drucker, W. Prager, Q. Appl. Math. 10 ( 1 952) 1 57. A.C.F. Cocks, I .C. Sinka , Mech. Mater. in press. P. Redanz, NA Fleck, Acta Mater 49 (200 1 ) 4325. R.S. Ransing, R.W. Lewis, D.T. Gethin, Philos. Trans. R. Soc. Lond. A- Math. Phys. Eng. Sci. 362 (2004) 1 867. A Procopio, A. Zavaliangos, J . Mech. Phys. Solids 53 (2005) 1 523. K.G. Ewsuk (Ed.), Compaction science and technology, M RS Bull. 22 ( 1 997) 1 4 M . Reiterer, T . Kraft, U . Janosovits, H . Riedei , Ceram. I nt. i n Press T. Kraft, H. Riedle, O. Rosenfelder, I nt. J. Powder Metall. 39 (2003) 27. J . o . Kirsch, J . K. Drenne, J. Pharm. Biomed. Anal. 1 9 ( 1 999) 362.
CHAPTER 1 7 D i rect Pel letizat i o n of P ha rmace utical Pel lets i n F l u i d- Bed P rocesses Peter Kleinebudde * and Klaus Knop
Institute of Pharmaceutics and Biopharmaceutics, Heinrich-Heine-University Duesseldorf, Universitaetsstr. 1, 40225 Duesseldorf, Germany Contents
1. 2. 3. 4. 5. 6.
Fluid-bed equipment Granulation vs. pelletization Direct pelletization vs. layering of seeds Mechanisms of agglomeration/pelletization Response variables Wet pelletization 6. 1 . Process description 6.2. Pelletization aids 6.3. Equipment variables 6.3. 1 . Type of equipment 6.3.2. Diameter of rotor plate 6.3.3. Number, diameter and distance of spray nozzles 6.3.4. Surface of the rotor plate 6.3.5. PTFE lining, baffles and choppers 6.4. Process variables 6.4. 1 . Load 6.4.2. Spray rate 6.4.3. Rotor speed 6.4.4. Wet-massing time 6.4.5. Inlet air temperature 6.4.6. Air flow rate 6.4.7. Atomizing air pressure 6.4.8. Gap width/pressure difference 6.5. Formulation variables 6.5. 1 . Fraction of drug 6.5.2. Particle size and size distribution 6.5.3. Type and amount of binder 6.5.4. Solubility 6.5.5. Moisture content 6.6. Reproducibility
*Corresponding author. E-mail:
[email protected] Granulation Edited by A.D. Sa/man, MJ. Houns/ow and J. P. K. Seville " 2007 Elsevier SV All rights reserved
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7. Melt pelletization 7. 1 . Process description 7.2. Advantages of the process 7.3. Meltable binders 7.4. Mechanisms of pellet formation 7.5. Variables with influence on the process of melt agglomeration 7.5. 1 . Equipment variables 7.5.2. Process variables 7.5.3. Formulation variables 7.6. Process monitoring and control References
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1 . FLUID-BED EQUIPMENT
Currently, there are two kinds of fluid-bed equipment available for direct pellet ization: the conventional fluid-bed granulator and the rotary fluid-bed processor. The schematic diagram of a conventional fluid-bed granulator is shown in Fig. 1 A. The product (first powder, later granules or pellets) is fluidized in the cylindrical product container by an airstream. The in/et air passes a screen or a perforated plate, fluidizes the particles and leaves the product container through a filter. This exhaust air filter prevents product losses and air pollution. The fluidizing air can be heated to the desired temperature to dry or melt the fluidized product. The binder solution or molten binder is sprayed onto the fluidized particles through a nozzle which has to be heated in case of molten binder. The spray nozzle is usually an air-atomising nozzle which uses pressurized air to produce droplets from a liquid. The droplet size can easily be controlled by the atomizing air pressure. The position of the nozzle is above the f1uidized product in most cases .
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A rotary fluid-bed processor (Fig. 1 B) has a rotating friction plate instead of a screen at the bottom of the product container. The inlet air passes through an air gap between the rotating plate and the wall of the product container. The movement of the particles in the equipment is helical and is the result of three forces: the centrifugal forces from the rotating plate, the fluidizing force from the airstream through the gap and the force of gravity. The nozzle or the nozzles in the rotary processor are often positioned tangentially in the wall of the container in the height of the fluidized product. A more detailed description of fluid-bed equipment is given in chapter "Equip ment" by Jacob. 2. G RANU LATION VS. PELLETIZATIO N
The term pellet is used i n many industries like food, animal feed, fertilizer, plas tics, mining, chemical and energy industry. Depending on the requirements of the intended use the pellet properties differ, e.g. in their size and mechanical strength. In some cases the pellets have diameters of several centimetres. Pharmaceutical pellets are agglomerates made from fine powder particles, characterized by nearly spherical or cylindrical shape, mean diameters of 0.2-2.0 mm and a narrow particle size distribution. The surface of pellets is typi cally smooth and of low porosity. The size range is typical for granules and pellets. Smaller particulate dosage forms are usually denoted as microparticles and larger particles are usually tab lets prepared by uniaxial compression. The defined shape, smooth surface and small particle size distribution distinguish pellets from conventional agglomerates or granules. Conventional granules usually have an irregular shape, a rough surface and a broader particle size distribution. Thus, pellets are a special type of granules. However, there is a smooth tran sition between granules and pellets and a lot of controversy and discussion ap pears in the literature about the identification of agglomerated particles as pellets or granules. One simple approach for the c1assification is based on shape pa rameters derived from image analysis. The surface structure and the particle size distribution are not taken into account by this approach. There is also controversy concerning suitable shape parameters. One parameter is the aspect ratio, de fined as the ratio of the longest Feret diameter and the Feret diameter perpen dicular to this diameter. Most image analysis systems allow the calculation of the aspect ratio. An ideal sphere should have an aspect ratio of 1 . With increasing aspect ratio the deviation from spherical shape increases. In practice, the value 1 for aspect ratio is usually not achieved due to unavoidable errors in image anal ysis systems. Therefore, a mean aspect ratio of 1 . 1 can be considered as prac tically spherical [1 ,2].
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Pellets can be manufactured in the same way as granules. In most cases some process parameters have to be fixed and controlled more strictly and at the same time changes in the formulation variables, e.g. the amount of granulation liquid, are required to obtain pellets instead of granules. In some cases special excipi ents are required for pelletization. In many cases pellets are coated in orderto obtain the desired release profile of the dosage form. In this case pellets are advantageous compared to conventional gran ules. The specific surface area of pellets having a defined particle size is smaller due to the spherical shape and smooth surface. This allows the use of less film forming polymer to achieve a required film thickness, simplifies the coating process and improves the reproducibility of the release profile, which is critical for drug products. The use of pellets is of relevance and importance, if the release profile relies on the intact body of the dosage form. Therefore, pellets are frequently used in gastric resistant and modified release dosage forms. In these cases multiple unit dosage forms (MUDF) like pellets have important biopharmaceutical advantages compared to single unit dosage forms (SUDF) like coated tablets. Usually, several hundred pellets filled into a capsule give one dose. The capsule shell dissolves rapidly after application. The passage time in the gastrointestinal (GI)-tract is more consistent for M UDF, which results in less variation concerning the plasma level-time profiles ofthe drug. Consequently, the reliability of the dosage form is higher in the case of MUDF. A coated SUDF can result in undesired release behaviour (time or place of release), if the coating film breaks during production, storage or application. This so called dose dumping, probably leading to severe unwanted effects of a drug product, is less likely to occur for MUDF like coated pellets. Owing to the dis tribution of the pellets in the GI-tract the risk of a local irritation is diminished. Furthermore, several pellets with varying release profiles can be combined within one dose allowing the adjustment of the final release profile. Compared to larger SUDF the specific surface area of pellets is much higher. This requires a higher amount of polymer per dose to achieve the desired film thickness and leads to longer coating process. The volume of the dosage form is higher for MUDF, which is a problem of swallowing, especially in case of high-dose drugs. Recently, coated pellets are compressed to rapidly disintegrating tablets [3]. For those purposes small pellets with mean diameters below 0.5 mm are most suitable. Such pellets can be produced by the direct pelletization methods described below. 3. DIRECT PELLETIZATION VS. LAYERIN G OF SEEDS
Owing to their internal structure homogeneous pellets can be distinguished from heterogeneous pellets. 80th types can be coated with a thin polymer film. Hetero geneous pellets consist of an inner core region and an outer shell region of a different composition. Homogeneous pellets have a macroscopically uniform structure without a core region.
783
Direct Pelletization of Pharmaceutical Pellets
The layering on seed material or starting core material leads to heterogeneous pellets. Usually, sugar spheres consisting of a sugar-starch mixture are used as seed material. Recently, spherical particles made of microcrystalline cellulose (MCC) gained more attention. In some cases, pure drug crystals or other ma terials like solid acids (e.g. tartaric acid) are used as seed material for the pel letization. Usually, a solution or suspension of the drug is sprayed on the seed materials. It is also possible to add the drug continuously as a fine powder and fix it on the seed material by the addition of a binder solution. The layering can be performed in many types of equipment: disc or pan agglomerators, conventional fluid-bed equipment, rotary fluid-bed equipment, etc. (Figs. 2 and 3). Owing to the simple process and equipment requirements layering processes are widely used for pelletization. However, there are some disadvantages. The
Ro llin g
statting germ
Powder
Binder droplets
DryinQ/ Solidifying
Liquid
bri d g e
Solid bridge
L.. y.r form.tion
First layer
P e l let
"Onion" structure
Fig. 2. Principle of the powder layering process (Souree: Glatt) .
Wettingl distribution
Soli dify i n g/Layer formation
Pe l let
t
Starti n g core
S u s p e n d e d a u x i l ia ry m atter a n d d i s s oilled b i n d e r
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" O n i o n " structure
Fig. 3. Principle of the suspension and solution layering process (Souree: Glatt).
784
P. Kleinebudde and K. Knop
Spr�ying
Powder Si n d e r droplets
Rolling
Liq u i d bridge
Drying/Solidifying
Pellet
S o l i d b ri d g e
Fig. 4. Principle of the direct pelletization process (Source: Glatt).
amount of drug loading is usually limited. Therefore, layering processes are not suitable for high-dose drugs. If a spray loss occurs, the composition of the final pellets can vary. This can have negative consequences for the drug content and the uniformity of content. In direct pelletization processes, the powdered starting materials are converted into homogeneous pellets in one process. The pelletization is facilitated by the addition of a binding liquid and allowing a suitable movement of the wetted pow ders. According to the nature of the liquid binder the process is described as wet pelletization or melt pelletization. In a wet pelletization process the binding liquid is liquid at room temperature. The solidification of the pellets is achieved by drying the liquid. The evaporation of the binding liquid leaves the drug and other excipients. Melt pelletization is performed at elevated temperatures at which the binder is molten. Solidification of the pellets is achieved by cooling so that the binding liquid solidifies. The pellets contain the drug, the solidified binding liquid and probably other excipients. The pellets are usually almost spherical. However, at the same time they are of a certain minimal size distribution. Direct pelletization processes are mainly performed in high shear mixers and fluid-bed equipment. Although the direct pelletization processes are known since a long time they have not been used widely for the production of spherical pellets ( Fig. 4). In this chapter, only direct pelletization processes are discussed but not lay ering processes. Furthermore, only fluid-bed processes are considered.
4. MECHANISMS OF AGGLOMERATION/PELLETIZATION
The mechanism of nucleation and particle growth in wet fluid-bed agglomeration is described in detail in "fluidized-bed spray granulation" by Mörl and Heinrich
Direct Pelletization of Pharmaceutical Pellets
785
and in "Fluidization of cohesive powders" by Seville. A comprehensive review of the mechanisms of agglomeration during wet granulation is given by Iverson et al. [4]. During fluid-bed granulation, the fluidized powder particles are wetted by the binder solution which is sprayed onto the particles. These wetted particles can stick together by random collision and form greater agglomerates. For the for mation of pellets it is necessary that the agglomerates remain in a sufficiently wet state to allow plastic deformation and densification. So the liquid saturation of the agglomerates during the granulation phase is one important factor in fluid-bed pelletization. The other one is the height of the shearing forces. Only if these forces are high enough to deform and densify the wet agglomerates pellets can be formed. In a conventional fluid-bed granulator, the shearing forces are rather low and pelletization is only possible under optimized conditions. In a rotary processor, the pellet formation is easier due to the higher shearing forces applied from the rotating friction plate. 5. RESPONSE VARIABLES
The response variables for pharmaceutical pellets are mainly related to the later use of these pellets. Thus, in most of the pharmaceutical literature the produced pellets are characterized with respect to several response variables. These are the same for wet and melt pelletization processes. Most important for the finished pellet product is the desired dissolution profile. Depending on the intended use, an immediate or modified dissolution of the incorporated drug is intended. Usually, immediate or fast releases rely on a fast disintegration or dissolution of the whole pellet after application. A modified dis solution can either be achieved by the uncoated pellet itself or by applying a coating polymer on the pellet. Since pellets are coated afterwards in many cases, the outer specific surface area should be constant from batch to batch resulting in a high product con formity. The thickness of the polymer film depends on the ratio of applied polymer to the surface area of the pellets. In order to achieve the conformity of the specific surface area, it is necessary to produce pellets of an equal mean particle size and particle size distribution, of an equal shape, porosity and surface texture. A de viation for one or more parameter will result in different specific surface area, leading to a change in film thickness and consequently in the intended dissolution profile [5]. Apart from the variables mentioned above, certain mechanical properties like the breaking force or the friability are of importance for further handling of the pellets. Further interesting response variables are the flow properties as weil as bulk and tapped density of the pellets.
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P. Kleinebudde and K. Knop
In order to evaluate the production process the yield is also used as a response variable. In some cases the total yield is determined. This includes the whole pellet batch. A loss in total yield can be attributed to material adhering to the wall or the friction plate or material, which has been transported to the filter or even leaving the equipment. The total yield can therefore be a useful response variable to describe the process performance. However, in many studies the usable yield is used as a response variable. For this purpose, a more or less broad range of particle sizes is arbitrarily defined as usable yield of the pellets. There are large differences for this definition depending on the intended use of the pellets, which makes a comparison of the usable yield values impossible. The definition for the undersized pellets (fines) or the oversized pellets (Iumps) also depends on the goals of the individual study and is somewhat arbitrary, making comparisons impossible. Sometimes the usable yield is used together with the mean particle size or a particle size distribution, but in other cases it is used instead. If the primary of the paper is to optimize a certain product the usable yield might be appropriate. However, if the primary focus of the paper is to understand the process, the usable yield does not help. For example, if authors find that a certain change of a process parameter results in a decrease of the usable yield, this finding does not contribute to the understanding of the process. Possibly the yield is decreased by an increase in particle size, because the fraction of oversized pellets is increased. An increase of undersized pellets due to a smaller particle size can also reduce the usable yield. Even a simultaneous increase of oversized and undersized fractions indicating a broadening of the particle size distribution or a change to a bi modal particle size distribution will lower the usable yield. It can be recom mended to use appropriate parameters for the mean particle size and the var iation in particle size or to give the whole particle size distribution instead of using the usable yield. In many cases experimental designs like full or fractionated factorial designs are used to investigate a certain pelletization process. From these experiments certain conclusions can be drawn from the investigated design space, but offen it is difficult to generalize these conclusions. Mechanistic approaches are rarely found in the pharmaceutical literature.
6. WET PELLETIZATION 6.1 . Process description
Direct wet pelletization can be performed in different types of fluid-bed equip ment. It can be described as a one pot process, because all process steps can be performed in the same type of equipment. A few studies are available using
Direct Pelletization of Pharmaceutical Pellets
787
conventional fluid-bed equipment [6-8]. Most work is based on the use of rotary or centrifugal fluid-bed equipment. The rotor insert comprises a cylinder with a solid rotating disc at its base leaving a gap between the cylinder and the rotating disc for the fluidizing air. Thus, a rotary processor is a hybrid between a fluid bed and a spheronizer (see chapters "Equipment" and "ExtrusionjSpheronisation"). The further process description focuses on rotary processing. A review from Gu et al. on wet pelletization by rotary processing has been published recently [9]. Rotary granulation is similar to fluid-bed granulation with the exception that the rotating disk produces a denser, rounder, smoother surfaced granule due to the acting agitative forces. In rotary equipment, three forces are acting at the same time: the centrifugal force created by plate rotation, the vertical force created by slit air and the gravitational force allowing the product to fall towards the centre of the rotor plate. An ideal product movement is of high i mportance. This movement is described in terms of rope-like tumbling, twisted rope, spiral, spiralling helix and others. Especially in the beginning of the process having a dry or moderate wet powder this movement is difficult to achieve. However, at the end of the process the movement is of critical importance. Usually, different steps of the process can be distinguished: 1 . The first step is called setup or mixing andjor heating. During this step most process parameters are adjusted to their set values. At the same time mixing can occur and the inlet air temperature can be increased above room tem perature in order to avoid condensation of liquid during the following spraying phase. 2. During the second stage of the process, called spraying, moistening or liquid addition stage, the powder is moistened by spraying a liquid to the powder continuously. Usually, the spray nozzle is placed in the powder bed and a tangential spraying is chosen. This setup allows a very uniform distribution of the liquid in the powder bed with a minimal disturbance of the product move me nt. Homogeneous distribution of the liquid is a prerequisite to avoid adhe sion to the product chamber wall. The added liquid is partly removed by the fluidized air. The spray rate exceeds the drying rate giving rise to a steady increase in product moisture content. During the spraying stage the fluidization of the mass will become less effective, because the liquid addition and the agitating forces cause a densification of the mass. An induction period where nuciei agglomerates are consolidated but do not grow is followed by coales cence growth. Thus, the process can be described by an induction growth showing a delay period during which little growth occurs. After reaching a certain, probably desired moisture content of the liquid spraying is terminated. If a constant amount of liquid is applied to the powder, the final moisture content depends on many other variables like the amount, humidity and ve locity of the fluidizing air, the liquid spray rate, the rotor speed and the batch
788
P. Kleinebudde and K. Knop
size. The moisture content of the mass at the end of the liquid addition is critical for the formation of pellets. At any time the moisture content of the granules depend on the extent of liquid addition and evaporation. Methods for end-point control are presented in Chapter 1 0 by S. Watano. 3. After spraying is stopped, usually the rotor plate continues to run at the same or a different speed as before. This stage is ca lied spheronization or wet massing. At latest during this phase the rope-like movement occurs and pellets are formed and will grow further. During this stage the pellets can initially grow further and the shape can be improved. However, due to evaporation the moisture content of the pellets starts to drop and a further growth is Iimited due to a decreasing deformability. 4. At the end of the process drying can take place usually at elevated inlet air temperature. However, due to the Iimited drying capacity of the single-wall rotary processors drying might be performed externally. It is highly important that the total load of powder is moved all the time and a loss of powder or wet mass does not occur due to pneumatic transport in the first stage before being wet enough, due to slipping through the gap between the rotor plate and the wall of the chamber or due to adhesion to the wall of the chamber or to the friction plate after being wetted. The remaining solid mass will be over wetted by applying a fixed amount of wetting liquid and the rope-Iike movement can be disturbed significantly. A uniformly moistened mass is essential for sphe roid formation and growth in a controlled manner to give pellets with a narrow size distribution [1 0]. Only a few papers give information about the evolution or kinetics of the proc ess parameters [1 2,1 3]. Figure 5 gives an example for a direct wet pelletization process [1 1 ]. After filling the powder mixture into the chamber the fluidizing air flow was initiated while the friction plate was elevated to adjust the air gap pres sure difference and then the rotation of the friction plate was turned on. Tem perature and fluidizing air flow rate were set to 40°C and 90 m 3 h - 1 , respectively. After the setup, the liquid addition started (first vertical line in Fig. 5). The initial decrease in the fluctuating torque values seemed to be related to the warming up of the rotary processor. During this period the water content of the powder in creased and the mass became denser. After a certain liquid addition time a rapid increase in torque was observed, accompanied by a further densification of the mass and a faster, rope-like movement of the mass. The increase in torque (�Tq) was computed as the difference between the minimum torque value (baseline) and a running mean of the last 1 00 torque values. The liquid addition was con tinued until the �Tq reached a desired value. After the liquid addition was stopped (second vertical line in Fig. 5) wet massing was continued for 6 min while the torque values started to decrease.
789
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Fig. 5. Process description of a direct pelletization experiment; development of different process parameters; (a) torque; (b) air gap pressure difference and f1uidizing air flow rate; (c) inlet air temperature (upper profile), product temperature (middle profile), outlet air temperature (lower profile); the vertical lines indicate start and stop of liquid addition [ 1 1 ] .
Direct wet pelletization is a multivariate process that demands a high level of control of all variables in order to achieve the desired product characteristics [14].
6.2. Pelletization aids
A suitable formulation for spheronization should possess a certain plasticity. In direct wet pelletization, the required plasticity is achieved by adding liquids,
790
P. Kleinebudde and K. Knop
especially water, to suitable powder mixtures. The fraction of liquid binder is critical for the success of the process. MCC is often used as a spheronization or pelletization aid in direct wet pelletization. MCC is weil known as a pelletization aid in extrusionjspheronization. The role of MCC has mainly been discussed with respect to extrusionjspheronization, but the proposed models can also be applied to direct pelletization [ 1 5]. On the basis of thermal studies about the interaction of water and MCC, Fiel den et 81. [ 1 6] have suggested that MCC can be described as a 'molecular sponge'. The material is capable of physically retaining a high percentage of water within itself, but allowing removal by evaporation to take place with great ease. The highly absorbent and moisture-retaining characteristics are physical in nature and unaffected by processing. The function of MCC is claimed to be twofold: it controls the movement of water through the wet powder mass during extrusion and modifies the rheological properties of the other ingredients in the mixture, conferring a degree of plasticity. The 'sponge' model has been explained further by Ek and Newton [1 7]. During extrusion, the 'sponges' are compressed until water is squeezed out and lubricates the particles flowing through the ex truder. Variations in water content will be needed for different types of extruders because different shear forces are involved. After extrusion, the volume of the 'sponges' will increase and the extrudate will be apparentiy 'dry' and brittle, allowing it to be chopped into short lengths in the spheronizer. Subjecting these cylinders to the forces of spheronization again compresses the 'sponges' and will allow deformation of the 'soft' structures. The 'sponge' model explains a number of observations and has been supported in the literature [1 8,1 9] . Another model has been proposed by Kleinebudde [20,21]: the 'crystallite-gel' model. He proposed that a 'gel' is formed during extrusion with MCC. In the presence of a liquid, especially of water, the MCC particles will break down into smaller subunits due to the application of shear forces during granulation and extrusion. With increasing shear stress this process will be more or less com plete, finally single crystallites of colloidal size may occur. These single particles are able to form a 'crystallite gel' and immobilize the liquid. The viscosity of the 'gel' depends on the particle size of the resulting components and the liquid content. Because the disruption into single crystallites is thought to be incom plete, the plastic, hydrated, semisolid mass of MCC is not a gel in the classical colloid chemical sense [22]. However, the resulting crystallites and porous par ticles form a coherent 'gel-like' network with a high fraction of insoluble solid phase and immobilize the granulation liquid. The inclusion of further components into the formulation leads to a two-phase model of a wet extrudate: a percolating 'crystallite-gel' phase formed by MCC and water during extrusion and a filler phase formed by the second component of the binary mixture. During 'gel' for mation the MCC particles are rearranged. The coherence of the solid network can be established by the formation of secondary valence bonds between the
Direct Pelletization of Pharmaceutical Pellets
791
amorphous ends of the single crystallites or the crystallites on the surface of aggregates. The 'crystallite-gel' model is able to explain many observations and was applied also to other granulation processes [1 5,23,24]. Neither of the two models has been directly proved and there is some debate about the value of these models. While the 'crystallite-gel' model proposes a change in the particle structure during processing, the 'sponge' model implies that the original particles will stay intact. The breaking of the aggregates into individual particles was thought to be unlikely to occur by extrusion as the shear forces are relatively low [1 7]. The individual particles of MCC are very difficult to reduce further in size to colloidal dimensions by mechanical means. Individual particles and their agglomerates have been differentiated concerning particle size analysis of MCC [25]. During characterization of MCC, different degrees of de-agglom eration may be applied. Individual particles were separated from agglomerates by ultrasonic treatment of a water suspension of agglomerates. The median weight diameter of the individual particles was in the range of 20-30 11m for three types of MCC while the agglomerates were in the range of 80-1 20 11m. Brittain et 81. have shown that the mean particle size of an MCC suspension decreases with the energy input during the preparation of the suspension [26]. The blending step needed to affect the suspension of the material results in a disintegration of the MCC particles and a concomitant increase in the viscosity of the slurry. In wet extrusion as weil as in wet granulation it has been observed several times that the structure of the original MCC particles has changed deeply [20,23,24,27]. Dif ferent types of MCC produced colloidal particles after high-pressure homogen i zation [28]. In the same study it was confirmed that extrudates from the same types of MCC also contained colloidal particles. In the presence of water it is possible to decrease the particle size of MCC by applying mechanical energy. In a monograph about microcrystal polymer science, Battista has suggested as definition: systems of colloidal-size polymer microcrystals whose suspensoid properties are largely determined by the relative proportion of discrete unit par ticles in suspension vs. the proportion of the same particles present as aggre gates, each aggregate containing varying numbers of the same microcrystals clustered together [29]. One important example for microcrystal polymer science is MCC. Gels can be produced from MCC [30]. These gels are clearly composed of a highly polydisperse distribution of cellulose microcrystals and aggregates thereof. The microcrystals are released into a liquid medium by mechanical en ergy. Recovery of the smallest microcrystal unit component is highly dependent on the severity of the mechanical disintegration treatment. Mechanical agitation in a water slurry frees a fraction of the unhinged crystals. This fraction can be increased by improvement in mechanical energy input, preferably by high-shear action. The presence of a minimal concentration of single colloidal microcrystals in association with much larger colloidal particles comprising aggregations of the aforementioned basic unit microcrystal is a prerequisite for the formation of stable
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P. Kleinebudde and K. Knop
polymer microcrystal gel system. The microcrystals pervade the whole system at low concentrations without settling, the insoluble microcrystals touching each other. Their three-dimensional network has a certain rigidity and consequently they should be characterized as gels. Commercial pure MCC gels may have only 20-30% of individually dispersed microcrystals; the remainder are made up of aggregates of unhinged microcrys tals as large as 1 0-50 Jlm. It is important therefore to recognize this fact in interpreting data on the measured properties of MCC gels. The size and shape of the microcrystals, as weil as the properties of each cellulose suspensoid, de pends on the history of the precursor cellulose fibres. In general, an increase in the viscosity of a gel at a fixed solid concentration relates to the efficiency of microcrystal deaggregation. However, once a certain percentage of microcrystals have been freed and hydrated to develop maximum viscosity, it is difficult to produce further deaggregation of the remaining aggregated particles, probably because the brush-heap matrix of hydrated single crystals shields the remaining aggregates from direct shear-energy input. The general viscosity properties of MCC solutions are affected by the size of the microcrystals (which varies widely depending on the source), the polydispersity or size distribution (which is influ enced by the method and severity of mechanical attrition used), and the total concentration of particles. The amount of water or granulation liquid required for pelletization depends on the fraction of MCC in the formulation [1 5,31]. A linear relation between the amount of water (based on dry mass) and the fraction of MCC has been found (Fig. 6). Compared to extrusionj spheronization or high-shear granulation, the shear forces applied in fluid-bed processes including the rotor processes are rather low. This results in a lower slope of the straight line [1 5]. If the fraction of MCC is va ried in an experimental plan, the amount of liquid should be adapted. If the amount of liquid is kept constant, the results are not directly comparable. Table 1 gives an overview about the fraction and type of MCC used for direct pelletization. Depending on the individual process and the incorporated drug, 1 0-45% MCC are recommended for successful pelletization [1 5,31 ,32]. With 1 0% pelletization was possible, while other formulations required 20% or more of MCC [32]. Vecchio et al. [31 ] reported that 30-45% of MCC brought satisfactory results; a decrease led to an increased stickiness of the material and produced irregular large granules. With 1 5% of MCC they observed a bimodal size dis tribution. MCC not only confers plasticity to the wetted mass, but also imparts binding properties that are essential to obtain pellet strength and integrity. The type of MCC was found to be of less importance concerning the final pellet properties [33]. While some authors use a fixed level of MCC others study the importance of the fraction of MCC in the formulation. In some cases the studied range is rather smalI, e.g. 30-35% [14], while in other cases a wide range has been investigated, e.g. 1 0-1 00% [1 5,33].
793
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Source [6-8, 35] [13,32,36] [33] [1 5] [31 ] [37] [38] [ 1 0,39,40] [41 ] [34] [42] [43] [5,1 4,44] [45] [12] [46] [47] [48] [1 1 ] [49] [50] [51]
MCC type
MCC fraction
Avicel PH 1 02 Avicel PH 1 0 1 , 1 02, 200 Avicel PH 1 0 1 Avicel P H 1 0 1 Avicel PH 1 02 Emcocel 50M Avicel PH 1 0 1 Avicel P H 1 0 1 (bentonite, kaolin) Avicel PH 1 0 1 Avicel PH 1 01 Avicel PH 1 01 Avicel PH 1 01 Avicel PH 1 01 Emcocel Avicel PH 1 0 1 , PH 1 02, RC 591 Avicel RC 581 Avicel CL-6 1 1 or RC 581 Avicel PH 1 0 1 Avicel PH 1 01 Emcocel 90 M , 50 M, SM1 5, H D90 Emcocel 90M; 50M
1 0; 20; 30 1 0; 30; 50; 75; 1 00 1 0-1 00 1 5; 20; 30; 45 1 8; 47.5 24 25 25 (25) 25; 30; 35 30 30; 40; 50 30; 35 35 40; 1 00 42.5-1 00 50 50 50 50 50 + 50 (core and layering) 50 + 50 (core and layering)
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An increasing fraction of MCC resulted in smaller pellets for the same torque increase [1 5]. This might be attributed to a more pronounced shrinking of these pellets due to the high water content. Paterakis et al. have observed a smaller size distribution of the pellets with increasing fraction of MCC in the formulation [34]. Pellets based on MCC as a pelletization aid possess properties which can be in some cases disadvantageous. For instance, pellets containing MCC tend to swell but do not disintegrate during the application. As a consequence, they release the drug according to a matrix release profile [31 ]. According to the release equations derived by Higuchi, the release depends among other variables on the size of the pellet and the solubility of the drug. For drugs with low solubility, the dissolution rate can be too low. Identifying a pelletization aid that could substitute MCC and give rise to fast disintegrating pellets would be advantageous. Kristensen et al. have used water insoluble hydrated aluminium silicates, namely kaolin and bentonite, as alternative pelletization aids [41 ]. The fraction of kaolin or bentonite was set to 1 5-30%. Kaolin was found to be the most promising candidate for a pelletization aid, because it allowed the formulation of fast-disintegrating and fast-releasing pellets. However, the strength of the pellets from the kaolin for mulation was much lower. Gauthier and Aiache also present formulations without MCC [46]. 6.3. Equipment variables 6. 3. 1. Type of equipment
Different types of fluid-bed equipment can be used for direct pelletization: con ventional, rotary and tumblingjagitated equipment. Most of the work has been conducted in rotary equipment. Well-known rotary processors are made by the companies Glatt, FreundfVector and Niro-Aeromatic (see the chapter on 'Equip ment'). Principally, single-wall and double-wall rotary processors can be distin guished. The double-wall rotary processors have a higher drying capacity, because more air can pass the region between the inner and outer cylindrical wall. While in the rotary processors from Niro-Aeromatic and Glatt the nozzles are spraying tangentially in the bed, the CF-Granulator from FreundfVector uses a top spray system. Direct comparisons between different types of rotary equip me nt are, to the authors' knowledge, not published. Conventional fluidized-bed equipment has been used by Knop et al. [6-8]. The authors have not used microcrystalline cellulose or other pelletization aids but water soluble binder materials instead. In the first attempts the pellets did not show a satisfying strength and density. In a later paper a rotating motion of the material was created by the use of pneumatic nozzles, which were mounted tangentially in the chamber of a conventional fluidized-bed equipment. The
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Direct Pelletization of Pharmaceutical Pellets
rotating motion of the material resulted in a stronger densification and spheronization of the material. In a series of papers, Watano et al. used an agitated fluidized bed for gran ulation purposes [52-56]. An agitator is placed in the fluidized-bed chamber in stead of a rotor plate. The agitator is similar to those used in high-shear mixers and is used to control the movement of the particles in the product chamber. Most of the work has been performed in a rotary equipment with a rotor plate as main equipment detail. Studies have been performed in the equipment from Freund-Vector [47,48,50,51], Glatt [1 1 , 1 2 , 1 5,33,34,37,41-43,46,49,57] and Niro-Aeromatic [5, 1 0, 1 3, 1 4,31 ,32,36,38-40,44,45,58-63]. 6. 3. 2. Diameter of rotor plate
The diameter of the rotor plate is fixed for a given type of equipment. Most of the work has been published for laboratory equipment. Information about scale-up can be found in the chapter on 'Scale-up'. Chukwumezie et al. [48] have studied a scale-up in Flo-Coaters from Vector/Freund using rotor inserts of 9 (FLM 1 ) , 1 2 and 1 9 inch (both FLM 1 5) for batches of 1 , 5 , and 1 0 kg. The results are de scribed in Section 6.4. 1 . -
-
6. 3. 3. Number, diameter and distance of spray nozzles
The number and diameter of the nozzles has not been investigated. In the ma chines from Glatt and Niro/Aeromatic, the nozzles allow a tangential spraying directly in the rotating mass. The distance of spray nozzle between nozzle and rotor plate was studied by Rashid et al. using a CF-granulator [51]. which operates in top spray mode. Variation of the distance in the range 5-7 cm had no significant effects on the studied pellet characteristics. 6. 3. 4. Surface of the rotor plate
A smooth plate applies less energy than a textured plate [42,47], but is best in avoiding material adhesion. The most spherical pellets were achieved using a textured plate [42], which is able to transmit more mechanical energy to the wet mass. However, during drying an excess of mechanical energy can lead to at trition. There is a strong interaction with the rotor speed. A Teflon rotor plate resulted in a higher loss of drying compared to a stainless steel rotor plate [48]. This was attributed to a d ifference in heat conduction. The Teflon rotor plate tended to insulate the pellet bed from the drying medium,
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whereas the stainless-steel rotor plate allowed for a better heat conduction and consequently better heat transfer and drying.
6.3. 5. PTFE lining, baffles and choppers
In some studies a PTFE-lining of the product chamber has been used in order to reduce adhesion of the product to the container wall [ 1 3 , 14,32,36,45]. 8affles and choppers can be used in order to improve the material motion in a rotary processor [45]. Vertommen et al. [14,45] have not seen an effect of an additional chopper on the particle size distribution. The chopper did also not affect the amount of larger agglomerates. 6.4. P rocess variables 6. 4. 1. Load
Liew et al. [1 0] were able to optimize a pelletization process based on a load of 0.5 kg. Robinson and Hollenbeck [37] could show that a larger load improved yield as weil as size and shape characteristics of pellets (0.5 vs. 1 kg). In other studies, the load typically varies between 0.5 kg [39] and 6 kg [32], depending on the size of the rotor plate. Chukwumezie et al. [48] have studied a scale-up in Flo-Coaters from VectorJ Freund batch sizes of 1 , 5, and 1 0 kg. Scale-up was based on geometrie similarity using the radius of the rotor plate and the centrifugal force as similarity factors. The centrifugal force was kept constant by adapting the rotor speed. The particle size appeared to increase with larger batch size. The authors explained this by a greater attrition of the smaller sized batches. The drying efficiency was lower for the larger batch sizes. Therefore, the water content at a given time might be higher at a larger batch size resulting in larger pellets. 6. 4. 2. Spray rate
Together with other variables like the atomizing air pressure, the spray rate de termines the droplet size of the wetting liquid and the uniformity of liquid distri bution in the solid mass [40]. A low spray rate is associated with longer processing time resulting in a lower porosity of the pellets [36]. Higher spray rate results in a higher water content at the end of the spraying stage. The higher spray rates reduce the liquid addition period and during the shorter time less moisture will be evaporated. Thus, a higher spray rate will result in larger pellets, if all other factors are kept constant [31 ,34,39,40]. A higher spray rate was also found to lead to a broader size distribution [34].
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6. 4. 3. Rotor speed
The rotor speed affects mixing, liquid distribution [ 1 0], agitation, pellet growth and shaping. Holm found that the rotor speed was the dominating factor for the po rosity of pellets [36]. In a fractional factorial design, an increase in rotor speed from 1 80 to 280 rpm was the dominating factor for most response variables [51 ] . In this study, the pellets that were larger, showed a higher bulk density and an improved round ness with an increase in rotor speed. In other studies, the pellet size was smaller with an increase in speed, e.g. from 1 000 to 1 400 rpm [49]. The different findings might be explained by the different investigated ranges of rotor speeds, which can lead to different particle growth or particle reduction phenomena. Another explanation might be that the production methods differ from each other. In most studies the rotor speed was constant during mixing, liquid addition, wet-massing and drying. However, Liew et al. [ 1 0] suggested to use different speeds (low-high-Iow) during the different stages. A high rotor speed is useful during the liquid addition stage since it promotes a uniform liquid distribution, which is essential in the process. Furthermore, it reduces the material adhesion and enhances the break up of loose chunks of moist agglomerates. During wet massing, a high rotor speed can induce an excessive coalescence and growth due to stronger centrifugal forces particularly once the powder mass is ade quately wetted. This leads to a wider size distribution. Liew et al. suggest the use of a low rotor speed during mixing and early wet-massing stage until the mass is slightly wetted, which makes it more cohesive and less susceptible to be blown up out of the chamber. During the remaining liquid addition stage the rotor speed should be high but lowered again during the wet-massing stage. This rotor speed regime leads to a more controllable agglomeration process. A reduced rotor speed during the first stage [50] or the drying stage [46] was also recommended by other authors. Pisek et al. [42] reported that using a smooth rotor plate and a higher rotor speed during the wet-massing stage resulted in more spherical pellets with smoother surface. In contrast, using a textured rotor plate smaller and less spherical pellets with a rougher surface were obtained by increasing the rotor speed during the wet-massing stage. 6. 4.4. Wet-massing time
During the wet-massing time the product starts to dry, because no further liquid is added but the air flow leads to an evaporation of the granulation liquid. The drying can result in a change in deformability of the pellets and further drying will lead to an increasing abrasion of particles from the surface of the pellets. During the wet massing stage the pellets can be further spheronized, especially in the beginning at the initial liquid content.
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6. 4. 5. Inlet air temperature
Increasing inlet air temperature decreases the mean pellet size [34]. A higher inlet air temperature results in an evaporation of the moistening liquid. Thus, the moisture content of the wet mass is lower at the end of the liquid addition stage. If the other variables are kept constant, a lower moisture content of the wet mass results in the formation of sm aller pellets. 6. 4. 6. Air flow rate
The air flow rate is important for the drying capacity of the air and for the air velocity giving rise to the fluidization of the wet mass. 6. 4. 7. Atomizing air pressure
The atomizing air pressure is one determining factor for the drop size distribution of the wet-massing liquid. Together with the nozzle diameter, the spray rate and the physico-chemical properties of the liquid like surface tension, viscosity and density the atomizing air pressure controls the spray process. Depending on the range studied, the atomizing air pressure can be of minor importance [49,51]. 6. 4. 8. Gap widthjpressure difference
A positive pressure difference across the gap due to an air flow is necessary for the fluidization of the powder and wetted mass. If air passes through the gap, a slipping of the powder between the rotor plate and the chamber wall is avoided. The fluidizing air can also help to prevent the wet mass from adhering to the wall of the production chamber. If the powder is not completely available for pellet ization due to sticking to the wall or slipping through the gap, the wetting liquid is distributed to a smaller amount of solid material giving rise to a higher water content of the remaining load and thus to an undesired pellet size. Adhesion to the wall is crucial to the rope-like movement of the wet mass. Pellets with a much larger diameter were observed in spheronization experiments where substantial wall adhesion occurred [39]. The moisture content of wet pellets was found to decrease linearly with time after the complete addition of water (Fig. 5) [1 1 , 39]. With increasing pressure difference the decrease in water content was more pronounced [39]. This was attributed to the drying effect of the air passing the gap between rotor plate and process chamber. In case of a cylindrical chamber, the pressure difference is directly related to the amount of air passing the gap. In a conical chamber, the pressure difference can be adjusted independently from the air flow rate. At a given air flow rate giving a certain drying capacity the pressure difference across
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the gap giving the air velocity can be adjusted by raising or lowering the position of the plate giving rise to a wider or smaller gap width. During the drying phase an increased gap pressure difference can also result in increased attrition of the pellets [39]. Rashid et al. [51 ] have shown that an increase in the air flow rate from 1 40 to 240 I min- 1 resulted in significantly smaller pellets of a lower bulk density. 6.5. Form ulation variables 6.5. 1. Fraction of drug
Often it is aimed to incorporate a high fraction of drug into the pellets. With increasing fraction of drug, less pelletization aid is available. Depending on the physico-chemical properties of the drug the maximal fraction is limited. Si enkiewicz et al. [33] used formulations containing 0-90% of theophylline for direct pelletization. As the proportion of the drug increased, the process became more difficult to carry out to completion. A theophylline content of up to 50% resulted in spherical and elegant pellets, but 70 and 90% of theophylline gave more granular products. Vecchio et al. have incorporated 55-85% indobufen in pellet formu lations [31]. A fraction of 85% was not suitable for pelletization. 6. 5. 2. Partic/e size and size distribution
Sienkiewicz et al. tested three different particle sizes of theophylline for direct pelletization. Particle size of the drug was the most important factor in spheronizat ion. A large particle size was found to be most useful [33], while small theophylline particles showed a tendency to adhere to the wall. The adhesion prevented the rope-like movement of the wet mass required for the spheronization. Furthermore, the effects were more pronounced at a higher fraction of drug in the formulation. Drugs of a small particle size cause difficulties for direct pelletization in fluid bed equipment. Pisek et al. [42] tested ketoprofen of an average diameter of 7 J.lm. Using a textured disc it was not possible to produce pellets. Holm [32] found that the pellet size distributions for formulations with a coarse quality of dicalcium phosphate were less critical to the level of moisture content when compared with formulations containing lactose 450 mesh. The pelletization process was more critical for the formulations with the fine grade of dicalcium phosphate. 6. 5. 3. Type and amount of binder
A high amount of binding liquid results in more spherical particles and larger particle size [31 ,44,47,49]. Usually, water can be used alone as binding liquid, if a suitable pelletization aid like MCC is included in the dry formulation.
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PVP as an additional binder was found to be favourable compared to H PC due to less rapid particle agglomeration [46]. Other authors found that a binder dis solved in the aqueous phase caused the adhesion of the material to the product container and the disc [32], preventing a homogeneous flow. 6. 5. 4. Solubility
Soluble drugs need less water for pelletization than those with lower solubility [42]. The drug can partly dissolve in the wetting liquid, which increases the ratio of liquid to solid mass. 6. 5. 5. Moisture content
The moisture content at the end of the liquid addition stage is critical for the process. There is a sensitive relation between moisture content and particle size (Fig. 7). The process is extremely moisture sensitive and must be tightly controlled when trying to achieve a particular mean granule size [32,49]. The moisture sen sitivity depends strongly on the formulation, especially the fraction of pelletization aid. Owing to the multiple interactions between the different equipment, process and formulation variables the equipment and process variables have to be ad justed according to the physico-chemical properties of the drugs and the excipi ents in the formulation and the desired characteristics of the pellets, e.g. size. The moisture content is difficult to adjust, because direct pelletization is a multivariate process. Liquid is introduced by the moisture content of the starting materials, the moisture in the slit and spraying air and by the sprayed liquid. At the same time liquid is removed throughout the process by evaporation. The evap oration is affected by the amount, humidity and temperature of the spraying and
� 1200
Jo 1000 .� 800 '"
�
600
�
400
� c:
. dicalcium phosphate {coarse)/MCC (J0/30 w/w) " Lactose 450 mesh/MCC (70/30 w/w)
Ol
� 200 GI
E
moisture content, Itf.
Fig. 7. Relation between the moisture content (relative to dry material) after liquid addition and mean particle size of the final product for two formulations ([32], Fig. 6).
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slit air, the load and the rotor speed. Owing to the high importance of the moisture content many attempts have been made to control the moisture content of the wet mass. This can be used for end-point control of the liquid addition stage (see Chapter "Online Monitoring"). 6.6. Reproducibility
Holm has tested the reproducibility of the particle size distribution by con ducting the same experiment six times adding 2570 9 water at a spray rate of 200 9 min - 1 . The relative standard deviation of the mean granule size was 3.9% and the moisture content was kept within 0.3% [ 1 3]. For a formulation containing dicalcium phosphate, a suitable correlation between the power consumption of the rotor plate at the end of liquid addition and the mean granule size exist. This was not the case for a formulation containing lactose 450 mesh. Vertommen and Kinget reported differences in the geometrie mean diameter up to 60 I-lm and differences in the range d1 6%-d84% up to 35 1-lm. They classify the pelletization process in a rotor processor as a critical but nevertheless repro ducible one [14]. Kristensen et al. [1 1 ] achieved a mean particle size of 683 ± 40 I-lm in eight experiments. They used the increase in torque to control the end-point of the liquid addition stage. Although the end of the liquid addition stage varied between 28 and 44 min the pellets size could be kept within a small range. The variation in the time for liquid addition was explained by a varying spray rate.
7. MELT PELLETIZATION
An alternative way to obtain pellets by agglomeration in a fluidized bed is the process of melt pelletization. In this process, the powder particles are agglom erated in the fluidized state at a higher temperature by a molten binder, which solidifies during cooling. Melt granulation in a fluidized bed was first described by Heinemann and Rothe in a patent in the early 1 970s [64]. They granulated powdered drugs and excipi ents with powdered polyethylene glycol or a wax in a fluidized bed at temper atures above the melting point of the binders. Since this publication only little research has been done in that field. Most of the authors described the melt granulation process and the influence of variables on it. Only a few focused on the special properties of pellets concerning melt pelletization [65-67]. But like in the case of wet pelletization it is possible to transfer the knowledge of the melt granulation process to the melt pelletization process.
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7.1 . Process description
There are two approaches to melt pelletization in a fluidized bed, which differ in their methods of binder addition: •
Addition of powdered binder: The drug substance and all other high melting point solids are placed in a fluid bed granulator together with the powdered binder at room temperature. The powders are fluidized by hot fluidizing air and when the melting point of the binder is reached the fluidized particles begin to agglomerate. The agglomer ation phase is short because all of the molten binder is present at once. When the agglomeration is finished, cold air is used to fluidize and the binder solidifies or crystallizes. The granules or pellets are cooled in the same apparatus by this way. No spraying equipment is necessary for this process and it can be carried out in a conventional fluid-bed granulator or dryer [67-70] or in a rotary flu idized-bed processor when higher shearing forces are desired [65,71].
Addition as molten binder: The non-meltable ingredients are fluidized by hot air. The binder has to be heated above its melting point outside the apparatus, delivered through a heated tube to the heated nozzle and dispersed with hot pressured air into droplets of molten binder. When the desired temperature in the product chamber is reached, the molten binder is sprayed onto the fluidized particles. After all the molten binder was added and agglomeration was finished, the heater for the fluidizing air is turned off and cold air cools the agglomerates and the binder solidifies. This procedure is more similar to that of wet granulation in fluidized bed where a binder solution is sprayed onto the particles, but no drying step is necessary. So far, research in this field has only been done in conventional fluid bed equipment with additional heating supply for the molten binder [66,68,72]. A special case is the tumbling melt granulation (so ca lied by the authors) [73-78] where seed material is heated by hot air in a centrifugal fluidizing gran ulator and a powdered mixture of meltable and effectively non-meltable material is fed onto the preheated seeds which are moved by the centrifugal forces of the granulator. The meltable material melts and leads to an adherence of the powder mixture to the seeds, so acting as a binder. After cooling the powdered material forms a solidified layer around the seed material. This is rather a coating or layering process and will not be discussed here in detail. •
7.2. Advantages of the process
The melt pelletization in a fluidized bed has several advantages over the more common wet pelletization. There is no need of a solvent Iike water, alcohol or
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other organic solvents. So a drying step is no longer necessary. This reduces the supply of energy and the time of the process. Process times can be shortened to half an hour in the laboratory scale [67,69]. The renunciation of water makes it possible to agglomerate material, that undergoes hydrolysis in the presence of water or even to agglomerate effervescent mixtures containing anhydrous citric acid and sodium bicarbonate [69]. With the right choice of binder it is possible to produce fast-dissolving pellets (e.g. with polyethylene glycol) or pellets with prolonged release properties (e.g. with waxes). In comparison with the melt pelletization in a high-shear mixer, the process in the fluidized bed allows a better control of the product temperature. The product temperature is easily adjustable by heating or cooling the fluidizing air to the desired temperature. So the melting of the binder is achieved by hot air above the melting point of the binder and solidification occurs with cold fluidizing air. The fluidizing air (in a rotary processor together with the rotating friction plate) keeps the product in motion during the whole process, since heating and cooling is running in the same equipment. One disadvantage compared to the melt ag glomeration in a high shear mixer is that the shearing forces in the fluidized bed are significantly lower. This can be overcome to a certain degree by using a rotary processor with a rotating friction plate. Higher shearing forces lead to agglom erates, which show a denser and more spherical structure. The process of melt pelletization in a fluidized bed can be described as simple and easy to contro!. More specifically, when the binder is added in a powdered form there are only a few variables to be considered. 7.3. Meltable binders
The main factor is the choice of a suitable binder as it is in the process of wet granulation. The binder for melt agglomeration has to meet at least the following requirements: its melting point or range has to be above 30 or 40°C to ensure sufficient hardness at room temperature during storage. lf the binder is intended to act as a matrix substance for controlled release the melting point has to be above 3JOC. On the other hand, the melting point should not be too high because the product in the fluidized bed has to be heated above this temperature to form agglomerates. For practical and energetic reasons the temperature in a fluidized bed is Iimited to approximately 1 00°C and the thermal sensitivity of active and other ingredients has to be considered. Pharmacological and toxicological safe ness are further prerequisites for the use as a binder. Additionally, it has to be available in a pharmaceutical grade and defined quality in respect to crystal modification and other important properties. Two different kinds of substances were used in recent studies as meltable binders: substances with a good solubility in water like polyethylene glycol (of
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molecular weight 3000 to 20,000) which give rise to pellets with a rapid disso lution behaviour. On the other hand, hydrophobie material, such as fatty acids, glycerides and waxes result in pellets with a prolonged or sustained release or having taste masking properties. In a patent, Reo and Roche claimed that the binder in melt agglomeration in a fluidized bed can also be an active drug [71]. As mentioned above, the drug must have a melting point between 30 and 1 00°C in that special case and it must be ensured that no degradation takes place during melting. Ibuprofen with a melting point near 75°C seems to be a suitable drug which fulfils the requirements and is described as an example in the patent. 7.4. Mechanisms of pellet formation
The principle mechanisms of pellet formation in melt agglomeration in a fluidized bed are the same as in wet granulation. First, small agglomerates (nuclei) are built during nucleation, which grow by coalescence between the agglomerates or layering of fine particles onto the agglomerates. According to Abberger [68] and Abberger and Henck [79], the formation of agglomerates in fluidized-bed melt pelletization can be described by two mechanisms: on the one hand distribution and coalescence and on the other immersion and layering. 80th mechanisms were discussed earlier by Schaefer and Mathiesen [80] for the melt granulation in a high-shear mixer. •
•
Distribution and coalescence (Fig. 8): The molten binder comes into contact with the surface of a solid particle, the particle surface is wetted by the binder and the binder is distributed more or less evenly on it. The surface is now sticky and adhesive due to the molten binder. The nuclei are formed by random collisions of wetted particles. A nucleus is only built when the forces between the particles due to the liquid bridges of the molten binder are high enough. In contrast to wet granulation in a fluidized bed, no evaporation of solvent is possible and the liquid bridges or the liquid film remain between the particles until solidification takes place during the cooling phase. The nuclei grow by further collision to greater agglomerates. The ag glomerates may have air entrapped because of the unsaturated voids between the particles. When the shearing forces in the (rotary) fluidized bed are high enough , dens ification of the agglomerates is possible and the resulting granules may have a more spherical shape. Under these conditions pellets will be obtained. Immersion and layering (Fig. 9): The powder particles come in contact with a greater droplet of the molten binder by random collision; the particles stick onto the surface of the liquid droplet and
805
Direct Pelletization of Pharmaceutical Pellets ..... + •• • • •• ••
:
powder particles
-
• •• • • • •• • • ••• • •• •• • • •• • •• ••
distribution
binder
coalescence
Fig. 8. Mechanism of distribution and coalescence (modified according to [80]).
-
+
powder particles
binder
immersion
layering
Fig. 9. Mechanism of immersion and layering (modified accordi ng to [80]).
form a droplet with a surface of wetted solid particles. The size of this nucleus mainly depends on the size of the binder droplet. The particles can be immersed in the liquid and the binder can move outwards due to capillary forces of the liquid. The surface of the nucleus is now partly covered by the molten binder again and more powder particles can adhere and form a layer. Therefore, this process is called layering. When more and more particles adhere to the surface and more binder is sucked out it is possible that a cavity is formed in the middle of the granule. This structure of a hollow pellet with a dense wall remains during melt pelletization in a fluidized bed due to the relatively low shearing forces. An example is shown in Fig. 1 0, similar pellets were shown by Abberger [68] and Haramiishi [81]. Of course, coalescence of nuclei or agglomerates is also possible as in the case of dis tribution. Which of the two mechanisms is dominant depends mainly on the relative size of the binder droplets to the solid powder particles. Distribution of the molten binder on the surface of the powder particles will be more likely when the droplets of the binder are small in comparison to the size of the solid powder particles. On the other hand, when the droplets are larger than the powder particles immersion will be the preferred mechanism. Other factors such as the viscosity of the molten binder, the amount of binder and the kind of shearing forces during the process may aIso influence the agglomeration mechanism.
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Fig. 1 0 . Cut through a hollow pellet obtained by f1uidized melt pelletization (SEM photo by Pauli and Matthee).
7.5. Variables with influence on the process of melt agglomeration 7. 5. 1. Equipment variables •
Rotary fluidized-bed processor: The use of a rotary fluidized-bed processor instead of a conventional one in creases the shearing forces during agglomeration. Higher shearing forces lead to a stronger densification of the growing agglomerates and to more spherical agglomerates. The advantage of the rotary fluidized-bed granulator for the for mation of pellets was investigated by several authors for the wet granulation (see the previous chapter), but only two publications deal with the melt agglomeration in a rotary processor [65,71].
•
Structure of the rotating friction plate: The friction plate of a rotary processor can have a smooth surface or can be grooved in a longitudinal or crosshatched way. It was shown [65] that this surface structure had a significant influence on the properties of the agglom erates. The grooved plates provided higher shearing forces and therefore the resulting agglomerates had a greater size and showed a more spherical shape.
•
Type and position of the spray nozzle: If the molten binder is sprayed onto the particles in a fluidized bed through a heated spray nozzle, the type, the temperature and the position of the spray nozzle in the granulation chamber may influence the agglomeration process.
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No systematic investigations have been published about this influence con cerning melt agglomeration. 7. 5. 2. Process variables •
Temperature of the fluidizing air: The temperature during agglomeration is one key factor in melt pelletization. The temperature of the product has to be high enough that the binder is sof tened or melted; otherwise no agglomeration will take place. The temperature of a fluidized air processor is usually controlled by the inlet air temperature. This temperature has to be higher than the desired product temperature due to heat loss to the environment. The heat loss is smaller than during wet granulation because no evaporation of solvent takes place. When the product temperature is above the melting point of the binder the influence of temperature is only smalI, regardless of the kind of addition of the binder (as powder particles or in a molten state) [68,72]. Because the viscosity of the molten binder is lower at higher temperatures, the agglomerates may be more deformable, greater and more spherical.
•
Fluidizing air flow: The air flow in a fluidized bed can only be varied within limits. A minimum fluidization velocity is necessary to fluidize the particles and filter clogging will take place at high air flow rates. Vilhelmsen et al. [65] showed that the fluidizing air flow rate within these limits had no significant influence on the properties of agglomerates produced in rotary fluidized-bed melt pelletization.
•
Process time: It is expected that the time during the process when the product temperature is above the melting point of the binder has an influence on the formation of agglomerates. When the particles, nuclei and agglomerates have more time to come into contact with each other it is more likely that particle growth will take place. A longer residence time during the agglomeration phase may additionally cause more densification of the agglomerates and give rise to higher liquid saturation (with the molten binder), which will lead to larger granules. But in vestigations showed that there was only a slight or no influence in the con ventional fluidized bed [69,72]. This can be explained by the relatively low shearing forces. The shearing forces in the rotary fluidized bed were higher and the agglomerate size increased with increasing process time as expected [65].
•
Rotor speed: The rotating disk in a rotary processor together with the fluidizing air flow is responsible for the movement of the particles in the rotary fluidized-bed
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granulator. A higher rotating speed causes higher shearing forces and therefore increased agglomerate size [65]. •
Atomizing air pressure and liquid addition rate: As mentioned above, the molten binder can be sprayed onto the fluidized par ticles. The size of the binder droplets has a major influence on the agglom eration process and agglomerate properties. The size of the droplets depends on the atomizing air pressure, the liquid addition rate and the viscosity of the molten binder which will be discussed later.
7. 5. 3. Formulation variables •
•
•
Amount of binder in the formulation: The influence of the amount of binder in the formulation was investigated for both ways of adding the binder: in a powdered form [65,67,69] and as droplets in the molten state [66,68,72]. In most cases, an increasing amount of binder led to larger agglomerates, which can be explained by a higher liquid saturation during the agglomeration phase. A higher liquid saturation results in more liquid bridges according to the mechanism of coalescence. In one case [67], the agglomerate size was reported to decrease with the increasing amount of binder. This may be explained by the mechanism of immersion when only a slight agglomerate growth (Iayering) occurs after the nucleation phase. The amount of binder can be varied only between limits. If there is only a small amount of binder, less agglomeration will take place and a lot of ungranulated material remains. If there is too much binder in the formulation the formation of large lumps will be the result and fluidization is no longer possible. This is similar to an over-wetted fluidized bed during wet granulation. The upper limit for the amount of binder was found to be around 28% for polyethylene glycol as a binder [65,72]. Size of the binder particles: When the binder is added as a solid material in a powdered form or as flakes its size influences the resulting agglomerate size. An increasing binder size leads to larger agglomerates [67,68]. Immersion was suggested to be the main ag glomeration mechanism in this case. The binder particles acted as seeds. Larger seed particles resulted in larger agglomerates. Layering seemed to be the only growth mechanism after the nucleation phase. Size of the binder spray droplets: The size of the binder droplets when sprayed through a nozzle is influenced by the atomizing air pressure, the liquid addition rate and the viscosity of the molten binder as stated above. The viscosity depends on the kind of binder
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(e.g. the molecular weight in the case of polyethylene glycol) and the temper ature of the melt. If the formulation and the liquid addition rate are given , the atomizing air pressure is the variable to control the droplet size of the sprayed binder. The mechanism of agglomerate formation is primarily dependent on the ratio of the sizes of binder droplets to solid particles. The melt agglomeration of fine powders with sprayed binder droplets often follows the immersion mech anism as nucleation and further agglomerate growth by coalescence between nuclei or agglomerates. The influence of droplet size on the size of the ag glomerates is difficult to interpret. Abberger [68] found larger agglomerates with larger droplets during the nucleation phase but no influence on the granule growth later. Seo et al. [72] reported only Iittle influence of droplet size on agglomerate size. •
Crystallization behaviour of the binder: Kidokoro et al. [82] investigated the crystallization behaviour of polyethylene gly col and found two different crystallization mechanisms. They showed that it is possible to reduce the amount of remaining fine particles after fluidized-bed melt agglomeration by using a polyethylene glycol with a slow crystallization behaviour.
7.6. Process monitoring and control
The monitoring and control of the melt pelletization process as weil as the de termination of the end point of pellet formation during the agglomeration phase are of great importance. But no systematic approach has been made until now. Some possible parameters for process monitoring are •
Product temperature: The product temperature in fluidized-bed melt pelletization is easy to control by the inlet air temperature as mentioned above. This was the only parameter, which was monitored or controlled in previous investigations.
•
Rheological behaviour of the fluidized particles: No systematic investigations have been published concerning the measurement andjor control of the rheological behaviour of the fluidized particles during hot melt agglomeration. It seems to be possible to measure the powder consumption of the rotor motor or the torque of the rotor shaft to get information about the behaviour of the particles in a rotary processor and the status of the process. This has been reported for wet granulation in a rotary processor [1 1 ,1 5].
•
Particle size: N IR-spectroscopic methods may be used to measure the particle size or other product properties on-line or in-line in the fluidized bed in future.
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P . Kleinebudde and K . Knop
REFERENCES [1] [2] [3] [4] [5] [6] [7] [8] [9] [ 1 0] [11] [ 1 2] [ 1 3] [ 1 4] [ 1 5] [ 1 6] [ 1 7] [ 1 8] [ 1 9] [20] [21 ] [22] [23] [24] [25] [26] [27] [28] [29] [30] [31 ] [32] [33] [34] [35] [36] [37] [38] [39] [40] [41 ] [42] [43]
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Direct Pelletization of Pharmaceutical Pellets [44] [45] [46] [47] [48] [49] [50] [51 ] [52] [53] [54] [55] [56] [57] [58] [59] [60] [61 ] [62] [63] [64] [65] [66] [67] [68] [69] [70] [71 ] [72] [73] [74] [75] [76] [77] [78] [79] [80] [81 ] [82]
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J . Vertommen, P . Rombaut, R . Kinget, Int. J . Pharm. 1 46 ( 1 997) 21 . J. Vertommen, B. Jaucot, P. Rombaut, R. Kinget, Pharm. Dev. Technol. 1 ( 1 996) 365. P. Gauthier, J.-M. Aiache, Pharm. Technol. Eur. 1 3 (2001 ) 22. B.N. Chukwumezie, M. Wojcik, P. Malak, F. D'Amico, M.C. Adeyeye, Pharm. Dev. Technol. 9 (2004) 49. B.N. Chukwumezie, M. Wojcik, P. Malak, M . C. Adeyeye, AAPS Pharm. Sci. Tech. 3 (2002) article 2. E.S. Korakianiti, D.M. Rekkas, P.P. Dallas, N.H. Choulis, STP Pharma Sci . 12 (2002) 1 91 . H A Rashid, J . Heinamaki, J . Yliruusi, STP Pharma Sci. 8 ( 1 998) 1 63. H A Rashid, J . Heinamaki, O. Antikainen, J. Yliruusi, Drug Dev. Ind. Pharm. 25 (1 999) 605. S. Watano, S. Yoshinobu, K. Miyanami, T. Murakami, Y. Ito, T.e.a. Kamata, Chem. Pharm. Bull. 43 ( 1 995) 1 2 1 2. S. Watano, S. Yoshinobu, K. Miyanami, T. Murakami , N. Nagami, Y.e.a. Ito, Chem. Pharm. Bull. 43 (1 995) 1 2 1 7. S. Watano, Y. Sato, K. Miyanami, Y. Ito, T. Kamata, N.e.a. Oda, Chem. Pharm. Bull. 43 ( 1 995) 1 224. S. Watano, Y. Sato, K. Miyanami, Chem. Pharm. Bull. 43 ( 1 995) 1 227. S. Watano, H. Takashima, K. Miyanami , Chem. Pharm. Bull. 45 (1 997) 7 1 0. E.S. Korakianiti, D . M . Rekkas, P.P. Dallas, N . H . Choulis, J. Drug Delivery Sci . Technol. 1 4 (2004) 207. P.W.S. Heng, C .v. Liew, L. Gu, I nt. J. Pharm. 241 (2002) 1 73. C .v. Liew, L. Gu, P.W.S. Heng, I nt. J . Pharm. 242 (2002) 345. C.v. Liew, L.S.C. Wan, P.W.S. Heng, STP Pharma Sci. 8 (1 998) 297. J. Vertommen, R. Kinget, J. Applied Ichthyol. 14 ( 1 998) 259. J. Vertommen, R. Kinget, STP Pharma Sci. 6 ( 1 996) 335. L.S.C. Wan, P.W.S. Heng, Y.T.F. Tan , STP Pharma Sci. 5 ( 1 995) 1 28. A. Heinemann, W. Rothe, Verfahren zur Granulierung von pulverförmigen Tablettenmassen. [DT 21 27683]. 1 975. T. Vilhelmsen, J. Kristensen, T. Schaefer, Int. J. Pharm. 275 (2004) 1 4 1 . T. Abberger, A. Seo, T. Schaefer, Int. J. Pharm. 249 (2002) 1 85. A. Pauli, K. Knop, B.C. Lippold, Fluidized bed melt pelletization: Effects of binder particle size, 2004, pp. 3 1 -32. T. Abberger, Pharmazie 56 (2001 ) 949. F . M . Yanze, C. Duru, M. Jacob, Drug Dev. Ind. Pharm. 26 (2000) 1 1 67. M . Kidokoro, Y. Haramiishi, S. Sagasaki, T. Shimizu , Y. Yamamoto, Drug Dev. Ind. Pharm. 28 (2002) 67. J.P. Reo, E.J. Roche, Dry granulation using a fluidized bed. [EP 0 582 380 B 1 ] . 1 996. A. Seo, P. Holm, T. Schaefer, Eur. J . Pharm. Sci. 16 (2002) 95. T. Maejima, T. Osawa, K. Nakajima, M. Kobayashi, Chem. Pharm. Bull. 45 (1 997) 5 1 8. T. Maejima, T. Osawa, K. Nakajima, M. Kobayashi, Chem. Pharm. Bull. 45 (1 997) 1 833. T. Maejima, T. Osawa, K. Nakajima, M. Kobayashi , Chem. Pharm. Bull. 45 ( 1 997) 904. T. Maejima, T. Osawa, K. Nakajima, M. Kobayashi, Chem. Pharm. Bull. 45 (1 997) 1 332. T. Maejima, T. Osawa, K. Nakajima, M. Kobayashi, Chem. Pharm. Bull. 46 ( 1 998) 531 . T. Maejima, M . Kubo, T. Osawa, K. Nakajima, M. Kobayashi, Chem. Pharm. Bull. 46 ( 1 998) 534. T. Abberger, J.O. Henck, Pharmazie 55 (2000) 521 . T. Schaefer, C. Mathiesen, I nt. J. Pharm. 1 39 ( 1 996) 1 39. Y. Haramiishi, Y. Kitazawa, M . Sakai, K. Kataoka, Yakugaku Zasshi-J. Pharm. Soc. Jpn. 1 1 1 ( 1 99 1 ) 5 1 5. M . Kidokoro, K. Sasaki, Y. Haramiishi, N . Matahira, Chem. Pharm. BuH. 51 (2003) 487.
CHAPTER 1 8 S hear-I n d u ced D is pers i o n of Particle Agg lomerates D . L . Feke *
Department of Ghemical Engineering, Gase Western Reserve University, Gleveland, OH, 44106-7217, USA Contents
1. 2. 3. 4.
Introduction Background Experimental Methods Experimental Results 4. 1 . Effect of packing density within the agglomerate 4.2. Effect of applied shear stress on the dispersion process 4.3. Effect of fluid viscosity on the dispersion process 4.4. Infiltration of processing liquids within agglomerates 4.5. Flow of fluid within the agglomerate 4.6. Transition between kinetic regimes 4.7. Dispersion of agglomerates containing binders 4.8. Investigation of the role of shear dynamics on dispersion 5. Gonclusions and synthesis of results - dispersion maps Acknowledgments References
815 818 820 822 822 823 824 825 827 828 834 836 848 851 851
1 . I NTRODUCTION
The breaking of agglomerates or assemblies of small (nanometer to micrometer) particles is frequently encountered in a wide range of industries including material processing, pharmaceuticals, mining, and food technologies. Often, the process ing goal is the dispersion into smaller clusters (or if possible, into its constituent particles) and distribution of these finely divided units throughout the suspending medium. Usually, the quality of the resulting product depends on the degree of dispersion achieved. Hence, a better understanding of the parameters that con trol the dispersion process can lead to advances in processing techniques or the design of efficient mixing equipment.
* Corresponding author. E-mail:
[email protected] G ranulation
Edited by A .D. Salman. M.J. Houns/ow and J. P. K. Seville C 2007 Elsevier s.v. All rights reserved
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This chapter presents a summary of the current state of understanding of agglomerate dispersion phenomena. 80th experimental approaches to elucidat ing the fundamental phenomena and modeling of these phenomena are de scribed. In practice, the dispersion operations described above are commonly achieved by suspending the agglomerates (or individual particles) within fluids and sub jecting them to agitation or shearing motions. In some cases, this step is preceded by some chemical treatment (e.g., intercalation of layered nano-solids, wetting of fine-particle agglomerates) to ease the dispersion. In industrial equipment, the shearing motions are inherently complex, and an understanding of the funda mental phenomena underlying dispersion operations is consequently difficult to glean. In order to surmount this obstacle, it is generally useful to study dispersion in well-defined, controlled-flow fields. In addition, we have found it useful to ob serve and analyze agglomerate dispersion phenomena in studies of single, well characterized spherical agglomerates subjected to hydrodynamic stress. In general, the dispersion of particle agglomerates into liquids is generally thought to consist of three steps, some of which may occur in parallel. A variety of chemical and physical effects govern the outcome of these processes. First, the agglomerates must be incorporated into the liquid medium. Para meters that control the wetting and spreading of the solid particles by the liquid medium, such as the interfacial tension and contact angle, determine the outcome and rate of the incorporation step. In addition, the size and surface texture (morphology) of the individual particles also play roles in the incorporation process. Since they are porous structures, fluid infiltration into agglomerated particles may aiso occur. Agglomerates that are well-wetted by the processing medium may experience extensive fluid infiltration. The presence of such processing fluid within agglomerates can have several effects. For example, the cohesive force between particles can be altered. Also, the additional capillary forces resulting from incorporated liquid may, in some cases, drive a rearrangement of the in ternal structure within the agglomerate. In addition, fluid within the pores of an agglomerate can be driven by external flows, and thereby affect the distribution of hydrodynamic stress on the agglomerate. The second step in particle processing is the application of hydrodynamic shearing motions to break apart the agglomerates and to distribute the fragments throughout the processing media. The process of breaking the agglomerates is known as dispersive mixing, while distributive mixing refers to the delocalization of the fragmented agglomerates throughout the processing medium. The best possible outcome of dispersive mixing operations is the complete breakdown of the agglomerate into its constituent particles. Creation of a completely homo geneous suspension of particles in the processing fluid is the usual goal for distributive mixing operations.
Shear-Induced Dispersion of Particle Agglomerates
817
The third aspect of particle processing has to do with the prevention of the reformation of particle clusters or assemblies once the original agglomerate has been broken. The naturally occurring interparticle forces can act to induce re agglomeration, and so strategies to prevent this from occurring, such as the use of stabilizing additives, which adsorb to and protect particle surfaces, may be employed. In this chapter, we focus attention solely on dispersive-mixing phenomena. Our goal is to provide fundamental insight from experimental studies that enables predictive modeling of dispersion behavior. In addition, a more thorough under standing of dispersion processing could enable the better design of practical mixing equipment, or interfacial engineering strategies for the particle agglom erates that could lead to a better control over dispersion operations. Many factors affect the outcome and rate of dispersive mixing. These include material properties such as the structure configuration and mechanical properties (e.g., cohesivity) of the agglomerates, the viscosity of the processing fluid and the various interfacial phenomena that govern the interaction between the processing fluid and particles. In addition, processing parameters such as flow-field geometry and shear rate history are important [1]. Our general approach is to study the response of individual, well-characterized agglomerates to controlled-flow fields. Agglomerate characteristics, such as the size, shape, and composition of the constituent particles, the size and the packing morphology within the agglomerate, and the presence (or absence) of infiltrated liquid within the agglomerate can be systematically controlled to elucidate differ ent aspects of the dispersion phenomena. Selection of the processing fluid de termines the wetting and infiltration interactions that govern the dispersion phenomena. Steady or time-varying flows, of controlled-strain rate are used to examine different dispersion regimes. In such experiments, we observe the crit ical shear stresses (at which dispersion commences), and analyze the relation ship between processing conditions and the modes and rate of dispersion, and the characteristics of the fragments produces by the dispersion process. Sub sequently, the results are interpreted in terms of the properties of agglomerate andjor fluid as weil as the processing history.
2. BACKGRO U N D
The manner and rate in which agglomerates disperse depends on the compe tition between those forces responsible for the cohesivity or rigidity of the ag glomerate and the hydrodynamic forces driving its fragmentation. The cohesive strength of agglomerates originates from three sourees: ( 1 ) interparticle forces such as van der Waals attractions and electrostatic effects between the solids; (2)
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interaction forces resulting from adsorbed surfactants or other secondary species such as binders; and (3) capillary forces from any liquid bridges present from infiltrated-processing liquid. Given detailed information (or assumptions) on the packing structure within the agglomerate, it is possible to quantify or predict the strength of an agglomerate. Most of these models correlate the tensile strength of the agglomerate to some lumped measure of the interparticle forces such as an effective Hamaker constant, which reflects the combination of forces that act within the agglomerate. The hydrodynamic forces, which act to disrupt the ag glomerate, depend on the details of the local flow field. Bulk fluid motions produce hydrodynamic stress on the periphery of the agglomerate. Also, additional shear stresses can act within the agglomerate structure since agglomerates are per meable to fluid flow, and for highly porous agglomerates, these internal stresses can significantly affect the dispersion process. Processing liquid, drawn into agglomerates through the capillary forces, can affect both the interparticle forces and the packing structure within the agglomerate itself. The complex interaction between all of these effects determines the rate and mechanism by which ag glomerates disperse. Several studies have been undertaken to characterize the dispersion process, to understand the various mechanisms and the principal factors affecting the outcome of dispersion [2-4]. For dry agglomerates (i.e., those in which no processing fluid is contained within the agglomerate structure), there are two c1assical dispersion modes; rupture and erosion [5,6]. Rupture occurs in those cases wherein the ratio of applied hydrodynamic stress to agglomerate cohesivity is large, and typically produces large fragments in a very short while following the application of shear. Erosion occurs at lower levels of stress, and typically pro duces smaller fragments over a longer period of shearing. Figure 1 contains images of the dispersion of silica agglomerates sheared within silicone oi!. Both dispersion modes are illustrated. These two c1assical-dispersion modes are cat egorized as cohesive-failure modes since they both result when cohesive forces between the fragment and neighboring particles are overcome. Also shown is the case of a different dispersion mode known as adhesive failure, which occurs when the wetted periphery of an agglomerate peels away from the core of the agglomerate. We have shown that this mode can occur under relatively low-shear stress conditions. Critical hydrodynamic conditions for dispersion are based, to a first approx imation, on a comparison of hydrodynamic forces exerted by the flow field and mechanical strength of the agglomerate. Manas-Zloczower et 81. [7,8] found that dispersion in simple shear flow could be correlated to a dimensionless quantity expressing the ratio of hydrodynamic stress and cohesive strength. Rwei et 81. [5] used the same concept to explain the extent of rupture observed in dispersion processes of carbon-black agglomerates of a range of packing density. Ottino and co-authors [9,1 0] labeled this ratio as the fragmentation number, Fa, and
Shear-Induced Dispersion of Particle Agglomerates
81 9
Dispersion Examples
Fig. 1 . Images showing the dispersion behavior of silica agglomerates sheared within silicone oil within the OSD device. The classical dispersion modes of rupture (occurring when the shear stress greatly exceed the cohesivity) or erosion (which occurs when the shear stress and the agglomerate cohesivity are of the same order of magnitude) are shown. Also shown is the mode of adhesive failure in which relatively large fragments peel from the surface of agglomerates under conditions of relatively low-shear stress.
related its value to the dispersion regime expected; erosion occurs at low fragmentation number, when hydrodynamic stresses are close to the cohesive strength while, at higher values of Fa, the dispersion process leads to rupture. During a practical dispersive-mixing operation, agglomerates may exhibit a combination of these dispersion mechanisms. As agglomerates are convected through mixing equipment, they may experience different flow conditions, and hence different values of Fa apply at different positions in the processing equip me nt. In addition, since the mechanical properties of agglomerates are often not homogeneous and the cohesivity of fragments may be different from that of the parent agglomerate, the value of Fa may change as dispersion proceeds, even when uniform stress conditions exists within the processing equipment. Kao and Mason [1 1 ] quantitatively related the initial stage of the erosion process of cohesionless agglomerates with a dimensionless quantity, yf indicating the effect of shear-rate magnitude on the dispersion process. Here y is the shear rate. Lee ef al. [1 2] and Rwei ef al. [6] used a similar model to analyze dispersion results obtained with titania and carbon black agglomerates, respectively. They found that for cohesive agglomerates the erosion rate depends on the fragmentation
820
D. L. Feke
number, and showed that both shear rate and shear stress play a fundamental role in dispersion kinetics. Lee et 81. [1 3] showed correlations between the erosion kinetics (and the consequent fragment size distribution) and the porosity of titania agglomerates. Yamada et 81. [14], studying the influence of matrix infiltration on the dispersibility of carbon black agglomerates, clearly distinguished different erosion regimes depending on the value of a dimensionless quantity that char acterizes the extent of fluid infiltration within the agglomerate. Levresse et 81. [1 5] studied this effect in more detail and analyzed the influence of fluid infiltration on the hydrodynamic stresses transmitted to an agglomerate with incorporated processing fluid. Bohin et 81. [ 1 6] developed a kinetic model for the erosion proc ess of sparse agglomerates, assuming the erosion rate to be proportional to the excess of hydrodynamic force to the cohesive force of the agglomerate. In the sections to follow, we elaborate on the experimental observations and modeling approaches found useful to quantify the dispersion phenomena.
3. EXPERIMENTAL METHODS
We have found it advantageous to use two types of tools in our experimental studies of dispersion. Figure 2 shows a schematic of the cone-and-plate (ep) shearing device in which single agglomerates suspended in a processing fluid can be subjected to a constant simple-shear flow. A camera, recording, and image analysis system allows monitoring of the dispersion process as a function of shearing conditions. Figure 3 shows a schematic of the oscillatory shear device (OSD), which employs a parallel-plate geometry. In this case, the rotation of the motor is converted into an oSciliatory translation of the plate. The dispersion of a single agglomerate placed in the gap between the moving plate and the station ary lower surface can be monitored with the video recording and analysis system. Operating variables include the rotation speed of the motor (which governs the Monitor
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Fig. 2. Schematic of the cone-and-plate shearing device.
821
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Erosion Kinetics
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oscillation frequeney), the amplitude of the plate oscillation, and the gap between the moving and fixed surface (all of which determines the shear rate). Time resolved images of the dispersion of the agglomerates are recorded using a digital camera positioned in front of the transparent front wall of the chamber. Using these experimental tools, we have been able to observe dispersion modes, quantify dispersion kinetics as a function of processing conditions, and identify system parameters and processing histories that lead to dispersion. We can also study the effect of incorporated binder on the mechanieal behavior of agglomerates or of an interacting particle pair, and correlate this information with dispersion results. For the erosion mode, we have found it convenient to quantify dispersion kine ties by monitoring the change in size of the parent agglomerate as fragments are removed from its periphery. Typically, for applied shear fields that have non-zero vorticity, the rotational motion of the agglomerate helps it to retain spherical symmetry as dispersion proeeeds. Figure 4 depicts typieal dispersion kinetics results. The fractional reduction is shown in the size of the parent agglomerate as a function of shearing time. In this particular example, the agglomerate initially
822
D. L. Feke
disperses at a constant rate, but eventually dispersion slows and a relatively stable structure (approximately 40% of the original size of the agglomerate) re mains even upon prolonged shearing. The slopes of asymptotes to the short- and long-time data provide values of the fast- and slow-dispersion rate constants.
4. EXPERIMENTAL RE5ULT5
I n this section, experimental results that illustrate the range of erosion behaviors and the factors that affect erosion kinetics are presented. 4.1 . Effect of packing density within the agglomerate
Figure 5 shows results of shearing agglomerates of carbon black in silicone oil (polydimethyl siloxane, or PDMS) at a fixed shear rate. The agglomerates differ only slightly in terms of the volume fraction of solids within the agglomerate. Note the qualitative difference between the dispersion behaviors of the two types of agglomerates. The lower density agglomerate disperses in a relatively rapid way, and if shearing was to continue, the agglomerate would have eroded to com pletion (fractional-size reduction approaching 1 00%). In contrast, the higher den sity agglomerate disperses more slowly at the initial stages, but then dispersion 0.5
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Shearing time, mi n Fig. 5. Erosion kinetics for agglomerates of carbon black (Cabot Monarch 900) sheared i n P D M S fluid (30,000 cS) a t a shear rate o f 56.7 S- 1 . Results for two agglomerates of slightly different packing density are shown [5,6].
Shear-Induced Dispersion of Particle Agglomerates
823
stops when only about 7% of the agglomerate has been removed. Clearly, the packing density has a profound effect on the rate and ultimate outcome of the dispersion process. Typically, the higher the packing density in an agglomerate, the larger is its cohesivity. This is primarily due to the increased number of particle-particle contacts within the agglomerate, each of which contributes to the overall cohesivity. It is expected that in any batch of agglomerates used in a practical process, there will be some variation in the packing density between individual agglom erates. Particle scientist should be aware that such minor variations in density can lead to very different dispersion outcomes.
4.2. Effect of applied shear stress on the dispersion process
The pronounced effect of shear stress on the outcome of the dispersion process can be exemplified by the results shown in Fig. 6. Here, the dispersion kinetics of agglomerates of fumed silica (2.6 mm diameter and packing density of 0. 1 4 gjcm3) sheared in PDMS fluid (1 0.2 Pa s) are displayed. As in the previous plots, the fractional reduction in the size of the parent agglomerate is presented as a function of the shearing time. The plot shows that the initial rate of dispersion (given by the slope of the dispersion kinetic curve) increases with increasing shear rate. Note that two 1. 0
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0 23.3 S- I ; D 3 7.4 s-\ A 102.3 S-I ; -I -I -I -I o 1 10 S ; * 1 1 5.4 S ; • 124.3 S ; • 1 66.6 S Fig. 6. Dispersion kinetics for silica agglomerates (2.6 mm diameter, 0 . 1 4 g/cm3) are shown as a function of applied shear rate. The suspending fluid is 1 0.2 Pa s PDMS [ 1 6] .
O. L. Feke
824
distinct dispersion kinetic behaviors are observed. For an applied shear rate below a certain value (approximately 1 05 S - 1 in this example), the agglomerate initially disperses, but then dispersion stops. In these cases, note that the size of residual core decreases with increasing shear rate. For shear rates about the critical value, the agglomerate disperses to completion in the matter of a few seconds. For extremely high-shear rates (higher than those presented in Fig. 6), dispersion would go to completion very rapidly, which is a characteristic of the rupture mode of dispersion.
4.3. Effect of fluid viscosity on the dispersion process
As discussed above, the simplest models for dispersion behavior identify the ratio of the hydrodynamic stress to the cohesive strength of the agglomerate as the parameter that controls the dispersion process. For the case of Newtonian fluids, hydrodynamic stress is the product of shear rate and fluid viscosity. Thus, for dispersion experiments performed in different liquids, equivalent hydrodynamic stress profiles can be developed by compensating for differences in viscosity by adjusting the applied shear rate. Figure 7 shows a comparison of the dispersion results for carbon black ag glomerates of various packing densities sheared in silicone oil [1 7] . The second set of experiments was done using a fluid of twice the viscosity as that of the first set, but with one-half of the applied shear rate. Thus, the shear-stress profile is equivalent in the two cases. (Note that under the conditions of these experiments, the PDMS fluid behaves in the Newtonian regime.) Kinetics of erosion
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Wet Dry Interface
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Fig. 1 5 . Schematic representation of the formation of a structural discontinuity within an agglomerate at the wet-dry interface due to capillary pressure driven infiltration. Such a weakened interface leads to another mechanism of agglomerate dispersion known as adhesive failure [ 1 8].
Shear-Induced Dispersion of Particle Agglomerates
833
pressure in this case (�350 kPa) to the shear strength of the agglomerate (�1 50 kPa) confirms that the agglomerate structure may undergo changes as a result of fluid infiltration. The notion that the wetted periphery of the agglomerate is detached from the dry residual core leads to this type of dispersion being con sidered to result from an adhesive failure at the wet-dry interface [1 8]. The observation that the stress required to initiate adhesive failure can be lower than the wet strength of the agglomerate is rationalized in terms of the schematic representation as in Fig. 1 6. The upper portion of a partially infiltrated agglomerate is shown. In the case of a planar-fracture surface that passes through the wetted-peripheral region, both the hydrodynamic force (wh ich is proportional to the applied hydrodynamic stress and the surface area of the spherical cap which subtends the fragment) and the cohesive force (which is proportional to the cohesive strength and the area of the fracture plane) are both proportional to the square of the agglomerate radius. Thus condition for the onset of dispersion can be based on a comparison of the hydrodynamic stress to the cohesive strength of the agglomerate, and is independent of the position of the fracture plane provided that it passes only through the wetted periphery. However, in the case of fracture sUrfaces which pass along the wet-dry in terface (wh ich can be weaker than the cohesive strength of the wetted region), the situation is more complex. If, for example, the wet-dry interface is presumed to have zero strength, then the full burden of resisting the hydrodynamic force falls to the portions of the fracture plane that pass through the wetted periphery. Since the area that provides resistance to dispersion is sm aller than the corre sponding area of a planar fracture surface, the stress on this area is effectively amplified by this geometrie effecl. Thus, the dispersion process can appear to
(a) (b) (e)
Fig. 1 6. Depiction of the upper half of a partially infiltrated agglomerate. Various potential fracture surfaces (a-c) are shown. In the case of plane a, the applied hydrodynamic force would need to overcome the wet cohesive strength along plane 8. Fracture surfaces b and c include portions of the wet-dry interface, which are weak compared to the wet-strength of the agglomerate. In these cases, the portions of the fracture surface, which cut across the wetted periphery bear a disproportionate amount of the hydrodynamic force [20].
834
D. L. Feke
6 �------� 5
ö/Ro=0. 1
__-
4 � u c o
E
� 3 ca
� 2
0.2
(/)
�
O +------.---.--� o 0.2 0.6 0.8 0.4
Fig. 1 7. Stress amplification within the load-bearing portions of the agglomerate, assuming that the strength of the wet-dry interface is zero. Shown is the stress amplification factor as a function of the fragment size (the fragment area being the surface area of the spherical cap subtended by the fragment) and depth of fluid infiltration within the agglomerates. Note that substantial stress amplification can occur, especially for small depths of fluid i nfiltration [21 ] .
initiate at hydrodynamic stress levels that are lower than those that would be required to initiate dispersion across a planar fracture surface wholly contained within the wetted periphery. The amount of stress amplification within the portions of the agglomerate that bear the hydrodynamic force can be computed, provided that some basic as sumptions are made. In the most extreme case, one can assume that the wet-dry interface has zero strength, and thus does not contribute any resistance to the applied hydrodynamic force. Figure 1 7 depicts the resulting stress amplification within the portions of the wetted periphery that bear the hydrodynamic force [21 ] . The stress amplification is shown (the ratio of the actual stress to the stress that would be present if a planar fracture surface were present) as a function of fragment size and depth of fluid infiltration. Dispersion can be anticipated when the hydrodynamic stress is equal to the stress required to disperse a fully in filtrated agglomerate divided by the stress amplification factor. Note that for small infiltration depths, the thickness of the region withstanding the hydrodynamic force is smalI, and thus the effective stress amplification can be high.
4.7. Dispersion of agglomerates containing binders
In some cases, agglomerates are prepared in a manner that incorporates ad ditives (binders) that aid both the production of the agglomerates and its handling
Shear-Induced Dispersion of Particle Agglomerates
835
properties. The presence of interstitial liquid is expected to affect two things. First, the rate at which external processing fluid infiltrates within the agglomerate is expected to be affected by the presence of interstitial liquids. Binders that are chemicaily incompatible with the external fluid will retard infiltration, whereas compatible interstitial liquids may enhance infiltration. Second, the presence of interstitial liquids can augment the cohesivity of the agglomerate via liquid ridges. The higher the concentration of the interstitial liquid, the greater the enhancement of cohesivity that can be expected. Figure 1 8 shows dispersion results for CaC03 agglomerates (65% porosity) sheared in at a constant applied stress of 2 1 50 Pa. Note that both the binder liquid and shearing fluid are both PDMS liquids, and thus are chemicaily com patible. Note that the general trend is that the higher the concentration of incor porated liquid, the smailer is the ultimate dispersion level, which is consistent with the notion that additional liquid bridges result from the incorporated liquid. In contrast, Fig. 19 shows the result for identical CaC03 agglomerates sheared under identical conditions, but using glycerol as the interstitial fluid. Note that at low concentrations of glycerol, the erosion rate and ultimate level of erosion is higher than that for neat CaC03 agglomerates (no interstitial liquids present). However, for higher concentrations of glycerol, the erosion kinetics deciine below that for the neat agglomerates. The interpretation of these results can be based on the coun teracting effects provided by the incorporated glycerol. At low-glycerol concentra tions, there are not enough liquid bridges to lead to a significant enhancement of the agglomerate cohesivity. However, since glycerol is essentiaily insoluble with the background PDMS, external fluid infiltration is retarded, and a prolonged fast dispersion period is seen. However, at higher glycerol concentrations, the en hanced cohesivity of the agglomerate leads to lower overail dispersion rates. In Fig. 20 a direct comparison of experimental results is shown, all of which are obtained using the same type of CaC0 3 agglomerates (65% porosity) sheared at 0.25 0.2
;p 0. 1 5
�
�
0.1
0 �
..,
• ..,
0
•
10
... •
• 0
0.05
�
0
20 30 Time (mln)
0 0% . 0.1 % "' 1 .0% . 20% 0 1 0%
40
50
Fig. 1 8. Dispersion kinetics for CaC03 agglomerates with various concentrations of 1 0 cSt PDMS as interstitial liquid, sheared in 60,000 cSt PDMS [22].
836
D. L. Feke
0.5 0045 004 0.35
..
0.3 cf ct 0.25 0.2
..
, ....
•
0.15 0.1
0 X
!!!!!
0.05
10
..
..
•
•
.. 1 .0 wt%
•
•
0
0
0
0
X
X
X
i
X
20
30
I!!
�
0.1 wt% O wt% 5.0 wt% 1 0 wt% 20 wt%
40
50
Time (min) Fig. 1 9. Dispersion kinetics for CaC0 3 agglomerates with various concentrations of glyc erol as interstitial liquid, sheared i n 60,000 cSt PDMS [22].
0.5
l
I t: o
O.4 0.3
/11
�E � Ci
0.2 0.1
IF=======:;----, • Polyester Resin
PDMS .. Glycerol . . - . . No additive •
Ä . . _ _ . _ _ . .. . _ _ . _ _ . - . . •
_
. . _. .
_ _
.
•
_ _
.__. _-
•
Ä L. O �-------.----.I�: -� 0. 1 0.01 10 1 00 Concentratlon of Additive (wt %)
Fig. 20. Comparison of the effects of varying amounts of interstitial liquids that exhibit a range of compatibility with the background processing liquid (PDMS). All results pertain to CaC03 agglomerates (65% porosity) sheared at 21 50 Pa [22].
2 1 50 Pa. Significant variations in the ultimate extent of dispersion are seen. Clearly, the compatibility between the binder additive and the processing fluid strongly influences dispersion kinetics.
4.8. I nvestigation of the rote of shear dynamics on dispersion
There are significant differences in the results of dispersion experiments performed under steady shear and unsteady shear conditions, even when the hydrodynamic
Shear-Induced Dispersion of Particle Agglomerates
837 • OSD mean 600
0.4 0.35 0.3
� S 0.2 0:: c
�
0.25
0. 1 5 0. 1 0.05
• C&P
(jlllcan = 600 (jma. = 900 •
o OSD max 600
(j = 600
(jl11can = 400 (jmax = 600
•
o
1 .5
0.5
o
o
o
2
2.5
time (min)
Fig. 21 . Comparison of dispersion results for precipitated silica agglomerates in SBR. Data for the fractional reduction in size as a function of shearing time are shown for a cone and-plate (CP) experiment as weil as oscillatory flow experiments in which the mean or maximum stress matches that for the CP experiment [23].
eonditions in the two eases are similar. Figure 21 shows typieal result for agglom erates of preeipitated siliea sheared in POMS fluids [23]. Three sets of data are shown. In these experiments, the preeipitated siliea also had a 1 50 m2jg BET surfaee area, and the primary particles tended to be clustered into hard aggregates of 250 nm as determined by a light seattering teehnique. These aggregates were fashioned into 2.6 mm agglomerates (solids volume fraction of 0. 1 6) using the eompaction and shaping procedures deseribed in our previous reports. In addition to using POMS fluids as the dispersion media (viseosities of 1 0,000 cSt (�1 0 Pa s) or 30,000 eSt (�30 Pa s)), some experiments were performed using another liquid polymer, styrene-butadiene rubber (SBR) of viscosity 1 0 Pa s. The diamond symbols show the dispersion results for shearing in the CP deviee (steady shear) at an applied stress of 600 Pa. The filled eircles are the dispersion results for shearing in the oseillatory deviee for the case when the mean stress over a cycle is 600 Pa, while the open eircles eorrespond to the ease where the maximum stress over a cycie is 600 Pa. Note that the steady-shear results fall between the two eases for the OSO. Since the dispersion kinetics in the CP device are greater than the case where the peak stress in an OSO experiment is set to the same value, this suggests that the duration of the stress above a threshold value determines dispersion kinetics. However, since the OSO results for the case when the mean stress matches the stress in the CP experiment show a faster dispersion kinetic than that of the CP experiment, this indicates that the absolute magnitude of the applied stress also determines dispersion kineties.
838
D. L. Feke
To further iIIustrate the complex dependence of dispersion kinetics on hydro dynamic conditions, consider the OSO data shown in Fig. 22. Two sets of dis persion results for precipitated silica particles are shown; one for low-density (and hence weaker) agglomerates, and the other for higher density (stronger) ag glomerates. The mean stress in all experiments was set to an identical value (580 Pa). However, this hydrodynamic condition was accomplished by using ei ther a lower viscosity POMS fluid (1 0 Pa s) at a higher shear rate (red symbols) or a higher viscosity POMS fluid (30 Pa s) at a lower shear rate (blue symbols). As can be expected, the absolute magnitude of the dispersion rate is larger for the ca se of the lower density agglomerates. However, note that in both cases, dispersion proceeds at a faster rate for the cases when a higher shear rate was applied than when using a lower shear rate. Also note that there is a larger spread between the dispersion results for the case of the weaker agglomerates in comparison to the results for the stronger agglomerates. This result suggests that characterization of the hydrodynamic conditions through shear stress alone is not adequate for the prediction of dispersion kinetics. Furthermore, the ratio of shear stress to cohesivity is not an adequate predictor of dispersion kinetics as weil. In order to quantify these effects, it would be beneficial to devise a predictive model for dispersion kinetics of agglomerates that would be sensitive to the nature of the applied hydrodynamic stress field as weil as to the cohesivity of agglomerates. Based on consideration of the spectrum of our experimental
'10
" ( 1-1»
o
•
•
. o
o
., 0.2
..
0.1
0
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0
0.'
0.'
•
o
o
0
0.2
. 0
0.1
8
• 0
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I
u
�( I"") ' Visca.;ly
. Viscosily
0.184 · 1)-10 Pa s • 0.184 · 1)slO Pa s o 0 0.184 · 1)=30 Pas • 0. 1 84 · 1)=30 Pa s
0.'
0.'
OSO Device . (TIOeIll-S80 Pa
0
0 • S O • 0
0.02
o 0.
• o
•
O.191 - TF 30 P.lI$ O.191 - 1l"JO PlIIS
• •
0
O.191 - Tt- l 0 P U O.\91 - 1}=IO P u
o 0
0
o
•
• 0."
titnc(iS'IiiI)
0.06
0.08
0.1
Fig. 22. Comparison of dispersion kinetics for precipitated silica agglomerates. The lett graph shows results for the case of relatively low density (weak) agglomerates for which #(1 -4» is 0 . 1 84, while the graph on the right shows results for higher density (stronger) agglomerates for which #(1 -4» is 0. 1 91 . In both cases, the hydrodynamic conditions were such that a mean stress of 580 Pa was applied tho the agglomerates. However, this was accomplished by using a lower viscosity fluid and a higher shear rate, or a higher viscosity fluid and a lower shear rate [23].
839
Shear-Induced Dispersion of Particle Agglomerates
observations, a useful form for such a kinetic model is [23] dR - dt (Fh - Fe) "2Y for Fh > Fe
(2)
cx:
where R is the radius of the agglomerate, Fh the hydrodynamic force applied to the agglomerate, Fe the cohesivity of the agglomerate, y the shear rate, and K a scaling parameter that reflects the geometry of the flow field. This model can be interpreted as folIows. The left-hand side of this expression characterizes the rate of material removal from the parent agglomerate. Unless the hydrodynamic force exceeds the agglomerate cohesivity, no dispersion will take place. The dispersion rate is taken to be proportional to the hydrodynamic force applied in excess of the cohesive force (which determines whether fragments can be broken from the parent agglomerate) and the applied shear rate (wh ich determines the rate at which fragments can be removed from the vicinity of the parent agglomerate). The model expressed in equation (2) can be rewritten in terms of strain by rec ognizing that }' = yf as (3) Figure 23 shows dispersion results for precipitated silica agglomerates subjected to a mean hydrodynamic stress of 875 Pa, but under two different shearing con ditions. As was the case in Fig. 22, the absolute dispersion kinetics is faster in the case of higher shear rates. For this set of data, both the hydrodynamic force Fh and cohesive force are constant (since similar agglomerates are used in all cases). According to the kinetic model presented in equation (2), under these conditions, the dispersion rate is predicted to be higher for the case of the higher applied shear rate, as is observed experimentally. Shear Stress 875 Pa Real Time t
0.6 0.5 Q
�� ...
0.4 0.3
•
p25 · 1 0 Pa s
p26 - 1 0 Pa s p27 · 1 0 Pa s • - Model Prediction pl 0 - 30 Pa s •
silica /(1- > Fe), the erosion rate becomes proportional to the energy input of the system (4) However, for smaller hydrodynamic force (Fh � Fe ), this proportionality is lost. Experimental results confirmed the predictions. In Figs. 25 and 26, we present the erosion kinetics observed when disper sing identical agglomerates with a reduced solid-volume fraction of 0. 1 94 using
841
Shear-Induced Dispersion of Particle Agglomerates Erosion Kinetics for IdenticaI Power Input 3 P!V=50,OOO W/m
0.5
- /(1 --$)=0. 194
�-�-�-�-�-�-�-�-�-��
- Model Prediction 1'1'== 1 0 Pa s ....
0.4
• •
�
Model Prediction 11=30 Pa s Experiments Tl=
10 Pa s
.. '
•
Experiments 11=30 Pa s
0.3
� �
..!. 0.2
0. 1
0.02
time (min)
0.04
0.08
0.06
0. 1
Fig. 25. OSD results at fixed power input, but with the applied stress comparable to the cohesive strength of the agglomerate [23].
Erosion Kinetics for Identical Power Inp ut J PN=90,OOO W/m • /(1--$)=0. 1 94 - Model Prediction 11=10 Pa s .. -.
0.5
� S �
• •
.� .
Model Prediction 11=30 Pa s Experiments 11= 10 Pa s
..
Experiments 11=30 Pa s
..
.,
'
..'
0.4
•
0.3
0.2
0. 1
0.01
0.02
0.03
0.04
0.05
time (min)
Fig. 26. OSD results at fixed power input, but with the applied stress far in excess of the cohesive strength of the agglomerate [23].
polymers of different viscosity with a flow field set to have an energy input per unit volume of 50,000 or 90,000 W/m 3 . The specific mean stresses and shear rates applied in these experiments are summarized in Table 1 . I n the case of relatively low-energy input (Fig. 25), the high-molecular weight fluid leads to faster erosion kinetics due to the high-hydrodynamic stress applied by comparison with the case of low-molecular weight fluid. However, the erosion
D. L. Feke
842
.
Table 1 . OSD parameters used in the silica dispersion experiments at constant power i nput
Shear Viscosity (Pa · s)
Y 1,mean =
9.3 28 9.3 28
71 42 98 57
fj;/l;"Y' 2,mean(S- 1 )
0"1 mean = ,
670 1 1 80 914 1 580
/fi;.0"2 mean (Pa) /12
'
PjV (Jjm3) 50,000 50,000 90,000 90,000
kinetics becomes proportional to the power input at higher stress (see Fig. 26) and the erosion profiles are very similar, despite the fact that the high-viscosity fluid exerts a larger hydrodynamic stress than the low-viscosity fluid. Additional information can be obtained by examining the experimental results in the context of the model. The initial rate of agglomerate erosion, when cal culated with respect to strain imposed, can be calculated considering the orien tation of the spherical cap, which leads to the strongest hydrodynamic forces (8 = rt/2,
)=0,190 · F,=I.5 . SBR 11=18 r. (J�=600 Pa s ·
os •
•
•
0.4
• 0. •
0.2 -•
0, 1
•
•
•
,.
• • •
0,05
0,1
0,15
0,2
time (min)
Fig. 29. Comparison of the dispersion curves for silica agglomerates subjected to an oscillatory shear-flow field of mean stress 600 Pa, but applied with two different oscillation frequencies. The upper set of data was obtained using lower frequency, higher strain conditions [25].
Figure 29 provides an example for silica agglomerates subjected to a cycle mean stress of 600 Pa for two different frequency conditions [25]. Note that the dispersion experiment that utilized the larger amplitude of strain (gauged by the parameter A, which represents the amplitude of the oscillation of the driving plate) and correspondingly lower frequency resulted in faster dispersion than the ex periment in which a smaller strain (and higher frequency) was used. Recall that in simple-shear flow, the principle strain directions are along the ± 45° diagonals. These are the locations along the surface of the agglomerate where the production of dispersion fragments is most likely to occur. In the case of the higher strain experiments, a greater fraction of the agglomerate surface will rotate through these favorable positions than in the case of a low-strain flow field. Thus different dispersion kinetics may be expected. In order to analyze and provide a basis for the experimental results, one can resort to an analysis of the details of the shear stress profile acting upon the agglomerates within an OSO experiment. A summary of this analysis for dry agglomerates is presented here. Within an OSO experiment, different portions of the agglomerate experience compression, while other portions experience tensile stresses. If the tensile stress exceeds the local cohesivity, dispersion is expected to occur. Assuming that the agglomerates are dry (no infiltrated processing fluid), if the local frag mentation number Fa exceeds unity, then dispersion can occur, given that the duration of the stress at this value is adequate. As a measure of the likelihood of
Shear-Induced Dispersion of Particle Agglomerates
845
erosion at any given point on the surface of an agglomerate, we use the local value of (Fa - 1 ) which is a relative measure of the degree to which the applied stress exceeds cohesivity. Figure 30 provides a set of polar plots that give the likelihood of erosion for positions on the midplane of the agglomerate for different times within a half cycle. (See [26] for further details.) In this example, the cycle-averaged value of Fa is 2. The distance from the center of each polar plot gives the local value of (Fa -1 ), and the square inserts and depict the specific instance within the cycle. Progressing from the upper left plot to the lower right plot, we see that the likelihood of erosion starts off to be the greatest along the 1 35-3 1 5° axis, diminishes to zero in the center plot (which corresponds to the point of the
&; 90
24
120
-
1 ,. ,
180
:
.
_
)l
330
20
0
\
I
240
210
02
330 300
'0
U -2 I,' -t.20:1
120
ISO
180 f-!
210
.0
�''
dispersion
Fig. 2. Dispersion and wetting transformation maps for binder dispersion: (a) in a me chanical mixer; (b) spray-on in a f1uid-bed g ranulator; (c) coverage of binder on the particle surfaces.
Scale-Up of High-Shear Binder-Agglomeration Processes
861
Surface Reaction, Drying slow, incomplete reaction
fast, complete reaction
wetting coverage Fig. 3. Chemical reactions between the binder and the solid powders depend on disper sion and wetting coverage at the solid-liquid interface. In drying, the rate also depends on the liquid coverage over the solid surface; a higher coverage area provides more liquid vapor interface for drying.
granulation. In another example, granular detergents are made by an acid-base reaction between binder and powder. In such cases, reactions occur at the sur face interface between the binder and powder; thus, the extent and rate of the reaction depends on the wetting coverage. Drying is somewhat analogous to this, except that the drying rate increases with increasing liquid-gas surface area. This occurs when the binder is thinly distributed over a large powder surface area. Both reaction rate and drying are very important transformations because they can significantly affect binder properties (e.g . , viscosity, yield stress) and the effective binder loading (i.e., liquid saturation), which are key to the transforma tions of granule growth and consolidation (Fig. 3). 2.3. Granule structure - saturation
The primary factor controlling agglomerate growth is the relative binder loading level and degree of saturation in the granule structure (Fig. 4). The filling of the binder in the granule pores is expressed as the saturation ratio, relating the binder volume bridging between particles within the agglomerate to the total available pore and void space between particles [12-14] . The saturation ratio is increased by adding more binder andjor by consolidating agglomerates to reduce their internal porosity. The growth process depends on the success of particles stick ing together upon collision. More growth occurs with increasing binder saturation, especially as the saturation approach es 1 00%. In the (fully-saturated) capillary state, rapid growth occurs by coalescence. Beyond 1 00% saturation, the particles are suspended in a continuous liquid phase and a paste or over-wet mass results. 2.4. N ucleation
The nucleation stage of an agglomeration process is the initial phase where small agglomerates (nuclei) are formed. Two basic mechanisms can be considered
862
P. Mort
Relative binder loading in liquid bridge structures a) Filling pores by binder addition: b) Pore space reduction by consolidation: pendular
funicular saturation
capillary I 1 00%
droplet ..
Fig. 4. The structure of granules evolves with increasing binder saturation. Saturation increases by: (a) additional binder loading andjor (b) granular consolidation.
a) Distribution Mechanism
• •-_ . solid particles
+
agglomerate growth
• dispersion � . -
�
wetted particles
binder
agglomerate, size and size distribution controlled by growth mechanism
b) Immersion Mechanism •
.
•
:
•
.
solid particles
+• binder
immersion agglomerate, size controlled size of binder "template"
Fig. 5. Agglomeration nucleation mechanisms: (a) distribution; (b) immersion. Granule properties typicaJly depend on the mode of nucleation and growth.
[ 1 5] . The distribution case assumes that the binder disperses as a film on the particle surfaces; nuclei are formed by successful collision and bridging of the particles (Fig. 5a). The immersion case considers a binder droplet or other binder mass as the core of the agglomerate, to which finer solid particles are attached and embedded (Fig. Sb). The results of the agglomeration, especially the size distribution of the agglomerates, can be related to the prevailing mechanism. The immersion mechanism is attractive because the binder droplet size can be used as a control parameter for the product agglomerate size [16] . Immersion is also very useful as a way to encapsulate a sticky binder in a dry shell. An example of experimental work on agglomerate nucleation by droplet immersion shows the effect of binder viscosity and powder-fluid interactions [1 7]. In this case, binder viscosity is a function of the solution concentration of
Scale-Up of High-Shear Binder-Agglomeration Processes
863
Fig. 6. Binder droplet nucleation experiments from Hapgood [1 7] using an initial binder droplet diameter of �2 mm in lactose powder: (a) dyed water, d = 6.5 mm; (b) dyed solution of 3.5 wt% HPC, viscosity = 1 7 cP, d = 3.5 mm; (c) dyed solution of 7 wt% HPC, viscosity = 1 05 cP, d = 3.0 mm.
hydroxypropyl cellulose (HPC). Relatively large (�2 mm) individual binder drop lets with a dye tracer are contacted with a static bed of fine powder. The binder wets into the powder forming nuclei, which are recovered, dried and analyzed (Fig. 6). The lower viscosity binder (water) wets the hydrophilic excipient (lac tose) and spreads out from the core (dyed center, capillary structure) to form a looser network of extended pendular hydrate bonds. On the other hand, the water in the more viscous HPC solution is less available to spread and chem ically interact with the lactose and the agglomerate retains only a dense capillary core nucleus. This work shows the net effects of initial dispersion of binder in the powder (i.e., as discrete droplets), wetting-spreading interactions between the binder and the powder and chemical interactions between the binder and powder substrate. Schaafsma et 81. [1 8] proposed a quantitative nucleation ratio based on the volume ratio of the agglomerate nucleus relative to the binder droplet. It is in structive to notice that while the absolute size of nuclei formed using the simple single-droplet nucleation experiment (as shown in Fig. 6) can be an order of magnitude larger than nuclei formed in an actual granulation process with a spray atomizer, the nucleation ratio is reasonably consistent across scales. For exam pie, structural differentiation of lactose nuclei made with different binders (water vs. H PC solution) has been shown to be consistent for a wide range of droplet sizes [1 7] (Fig. 7). This suggests that the simple single-droplet experiment is a useful first step to investigate binder-powder interactions and their effects on the formation of nuclei structures [1 9].
2.5. Granule g rowth - stokes criterion tor viscous dissipation
Growth processes can be modeled using a force or energy balance that relates forces applied in the process to material properties. The relevant material prop erties depend on the growth mechanism (Fig. 8). In terms of process control
864
50
? 40 § 30 Q
� 20 c: 0
CI) t3 ::J 2:
10
\.
•
ys]\
•
I spra
.1
water 7% HPC soln .
: I single drop/ets I
• • •
P. Mort
+
•
•
•
0 1 00
1 0000
1 000 Nucleus size ( um)
Fig. 7. Nucleation ratio (K) for agglomerates formed with lactose powder and a binder (either water or an aqueous HPC solution), using both single droplet experiments with a syringe (as per Fig. 6) and nucleation experiments with a spray atomizer.
Agglomerate Growth:
"� '"
a) Viscous Stokes: 0 () '"
(jj -0 '5
c:
:ci
large MPS
b) Yield-coalescence: '" '"
�
Cii
-0
small MPS impact velocity
Qi '5-
:m (1l ()
small MPS
c) Yield-breakage case: '" '"
�
Cii
large MPS
Q. impact stress
-'" (1l
�
.0
large MPS small MPS impact stress
Fig. 8. Growth transformations analyzed in terms of force balances, where the extent of size growth is given by the mean particle size ( MPS) of the granular distribution: (a) viscous Stokes case describes growth limited by viscous dissipation in binder layer; it assumes good binder coverage and the formation of liquid bridges on contact. (b) In the yield-coalescence case, plastic deformation and binder flow must be activated to form bridges between particles andjor embed particles into a binder droplet. To activate binder flow, the stress at impact must exceed the yield stress of the material (either binder or granular composite). In this case, it is assumed that the energy dissipation in plastic deformation of the material is large compared to the impact energy; therefore, no rebound occurs. (c) The yield-deformation-breakage case describes an upper limit to growth based on granular breakage, where the shear stress increases with increasing granule size.
parameters and material praperties, the Stokes criteria (Fig. 8a) and the elas tic-plastic transformation maps for coalescence (Fig. 8b) appear to be in con tradiction. Obviously, it is of critical importance for scale-up and process contral that the mechanism of grawth is understood. The viscous Stokes criterion for granulation considers the force balance be tween colliding particles according to the dispersion mechanism (Fig. 5a) [20]. In this case, good binder coverage is assumed, and the success of collisions in
865
Scale-Up of H igh-Shear Binder-Agglomeration Processes
producing larger agglomerates depends on whether the eollision energy is suffi ciently dissipated by the viseous binder to prevent the elastie rebound from breaking the binder bridge between the particles. Further, it is assumed that the binder rheology and surfaee tension permit the spontaneously formation of a liquid bridge on eontaet. The limitation to growth oeeurs when the viseous dis sipation in the binder is not sufficient to absorb the elastie rebound energy of the eollision, as with a low binder viseosity or high eollision velocity (Fig. 8a). The Stokes eriterion is expressed in the form of a viseous Stokes number (Stv), given as the ratio of the eollision energy to the energy of viseous dissipation equation (1 ), where ä is the harmonie mean particle size in a eollision of two particles equation (2), U the eollision velocity, P p the particle density and 11 the binder viseosity. The eritical Stokes number (S�) accounts for binder loading in a system equation (3) where it is assumed that particles possess a solid core. Here, e is the particle coefficient of restitution, h is the binder thickness at the collision surface and ha a charaeteristic length scale of surface asperities. For conditions in which Stv is less than the critical value, S�, collisions are successful and growth occurs. For Stv > Se;, viscous dissipation is insufficient and rebound occurs (Fig. 9). While it is difficult to measure the parameters in the critical Stokes number, it can be convenient, in practice, to correlate the ratio hjha to the degree of binder dispersion. For example, a poorly dispersed binder will result in some areas with thick binder eoverage and others with little to no binder. The result is a distribution
1) Particles on
collision course
2) Liquid bridge lorms on contact 3) Elastic collision 01 core particles, then rebound 4) Is viscous dissipation >
inertia?
rebound Stv > St'
/ , No
'- Yes
�
agglo meration Stv < St'
Fig. 9. Agglomeration sequence described by Stokes criteria.
866
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of critical Stokes numbers or even a bimodal distribution, leading to heteroge neous growth. 8pp Ua Stv = (1 ) 9 1] (2)
(3) Binder rheology is not necessarily confined to Newtonian fluids. In fact, many binder systems exhibit yield-stress behavior. Examples include binder solutions containing longer-chain polymers, especially when the local activity of the poly mer on the particle surface changes due to water evaporation, hydration andjor partial dissolution of the particulate solid. In such cases, small collision velocities andjor short collision times may be insufficient to allow for substantial binder flow and liquid bridge formation and more energetic particle collisions may be required to induce agglomerate growth. The combination of a high binder yield stress and a low collision velocity results in low growth while a low yield stress and higher collision velocity results in more growth (Fig. 8b), as long as the dissipation is sufficient to prevent rebound. Energy dissipation can be quantified in terms of viscosity or loss modulus. It is important to note that binder rheology at the time of collision is relevant to this analysis; this is not necessarily the same as the rheology of the starting binder material, measured before addition to the agglomeration process. One must consider other transformations that may alter the binder rheology after it is added to the granulation, such as thermal effects, drying and hydration. Kinetics of these transformations must be considered in processes where binder rheology changes simultaneously with agglomerate growth and consolidation. Other examples of yield-stress binder rheology are found in melt agglomer ation. Here, the binder is added as a powder or flake solid, mixed with the other powders, and then transformed into a binder by heating the entire mixture. In its transformation from solid to liquid the binder typically passes through a critical sem i-solid or glassy state where the yield-stress drops into the range of shear stress in the process, and growth occurs. Thermo-mechanical analysis can be used to quantify this growth onset [21]. In cases where the binder solids are larger in size than the other powders, melt-agglomeration may proceed according to an immersion mechanism, where the finer solids are embedded into the semi-solid binder particle.
Scale-Up of High-Shear Binder-Agglomeration Processes
867
2.6. Granule g rowth - coalescence
Granular deformation leading to coalescence is a well-documented growth mechanism [22-24]. In coalescence, colliding granules stick together if the col lision force is sufficient to plastically deform the granules, increasing the zone of contact, and consolidate the granular microstructures to the extent that enough binder is expressed into the contact zone (Fig. 9). Iveson and Utster proposed a granular growth regime map that shows increasingly rapid growth with increasing deformation at relatively high binder loading [25]. Assuming that there is enough fluid binder within the granular microstructure to hold the deformed parts together and prevent fracture, then growth will occur. Although rebound will occur if the collision is not of sufficient energy to induce elastic to plastic deformation, once the plastic yield stress is exceeded, the energy absorbed is typically quite high compared to the collision energy, minimizing the chance of an elastic rebound to break the formed bridge. Thus, the key transformation is the deformation of the granular microstructure and the flow of capillary binder to the contact zone, where the coalescence bridge is formed. Iveson and Utster describe this deformation propensity in terms of a deformation number (Oe), where Yg is the granule dy namic yield stress, Pp the granule density and U a characteristic collision velocity for the granulator Oe =
2 Pp U Yg
(4)
The key material parameters relate to the deformation of the composite granular microstructure; typically, this is measured as an apparent plastic yield stress of the granular material (Fig. 8b). Note that the yield stress of the wet mass may depend on the deformation rate, which depends on the time scale of collisions and shear-induced consolidation associated with a given agglomeration process [26]. Figure 1 0 Returning to the apparent contradiction in the transformation maps for the Stokes' criterion vs. plastic coalescence (Fig. 8a and b), on closer anal ysis, the micro-scale models are not necessarily contradictory. In the case of elastic-plastic collisions leading to coalescence, consider that the critical Stokes number (S�) equation (3) accounts for binder loading in terms of the binder thickness at the zone of contact. During plastic deformation and microstructure consolidation, the binder thickness in the contact zone, h, may increase sub stantially as binder is expressed from the pore structure into the contact zone, thereby increasing the instantaneous value of S� at the relevant interface. Fur ther, the value of S� increases with a decrease in the coefficient of restitution (e), as in the transformation from elastic to plastic deformation. Thus, the force balance analyses remain consistent when one treats S� as a variable that can
868
P. Mort collision of agglomerates
O"j < O"y
O"j
� elastic rebound
>
O"y
� plastic deformation of granules, flow of binder into contact zone, coalescence
Fig. 1 0. Agglomerate growth by plastic deformation and coalescence. Plastic deformation occurs when the collision impact stress (O"i) exceeds the plastic deformation yield stress of the composite granular material (O"y). Plastic deformation of the granules increases the contact zone area. If sufficient binder flows into the contact zone, coalescence occurs.
undergo instantaneous change during collisions involving micro-structural redis tribution of binder and/or change in restitution due to elastic-plastic transition. 2.7. Growth limitation
The yield-deformation-breakage case (Fig. 8c) considers the upper limit of growth in the process, beyond which breakage becomes dominant. The yield limit is expressed as a "Deformation-breakage Stokes number", Stdef [27]. This is the ratio between the kinetic energy of a collision to the energy required for breakage (equation (5)), where Tb is the shear stress required to deform and break the granule. Assuming that the local collision velocity is proportional to the shear rate and the particle size (equation (6)), and that the granule's yield strength is ap proximated by a power-Iaw rheology model (equation (7)), a power-Iaw relation ship is predicted between the limiting size, a* , and the shear rate in the mixer (equation (8)). This approach has been used to analyze the scale-up of agitated fluid-bed granulators [2, 1 0,27]. Ppu2 Stdef = -2Tb U�y x a Tb
=
kyn
a* = y« n/2)-1) + c
(5) (6) (7)
(8)
Scale-Up of High-Shear Binder-Agglomeration Processes
869
Growth is limited by the balance of the collision stress applied to the granule relative to the inherent fracture stress of the granular material. In theory, agglomerate strength can be considered on the basis of binder-bridge strength between particles [28]. In practice, it is observed that large agglomerates are more prone to fracture than smaller ones for two reasons: ( 1 ) for a given impact force, the larger the size of the agglomerate, the greater the moment and the larger the stress that will be exerted on a weak point in the micro structure; and (2) as a composite material, larger agglomerates are more likely to contain a larger number of flaws through which cracks can propagate and cause fracture. While the approach described above provides reasonable correlation with ex perimental data, it should be noted that it relies heavily on the approximate re lationshi p given in equation (8), where the shear rate is related to the impeller tip speed and a characteristic particle size. In actuality, the material will see a dis tribution of shear and impact stresses which could lead to breakage, and the distribution will typically depend on the pattern of flow in a mixer-granulator. Another approach is to experimentally measure the critical stress directly using a set of tracer particles [29]. Tracers with known yield stress and breakage be havior are added to the mixer; examination of their remains provides an exper imental basis for the in situ stress state in the mixer. Breakage of agglomerates also affects the homogeneity of the product [30]. The dynamic situation of granule growth and breakage leads to a continuous exchange of particles, which improves the homogeneity of the granules. When granule breakage is absent, any heterogeneity due to the non uniform distribution of the binder in the nucleation stage tends to remain in the final product. In terms of process control parameters and material properties, the elastic plastic transformation map for coalescence (Fig. 8b) and the yield-breakage map (Fig. 8c) appear to be in opposition. In the plastic coalescence case, more growth occurs with increased process energy. In the yield-breakage case, an increase in process energy causes more breakage, lowering the stable size limit. Although both cases are driven by mechanical interaction between the process and the granular materials, the product result is very different. In the elastic-plastic de formation case, the granule is able to absorb all of the impact energy and dis sipate it through plastic deformation and heat, resulting in coalescence. On the other hand, the material undergoing yield-breakage cannot absorb all the energy; it reaches a fracture point that limits its growth. The transition between plastic to breakage behavior can be strongly influenced by material properties such as moisture content and temperature [31]. Thus, the relevant transformation map may change during a typical agglomeration process, e.g., progression in tem perature and moisture level in a fluid-bed d ryer-agglomerator may move the process from case 8b-c or vice versa.
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2.8. Granule consolidation
Agglomerate consolidation requires the deformation of a granular structure into a dense-packed structure. Plastic deformation occurs when the localized impact force exceeds the composite yield stress of the granule (Fig. 1 1 ). Consolidation can increase the binder saturation ratio by reducing the intragranule void volume and can trigger coalescence when the saturation ratio reaches a critical point. Thus, the consolidation transformation is integral to the mechanism of growth coalescence by plastic deformation. If the yield stress occurs between an elastic and plastic regime, consolidation will occur. Below critical saturation, the granular strength tends to increase with consolidation, typically with an increase in res titution coefficient andjor yield stress. The linkage of consolidation and growth implies two potential feedback loops: ( 1 ) a negative feedback to offset growth - as growth proceeds by coalescence, granular densification may cause an increase in the apparent yield stress, thereby limiting further coalescence; and (2) positive feedback which can poten tially lead to runaway growth if consolidation increases binder saturation beyond a critical point (e.g., from capillary to droplet structure in Fig. 4b) or if the yield stress is reduced as the result of the internal heat produced by the work of plastic deformation. The dominant scenario is reflected in the value of the exponent "n" in equations (7) and (8). When n > 1 , we see a consolidation strengthening effect where the yield stress of the granule increases with consolidation. On the other hand, a value of n < 1 implies a softening of the material with increasing con solidation, which can lead to runaway growth. Obviously, the negative feedback scenario is preferred from the perspective of process control. 2.9. Attrition, breakage
As discussed earlier in the discussion of growth limitation, agglomerate breakage is a dynamic part of the process. It is essential to limit growth and to help improve Agglomerate Consolidation
density
� high density
impact stress
8
Fig. 1 1 . Consolidation of granular microstructure and the elimination of intra-granular po rosity.
871
Scale-Up of High-Shear Binder-Agglomeration Processes
the compositional homogeneity of the product. Beyond this, the details of granule attrition and breakage are quite complex. There are different mechanisms for surface breakage (i.e., erosion, abrasion) and particle breakage (fracture, shattering). These depend on material properties including elastic modulus, hardness and fracture toughness (i.e., the resistance to crack propagation), particle shape and impact conditions. In this illustration (Fig. 1 2), a tough particle may survive a high level of impacts before it finally shatters, while a particle with a lower toughness andjor more irregular shape may progressively break into smaller fragments with increasing impact stress andjor increasing number of impact events. Generally, one of the prime reasons for doing agglomeration is to avoid problems that are encountered with fine particles, e.g., hygiene, dust explo sively, or other product performance issues correlated with fines. Obviously, once having made the investment to make the agglomerates, it is paramount to avoid their attrition or abrasion in subsequent handling and conveying opera tions. Here, there is a balance in approach toward specifying more gentle han dling operations vs. the design and production of the agglomerates with increased resistance to attrition. There are a number of criteria for particle breakage, depending on the particle characteristics, material properties and the details of stress loading (compression, shear, stress rate, number of impacts, fatigue, etc.) [32,33].
Agglomerate Attrition a) Impact breakage
b) Compression / shear
c: 0 .Ci; CI) Q)
0. E
0 0
impact stress
�
0
breakage I
!JJ
0
� abrasion 0
0 0 0
shear stress
Fig. 12. Attrition of granules as a funcbon applied stress and material properties (com posite material toughness, flaw distribution, shape, etc.): (a) single particle impact mode tends to cause intermediate breakage and/or shattering depending on material properties and impact stress; (b) in multi-particle interactions (e.g. , shear and compression in bulk handling operations), abrasion can be a problem along with breakage. A more detailed discussion of breakage mechanisms and material property relations are cited in the lit erature.
872
P. Mort
3. SCALE U P OF PROCESS EQUIPMENT - THE MACRO-APPROACH
Scale-up of agglomeration processes based on equipment parameters is referred to herein as the macro-scale approach. Typically, the macro-scale approach de termines desired operating conditions over a size range of unit operations using dimensionless groups, such as Froude number, Reynolds number, Power number, swept volume, delivery number and spray flux. While the actual unit operations may or may not be geometrically similar, it is generally sought to maintain the similarity of stress and powder flow fields across a set scales, especially for mixer granulators where the applied stress is critical to the micro-scale transformations. In order to control the stress and flow fields of the powder and granular ma terials, several other dimensioned parameters or parameter groups that are often used including mixer impeller tip speed, power draw and power draw derivatives. The effect of process time can be combined with power draw in a mixer to be expressed as the cumulative or specific energy dissipation. These operating parameters may typically affect multiple product transforma tions. It is a challenge to scale up equipment in a way that maintains key product attributes while also achieving an economical and industrially efficient operation. For example, impeller speed andjor the Froude number in a vertical granulator affect binder dispersion, consolidation, coalescence and breakage. Herein is a classic challenge for scale-up: one cannot increase the mixer diameter and keep both Froude number and tip speed constant. The suggested approach identifies the critical transformations based on product attributes and the selects appro priate scale-up criteria. If it is not possible to resolve the key transformations simultaneously, it is then advisable to separate the transformations, either tem porally or spatially. For example, by staged processing in a batch unit or adding additional unit operations in a continuous process.
3.1 . Power-draw, torque
A measurable process parameter, such as power draw in a high-shear vertical granulator, is often used to determine the desired process residence time (e.g., endpoint in a batch mixer or fili level in a continuous mixer). In the pharmaceutical and powder technology literature, there are numerous references on the use of power draw, torque or other similar indicator for endpoint control and scale-up of batch granulation processes [34-39]. While these provide guidelines for scale-up of the equipment operation, empirical adjustment of parameters may still be re quired to achieve the desired granular product attributes, such as granule size, size distribution and particle density. I n a classical scale-up approach [40], dimensionless groups relating process parameters and wet-mass material properties are applied over a series of vertical
Scale-Up of H igh-Shear Binder-Agglomeration Processes
873
mixer-granulators. The power number (Np) relates the net power draw (I1P) to mixer size (0), rotational speed of the agitator (N) and the instantaneous product bulk density (p) (equation (9)). A pseudo-Reynolds number (Re*) describes the kinematic flow in the mixer in terms of product bulk density (p), agitator tip speed (ND), characteristic shear dimension (0) and a pseudo-viscosity ( 11 *) (equation ( 1 0)). Here, 11* is a torque measurement obtained using a Mixer Torque Rheo meter (MTR). The MTR compares the measured torque to the applied shear in order to measure the consistency of the wet mass [41 ]. Other references provide rheological measurements based on compression of the wet mass [42]. Shear cells have also been used to measure the cohesivity or tensile strength of a wet mass sampie as a function of its compression state [43]. Each of these methods provide a reasonable correlation between a measured constitutive property and the power draw in the granulation process, where product sampies are collected intermittently at different residence times in a batch operation and measurements are made on their rheo-mechanical consistency. The MTR torque is assumed to relate to bulk flow behavior of the wet mass, in a way that is analogous to viscosity in a liquid system . The Froude number (Fr) is the ratio of centrifugal to gravitational forces, and describes the state of fluidization in the mixer (equa tion (1 1 )). The Fill number describes the relative loading level of the mixer (equation ( 1 2)). I1P Np = (9) 3 5 -
pN 0
Re* = Fr =
pN02
11* N20 9
�-
Fill # = � 0
( 1 0) (1 1 ) ( 1 2)
Analysis of data over a range of mixer scales collapse to an apparent power-Iaw relationship between Np and the product of Fr, Re* and fill numbers [40]. The strongest correlation appears between the power draw and the rate of energy dissipation (i.e., pseudo-viscosity) in the wet mass. The overlap of the data at different scales implies that there is a consistent scale-up relationship between the power draw of the mixer and the wet-mass consistency of the mixture; further, this relationship can be extended across mixers that are not necessarily geo metrically similar. This approach demonstrates the use of MTR to characterize sampies extracted from the process. It shows that the relevant rheo-mechanical properties of the wet-mass change as the bulk material is transformed during the agglomeration process. Although this approach does not directly address the
874
P. Mort
scaling of micro-scale product attributes, the inclusion of product density and wet-mass viscosity in the dimensionless groups provide indirect linkages. Some correlation has been shown between the wet-mass properties and subsequent dry-granule product attributes [44]. The importance of the pseudo-Reynolds number underscores the interaction between the wet-mass rheo-mechanical properties (i.e., the transmission of stress through the material) and the tip speed (ND) of the mixer. Note that the collision velocity (U in equations ( 1 ), (4), (5), and (6), a key parameter in the micro-scale analysis, is dependent on the tip speed. This highlights the impor tance of tip speed in scaling up mixer-granulation devices. In another example from the pharmaceutical literature, lab scale tests were done to define an optimum power level for endpoint control in the scale up of a granulation process in a vertical mixer granulator [45]. The granulation process was followed by tabletting. The critical properties of granular flow, tablet weight variation and tablet disintegration time were optimized together at a single power-draw endpoint on the lab scale. On scale-up to a larger mixer, however, several product attribute issues were encountered. In maintaining similar mechanical fluidization for binder/powder dispersion (i.e., constant Fr), more granular densification occurred, which had a negative effect on tablet properties. Increased granular densification due to the higher impeller tip speed is often encountered when using a Froude Number scale-up to a larger diameter mixer. To adjust the density, the rotational speed can be reduced to approach tip speed (i.e., kinematic) similarity. To maintain equivalent binder distribution at the lower state of fluidization, a reduction of the binder spray flux (i.e., a longer batch time) may be required. It should be noted that the method of binder addition and its distribution in the powder typically becomes more and more critical at larger scales. Another approach to scale-up using power-measurement employs a small-scale batch mixer to estimate the optimal binder loading levels for a formulation to be produced at a larger scale (Fig. 1 3). In this example, an excess of a binder liquid is intentionally added to the batch mixer-agglomerator at a controlled feed rate, and the power-draw or torque is monitored. In a system where growth is driven by saturation coalescence, a sudden increase in the power draw indicates the onset of rapid agglomerate growth. The level of binder present in the mixer at the power draw onset point is defined as an empirical limit for binder addition in the given formulation. To avoid over-agglomeration on scale-up to a production system, the binder addition level is maintained at or below this limit. Note the increase in power consumption can also result in increased product heating due to shaft work (Fig. 1 3b). Additional examples showing the correlation between power consumption and temperature change are documented in the literature [46]. It should be noted that the binder content at the power draw onset in a small batch mixer is an empirical indicator, not an absolute measure of binder loading
875
Scale-Up of High-Shear Binder-Agglomeration Processes Add binder
Q) :l er
Q) :l er
t-
es
t-
;: �
�
es
es
....
E Q) t-
Q) a.
-0
Qj
"0
Q) ;: 0 a..
� 0 a..
(a)
es
� 2 �
Batch time
(b)
Batch time
Fig. 1 3 . Determination of formulation binder limit using analysis of power draw onset in a batch mixer: (a) link from power-onset to binder level; (b) increased power draw (i .e., post onset over-agglomeration) results in an increase in frictional heating of the product.
capacity. The more fundamental characteristic of wet agglomerate structure is the saturation [47], which is discussed in more detail earlier in this chapter. Ac celerated growth by coalescence and increased power draw typically occur at a critical state of capillary-filled saturation [48]. This structure depends not only on the binder loading level, but also on other scale-dependent process parameters and/or environmental conditions that can affect consolidation, e.g., the tip speed of the impeller, temperature, relative humidity. There is a nesting effect of interrelationships between binder loading, consol idation, saturation, granule growth and power draw. While feedback among these interrelationships may have a confounding effect, one can pose a rational se quence of cause and effect as folIows: ( 1 ) binder loading and/or consolidation causes an increase in the saturation of the granular structure; (2) increased sat uration causes an acceleration of the granular growth kinetics; (3) the combination of the increased particle size and surface-moist cohesion (due to higher saturation) can increase the shear stress transmission within the flow pattern, resulting in an increase in power draw. Further implications are discussed in Section 3.4.2.
3.2. Specific energy (E/M)
The net specific energy is a measure of the transformation work being done on the producl. Integrating the net power draw over the residence time gives the net energy consumed in the agglomeration process. In a batch process, the net energy divided by the mass holdup gives the net specific energy input, or E/M. In
876
P. Mort
a continuous process, the specific energy can be obtained directly by dividing the net power draw by the feed rate. Specific energy is an appealing scale-up ap proach, with analogies in other process technologies, e.g., extrusion, kneading and milling. Recent work reports that process work can be effectively used to complement power draw analysis for more robust process control [49]. On the one hand, the advantage of specific energy is that it combines effects of net power, time and mass into a single group. On the other, the practical difficulty of the approach is determining the net power draw. The net power draw is that which is used to do productive work of agglomeration, i.e., to transform the product. Net power draw can be calculated as the difference between the gross power draw, which is easily measured, and the baseline power consumption. As a first approximation, the baseline can be measured by running the empty mixer. However, there are typically additional parts of the gross power consumption that are not directly related to the productive work of granulation. Examples include product fluidization, mixing, conveying, andjor drag caused by build up of product on mixer walls andjor impeller tools [50,51]. These effects may change from batch to batch, within a batch or during a continuous run and hence it can be difficult to pin down a constant value for the power draw baseline. Nevertheless, the specific energy approach offers some advantages. If care is taken to measure baseline power consumption, the resulting net energy can be shown to be a useful parameter for scale-up, especially in an agglomeration process that is driven by coalescence. With the coalescence mechanism, smaller agglomerates are fused together to make larger agglomerates by a mechanical consolidation process. If the energy of the process provides a force that is suffi cient to overcome the plastic yield stress of the agglomerates, then they will deform at their contact points and coalesce to a larger size. This energy balance can be expressed as a dimensionless group (see x-axis, Fig. 1 4b). This group is similar to the Stokes' deformation number described later in the micro-scale section, except that the energy in current expression is measured directly from the power draw consumption. The yield stress of the wet agglomerate (i.e., a binder-powder composite) is a critical material property that lumps together the composite effects of raw material properties (binder and solids) as weil as process and environmental factors, such as temperature and relative humidity. Yield stress is typically measured using a mechanical testing machine to collect load-displacement data on a small bed of granules (e.g., in a tablet die); these data can be analyzed by a number of different methods to determine a yield stress value [52-54]. Note that conventional load-displacement experiments are typically done at fairly low compression rates. While these data typically provide a useful and convenient basis for comparison, it should be noted that the in situ compression rates can be significantiy higher in the granulation device, especially for direct impact consolidation. On the other hand, in situ shear interactions are generally more gradual. Measuring energy dissipation
877
Seale-Up of High-Shear Binder-Agglomeration Proeesses
100
� 1 0 ::!---'-rI----i o
"0
(a)
1 00 ::r-------,
::r-------,
batch ti me
�
o
(b)
In(d/do) =
f(x)
10
x
=
(E.M) *p/Gy (
Gy = f(T,binder)
11
E = f( N )
1
Fig. 1 4. Scaling of agglomerate g rowth by eoaleseenee meehanism using speeifie energy
vs. yield stress of the wet-mass material. (a) The data in represent various binder loading
levels, operating temperatures (T) and operating speeds (N) in a horizontal-axis plough share mixer. The batehes are run for various bateh times and then eharaeterized for size growth, where the geometrie mean size on a mass basis (d) is eompared to the initial mean size (da) . (b) When resealed as speeifie energy (E/M) relative to yield stress (ay) , the data eoliapse to a master growth curve.
and deformation behavior at higher strain rates is a more difficult endeavor. Re sults of such experiments highlight the importance of viscous limitations in the kinetics of binder redistribution at high consolidation rates [55]. 3.3. Swept volume
Relative swept volume can be used to compare different mixing equipment de signs and size scales [56]. It considers the volume of product swept away by the impeller of mixing bl ade in a given period of time, combining the affects of product fill level, impeller speed and impeller design. This approach is valid as long as there is good mixing (i.e. , powder flow) throughout the filled volume of the mixer. The idea of swept volume analysis can be extended using a modeling ap proach to consider the probability, frequency and distribution of interactions be tween the active mixing elements (tools) and the product. Ideally, one seeks to have a tight distribution of interaction frequency such that transformations are uniform across the whole product. This approach can be useful in estimating relative impact velocities between product and active mixing elements or between a moving product and vessel wall. The velocity of impact and frequency thereof can be used as a way to scale physical transformations such as coalescence (growth) and consolidation (densification). As such, this approach can link equip ment parameters and micro-scale analyses of product transformations. Once again, the key to completing this link is an understanding of the constitutive properties of the wet-mass mixture.
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CFD Model Section �
mixing tools
V CFD results:
shovels
Appro ach' Measure or estimate residence time, RTD [C FD model used here]: Use geometry (tool design), shaft speed and fluidization (Fr#) to estimate product / tool interactions ( i . e . , swept volu me).
virtual particle injection
I
product
Q)
0.8
-
u 0.6 ca
"t: :::J
(f) 0.4 Q) Cl
� 0.2 Q)
> «
0.0 0.0
....... 300 L
;::;/ � /
2.0
/
Stardard Low Speed 4.0
/
/
-
6.0
8.0
------
....
.....
Impeller Tip Speed ( m/s)
1 0.0
�Stancard High peed 12.0
14.0
Fig. 1 9. Surface velocities as a function of i mpeller tip speed and granulator scale [23].
revolution, even though the impeller was running at 1 80 rpm, the standard "Iow" speed setting. Stagnation of the bed during solution delivery is clearly undesir able, but Plank et al. [23] demonstrated that it was not an unusual occurrence. Maintaining constant spray flux on scale-up is actually challenging. The sim plest method is to maintain the same flowrate through the nozzle, but this extends the total granulation time in proportion to the scale-up ratio. If the saturation exceeds the nucleation regime limit (see Section 3), then the growth and con solidation will be affected. This is usually undesirable. In mixer granulators, the powder surface velocity often decreases as the granulator scale increases, and the spray width and drop sizes do not usually compensate for this. Increasing the
916
K.P. Hapgood e t al.
impeller speed to maintain equivalent surface velocity at full scale may signifi cantly affect the forces experienced by the granules, and again change the con solidation rate and Stdef growth regime. Alternatively, the total granulation time can be maintained during scale-up, and the solution flow rate increases proportionally. This is the more common ap proach in pharmaceutical granulation, and results in a significant increase in the spray f1ux. Table 1 below gives an example of scale-up from a 1 5 kg batch to a 70 kg batch. Initially, the calculated spray flux 'Pa = 0.36, which is in the inter mediate nucleation regime. Powder velocity data is taken from Fig. 1 9. In the first case, the spray rate is maintained constant, but there is still an increase in spray flux. The second case considers if the spray rate is adjusted to maintain constant granulation time. In both cases, the spray flux increases and moves firmly into the mechanical dispersion regime. Note that the example above implicitly assumes that the fan spray is orientated perpendicularly to the direction of powder flow. This is often overlooked in in dustrial granulation in mixers, particularly is the powder flow direction changes on scale-up due to the usually lower mixing intensity. In the examples in Table 1 , 'Pa increases at least 1 0-fold if the powder runs through the fan length ways, as the spray width decreases to less than 5 cm for most nozzles. A conical nozzle eliminates the orientation effects, but often creates new problems due to wet patches and buildup on the granulator walls. Alternatively, the spray nozzle can be placed directly over the chopper, where the turbulent powder flow and strong localised shear forces ensure minimal effect of nozzle orientation and minimal effect of high spray flux. Figure 20, shows the size distribution of granules formed in a 300 L mixer using a single nozzle. Owing to the turbulent flow, the powder direction through the spray could not be determined. However, by taking the best and worst possible cases, the spray flux is not less than 1 .6 and could exceed 'Pa = 1 2. This is the mechanical dispersion regime and the chopper is able to Table 1 . The effect of scale-up on spray flux 'I'a in a mixer granulator
Mixer size
65 L mixer
300 L mixer
Scale-up approach Base case Constant spray rate Constant granulation time 70 kg 1 5 kg 70 kg Batch size 1 kg/min 1 kg/min 4.7 kg/min Flowrate 1 000 Jlm 400 Jlm 400 Jlm Drop size 0.40 m 0.25 m 0.25 m Spray width 1 08 rpm 1 08 rpm 21 6 rpm Im peiler speed 0.35 m/s 0.35 m/s 0.7 m/s Powder velocity Spray flux 'Pa
0.35
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917
Granulation Rate Processes 30% �======�----� � Single noule. parallel to powdcr flow
25%
____ Single nozzlc. perpcndicular to powder tlow
20% "ö 1 25 Ilm (avoiding ungranulated material) and plotted the normalized percentage of each compo ne nt against the fraction of material greater than 1 25 Ilm. The extent of gran ulation is an important variable but is difficult to define and measure. In Fig. 29, the fraction of granules larger than 1 25 Ilm is a measure of the extent of gran ulation. Since only a very low percentage of starting excipient particles were larger than 1 25 Ilm, we have a clean comparison of the composition of the gran ules only. Each data point in Fig. 29 summarizes the three compositions at a particular liquid level and different sets of processing conditions. The distribution of the components is complex but can be explained by a combination of competition for the available granulating fluid and preferential granulation of the finest particles. Initially, at low liquid levels, liquid bridges hold the particles together. However, liquid that contacts the MCC particles can be absorbed into the MCC internal pores. If the MCC manages to (briefly) form a liquid bridge, it will absorb the fluid, fall off the granule and return to the excipient 1 80%
�
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Fig. 29. Effect of porous MCC particles on granule composition [35].
926
K.P. Hapgood et al.
size fractions. This creates granules initially depleted in MCC, and therefore preferentially composed of lactose and H PC as shown in Fig. 29. When approx imately 40% of the material is > 1 25 f.lm, the MCC and lactose curves cross indicating a switch in granulation behaviour. At this point, enough water has been added to hydrate the HPC and at least partially saturate the MCC particles and/or form a liquid layer at the surface. The MCC particles are generally smaller than the lactose and is now capable of forming liquid bridges. The granules compo sitions now become enriched with lactose and HPC. 2.3.3. Nucleus structures
Once the drop has imbibed into the powder, the structure of the nucleus depends on the properties of the formulation, as weil as the kinetics of consolidation and further re-wetting in the granulator. Several theoretical relationships between drop size and nuclei size have been proposed [36-38]. The simplest description of nucleus structure is to compare the drop diameter or volume to the nucleus diameter or volume. Waldie [39] was the first to recognize that each spray drop formed an individual nuclei. A known number of droplets were introduced into a fluidized bed and retrieved a short time later. He found a correlation between the nucleus diameter and droplet diameter, that held over three orders of magnitude: ( 1 9) dg cx d� where dg is the granule diameter, dd the drop diameter and n a correlation co efficient found to range between 0.8and 0.85. More recently, Schaafsma etal [37] recognised that peaks in their product size distribution were caused by two or more drops coalescing in the spray or on the surface to form larger agglomerates: (20) where Nd is the number of drops used to form the agglomerate and K the nu cleation ratio. The nucleation ratio is a constant, which is expected to depend on material properties including contact angle, granule porosity, particle size distri bution and others. Physically, the nucleation ratio represents the structure of the nuclei: (21 ) where s i s the wetting saturation [37,40]. The nuclei distribution of lactose formed is shown in Fig. 30. The nucleation ratio has been found to vary widely, values between 2.9 and 1 6 have been reported [40,41 ] , depending on the powder and binder combination
927
Granulation Rate Processes � E c -
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Fig. 3 1 . Nuclei formed from lactose and (Ieft to right) water, 1 7cP H PC solution, and 1 05cP H PC solution. Actual nucleus diameters are 6.5, 3.5, 3.0 mm respectively [ 1 9] .
used. Figure 31 shows lactose powder nucleated with three fluids with different viscosities. Red dye was added to the fluids to indicate spreading. The most viscous 1 05cP HPC solution formed nuclei shaped like stubby cylinders. As the viscosity decreases to a 1 7cP H PC solution, the base of the stubby cylinder begins to spread forming a mushroom shape. For the water nuclei extensive fluid spreading beneath the powder surface gives a white, spherical, crumbly shell of lactose encompassing a dark pink 'stalk' where the drop imbibition occurred. Nuclei morphology is therefore a complex balance of several factors including: • • • •
particle size; the rate of drop penetration; the rate of secondary spreading; and the rate of drying.
Very fine powders undergo particle rearrangement and shrinkage and can be clearly separated from the dry feed powder. For coarser powders, liquid spreading,
928
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evaporation and nuclei attrition will affect the nuclei size and liquid distribution in a granulator. The difference in nuclei size and saturation between the water- and H PC based nuclei is due to balance between the rate of drying compared to the rate of liquid spreading. In nuclei formed from low viscosity fluids such as water, the drop penetration and secondary spreading stages occur at a similar or faster rate than the drying stage, and spherical nuclei are generally formed. For nuclei formed from high-viscosity fluids, the rate of drying becomes com parable or faster than the fluid spreading and only a highly saturated core is formed. The nuclei saturation is closely related to the nucleation ratio K (Fig. 32). Large nuclei mean that the fluid has spread some distance from the original core, causing the total overall nuclei saturation to be quite low. Some nuclei are more than 50 times the volume of the original drop [31 ] , with the nuclei saturation as low as 3%.
2.4. Summary
In any granulation process the first aim should be to ensure good wetting and nucleation, thus removing binder distribution problems from the picture and allow the engineer to concentrate on other issues. In this respect, wetting thermody namics, wetting kinetics and spray flux considerations are important. The two di mensionless groups 'I' and 'p capture the impact of the key formulation properties a
Granulation Rate Processes
929
and process parameters on wetting and nucleation. The regime analysis presented in this section provides the tools for quantitative analysis and design. 3. GROWTH AND CONSOLI DATION 3. 1 . Background
The last decade has seen a rapid advancement in the understanding of growth and consolidation in agitated wet granulation processes. A major turning point in this field was the publication of the land mark paper by Ennis and co-workers [42], in which they proposed a physically based model for predicting the growth be haviour of granules. The beauty of the Ennis model is that it is physically based and, in theory at least, the variables in the model are measurable and the el egance of the model was its simplicity. However, such simplicity inevitably brings with it many assumptions, and the accuracy of these was immediately the subject of much debate within the granulation research community. This debate served to trigger an explosion of interest in quantifying growth mechanisms, and challenged researchers to attempt to develop more advanced coalescence models to include some of the important effects neglected in Ennis's version. In this section we begin by describing granule growth regimes and present a regime map that captures many of the of the complex granule growth mechanisms in a relatively simple way that is immediately useful for scale up and operational trouble shooting. We then look critically at recent detailed studies attempting to model accurately different aspects of granule growth and consolidation. 3.2. Granule growth reg imes
There are two main forms of granule growth. In some systems, granules grow, more or less steadily with time. Figure 33 shows the median granule size versus time for sand granulated in a tumbling drum. The rate of growth is approximately constant. We term this behaviour "steady growth". However, in other systems, there can be a long period of time in which no growth occurs at all. During this period of time, the granules consolidate. This phase has been variously referred to as the "nuclei", "no growth", "induction" or "compaction" phase [43-46]. Eventually, if a time is reached where granules have consolidated sufficiently for liquid binder to be squeezed to their surface, rapid growth can follow. Figure 34 shows an example of this type of growth behaviour. We term this an "induction-growth" system. There are also several other distinct regimes of granulation behaviour. Nucle ation only behaviour occurs when granule nuclei form during the binder-addition phase, but no further growth occurs after that (e.g. Butensky and Hyman [36],
930
K.P. Hapgood et al. 3 �
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Fig. 61 . Ratio of bond rupture to bond formation energy for pellets made from the four different binders as a function of radial strain i n the bond zone.
This difference is highlighted in Fig. 6 1 , which shows the ratio of the com pressive work done to form the bond versus the energy required to rupture it, as a function of radial strain in the bond region. Compared on this basis, the 60 Pa s silicone oil produced bonds that were approximately two orders of magnitude "stronger" than the bonds between granules bound with water. To a first ap proximation, the ratio of bond rupture to formation energy was approximately independent of the amount of strain (Fig. 61 ). Hence knowing how this ratio varies with granule properties and strain rate may prove useful in modelling granule coalescence. The experimental work discussed was preliminary and limited in extent. Nev ertheless, it is clear that the bonding process between collided granules is a complex phenomena. Much more experimental and theoretical work is needed, particularly to include dynamic viscous effects, which through their influence on the bulk deformation behaviour have a large influence on how much energy is actually needed to rupture a bond.
3.6. Summary comments on granule growth and consolidation
The key formulation properties and process parameters that impact on granule growth and consolidation are identified and captured in a series of important dimensionless groups smax, Sfdef, Stv and Ca. A regime map is presented which defines the different growth regimes and is a useful tool for scale up, design and trouble shooting.
962
K.P. Hapgood et al.
There are now several physical based models for coalescence and consoli dation, which can be used in quantitative frameworks such as population bal ances to track the generation of granule attribute distributions. None of these models are completely predictive, nor does any model completely capture the very complex physics involved. Nevertheless, they are powerful tools when used cautiously with some experimental validation. Further improvement to the validity and application of the models is reliant on ( 1 ) more complete information o n velocity and stress distributions i n granulators; and (2) more comprehensive constitutive models for granule mechanical properties. 4. WET GRANU LE BREAKAGE
This section considers the last of the three classes of granulation processes that control granule attributes - breakage and attrition. There are really two separate phenomena to consider: 1 . Breakage of wel granules in the granulator; and 2. Attrition or fracture of dried granules in the granulator, drier or in subsequent handling.
Breakage of wet granules will influence and may control the final granule size distribution, especially in high-shear granulators. In some circumstances, break age can be used to limit the maximum granule size or to help distribute a viscous binder. Wet granule breakage in granulators is less weil understood than either nucleation or growth. It remains an active research area. In this section we will review some of the current research and attempt to define key formulation and granule properties for developing the controlling groups or equations for the breakage processes. Attrition of dry granules leads to the generation of dusty fines. This phenomena is important in fluid bed granulation (where granulation and drying occur simul taneously) and in downstream handling of dried granules from any granulation process. A study of dry granule attrition is beyond the scope of this chapter. For more information see chapter Single granule in this handbook, Litster and Ennis [2] and Bika el al. [68]. 4. 1 . Experimental observations
Few investigators have described or studied wet granule breakage in granulation processes. Some preferential growth mechanisms in tumbling granulation may involve attrition or breakage of weak granules (crushing and layering, abrasion transfer) [69]. However, breakage is much more likely in higher intensity mixer
963
Granulation Rate Processes
and hybrid granulators. The limited work on wet granule breakage focuses on these processes. Several studies show an increase in agitation intensity (increased impeller speed) reduces the final granule mean size in granulation experiments [56,70,71]. For example, Fig. 62 shows median granule size from three scales of agitated fluid bed granulator decreases with increasing agitator tip speed [9]. However, reduction in product size with increased agitation could also be ex plained by a reduction in the maximum granule size for coalescence. So changes to granule size distribution, on theirown, are insufficient evidence for wet granule breakage as a key mechanism for controlling granule properties. However, wet granule breakage has been identified clearly in high-shear mixer experiments by other means. Ramaker and co-workers [22], Vonk et al. [41 ] and Pearson e t al. [72] both used coloured tracer granules or liquid to identify breakage of wet granules. Pearson et al. added narrow size fractions of weil formed tracer granules part way through a batch high-shear granulation. Some of the tracer granules were broken, leaving coloured tracer fragments in smaller granule size fractions. Large tracer granules ( > 1 mm) were more likely to be broken than smaller granules (Fig. 63). Knight et al. [70] showed that mean granule size decreased after impeller speed was suddenly increased part way through a batch high-shear mixer experiment. This was attributed to granule breakage. Vonk and co-workers added a coloured liquid at the start of the granulation process and observed the dispersion of the dye through a process of "destructive 800
...... o 10
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964
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_ _ _
TIme (sec)
Fig. 63. Breakage of tracer granules in high-shear mixers: Effect of tracer granule size on mass fraction of unbroken granules [72].
nucleation" where loosely bonded nuclei are broken down into smaller fragments via attrition or fragmentation (Fig. 64). The initial weak nuclei were quite large in these experiments (5 mm diameter). We can view this destructive nucleation process as simply a subset of all the breakage processes occurring in the gran ulator. In fact, all binder distribution in the "mechanical dispersion" (Section 2) is essentially a breakage process and should be treated as such. In summary, wet granule breakage is potentially an important process affecting binder distribution and granule size in high intensity processes. Therefore it is important to establish the conditions under which breakage will occur.
4.2. Predicting conditions for breakage
There is very little quantitative theory or modelling available to predict conditions for breakage, or the effect of formulation properties on wet granule breakage. Tardos ef al. [9] considered that a granule will break if the applied kinetic energy during an impact exceeds the energy required for breakage. This analysis leads to a Stokes deformation number criteria for breakage: (39) wh ere Sfdef is the Stokes deformation number as defined by equation (23) and Sfdef the critical value of Stokes number that must be exceeded for breakage to occur. There are strong analogies to the development of the Stokes deformation
965
Granulation Rate Processes
0° % °0 0 0 0 ... .... 0 o 0 o 0 0 00 0
Fig. 64. The destructive nucleation mechanism proposed by the Groningen group [41 ) .
number for granule deformation and growth (equation (23)). It is Iikely the critical value for breakage will be greater than that for coalescence as granules may deform plastically at the impact point without breakage of the granule. Note that the original work of Tardos et al. [9] proposed a more general char acteristic stress than the dynamic yield stress in equation (23) and considered breakage of granules by shear rather than impact. They postulate the granule will behave under shear as a Herschel-Buckley fluid, which is also what has been observed in measurements of granule dynamic yield stress (Iveson et al. [51], equation (24) and Fig. 40 above), i.e. (40) where r(Y) is the characteristic stress in the granule, ry the yield strength and y the average shear rate. Two simplifications were considered, neglecting either the apparent viscosity (r(y) = ry) or the yield stress (r(y) = kyn ) . In either case,
966
K.P. Hapgood et 8/. 1 00%
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Stdef Fig. 65. The relationship between the Stokes deformation number and the determined breakage numbers. The vertical line represents the experimentally determined boundary between breakage and no breakage [73].
the model predicts granules above a maximum size will break and this size is decreased with increasing shear rate. Tardos and co-workers measured granule deformation and break up under shear in a novel constant shear fluidized-bed granulator. Granules first elongated under shear and then broke at a Stokes deformation number of approximately 0.2. Van der Dries et al. [73] also used equation (39) as a criteria for breakage. However, they estimated the dynamic yield stress by assuming a Rumpf style expression for the granule strength and assumed the bond strength was due solely to viscous forces. In experiments using a laboratory high-shear mixer granulator, Stokes deformation number was varied by changing impeller speed and there was a sharp change in the number of unbroken granules at Stdef = 0.05 (see Fig. 65). Qualitatively, these results are consistent with those of Tardos et 81. [9]. Quantitatively, it is not possible to do a direct comparison because of the different methods of estimating granule strength and effective collision velocity. Kenningly et 81. [74] used a similar approach to predict a "crumb" region and a controlled growth region in mixer granulators. This general approach to predicting a breakage regime is a good starting point, but there remain a number of questions to be answered before a general break age regime map is available: 1 . It is not c1ear whether breakage of wet granules is predominately due to high velocity impacts or to shear within the powder bed. In fact, the mode of breakage may be a strong function of powder flow field and the design of impeller bl ades and choppers. 2. There is very Iimited experimental data to test the models at present. Stokes number is generally varied by changing the impeller speed or shear rate. There
Granulation Rate Processes
967
has been no systematic study of breakage of a wide range of formulations with very different mechanical properties. 3. The models equate granule breakage with plastic yield. A granule may deform plastically without breaking. A purely plastic granule will smear rather than break when its yield stress is exceeded. At high impeller speeds such ma terials may coat the granulator wall or form a paste. Semi-brittle granules will break at high impact velocity giving a maximum stable granule size or a weak crumb. Thus, considerable information about the granule mechanical proper ties is needed to predict their behaviour. Note this yield behaviour should be measured at strain rates similar to those during impact in the granulator, not in static mechanical tests. 4.3. Mechanical properties of semi-brittle wet agglomerates
The brittle nature of some wet agglomerates can be demonstrated using dynamic measurements of granule mechanical properties. In Section 3.5.2, uniaxial com pression test were performed to measure a peak flow stress or "yield" stress of granules as a function of strain rate. Iveson and Page [54] noted that in so me cases failure was by macroscopic crack formation and in others by plastic, almost paste like flow. However, uniaxial tests are not the best way to examine brittle behaviour. Smith [75] examined the failure behaviour of a wide range of formulations using diametrical compression tests using the same Instron dynamite testing machine as Iveson's earlier work. Three different modes of failure were observed: 1 . Brittle failure along a central crack (Fig. 66). In this case there is a clearly defined yield stress corresponding to crack formation and propagation at low strain (0.01-0.03). 2. Cone formation and diagonal cracking (Fig. 67). In this intermediate behaviour, a significant failure cone forms at the point of contact with cracking along the edge of the cone. There is still a clear peak stress but at much higher strains (0.07-0 . 1 0). 3. Squeeze flow (Fig. 68). The formulation behaves as a paste with completely plastic deformation. There is no macroscopic crack formation and no peak stress is observed. Smith's experiments were conducted at intermediate strain rates (0.005-1 0/s). Salman et al. [76] conducted ballistic studies at much higher velocities and strain rates (of order 1 5 ms 1 and 1 03/s). These experiments showed that there was a critical velocity above, which cracks propagated through the granules and fracture occurred. The critical velocity was a function of formulation properties and there was considerable plastic deformation before any cracking occurred.
968
K.P. HaPQood et 8/.
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This wide variety of behaviours reinforces the need for a more substantive inclusion of granule mechanical properties in breakage criteria. This remains an area of current research. 4.4. Concluding comments on wet granule breakage
Breakage is the least studied of the three classes of granule rate processes. Although, the fundamental basis for predicting breakage is incomplete, we
969
Granulation Rate Processes
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can still use our limited knowledge for scale up based on equation (39). For breakage, the appropriate velocity for the Stokes deformation number is the maximum collision velocity a granule can experience with another granule or with part of the granulator equipment. For mixer granulators, this is clearly the impeller tip speed. Equations (39) and (40) suggest breakage will increase with increasing tip speed. Figure 62 shows that the relationship between tip speed and granule mean size was the same for three different scales of agitated
970
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fluidised bed granulators, as we would expect if granule size were controlled by breakage processes. Controlling wet granule breakage gives the opportunity to give a narrow gran ule size distribution by growing granules up to a breakage limit [9,22,771. This has been the driving force in the development of some newer granulator designs [71 ,781. It is important to note that size distribution control will also depend on the impact velocity distribution and turnover of granules through the high impact
971
Granulation Rate Processes
region (impeiler or chopper). Granulators with broad impact velocity distributions and smalI, uncontrolled turnover through the high impact region are unlikely to ever yield narrow granule size distributions. 5. CONCLUDING COMMENTS : WHERE TO FROM H ERE IN THE FIELD OF GRANU LATION?
Analysis of granulation rate processes over the last decade has been very fruitful . We now know the key formulation properties and process parameters that control the rate processes of ( 1 ) nucleation and wetting, and (2) consolidation and growth. For both these rate processes, regime maps have been developed and validated based on the controlling dimensionless groups: Stv, Stdef, S, \f' and 'p. We are close to a similar understanding of wet granule breakage. This under standing is already reflected in the quality of research with the quantitative anal ysis in most recently published papers, a far cry from the qualitative descriptions of 1 0-1 5 years ago. This understanding is now at the point where it can be directly used in scaling granulation processes (e.g. keeping dimensionless spray flux constant to main tain nucleation conditions) and characterizing formulations for their granulation behaviour (e.g. measuring the dynamic yield stress of a new formulation) [3]. This quantitative understanding is already being built into population balance models to predict the generation of granule size distribution and density (see Chapter -Mode/ling in this handbook). Our improved knowledge also challenges us to improve our granulator designs, moving to regime separated granulators to simplify scale up and give better control of granule attributes. However, there are still important needs and opportunities for research and development in this field. We can characterise these in terms of the scale of observation (see Fig. 69): Particle to granule scale: We are yet to reach the point where we can quan titatively predict the behaviour of a granule by scaling up from measurements or models of particle-particle and particle-fluid interactions within the granule. Iveson's work on a non-dimensional correlation for granule strength, following the earlier work of Ennis and Tardos shows that we are making progress. DEM approaches provide great promise for predicting granule behaviour if the infor mation can be captured in terms of constitutive models at the granule level. This approach mimics that used for some time in thermodynamics where molecular modelling is used in lieu of experiments to predict bulk thermodynamic properties. Importantly we have a much improved suite of tools to provide particle level input to these simulations (AFM, nanoindentation and other micromechanical meas urements) and to help "scale up" to granule scale through detailed measurement of granule structure (X-ray microtomography). Subgranule scale modeling and a
972
K.P. Hapgood et 8/.
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Fig. 69. A summary of the status of wet granulation research using the scale of obser vation as a frame of reference.
characterization are discussed in detail in Chapter- Sub granule scale modelling in this handbook. Granule to granule bed scale: We have reasonable models for the granulation rate processes that incorporate granule properties. Our constitutive models for granule mechanics are still simplistic representation of a very complex three-phase system. There remains a need for improved characterization and models for granule mechanical behaviour. The current model - that of an elas tic-plastic material with strain rate dependent yield stress is a reasonable starting point only. Our quantitative understanding of granulation rate processes is now being used to create more predictive population balance models for a bed of granules to describe distributions of granule properties. The challenge is that one-dimen sional population balances looking only at the distribution of granule size n(x) or n(v) cannot effectively include the necessary information on granule porosity and liquid content needed to predict rate constants. Multidimensional population bal ances are needed which consider the distributions of volume of solid, liquid and gas in the granules ie. n(vs v" vg). Granule size, porosity and liquid saturation can all be calculated from this base distribution. For these multidimensional models, effective and efficient solution techniques remain an important research area. Multidimensional population balances are addressed in Chapter-Modelling of this handbook. ,
Granulation Rate Processes
973
Granule bed to vessel scale: The key issue here is the ability to model powder flow behaviour and mixing in the granulator and link this information effectively to our population balance models. Powder flow is not a solved problem, particularly in the "intermediate flow regime" experienced in many granulators. There are a number of possible approaches to quantifying powder flow in granulators: 1 . The use of macroscopic momentum balance equations with appropriate con stitutive equation to model the flow of powder as a continuum. This is anal ogous to traditional CFD models for fluid flow. 2. Application of DEM where each granule is tracked and its interactions with all other granules in the granulator simulated. 3. Use of flow characterization measurements such as PEPT to provide empirical models or correlations for velocity distributions and mixing. One approach is to characterize powder flow and use this information in com partmentalised models of a granulator. A population balance is written for each compartment and the transfer rates of material between compartments are mode led with the help of data from powder flow measurements. While this approach is still quite crude, it is more sophisticated than a single whole granulator model. Vessel to granulation circuit scale: Granulation plants include dryers, screens, crushers and solids handling that also impact on the quality of the product gran ules. Dynamic simulations of whole granulation circuits exist and are especially valuable where there is significant recycie of off spec granules. The current challenge is to incorporate more predictive models, especially of the granulator, into these simulations. As our models becomes more physically realistic, the way is opened for more sophisticated use of the models for plant optimization and in different types of model based control schemes. This is a natural transition al ready seen for fluid processing plants for which good predictive models of the unit operations have been available for several decades. Finally, integration of models across different length scale is a key to granulation design and modeling. However, such integration may lead to enor mous and unwieldy models and simulations. We need to develop effective and efficient modeling frameworks for this integration. This is a current area of re search in the modelling community and we need to take advantage of current developments in this area, not just in granulation, but more broadly in all par ticulate processes. Nomenclature EI
Ä
area flux of drops hitting powder surface (m2/s) area flux of powder through the spray zone (m2/s)
974
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initial area of the sampie (m2) the deformed contact area after impact (m2) Capillary number (-) bubble size (m) liquid drop size (m) specific surface mean particle size (m) particle diameter (m) Sauter mean size of particles (m) granule size (m) Drum granulator diameter (m) Young's modulus (Pa) coefficient of restitution (-) fraction of overlapping drops on powder surface (-) fraction of powder surface covered by drops (-) fraction of single drops on powder surface (-) gravitational acceleration (m/s2) liquid layer thickness (m) height of surface asperities (m) nucleation area ratio (m) compaction rate (-) spacing between two bubbles (m) particle mass (kg) number of drops hitting the powder surface per unit time (no./s ) flow rate of liquid into powder bed (m 3/s) Drop circular radius (m) particle radius (m) effective pore radius (m) pore radius (m) liquid saturation of pores (-) critical Stokes deformation number (-) critical Stokes deformation number (-) viscous Stokes number critical Stokes number time (s) powder circulation time (s) drop penetration time (s) velocity (m/s) collision velocity (mjs) bubble velocity (mjs) liquid flow rate (m3/s) drop volume (m 3) liquid penetration velocity (m/s) volumetrie spray rate (m 3/s) drop volume (m3) flat spray width (m)
Granulation Rate Processes
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975
granule dynamic yield stress ((Njm2 ) minimum granule porosity (-) bed voidage ( - ) granule porosity ( - ) surface tension (N m) granule deformation (m) granule density (kgjm 3) liquid density (kgjm 3) particie density (kgjm 3) liquid-vapour interfacial energy (Njm) effective powder bed voidage ( - ) tapped powder bed voidage ( - ) contact angle ( ) dimensionless spray flux ( - ) sphericity ( - ) dimensionless penetration time ( - ) viscosity (Pa s) impeller and chopper speed 0
REFERENCES [1] S.M. Iveson, JA Beathe, N.W. Page, Powder Techno!. 1 27 (2002) 1 49-1 6 1 . [2] J . D. Litster, B.J. Ennis, The Science and Engineering of Granulation Processes, Kluwer Academic Publishers, Dordrecht, 2004. [3] Y. He, L.X. Liu, J . D . Litster, Scale-Up Considerations in Granulation, in: D . M . Parikh, (Ed.), Handbook of Pharmaceutical Granulation Technology(2nd edition), Taylor & Francis, Boca Raton, 2005, pp. 459-489, Chapter 1 6 . [4] S.J . R Simons, R J . Fairbrother, Powder Techno!. 1 1 0 ( 1 -2) (2000) 44-58. [5] AC. Scott, M.J. Hounslow, T. Instone, Powder Techno!. 1 1 3 ( 1 -2) (2000) 205-2 1 3. [6] !. Krycer, D.G. Pope, Powder Techno! . 34 (1 983) 39-51 . [7] B.J. Ennis, J.D. Litster, Granulation and coating technologies for high value added industries, Client in-house short course, E&G Associates: Section 3(1 996). [8] RC. Rowe, Int. J. Pharm . 52 ( 1 989) 1 49-1 54. [9] G.!. Tardos, M . Irfan-Khan, P . R Mort, Powder Techno!. 94 (1 997) 245-258. [ 1 0] K.P. Hapgood, J . D. Litster, S.R Biggs, T. Howes, J. Colioid Int. Sci . 253 (2002) 353-366. [1 1 ] S. M iddleman, Modeliing Axisymmetric Flow: Dynamics of Films, Jets and Drops, Academic Press, San Diego, 1 995. [ 1 2] M . Denesul, G.L. Smith , B.J.J. Zelinski, N.J. Kreidl, D.R Uhlmann, Colioid Int. Sci . 1 58 ( 1 ) (1 993) 1 1 4-1 20. [ 1 3] D.J. Golchert, J.D. Litster, L.x. Liu, The use of X-ray micro-tomography to charac terize agglomerate structure, World Congress on Particle Technology 4, July 2 1 -25, 2002, Sydney. [ 1 4] L. Farber, G. Tardos, J . N . Michaels, Powder Techno!. 1 32 (2003) 57-63. [1 5] R Kohlus, Quantitative descriptors for granule structure characteristion, World Con gress of Particle Technology 4, IChemE , Sydney, Australia, 2002. [ 1 6] A Clarke, T.D. Blake, K. Carruthers, A. Woodward, Langmuir 1 8 (2002) 2980-2984. [ 1 7] J.D. Litster, K.P. Hapgood, J.N. Michaels, A Sims, M . Roberts, S.K. Kameneni, Powder Techno!. 1 1 4 (2001 ) 32-39.
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[ 1 8] w.J. Wildeboer, J.D. Litster, I .T. Cameron, Chem. Eng. Sci. 60 (2005) 3751-376 1 . [ 1 9] K.P. Hapgood, J.D. Litster, E.T. White, P.R. Mort, D.G. Jones, Powder Technol. 1 4 1 (1-2) (2004) 20-30. [20] PAL. Wauters, R.B. Jakobsen, J . D. Litster, G.M.H. Meesters, B. Scarlett, Powder Technol. 1 23 (2002) 1 66-1 77. [21 ] J.D. Litster, K.P. Hapgood, J.N. Michaels, A. Sims, M. Roberts, S.K. Kameneni, Powder Technol. 1 24 (2002) 272-280. [22] J.S. Ramaker, MA Jelgersma, P. Vonk, N.w.F. Kossen, Int. J. Pharm. 1 66 ( 1 ) ( 1 998) 89-97. [23] R. Plank, B. Diehl, H. Grinstead, J. Zega, . Powder Technol . 1 34 (3) (2003) 223-234. [24] Y. Mugumara, T. Tanaka, Y. Tsuji, Powder Technol. 1 09 (2000) 49-57. [25] J . D . Litster, K.P. Hapgood, S.K. Kamineni, T. Hsu, A. Sims, M. Roberts, J. Michaels, Scale-up of mixer granulators for effective liquid distribution, Proceedings AIChE Annual Meeting, Oct 3 1 -Nov. 5, 1 999, Dallas, TX, USA. [26] K.P. Hapgood, J.D. Litster, R. Smith, AIChE J 49 (2) (2003) 350-361 . [27] C.E. Capes, Particle Size Enlargement, Elsevier, Amsterdam; New York, 1 980. [28] M.E. Aulton, M. Banks, Fluidised bed granulation - factors influencing the quality of the product, Int. J . Pharm. Technol. and Prod. Manuf. 2 (4) ( 1 981 ) 24-29. [29] B. Rambali, L. Baert, L. Massart, I nt. J. Pharm. 252 ( 1 -2) (2003) 1 97-206. [30] K.P. Hapgood, R. Plank, S. Jain, J. Zega, World Congress Particle Technology 4, Sydney, Australia, 2002. [31 ] K.P. Hapgood, Nucleation and Binder Dispersion in Wet Granulation, PhD Thesis, The University of Queensland, 2000. [32] K.P. Hapgood, Case study: liquid distribution on scale-up, AAPS Summer Confer ence, Advances in Wet Granualtion Technologies, Lansdowne, VA, June 2003. [33] L. Farber, K.P. Hapgood, J.N. Michaels, World Congress Particle Technology Vol. 5, Orlando, FL, USA, 2006. [34] S.M. Iveson , S.Holt, S. Rapmond, C.E. Loo, S.R. Biggs, AIChE Annual Meeting, AIChE, 1 998. [35] R. Plank, J. Zega, L. Wei , Granule content as a function of size studied for wet granulation of a 3-component system. Paper presented at the AIChE Annual Meeting, Reno, NV, 2001 . [36] M . Butensky, D. Hyman, Ind. Eng. Chem. 1 0 (2) ( 1 97 1 ) 2 1 2-21 9. [37] S.H. Schaafsma, P. Vonk, N.w.F. Kossen , Int. J. Pharm. 1 93 (2) (2000) 1 75-1 87. [38] P.J. Sherrington, Chemical Eng. JulyjAugust ( 1 968) CE201 -CE2 1 5 . [39] B. Waldie, Chem. Eng. Sci. 4 6 ( 1 1 ) ( 1 99 1 ) 2781-2785. [40] S.H. Schaafsma, N.w.F. Kossen, M .T. Mos, L. Blauw, A.C. Hoffman , AIChE J 45 ( 1 998) 1 202-1 21 0. [41 ] P. Vonk, C.P.F. Guillaume, J.S. Ramaker, H . Vromans, N .W.F. Kossen, Int. J . Pharm. 1 57 (1 997) 93-1 02. [42] B.J. Ennis, G. Tardos, R. Pfeffer, Powder Technol. 65 ( 1 99 1 ) 257-272. [43] P.C. Kapur, D .w. Fuerstenau, I&EC Proc. Des. Dev. 8 ( 1 968) 56. [44] P.G. Smith, A.w. Nienow, Chem. Eng. Sci. 38 (8) ( 1 983) 1 223-1 231 . [45] C.C. Hung, H.O. Kono, Powder Technol. 55 ( 1 ) ( 1 988) 1 9-34. [46] F. Hoornaert, P.A.L. Wauters, G.M.H. Meesters, S.E. Pratsinis, B. Scarlett, Powder Technol. 96 (2) (1 998) 1 1 6-1 28. [47] C.E. Capes, P.V. Danckwerts, Trans. I. Chem. Eng. 43 (1 965) 1 1 6. [48] D.M. Newitt, J.M. Conway-Jones, Trans. I . Chem. Eng. 36 ( 1 958) 422. [49] S.M. Iveson, J . D. Litster, AIChE J 44 (1 998) 1 5 1 0-1 5 1 8. [50] S.M. Iveson, PAL. Wauters, S. Forrest, J.D. Litster, G.M.H. Meesters, B. Scarlett, Powder Technol. 1 1 7 (2001 ) 83-97. [51 ] S.M. Iveson, JA Beathe, N.W. Page, Powder Technol. 1 27 (2) (2002) 1 49-1 6 1 . [52] S.M. Iveson, N.W. Page, J . Appl . Mech. 7 1 (2004) 470-475. [53] L.X. Liu, S.M. Iveson , J.D. Litster, B.J. Ennis, AIChE J 46 (2000) 529-539.
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[54] S.M. Iveson, N.W Page, Powder Techno!. 1 1 7 (200 1 ) 1 1 3-1 22. [55] H. Rumpf, The Strength of Granules, and Agglomerates, in: WA. Knepper, ( Ed.), Agglomeration, Interscience, New York, 1 962, p. 379. [56] P. Holm, O. Jungersen, T. Schalfer, H . G . Kristensen , Pharm. Ind. 45 (8) ( 1 983) 806-81 1 . [57] N . Ouchiyama, T. Tanaka, I&EC process Des. Dev. 1 4 ( 1 975) 86. [58] K.V.S. Sastry, S.C. Panigraphy, DW. Fuerstenau , Trans. Soc. Mining Eng. 262 ( 1 977) 325. [59] S.M. Iveson , JD. Litster, B.J. Ennis, Powder Techno!. 88 ( 1 996) 1 5-20. [60] S.M. Iveson , JD. Litster, Powder Techno!. 99 ( 1 998) 243-250. [6 1 ] J.L. Moseley, T.J. O'Brien, Chem. Eng. Sei. 48 ( 1 993) 3043-3050. [62] M .J . Adams, C. Thornton, G. Lian, 1 st Int. Part. Tech. Forum, Vol 1 , Denver, Aug. 1 7-19, 1 994 pp. 220-224. [63] J.P.K. Seville, H . Silomon-Pflug, P.C. Knight, Powder Techno!. 97 ( 1 998) 1 60-1 69. [64] C . Thornton, Z. Ning, Powder Techno! . 99 ( 1 998) 1 54-1 62. [65] M .J. Hounslow, H.S. Mumtaz, A. P. Collier, J.P. Barrick, A.S. Bramley, Chem. Eng. Sei . 56 (7) (200 1 ) 2543-2552. [66] S . M . Iveson, Chem. Eng. Sei. 56 (2001 ) 221 5-2220. [67] T. Schalfer, C. Mathiesen, Int. J. Phamaceut. 1 39 ( 1 996) 1 39-148. [68] D.G. Bika, M. Gentzier, J.N. Michaels, Powder Techno!. 1 1 7 ( 1 -2) (200 1 ) 98-1 1 2 . [69] K.v.S. Sastry, D . W Feurstenau , Int. J . M iner. Process 2 (1 975) 1 87. [70] P.C. Knight, A. Johansen, H . G . Kristensen, T. Schaefer, J.P.K. Seville, Powder Techno!. 1 1 0 (2000) 204-209. [7 1 ] S. Watano, Y. Sato, K. Miyanami, T. Murakami, Chem. Pharm. Bull. 43 (7) ( 1 995) 1 2 1 2-1216. [72] J . M . K. Pearson , M .J . Hounslow, T. Instone, P.C. Knight, Proc. 3rd World Congress on Particle Technology, Vo!. 3, 1 998, paper 86. [73] K. Van den Dries, O.M. de Vegt, V. Girard, H. Vromans, Powder Techno!. 1 33 ( 1 -3) (2003) 228-236. [74] S.T. Keningley, P.C. Knight, A.D. Marson, Powder Techno!. 91 (1 997) 95-1 03. [75] R.M. Smith, Wet granule breakage in high shear mixers, PhD thesis, The University of Queensland, 2006. [76] AD. Salman, J. Fu, DA Gorham, M .J . Hounslow, Powder Techno!. 1 30 (2003) 359-366. [77] P.R. Mort, G . ! . Tardos, Kona 1 7 ( 1 999) 64. [78] B. Denes, Z. Ormos, H u ngarian J. Ind. Chem. 21 (3) ( 1 993) 225-23 1 .
CHAPTER 21 Breakage in G ra n u l at i o n Ag ba D . Salman * , Gavin K . Reynolds, Hong S i ng Tan , l a n Gabbott, and M ichael J. Hou nslow
Depattment of Chemical & Process Engineering, University of Sheffield, Mappin Street, Sheffield, S1 3JD, UK Contents
1 . I ntroduction 2. Breakage at the process scale 2. 1 . Observations of the breakage process 2.2. Measurement of the breakage process 2.3. Role of variables on breakage behaviour 2.3. 1 . Binder viscosity 2.3.2. Binder surface tension 2.3.3. Contact angle between binder and primary particle 2.3.4. Primary particle size and shape 2.3.5. Equipment-related variables 2.3.6. Binder content 2.3.7. Binder addition method 2.3.8. Agitation intensity 2.3.9. Granulation time 3. Breakage at the granule scale 3. 1 . Bonding forces in granules 3 . 1 . 1 . Rumpf's theory 3 . 1 .2. Kendall's theory 3.2. Measuring granule strength 3.2. 1 . Tensile strength 3.2.2. Dynamic-yield strength 3.2.3. Shear strength 3.2.4. Bending strength 3.2.5. Hardness 3.2.6. Summary 3.3. Dynamic strength of granules 3.3. 1 . M ulti-particle impact tests 3.3.2. Single-particle impact tests 3.3.3. Breakage patterns 3.3.4. Extent of breakage 3.4. Variables affecting granule strength 3.4. 1 . Binder viscosity * Corresponding author. E-mail: [email protected]
Granulation Edited by A.D. Salman, M.J. Hounslow and J. P. K. Seville f: 2007 Elsevier B.v. All riQhts reserved
980 982 982 984 987 988 989 990 990 990 991 991 992 993 994 994 997 999 1 000 1 000 1 002 1 003 1 004 1 005 1 006 1 006 1 007 1 008 1010 1013 1016 1016
980 3.4.2. Binder surface tension 3.4.3. Contact angle between binder and primary particle 3.4.4. Primary particle size and shape 3.4.5. Porosity and structure 3.4.6. Binder content 4. Modelling of Breakage 4. 1 . Predict the conditions for breakage 4.2. Process scale: population balance modelling 4.3. Micro scale: discrete modelling 4.4. M icro scale: continuum modelling 5. Conclusions References
A. D. Salman et al.
1017 1017 1019 1019 1 020 1 021 1 021 1 024 1 030 1 034 1 035 1 036
1 . I NTRODUCTION
The process of granulation is used in a wide range of industries, including mineral processing, agricultural products, detergents, pharmaceuticals, foodstuffs and speciality chemicals. Typically, fine powders are agglomerated together to form larger particles, or granules. In wet granulation, for example, liquid is used to stick the constituent particles together. Granules generally have a variety of advan tages over fine powders in that they flow weil, pose lower environmental hazards, and dissolve or disperse better. The process of granulation still remains relatively poorly understood. However, it is generally accepted that granulation is a combination of three rate processes, namely wetting and nucleation, consolidation and growth, and attrition and breakage [1]. In addition to the obvious growth retardation, attrition and breakage help to improve granule homogeneity [2] and granule strength by promoting consolidation. The importance of the study of granule breakage is in two principal areas. First, understanding breakage as a rate process and part of the granu lation process allows improved process design and specification. More specif ically, due to the importance of breakage in homogenising a batch of granules, improved knowledge of this process can lead to more controlled product quality. Second, study of the breakage of granules as products of the process can inform the behaviour of granules under further processing, handling and transporting conditions. In addition, deformation and breakage of granules can be used as a product quality tool to assess the granule properties. For example, it has been shown by Fu et al. [3] that the coefficient of restitution is very sensitive to var iability in granule composition and structure. This chapter discusses breakage in granulation from a number of different length scale perspectives. At the process scale, breakage is important in en hancing the material distribution and eventual strength of the product granules. Knowledge of how operating parameters and equipment design influence the breakage process can help to improve the properties of the granular products.
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Knowledge of the true rates of breakage can improve modelling and prediction of granulation behaviour. At the single-granule scale, extensive studies have been made to characterise granule strength and behaviour under static and dynamic conditions. Understanding how different variables affect the strength of granular materials again will assist in improving the properties of granular products. Also, knowledge of breakage behaviour at the single-particle scale can inform our understanding of breakage at the process scale. Sub-granule scale experimental studies can provide an understanding of how different variables and components contribute to the apparent granule strength, giving a physical basis for how to improve granule properties. In reviewing the modelling of granule breakage, a similar scale approach is adopted. Population balances are a powerful tool for modelling the influence of various rate processes on the properties of large groups of granules. Micro-mechanical modelling of granules allows further insight into the breakage behaviour of granules. Granulation in itself is a broad topic. In this case a granule, or an agglomerate, refers to a body that consists of constituent particles held together. Here, we define three-generic types of granule that will be discussed. First, a binderless granule is as described, whereby the constituent particles are held together by micro-scale forces, typically van der Waals forces. Second, a solid granule refers to a granule where the constituent particles are held together by solid bonds. Third, a wet granule is described as a granule which contains interstitial liquid. Although these three generic cases could all be described as granules, it is expected that they will exhibit different breakage behaviour due to the different nature of the constituent particle bonding forces. Figure 1 illustrates the typical fragmentation of the three types of granule under moderate impact conditions. In addition to different granule classifications, there are a wide range of prac tical processes to create granules, and a wide range of techniques to charac terise the breakage of granules. It is not the aim of this chapter to be completely exhaustive in reporting all of these. At the process scale, studies using high-shear mixer granulators and fluidised-bed granulators are reviewed. This is due to the
(a)
Binderless granule
(b)
Solid granule
(c)
Wet granule
Fig. 1 . Example of the typical impact fracture of the three generic types of granules under moderate impact conditions. These granules are between 4 and 5 mm i n diameter.
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increased perceived importance of the breakage process in these granulators and the focus of the literature on investigating breakage in this type of equipment, rather than any attempt at excluding other processes.
2. BREAKAGE AT THE PROCESS SCALE
Some of the early studies of attrition and breakage in the granulation process were carried out by Capes and Danckwerts [4] and Sastry et al. [5]. They pro posed that the mechanisms by which granules grow in tumbling drum granulators involved crushing and layering. This mechanism is now generaily considered as attrition and breakage [6], and describes the breakage of wet or dried granules due to impact, wear or compaction in the granulator or during subsequent product handling. In reviewing the experimental studies of breakage during granulation proc esses, two broad groupings of research can be found. These are firstly studies of the process, where breakage is inferred from observation of some ensemble property such as the temporal granule mean size. Second, are studies where the extent of breakage is identified directly during granulation, offen through addition of coloured dyes to create tracer granules, providing data from which breakage kinetics can be extracted. 2. 1 . Observations of the b reakage process
Knight et al. [7] examined size enlargement of melt granules with time and im peiler speed in a vertical axis high-shear mixer. They found great variation in agglomeration behaviour with impeiler speed. In particular, it was found that an increase in impeiler speed exhibited an increase in the extent of granule growth. However, this pattern did not continue indefinitely, and at high-impeiler speeds, there was a noticeable reduction in the extent of granule growth (see Fig. 2). They found that granule size distributions were bi modal throughout the granulation process. It was argued that the bimodal distribution persisted at long times due to the breakage of large granules into smail fragments. In addition, it was found that there was a considerable reduction in the fraction of relatively large granules above 1 mm at high-impeiler speeds. They deduced that these observations were evidence of a breakage process. They also observed a reduction in the size of the granules when increasing the mixer speed from 800 to 1 500 rpm for 1 min at the end of an 800 rpm batch (shown in Fig. 2). However, Iveson and Utster [8] argue that changes to the granule-size distribution, on their own, are insufficient ev idence for wet-granule breakage. For example, an increase in impeiler speed could contribute to an increase in rebound of coiliding granules due to the in-
983
Breakage in Granulation 1,500 ,------, • ,
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creased impact velocities. This would lead to a reduction in the coalescence probability, although an increase in collision rates would also be likely. Knight et al. [7] support their deduction through further analysis of the granule mor phology. They found that low-impeller speed granules exhibited high sphericity, whereas those from high-im peiler speed experiments has a more irregular shape, again consistent with a breakage process. Vonk et al. [9] highlighted the importance of breakage process in granulation and proposed a destructive nucleation-growth mechanism based on their high shear pelletisation experiments. They proposed that granulation starts with the formation of large primary nuclei, and small secondary nuclei are subsequently formed by the break-up of the primary nuclei (see Fig. 3). Break-up of the nuclei proceeds according to two mechanisms: attrition and fragmentation. The weak nuclei break due to the nucleijnuclei and nucleijwall collisions (attrition) and re duce into fragments as a consequence of the action of the impeller and chopper (fragmentation). Both mechanisms result in the formation of small secondary nuclei, which is then responsible for the subsequent growth. Granule growth then commences once the solid mass is sufficiently wetted and densification of the secondary nuclei occurs. Owing to the consolidation process, the stronger pellets can survive further impacts and in addition, the liquid squeezed to the pellet surface would also increase the coalescence probability. Granule breakage also occurs in low-impact fluidised-bed granulation. Biggs et al. [ 1 0] investigated the extent of granule breakage in fluidised-bed melt gran ulation using a "spray on-spray off" experiment. The results show that the mean granule size increases with binder spraying and subsequently decreases when
984
A. D. Salman et al.
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the binder spray is turned off (Fig. 4). Their results clearly iIIustrate that granules experience breakage even in a low-shear environment. 2.2. Measurement of the breakage process
Breakage during the granulation process has been identified more clearly through the addition of dyed tracer granules or binder. Ramaker et al. [1 1 ] used tracer pellets to investigate equilibrium between growth and breakage processes in two high-shear mixers: a coffee grinder (sm all scale, 0.25 1) and a Gral 1 0 (Iarge scale, 8 1). Amaranth was used to colour a fraction of the small pellets in an experiment. The dye concentration with processing time for different sieve frac tions was then measured. It was found that the dye distribution became more
985
Breakage in Granulation
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o
500 1 000 1 500 2000 2500 3000 Time (s)
Fig. 4. Change in mean size with time for spray-on spray off experiment in fluidised-bed granulation [ 1 0] . ( 6 ) Spray-on (.�) Spray-off.
homogeneous with time, and they found an exponential relationship for the dye concentration in a sieve cut. The exponential rate constant was termed the con version-rate constant. The smallest pellets were found to give higher conversion rate constants compared to larger ones, indicating fast growth of small pellets and fast formation of small pellets by break-up of larger pellets. An increase in the conversion-rate constants was also found at increasing impeller speeds, indicat ing faster break-up of pellets. They also concluded that the conversion-rate con stants were independent of the scale of the equipment used. Pearson et al. [12] carried out similar experiments to that of Ramaker [1 1 ] to investigate the breakage of granules in a vertical axis 30 L pilot-scale high-shear mixer. Detailed tracer experiments using tracers of different sizes and different processing times (ages) were used to study size and age effects on the breakage kinetics. Tracer granules were created under the same conditions as the stand ard batch, but with the addition of a blue dye, Patent V80. Tracer granules of different narrow sieve cuts were taken at different processing times, and sampies of these added to standard placebo batches at a specific operating time. The dye concentration with size was measured at different times after addition of the tracer granules. They quantified the tracer redistribution as X , the mass fraction of tracer smaller than the initial tracer size. Generally it was found that there was a fast movement of dye to smaller granule sizes, followed by a steady movement to larger sizes. For example, Fig. 5 shows the movement of dye for 1 090 11m tracer granules of different ages. An initial rapid redistribution of dye to smaller sizes followed by a slow increase can be seen in all cases. In addition, the extent of the initial movement to sm aller sizes is c1early a function of age, showing that younger granules exhibit a much greater breakage rate. They also present similar results for different age tracer particles of the same age. These show that larger tracer granules redistribute dye to smaller-size fractions to a much greater extent than smaller tracer granules. This is consistent with the general understanding that larger particles tend to be weaker than nominally identical smaller particles.
986
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C
�
e 6
� 0
� 0
0
..
e
0 ':' 0. 1 1-
0
0
0
0
0
0 4 minutes 0 8 minutes 0 12 minute 6 1 6 minutes 0.01 400
.1 600
800 time (s)
1 000
1 200
Fig. 5. Mass fraction of dye larger than initial tracer size (1 -X) for 1 090 Ilm tracers of different ages [1 2].
The observation of a reduction in breakage with increasing age is also consistent with the process of consolidation (see Section 2.3.9). Van den Dries et al. [2] attempted the addition of tracer granules into a high shear granulator to investigate the influence of breakage mechanism on granule homogeneity. Similar to Pearson et al. [12], tracer granules were added into the reference batch manufactured under similar conditions. They introduced a break age number to quantify the fraction of broken tracer granules, which is 1 00% minus the ratio of the tracer content present in the tracer granules in a particular size-class divided by the total amount of tracer in all the granules. To describe the extent of homogeneity, the excipient distribution in the granules is measured, expressed as the relative standard deviation (RSD) of the excipient concentration in the sieve fractions. A higher RSD therefore indicates poorer distribution. Figure 6 shows the relation between the breakage number and granule homogeneity, as it clearly demonstrates the higher degree of uniformity with increasing granule breakage. Tan et al. [1 3] carried out almost identical experiments to Pearson et al. [1 2] , but for a small-scale fluidised-bed melt granulator. Their tracer results suggested that larger granules were more prone to breakage than smaller granules during granulation. However, they performed an additional experiment where they added tracer granules, but did not add any further binder to promote aggregation. From this they observed tracer breakage without the complication of simultane ous aggregation and found the breakage rate to be independent of granule size. This apparent paradox was resolved by suggesting the actual aggregation rate to be faster for smaller granules than larger during the granulation process. They also found the breakage rate to be independent of granule age. This is
987
Breakage in Granulation SO
�
40
30
x
� 20 Q
x
10
(a)
0 0%
•
•
20%
40%
80%
60%
Breakage [%]
100%
SO x 40
x
x •
� 30
•
� 2O Q
o
10
0
(h)
•
o
0%
20%
60% 40"10 Breakage [%]
80%
100%
Fig. 6. Relationship between percentage of breakage and the distribution of various ex cipients (0 corn starchflactose 200 M; • estradiolfiactose 450 M; • H PCflactose 200 M; *estradiolflactose 200 M ; A estradiolflactose 1 00 M). The distribution is expressed as RSD. All components were added as powder, except for H PC, which was added as an aqueous solution. (a) Process time of 1 min, (b) process time of 1 5 min [2].
contradictory to the result of Pearson et al. [1 2] in high-shear granulation, but can be explained due to the lack of granule consolidation in the low-shear fluidising environment. It has been shown that detailed data from such tracer experiments can provide valuable insight into the kinetics of the breakage process useful for modelling purposes, such as that shown in Hounslow et al. [14] and Tan et al. [1 5] for high shear and fluidised-bed granulation, respectively (Section 4.1). The technique of adding tracer granules, if designed with care, can also be used to probe the in fluence of operating conditions on granulation mechanisms and granule properties. 2.3. Role of variables on breakage behaviour
This section discusses the roles that different variables play in the behaviour of the breakage process. In particular, the perspective is from the granulation
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process, and observations on breakage inferred from this scale. Specifically characterisation of single granule strength is not discussed here, but rather in Section 3.4. 2. 3. 1. Binder viscosity
Binder viscosity acts to affect wet-granule strength by determining viscous forces in liquid bridges between primary particles during relative movement under im pact conditions. The dynamic liquid-bridge strength within a wet granule is dom inated by viscous forces [1 6] and is additionally affected by capillary forces from the surface tension of the binder [ 1 7, 1 8]. This explains the results by Eliasen et al. [1 9] who investigated the effect of binder viscosity on the granulation of lactose monohydrate in a high-shear mixer. They found that a low-viscosity binder re duces the strength of the granules and makes them more susceptible to com minution during the granulation process. Knight [20] presented a brief review about the effect of binder viscosity on the granulation process in high-shear mixers. They summarise that in a high-shear mixer binder viscosity dominates the consolidation process above a critical vis cosity (1 Pa s), below which surface tension forces dominate. Similar to Keningley et 81. [21], they found that a critical minimum binder viscosity is required for a given size of constituent particles to form granules and this critical value in creases with increasing primary particle size. This is essentially due to the need of the higher viscous force to prevent granules formed from larger partic!es from breaking during the shearing process. !veson et 81. [22] studied the effects of binder viscosity and binder content on the granule consolidation process. They found that granule consolidation was a complex process controlled by a balance between the two mechanisms of in terparticle friction and viscous dissipation, which resist granule deformation. In creasing binder viscosity reduces the deformability of granules, hence reducing the consolidation rate. This is also shown by other studies that in general an increasing of binder viscosity reduces binder mobility in granules, limiting com paction by resisting binder migration to the granule surface [1 7,21 ,23,24]. Schaefer and Mathiesen [23] and Johansen and Schaefer [25] found that the initial growth rate was lower for higher viscosity binders, but that the subsequent growth rate was higher. It was also found that lower binder viscosity led to more spherical granules and an improved binder distribution. The laUer observation was also made by van den Dries et al. [2], who investigated the effect of binder viscosity on the granule-breakage mechanism. They defined a breakage number to quantify the fraction of broken tracer granules, which is 1 00% minus the ratio of the tracer content present in the tracer granules in a particular size class d ivided by the total amount of tracer in all the granules. Their results show that the binder viscosity had a very large influence on granule breakage and the
Breakage in G ranulation 1 00% 90% � 80% Q; 70% ..Q E 60% => c 50% (]) Cl 40% co -'" co 30% � III 20% 1 0% 0%
0
989
2 3 Viscosity (Pa.s)
4
5
Fig. 7. Influence of the binder viscosity on the g ranule breakage behaviour of lactose 200 M granules [2].
extent of granule breakage in turn greatly influenced the granule homogeneity. A high-viscosity binder results in stronger granules, less breakage and therefore low homogeneity (Fig. 7). Some other researchers also found that a high binder viscosity will result in larger granules with a wider size distribution [26,27]. Many works [28-30] were performed using aqueous-binder solution to inves tigate the effect of binder viscosity on the performance of fluidised-bed granu lation. The results are consistent; the increased binder viscosity produces stronger granules with a larger average size. This was attributed to the increase in adhesiveness and binder tackiness that promotes successful agglomeration. A different observation was, however, made by Ormos et al. [31 ] , who examined this effect to a high-viscosity range by increasing the binder concentration. They found the final average granule size and wear resistance to increase with higher binder concentration (hence viscosity) to an optimum, beyond which it will drop. The subsequent decrease in size and strength at higher binder viscosities has been attributed to the poor wetting of the more viscous binder on the powder, which induces weak adhesion between the particles.
2. 3. 2. Binder surface tension
Binder surface tension plays an important role in determining granule strength by causing capillary forces between primary particles at the initial stage of granu lation. This is confirmed by one of the earlier works by Capes and Danckwerts [4], who found that a minimum surface tension is required to form granules from particles of a given size. Iveson and Litster [32] and Iveson et al. [33] investigated the effects of binder surface tension on the dynamic-yield strength and intra-granular porosity. They
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found that decreases in binder surface tension decreased the dynamic-yield strength of granules and increased the minimum intra-granular porosity reached over the duration of the granulation experiment. 2. 3. 3. Contact angle between binder and primary particle
Contact angle of the liquid binder to solid partieIes affects the wetting behaviour of binder on the powder surface when it is first introduced into the granulator. It is worth noting here that the change in contact angle of a particular binder-solid system can also be affected by a change in binder surface tension and viscosity. It was mentioned by Simons and Pepin [34] that the influence of contact angle, together with other physiochemical parameters such as powder surface area, powder density and binder surface tension will determine the frictional forces between particles. Combining this with the capillary and viscous forces acting between constituent partieIes in the granule, the granule yield strength can be determined. Knight [35] reported that binder-wetting abilities, which were strongly related to binder contact angle, became a critical parameter to influence the granulation process when contact angle of liquid binder was elose to a critical value of above 90°. For contact angles above the critical angle, product granules tend to have wider-size distributions and lower strength. 2. 3. 4. Primary particle size and shape
It is generally assumed that high-granule strength is associated with small partieIe size, and Van den Dries et al. [2] have confirmed this to a certain extent. On the basis of his tracer experiments, it was found that a decrease in the starting primary partieIe size leads to a decrease in granule breakage. It was also ob served by Johansen and Schaefer [25] that highly spherical primary partieIes and a narrow primary particle-size distribution will dramatically decrease the granule strength because of a reduction in primary-particle interlocking. 2. 3. 5. Equipment-related variables
Schaefer et al. [36] pointed out that the effects of mixer construction on granule properties were rather complex. Furthermore, the effect of granulator capacity is more related to the issue of scaling-up the granulation process. Generally it has been found that larger mixers will produce rounder and smoother granules with a narrow size distribution [36], and lower porosity [37]. More work has been conducted on the construction effects of moving parts in a high-shear mixer, such as the impeller and chopper, on the granulation process.
Breakage in Granulation
991
Schaefer et al. [38] studied the effect of impeller shape on the granulation proc ess. They found that curved impeller bl ades gave rise to smooth granules of spherical shape, whereas plane impeller bl ades caused product granules with irregular shapes. Holm [39] also investigated the effect of impeller and shopper design in a high shear mixer. The effects of blade inclination and impeller rotation speed, which was equivalent to the relative volume swept out by the impeller, were described. It was found that a high-swept-out volume gave rise to low porosity and narrow granule size distributions. The chopper size and rotation speed was found to determine granule strength. The proportion of large granules reduced with in creasing chopper speed due to a comminuting effect in the case where granule strength was low, while the size of the chopper had no effect on the granule size distribution. It was concluded that the chopper continuously cut the mass into smaller fragments and promoted densification, although in the case of small particles it aided fluidisation of the mass. The breaking effect of chopper was also observed by other workers [26,40], who recorded a reduction in the amount of large granules with the use of chopper. 2.3. 6. Binder Gontent
Sherington and Oliver [41 ] state that the amount of binder is a principal parameter in controlling granulation. It is generally acknowledged that granulation rate and the mean size of the granule product increases with increasing binder content up to a certain extent. In addition, it has been shown that the porosity decreases with increasing binder content, due to pores being filled with binder [22,24,42]. Typi cally a reduction in porosity leads to an increase in granule strength, and hence a higher resistance to breakage. 2. 3. 7. Binder addition method
It is generally assumed that the method of binder addition will impose a consid erable effect on the granulation process and properties of the granules [20,43,44]. There are three main categories of binder addition: pouring, melting and spraying. Holm et al. [44] found that binder atomisation improved binder distribution, while binder addition without atomisation resulted in inhomogeneous liquid dis tribution, in particular at low impeller and chopper speeds. Knight et al. [20] studied the three binder addition methods in a high-shear mixer. They found that in spite of the binder addition method used, binder distribution was granule size dependent initially, but tended towards a uniform distribution with longer granulation time.
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2.3. 8. Agitation intensity
A higher impeller speed would lead to an increase in both the frequency and energy of collisions, thereby promoting both the granule consolidation and break age rate. Detailed results about the effects of impeller speed on granule-growth behaviours have been reported in the literature. A high-impeller speed was found to cause a higher granule growth rate [40,42] up to a certain limit, beyond which the growing significance of granule breakage will reduce the overall granule growth [7]. The former observation is most probable due to an increase in granule densification rate and consequently increases both the granule saturation, and hence probability of successful coalescence. The laUer observation is also Iikely to be caused by a loss in aggregation efficiency when the granule i mpact energy becomes too high. Since the consolidation process promotes granule growth while the breakage opposes granule growth, the net effect of impeller speeds on granule growth depends on the balance between these two competing processes [20 ,45]. In such cases, the effect of binder viscosity becomes important, as it will determine whether the wet granule formed is sufficiently strong to resist the shearing forces of the impeller. Schaefer et al. [38] found that variations of the impeller speed had liUle effect on porosity of the product granules. In contrast, Eliasen et al. [19,46] reported that granule porosity could increase with increasing impeller speed due to increased comminution. The laUer observation coincides with VialaUe [24] who reported that an increase in impeller speed gave rise to a faster compaction rate. There are some reports on the influence of impeller speed on the shapes of the granules. At higher impeller speeds, the smoothness and sphericity of the gran ules decreases due to increased granule breakage caused by the intensive im pact load of the impeller [7,46]. Here, granule spheronisation was counteracted due to continuous granule formation and breakage. An increase in chopper speed was found to reduce granule mean size [42], and the width of the granules size distribution [40,46], but liUle effect on granule porosity [42]. Although Schaefer et al. [42] reported that the chopper reduced the mean granule size, they concluded that its effect was inappreciable compared with the effects of other process variables. It was also reported by Hoornaert et al. [26] that increasing the chopper speed promoted the consolidation process, de pending on the shape of the chopper. The effects of impeller and chopper speeds on granule homogeneity were studied by van den Dries et al. [2]. It was found that an increase in impeller speed improved granule homogeneity by increasing the extent of granule breakage for cases where the granule strength was low compared with the impact forces generated by the impeller. In the case of fluidised-bed granulation, the intensity of fluidisation determines the uniformity of binder dispersion. It is commonly observed that increasing the
993
Breakage in Granulation
fluidising air velocity decreases the final granule size and the width of the size distribution [47,48]. This is mainly due to the increased powder flux through the spray zone that essentially decreases the amount of binder picked up per unit time. The increased agitation also reduces the probability of successful aggre gation, and the combination of two factors will effectively lead to a more uniform distribution of binder and subsequently results in a slower growth rate. 2. 3. 9. Granulation time
Schaefer [45] reports that granule strength increases by gradual densification as the granulation process time is extended. The densification process leads to a reduction in the granule porosity, an increase in primary particle packing and transport of the binder to the granule surface. This is in agreement with the work of Fu et al. [49]. They show that wet-granule porosity reduces with granulation time and also explain that this is due to the consolidation, or densification proc ess. Such a result is illustrated in Fig. 8 for two different experimental protocols (optimised and non-optimised operating conditions). For details of the operating conditions, refer to Fu et al. [49]. Additionally, Fu et al. [50] studied the impact breakage of wet granules of different granulation times. They found that the critical impact velocity required for breakage increased, approximately, linearly with increasing granulation time (Fig. 9). In their work, the measured critical velocity is defined as the minimum impact velocity required to form one or more visible cracks on the granule surface. 0.05 __ Optimised
'E (11 '0 c
---- Non-oplimised
0.04
.!!!
(/)
'0 c e (11 0
0.03
>, :.::t :t= (tS (/) .-
> 0 (I) 0 '0 a. (I) Cl � (I) > « �
0.02
0.01
0
10
20
30
40
50
Granulation time. minute
Fig. 8. Comparison of the standard deviation in the porosity for granules (size 4.35-4.75 mm) produced by the optimised and the non-optimised operating conditions. Durcal 40 is the powder material, PEG 400 is the binder and the binder ratio is 0 . 1 5 (Adapted from F u e t al. [49]).
994
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et 8/.
1 6 �------� • •
4 +---�----�--� 20 60 40 1 20 o 80 1 00 Granulation time (min) Fig. 9. The variation of the critical impact velocity with the granulation time for granules with a mean diameter of 4.5 m prepared with PEG 400 and Durcal 40 [50].
3. BREAKAGE AT THE GRANU L E SCALE
In Section 2, granule breakage was examined from a process perspective. Breakage was studied based on the properties of a batch of granules (macro scale) or a sam pie (mesoscale). In this section, studies of granule breakage at the microscale are reviewed in which single or small numbers of granules are examined. Interest in granule breakage at this scale is manifested in two main areas. First, the resistance or propensity to breakage of a granule as a product is important depending on the use of the granules. Second, understanding the properties of single granules that determine their strength can be linked with meso- and macro-scale studies allowing better understanding of the granulation process and control of granule properties. In particular with respect to breakage we are interested in some property or properties of the granule that can describe how easy or difficult it is to break. This concept of granule 'strength' would initially appear to be something that could be measured and perhaps predicted. 3. 1 . Bonding forces in g ranules
The strength of a material can be interpreted as the resistance of the material to permanent deformation and fracture during a stressing event. It is normal to attribute material strength to be a maximum allowable stress value before frac ture occurs. Hence, the stress distribution arising when a material is loaded plays a significant role in determining the fracture behaviour of the material. For a homogeneous elastic sphere (the proverbial particle) in contact with external bodies, c1assical theories of Hertz [51 ] and Lurje [52] can be superposed to the
Breakage i n Granulation
995
overall stress distribution within the sphere Kienzier and Schmitt [53]. More re cently, Shipway and Hutchings [54] derived numerical values for elastic stress fields developed in spheres under uniaxial compression and free impact against a platen. If the sphere is deformed inelastically, it is expected that there is dramatic departure of the resulting stress field fram the elastic case. Catastraphic failure of solid particles will take place once the maximum allowable stress of the material is exceeded. The failure modes can be c1assified into three categories viz. brittle, semi-brittle and ductile failures depending on the extent of plastic deformation experienced by the material during fracture. Brittle failure occurs without signif icant plastic deformation whereas substantial plastic deformation can be found in material fails in a ductile manner. An intermediate case where brittle fracture occurs at the boundaries of a small plastically deformed region is termed semi brittle failure [55]. However, while these descriptions are suitable for homogene ous continuum solid particles where local stresses can be transmitted throughout the entire volume of material, they are insufficient to describe the failure of gran ular solids. Granular material is a cluster of small particles held together by interparticle bonds. The interparticle bonds within a granular solid may be rup tured causing the particles at the point of load application to be sheared apart before the load can be transmitted thraughout the solid as in a homogenous elastic system [56]. Fram this it can be concluded that the strength of a granular medium is governed by interparticle bonding mechanisms rather than the strength of individual constituent particles. Furthermore, the load transmission in a granular medium is affected by its internal particle packing. It is c1ear that the perceived strength of a granule will be a function of the nature and concentration of its internal bonds. Before looking in more detail at granule strength, it is worth reviewing the interparticle forces that are Iikely to be contributing to a granule's strength. These inter-particle adhesive or bonding forces have been reviewed by Rumpf [57], Schubert [58] and Sherington [41 ] . The different types of bonds that may exist within a granule can be c1assified as folIows. Forces due to immobile films. A thin immobile liquid layer can be formed on the surface of primary particles due to reasons such as granule reaching a critical level of compaction or excess binder removal thraugh evaporation. Overlapping of the immobile liquid layer between primary particles praduces this bonding force. The strength of these bonds is dependent on contact area and the prap erties of the binder such as the tensile strength of the liquid layer. Forces due to mobile-liquid bridges. With increasing liquid content in the granule, the liquid between primary particles tends to be mobile, forming liquid bridges. In this case, adhesion forces arise fram surface tension forces at the liquid/air interface- and hydrostatic-suction pressure in the liquid bridge. Typically it is found that wet-granule strength increases with increasing liquid content up to the point at which the granule is saturated and the liquid bridges no longer exist.
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Forees due to solid bridges. Solid bridges ean be formed, for example, through ehemieal reaetions, erystallisation, binder solidifieation and sintering. If these types of bonds exist, they will typieally be the primary strength determining bonds. Forees due to attraetive effeets between solid partieles. Attraetive forees be tween solid particles ean take many different forms, sueh as van der Waals forees, magnetie and eleetrostatie. These are typieally short-range forees and are only signifieant for very small partieles sizes (less than 1 )lm), or eases where the particles have been brought close together by high eompression forees. Forees due to meehanieal interloeking between solid particles. Irregular shaped particles ean eontribute signifieantly to granule strength if they are paeked tightly, due to interloeking effeets. The relative importanee of these bonding forees in determining the strength of a granule will vary from ease to ease. In some types of granules, some of these forees will not exist and it is unlikely that all these forees will be aeting. For example, in a dry granule there will be no interstitial liquid and so there will be no internal forees due to immobile or mobile liquid films. In addition, these forees will also interaet with eaeh other. For example a liquid layer on a solid particle will reduee interparticle frietion and interloeking forees by aeting as a lubrieant. The relative magnitudes of the different bonds are also a strong funetion of particle size (see Fig. 1 0). In the ease of wet granules, it has been shown by Rumpf [57] that eontributions to wet granule strength by van der Waals forees, and forees from thin films on l� �------,
100
]
N
�
6
10
1
0.1
0.01 +-----.,----'''r-''--'l 1� 100 1 10 0.01 0.1
d, f1m Fig. 1 0 . Theoretical tensile strength, Rumpf [57]).
(Jt,
of agglomerates as a function of size, d (after
997
Breakage in Granulation
particle surfaces are usually very small. In addition, formation of solid bridges between primary particles is usually not applicable in the case of wet granules. It is also then assumed that the interlocking effect is only significant in a few specific cases. It is therefore widely accepted that the static strength of wet granules is determined principally by liquid-bridge forces between primary particles. It is due to the complicated interactions of these forces that it is difficult to define granule strength. As a result of trying to understand the failure of granular materials, prin cipally two theoretical paradigms have developed [35]. The first is attributed to Rumpf [57] and considers that a granule fails by simultaneous rupture of all the bonds along a fracture plane. Alternatively, Kendall [59] argued that a granule failed through crack nucleation and propagation, and adopted fracture mechanics to describe this. 3. 1. 1. Rumpf's theory
Rumpf [57] developed a classical model for predicting the static-tensile strength of granules. Considering a granule under the action of applied loads, he pointed out that fracture of the granule is mainly caused by the tensile stress generated within the assembly. The theoretical tensile strength of a granule is suggested to be the summation of all the interparticle bond strengths across the fracture sur face. The implicit assumption in this analysis is all the interparticle bonds across the fracture surface ruptured simultaneously during the fracture process. This leads to the derivation of the following expression for theoretical granule-tensile strength, (Jt, in its general form. (J t nF (1) where n is the average number of interparticle contacts per unit area across the granule cross-section and F the mean force required to separate them. It is found that n scales with granule-solid fraction and size of the constituent particles with a uniform primary particle size distribution. Therefore, equation can be rewritten as follows (Rumpf [57]): ( 1 8) � (Jt 1.1 (2) 8 02 where 8 and 0 are the intra-granular void fraction and constituent-particle diam eter, respectively. Nevertheless, the constituent particles of real granules are often poly-disperse and non-spherical. In respect to this problem, it is proposed that 0 in the foregoing should be substituted with the mean diameter, for instance the surface-volume mean diameter, of the real constituent particles [35]. Equa tions ( 1 ) and (3) are applicable to granules with different internal bonding mech anisms, which results in different expression for F. For wet granules, where =
-
=
998
A. D. Salman
et al.
primary particles are held together with liquid bridges, the model is given as: - 8 Yt (Jt = CS - cos e (3) 8 dp where C is a material constant (for uniform spheres C = 6), S the liquid satu ration, 8 the intra granular void fraction, dp the surface average diameter of pri mary particles, YI the liquid surface tension, and e the liquid-solid contact angle. In this case, the liquid saturation of a wet granule is defined as - 8 Ps S=H (4) 8 Pt where H is the moisture content, which can be calculated as the ratio between liquid mass and dry-solid mass. The powder and liquid densities are expressed as Ps and Pt, respectively. The model shows that wet granule-tensile strength is determined by starting material properties (C, dp, e and YI) and parameters that express granule structure (8 and S). It indicates that granule strength is propor tional to liquid surface tension and saturation, increases with decreasing porosity and is inversely proportional to primary particle size. In the case of binderless granules, the main bonding mechanism can be considered to be van der Waals interparticle attraction. In this case, can be expressed by the following well established relationship: AD (5) 24a2 where A is the Hamaker constant and a the separation between the surfaces of the constituent particles and where the remaining symbols have the same des ignation as before. However, there are a number of deficiencies in the model of Rumpf [57]. The model assumption that all the interparticle contacts in the fracture plane fail sud denly is contested by Kendall [59]. He argues that simultaneous failures do not usually occur in practice, where the real-failure mode is by cracking due to con tacting primary particles in a granule separating sequentially (see Section 3.1 .2, for more details on this argument). The assumption that a granule consists of mono-sized spheres is also not generally realistic. Kapur [60] shows that con stituent particles exhibit size variation and the content of the fines plays a dom inant role in determining the granule strength. Cheng [61 ] also showed that the shape of primary particles has a significant effect upon the strength of wet gran ules. The model also does not take account of interparticle friction forces. Chan et al. [62] found that reduction in porosity would increase friction forces between particles by reducing separation distances between substrate particles. Fu et al. [3] show that the critical impact velocity (the impact velocity above which a granule breaks) increases consistently with granulation time even though the binder content and air fraction remain relatively constant after a long period of
1
--
1
F
F=
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Breakage in Granulation
granulation. They argue that this is contradictory to the model of Rumpf [57], and suggest that this consistent increase in apparent granule strength is due to a densification of the interparticle contacts, and hence an increase in inter-primary particle friction which is not included in the model. In addition, the use of static capillary force in Rumpfs model is not ideal for describing the impact strength of granules. Inside a high-shear granulator, gran ules experience high impact strain rates with impact velocities as high as 1 0 ms - 1 . Under such conditions, the dynamic effects, such as viscous dissipation and liquefaction, may become significant [17]. Van den Dries et al. [2] highlighted the importance of the viscous forces in high-shear granulation, and modified the Rumpf model by considering the viscous forces using the Reynolds lubrication equation. The modified equation describes the tensile strength of a granule under dynamic conditions 9 (1 - Ei 91t,LWp (6) 8 � [',2 1 6d3,2 where up is the relative velocity of moving particles, f1 the binder viscosity and d 3 .2 is the surface mean diameter. This model assumes that the tensile strength is independent of the liquid saturation and only depends on the number of contact points between particles, which is consistent with the viscous force of a single liquid bridge between two moving particles. (Jt = -
-
3. 1 . 2. Kendal/'s theory
Kendall [59] argued that Rumpfs theory (Section 3. 1 . 1 ) failed to account for the actual failure mechanism found in granular materials and the theory led to over estimation of granule strength. According to Kendall [59), fracture of granule is a consequence of crack nucleation at flaws leading to subsequent crack propa gation through the granular structure. Thus, the failure mechanism in this case is sequential separation of interparticle bonds in contrast to the simultaneous bond rupture proposal of Rumpf [57]. The propagation of cracks through a granular solid consumes the amount of energy needed to create new surfaces along the crack planes. Griffith [63] initially developed fracture mechanics for linear elastic materials, the basis of which is an energy balance in which the strain energy released at the crack tip provides the driving force to create new surfaces. Kendall [59] applied these concepts to derive the following expression of fracture strength of granules, (Jf: (7) where
1 029
Breakage in Granulation
lection rate constants, attrition constants and aggregation rate constants were extracted and expressed as a function of individual operating conditions, forming a series of rate constant plot. The results look promising in revealing the de pendence of breakage rate on operating conditions, with two of the examples presented in Fig. 31 . It can be clearly seen that breakage selection rate (So) and the attrition constant (z) decreases with increasing bed temperature. This is at tributed to the stronger granules formed at higher bed temperature due to the slower binder solidification rate which allows the particles to move and pack closer as the binder remains molten for a longer period. This work clearly sug gests that the granule breakage rate can be quantified with sound physical basis and can be used to enhance the understanding of operating conditions on granule breakage during granulation. Biggs e t al. [1 0] present an alternative method of including breakage in a population balance model. They used a fluidised-bed granulator configuration where melted polyethylene glycol 1 500 was sprayed onto cool glass ballotini. They measured the mean granule size change with time during and after spraying (see Fig. 32). After spraying they noticed a decrease in mean granule size. They found that the relationship between the granule mean size and distribution standard deviation was the same during and after spraying, and hypothesised that the observed breakage process was the reverse of the growth process. This argument suggests that the granules break into the granules that were used to form them. They used a PBE of the form of equation (14), but included two aggregation rate constants as folIows: t � tspray off
(24)
t> tspray off
During spraying the aggregation rate constant was modified by the negative rate constant, and after spraying only the negative rate constant was used. They observed an exponential decrease in mean size after spraying (see Fig. 32) and so used an exponential model with characteristic time constant, in this part of the process. They used the EKE size-dependent aggregation kernel (see Table 1 ). The PBE was solved using the discretised population balance model of c,
0. 8 ,.-_ _ _ _ _ _ .---,
0.8 ,.-----�--...__,
'[ 0
0.6
;;;: .. Cl
0.2
,/'
�/ o
tJ. , � , .
0.6
0. 4 �.-�Jk�·A·lI;X-� � ...
250 500 750 1 000 1 250 1 500 Time(s)
�
o
0. 2
i
' �.fj.
f>., 4 -" ..- ....�.
,.
.
500
1000 1500 Time (s)
2000
o
500 1 000 1500 2000 2500 3000 Tlme (s)
Fig. 32. Comparison between model ( - ) and experimental ( . ) results of the mean granule size during ( 6 ) and after spraying (.) in a fluidised-bed granulator for liquid to solid ratios of (a) 0.05, (b) 0. 1 , and (c) 0.2 [ 1 0].
1 030
A. D. Salman et al.
Hounslow et al. [1 29]. Their modelling results presented in Fig. 32 show good agreement with the experimental results during the spraying of binder. However, discrepancies are found in the 'spray off' breakage regime. This approach rep resents a fairly straightforward way of including breakage in a PBE of a gran ulation process. However, there are problems with this approach as aggregation is a second-order rate process, and breakage is a first-order rate process. Therefore, trying to model breakage as a negative aggregation rate process is fundamentally flawed and will not succeed with any physical basis.
4.3. Micro scale : d iscrete modelling
Recently, computer simulation has been used to study the evolution of impact breakage for particulate systems. This is because the same granules can be tested repeatedly and information about different impact parameters at any in stant of time can be retrieved as required. Furthermore, computer simulation offers the advantage of revealing information, such as different energy dissipation or load transmission paths within a granule under impact that is not accessible through physical experiments. One example of the force transmission paths is shown in Fig. 33 [1 30], which iIIustrates the force transmission through the ag glomerate when the wall force is 6.5 mN. The lines show the location and ori entation of the (resultant) contact forces and its thickness indicates the
Fig. 33. Force IransmISSIon mrougn me granUles upon ImpaCl wnn me wall l l "UJ.
1 031
Breakage in Granulation
magnitude of the force, scaled to the current maximum. It is c1ear from this graph that larger forces are generated at the impact point near the wall . Unlike homogenous materials such a s steel, the granular medium exhibits discontinuous material structure with interaction occurring at interparticle con tacts only [ 1 3 1 ] . Hence, DEM is a suitable tool to study the macroscopic response of a particulate system, which depends on the discrete behaviour of its constit uent primary particles. Impact breakage of granules is one of the examples of application of DEM simulation. The evolution of granule impact is mode lied as a dynamic process by tracing the motion of the granule's constituent particles throughout the impact event using Newton's law of motion. The resulting particle motion is influenced by the interaction at the interparticle contacts. The simulation is advanced over a large number of small-time steps and the particle motion is updated continually. This methodology was initially proposed by Cundall and Strack [1 32]. Attempts to study granule impact breakage were initiated at Aston University by incorporating well-established particle interaction laws into the methodology of Cundall and Strack [1 32]. The DEM code at Aston code is capable of simulating the interactions between elastic, spherical, frictional and auto-adhesive particles. The earlier version of the code by Thornton and Yin [1 33] considered only elastic deformation at the interparticle contacts. Plastic yield was accounted for in the subsequent version developed by Thornton and Ning [1 34]. There are two types of force-displacement relationships according to the model in the Aston code namely normal and tangential interactions. For auto adhesive particle, the normal force-displacement relationship due to the pres ence of surface energy is determined using the theory of Johnson et al. [1 35]. This is an extension of Hertzian elastic contact mechanics that predicts the nor mal force increment, AP, as a result of an increase in the relative approach between two elastic spheres, Aa, as folIows: AP =
2E*a
[
]
3 jP' - 3 vPc 3 jP' - vPc
Aa
(25)
where E* is the effective elastic modulus, a the radius of the contact area, pr the effective Hertzian force and Pe the pu li-off force. The model for the tangential interaction is a combination of the theories of Mindlin and Deresiewicz [1 36] and Savkoor and Briggs [1 37]. According to Thornton and Yin [1 33], sliding between two contacting spheres must be preceded by a 'peeling' action, which causes a reduction in the contact areas of the spheres. Several researchers have used the Aston code to perform computer simulation of granule impact breakage against a target wall [91 , 1 00, 1 01 ,1 38, 1 39]. The recent review of Mishra and Thornton [98] reported that there were five factors governing the breakage behaviour of granules under impact. These factors were impact
1 032
A. D . Salman et al. 0.5 rn/sec
•
1 .5 m/see
Fig. 34. Fracture pattern at different impact velocities; solid tractions = 0.602. On the right-hand side, the top two images show views below the agglomerate, while the lower two images show views trom above (Adapted trom Mishra and Thornton [98]).
1 033
Breakage i n Granulation
velocity, bond strength (interface energy), granule porosity, particle contact density and the local structural arrangement of particles near the impact region. Inves tigating the combined effects of impact velocity and porosity, significant breakage was found to occur when the impact velocity exceeded a certain threshold value. Figure 34 shows a set of snapshots taken after the impact of the densest ag glomerate 4Y = 0.602 with the wall at different impact velocities. The upper two snapshots shown on the left-hand side of the figure shows that little breakage is observed up to an impact velocity of 1 ms� \ while the agglomerate exhibit clear evidence of fracture planes at impact velocities of 1 .5 and 2.0 ms� 1 . Once break age took place, dense granules always fractured while loose granules disinte grated. Granules with intermediate porosity exhibited mixed-mode failure where both fracture and disintegration were possible. Furthermore, they compared the breakage behaviours between similar granules, one with more particle contact density than the other. The granule with higher contact density fractured in contrast to disintegration shown by the granule with lower contact density. It was postulated that significant amount of stresses were transmitted through the bulk of the granule with higher contact density storing sufficient elastic energy for fracture. One of their findings suggested that different breakage patterns could be obtained when dif ferent granule surface was subjected to impact. This was due to the difference in local particle arrangement near the impact location. collisional contact with wall
collisional contact between particles
Fig. 35. A collision between two macroscopic particles showing the division of the particles i nto elementary triangles and examples of collisional and glued contact (adapted from Potapov and Campbell [ 1 4 1 ]).
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A. D. Salman et al.
Using the same code, Kafui and Thornton [140] simulated the collision between a pair of similar granules in order to understand the fragmentation process due to this impact arrangement. They proposed that the number of broken bonds within the granules and the amount of fines generated were proportional to a dimen sionless group, which accounted for the system properties. A slightly different approach was adopted by Potapov and Campbell [141] to represent an elastic solid by glueing polyhedral elements together. A particle in this case is viewed as a composite material glued together by many elements of known stiffness. An example of two contacting particles is shown in Fig. 35. The glue at the interface between two elements in a particle could withstand certain tensile stresses before it breaks, and the point of joint separation represents the formation of a crack. The corresponding energy released is then equivalent to the potential energy stored in that portion of the joint. For particle collision, the con tacting forces are accounted for by the normal and the tangential elastic force characterised by a normal and tangential stiffness. Using this modified technique, correlation between the breakage patterns of an elastic solid and different frac ture mechanism was established. 4.4. Micro scale: continuum modelling
A key problem with DEMmodelling of granule deformation and failure (see Sec tion 4.3) is the inclusion of the effect of binder. An alternate modelling approach considers granules as continuous bodies that can be specified in terms of a material model, representing the bulk deformation behaviour, and boundary con ditions that define the frictional and adhesive interactions [142]. Elastic materials exhibit restitution coefficients approaching unity, whereas wet granules typically exhibit restitution coefficients below 0.2 [3]. In this case, granules are generally considered to deform elastoplastically. Johnson [143] presented a theoretical model for the contact of an elastic-perfectly plastic sphere with a rigid wall . His model was based on fully developed plastic loading and perfectly elastic unload ing. Thornton et al. [144] refined this approach by defining a limiting contact pressure and approximating the evolution of the normal contact pressure distri bution by an elastic phase during which the pressure distribution was described by a truncated Hertzian pressure distribution. Unloading was considered to be elastic, but with a reduced contact curvature as a result of the irrecoverable plastic deformation. However, neither of these models considers the curvature a variable during loading. Li et al. [145, 1 46] used finite element analysis to examine the impact of non-adhesive elastic-perfectly plastic spherical particles. They found that the computed coefficients of restitution as a function of the impact velocity were intermediate between those predicted by the models of Johnson [1 43] and Thornton [144], although the differences were relatively small. Adams
Breakage in Granulation
1 035
et al. [142] suggests that this is probably because the cases investigated did not exhibit substantial elastic strains. Of particular interest in the modelling of granule interactions is the effect of binder at the interface of two colliding particles/granules. An attempt to model the influence of viscous liquid on particle collisions has been presented by Lian et al. [1 1 4]. Here, they developed an approximation to the elastohydrodynamic collision between two spherical solids with an interstitial incompressible Newtonian fluid of constant viscosity. They assumed a Hertzian-like profile for the elastic deforma tion, and developed a c1osed-form solution capable of predicting the evolution of relative particle velocity, force and restitution coefficient.
5. CONCLUSIONS
Experimental studies at the process scale have been able to investigate granule breakage using tracer particles. However, analysis of these results invariably requires removal of sampies for analysis, which can alter the properties of the granules in addition to increasing the quantity of work required to characterise a given set of conditions. Further work in this area in the future should concentrate on online sampling and analysis. By measuring particle size, shape and tracer concentration online, more detailed information about the breakage process can be obtained. At the single granule scale, characterisations of pre-product granules are re quired. A lot of the reviewed experimental work is based on measuring the strength, for example, of granules as products. These tend to be large, with well consolidated structures. It is unlikely that this type of granule is representative of the granules that are undergoing breakage during the process. In order to using single granule scale observations to inform our understanding of the breakage rate process, this needs to be addressed. The size of sampled granules needs to be reduced from, for example 5 mm, down to something more representative of the early stage of granulation. The work of Hounslow et al. [14] (see equation (21 )) shows that the breakage rate is highest in the early stage of granulation, and granules from this stage of the process should be characterised. In addition to this, there is a lot of characterisation of individual granule breakage against solid surfaces. It is expected that granule/granule interactions are an important part of the breakage process, and the resulting breakage behaviour from these types of interactions deserves more investigation. Already, interesting micro-mechanical work is being conducted to characterise the strength and breakage of sub-granule components, such as liquid bridges. This can be extended to characterise other types of bonds and to relate these to the bulk granule properties.
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A. D . Salman et al.
From the modelling perspective, more rigorous inclusion of breakage rates in PBM will require multi-dimensional models capable describing breakage de pendence by relevant granule properties, such as binder composition, rather than only size and time. Time-dependent breakage rates can implicitly include other breakage dependent properties, that happen to also change with time, such as porosity, but more physically based breakage rates will require these properties to be included in the PBM. Modelling of the single granule and sub-granule scale requires the key weaknesses to be addressed. In particular, DEM fails to ad equately model realistic interparticle bonds, and there is the need for incorpo ration of interstitial liquid. Overall, the importance of breakage during the granulation process has in creased in its perceived importance. Understanding in more detail, the role that breakage plays in the granulation process to distribute components and structure granules will allow better control and design of granular product properties in the future. REFERENCES [ 1 ] S . M . Iveson, Chem. Eng. Sci. 56 (200 1 ) 21 75-2220. [2] K. van den Dries, O . M . de Vegt, V. Girard, H. Vromans, Powder Techno! . 1 33 ( 1 -3) (2003) 228-236. [3] J . Fu, M . J . Adams, G . K. Reynolds, AD. Salman, M.J. Hounslow, Powder Techno!. 1 40 (3) (2004) 248-257. [4] C. Capes, P. Danckwerts, Trans. ! . Chem. Eng. 43 ( 1 965) T1 1 6-T1 24. [5] K. Sastry, S. Panigraphy, D . Fuerstenau, Trans. Soc. Min. Eng. 262 ( 1 977) 325-330. [6] B. Ennis, J. Utster, Particle Size Enlargement. Perry's Chemical Engineers' Hand book, in R. Perry, D. Green (Eds.), McGraw-Hill, 7th edition, New York, 1 997, pp. 20-89. [7] P.C. Knight, A Johansen, H . G . Kristensen, T. Schaefer, J . P . K. Seville, Powder Techno!. 1 1 0 (3) (2000) 204-209. [8] S . M . Iveson, J . D . Utster, K. Hapgood, B.J. Ennis, Powder Techno!. 1 1 7 ( 1 -2) (2001 ) 3-39. [9] P. Vonk, G. CPF, J.S. Ramaker, H . Vromans, N .W.F. Kossen, Int. J. Pharm. 1 57 ( 1 997) 93-1 02. [ 1 0] C . Biggs, R. Boerefijn , M . Buscan, A Salman, M . Hounslow, World Congress on Particle Technology, Sydney, Australia, 2002. [1 1 ] J.S. Ramaker, MA Jelgersma, P. Vonk, NW.F. Kossen, Int. J . Pharm. 1 66 ( 1 998) 89-97. [ 1 2] J . M.K. Pearson, M.J. Hounslow, T. Instone, AIChE J 47 (9) (2001 ) 1 978-1 983. [ 1 3] H . S . Tan, A D . Salman, M . J . Hounslow, Chem. Eng. Sci. 60 ( 1 4) (2005) 3835-3845. [ 1 4] M . J . Hounslow, J . M .K. Pearson, T. Instone, AIChE J 47 (9) (2001 ) 1 984-1 999. [1 5] H . S . Tan, A D . Salman, M . J . Hounslow, Powder Techno!. 1 43-144 (2004) 65-83. [1 6] DN Mazzone, G . ! . Tardos, R. Pfeffer, Powder Techno! . 51 ( 1 ) ( 1 987) 71-83. [1 7] B.J. Ennis, G. Tardos, R. Pfeffer, Powder Techno!. 65 ( 1 -3) ( 1 99 1 ) 257-272. [ 1 8] G . ! . Tardos, M . Irfan-Kahn, PR. Mort, Powder Techno! . 94 ( 1 997) 245-258. [ 1 9] H . Eliasen, T. Schaefer, H . Gjelstrup Kristensen, Int. J. Pharm. 1 76 ( 1 ) ( 1 998) 73-83.
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Breakage in Granulation
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[1 00] J. Subero, Z. Ning, M. Ghadiri , C. Thornton, Powder Technol. 1 05 ( 1 -3) ( 1 999) 66-73. [1 0 1 ] C. Thornton, M .T. Ciomocos, M.J. Adams, Powder Technol. 1 05 ( 1 -3) ( 1 999) 74-82. [1 02] A.D. Salman , G . K. Reynolds, J.S. Fu, Y.S. Cheong , CA Biggs, M.J. Adams, DA Gorham, J . Lukenics, M.J. Hounslow, Powder Technol. 1 43-144 (2004) 1 9-30. [1 03] J. Tomas, M. Schreier, T. Groger, S. Ehlers, Powder Technol. 1 05 ( 1 -3) ( 1 999) 39-51 . [1 04] K. Kafui , C. Thornton, Powders and Grains '93. Rotterdam, Balkema, 1 993. [1 05] R Moreno, M . Ghadiri, S.J. Antony, Powder Technol. 1 30 ( 1 -3) (2003) 1 32-1 37. [1 06] D.G. Papadopoulos, M. Ghadiri, Adv. Powder Technol. 7 (3) ( 1 996) 1 83-1 97. [1 07] K.M. Djamarani, I . M . Clark, Powder Technol. 93 (2) ( 1 997) 1 01 - 1 08. [1 08] R Schuhmann, Transactions of the AlME, 217 ( 1 960) 22-25. [1 09] H.J. Ryu, F. Saito, Solid State lonics 47 ( 1 -2) ( 1 99 1 ) 35-50. [1 1 0] J. Gilvarry, B. Bergstrom, 220 ( 1 96 1 ) 380-389. [1 1 1 ] Y.S. Cheong, G . K. Reynolds, AD. Salman , M.J. Hounslow, Int. J. Miner. Process. 74 (Supp. 1 ) (2004) S227-S237. [1 1 2] A.D. Salman, DA Gorham , A. Verba, Wear 1 86-1 87 (Part 1 ) ( 1 995) 92-98. [1 1 3] A Samimi , R Moreno, M. Ghadiri, Powder Technol . 1 43-144 (2004) 97-1 09. [1 1 4] G. Lian, M.J. Adams, C. Thornton, J. Fluid Mech. 31 1 ( 1 996) 1 4 1 - 1 52. [1 1 5] S.J.R Simons, D. Rossetti, P. Pagliai, R Ward, S. Fitzpatrick, Powder Technol. 1 40 (3) (2004) 280-289. [1 1 6] C.D. Willett, M.J. Adams, SA Johnson, J . P. K. Seville, Powder Technol. 1 30 ( 1 -3) (2003) 63-69. [1 1 7] J. Subero, D. Pascual, M. Ghadiri, Chem. Eng. Res. Design, Trans. Inst. Chem. Eng. Part A, 78 ( 1 ) (2000) 55-60. [1 1 8] D. Golchert, Use of Nano-indentation to determine bulk coating hardness of fertiliser coated seed, Ph.D. Thesis, University of Queensland, Australia, 2003. [1 1 9] D. Golchert, R Moreno, M. Ghadiri , J. Litster, Powder Technol 1 43-144 (2004) 84-96. [1 20] H . H ulbert, S. Katz, Chem . Eng. Sci . 1 9 (1 964) 555-574. [ 1 2 1 ] D. Ramkrishna, Population Balances: Theory and Applications to Particulate Sys tems in Engineering, 1 st edition, Academic Press, New York, 2000. [1 22] A Randolph, M. Larson, Theory of Particulate Processes, 1 st edition, Academic Press, New York, 1 97 1 . [1 23] M . J . Hounslow, RL. Ryall, V.R MarshalI, AIChEJ, 34 ( 1 1 ) ( 1 988) 1 82 1 -1 832. [1 24] AS. Bramley, M.J. Hounslow, RL. Ryall, J. Coll. and Interf. Sci . 1 83 (1 ) (1 996) 1 55-1 65. [1 25] AA Adetayo, B.J. Ennis, Powder Technol . 1 08 (2-3) (2000) 202-209. [1 26] G . K. Reynolds, CA Biggs, A.D. Salman , M . J . Hounslow, Powder Technol . 1 40 (3) (2004) 203-208. [1 27] C .F.w. Sanders, AW. Willemse, A D . Salman, M . J . Hounslow, Powder Technol . 1 38 ( 1 ) (2003) 1 8-24. [1 28] H .S. Tan, A.D. Salman, M . J . Hounslow, Chem. Eng. Sci . 60 ( 1 4) (2005) 3847-3866. [1 29] M . J . Hounslow, RL. Ryall, V.R MarshalI, AIChEJ 34 ( 1 1 ) ( 1 988) 1 821-1 832. [1 30] C. Thornton, L. Liu , Powder Technol. 1 43-144 (2004) 1 1 0-1 1 6. [ 1 3 1 ] K. Yin , Numerical modelling of agglomerate degradation . Ph . D. Thesis, Aston University, 1 992. [1 32] PA Cundall, O . D.L. Strack, Geotechnique 29 ( 1 ) ( 1 979) 47-65. [1 33] C. Thornton, K.K. Yin , Powder Technol . 65 ( 1 -3) ( 1 99 1 ) 1 53-1 66. [1 34] C . Thornton, Z. Ning, Powder Technol. 99 (2) ( 1 998) 1 54-1 62. [1 35] K.L. Johnson, K. Kendall, A.D. Roberts, Proc. Roy. Soc. Lond . , Series A (Math. Phys. Sci. ) , 324 ( 1 558) ( 1 971 ) 301-3 1 3. [1 36] R Mindlin, H . Deresiewicz, J. Appl. Mech. 20 (1 953) 327-344.
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A D . Salman et al.
[ 1 37] A.R. Savkoor, G.A. D . Briggs, Proc. R. Soc. London Sero A 356 ( 1 684) ( 1 977) 1 03-1 1 4. [1 38] C. Thornton, K.K. Yin , M.J. Adams, J. Phys. D (App!. Phys.) 29 (2) ( 1 996) 424-435. [1 39] K.D. Kafui, C. Thornton, Powder Techno! . 1 09 ( 1 -3) (2000) 1 1 3-1 32. [ 1 40] K. Kafui, C . Thornton, Fifth World Congress of Chemical Engineering, San Diego, California, USA, 1 996. [ 1 4 1 ] AV. Potapov, C.S. Campbell, Powder Techno!. 8 1 (3) ( 1 994) 207-2 1 6 . [1 42] M . J . Adams, C . J . Lawrence, M . E . D . Urso, J . Rance, Powder Technoi. 140 (3) (2004) 268-279. [1 43] K. Johnson, Contact Mechanics, Cambridge U niversity Press, Cambridge, 1 985. [1 44] C . Thornton, J . Appi. Mech. Trans. ASM E 64 (2) ( 1 997) 383-386. [1 45] L. Li, C. Thornton, C. Wu, Proc. Inst. Mech. Eng . , Part C J. Mech. Eng. Sci. 2 1 4 (8) (2000) 1 1 07-1 1 1 4. [1 46] L.-Y. Li, C.-Y. Wu, C . Thornton, Proc. Inst. Mech. Eng . , Part C J . Mech. Eng . Sci. 2 1 6 (C4) (2002) 421-43 1 . [1 47] M . Smoluchowski , Mathematical Theory of the Kinetics of the Coagulation of Colloidal Solutions. Zeitschrift für Physikalische Chemie 92 ( 1 9 1 7) 1 29. [1 48] A Golovin, Soviet Physics-Doklady 8 ( 1 963) 1 91 -1 93.
CHAPTER 22 F l u i d isat i o n of Co hes ive Particles J onathan P . K. Sevi lle *
Gentre for Formulation Engineering, Department of Ghemical Engineering, University of Birmingham, Birmingham B15 2TT, UK Contents 1 . Basic aspects of fluidisation 1 . 1 . Introduction 1 .2. Pressure drop through packed beds 1 .3 . Minimum fluidisation velocity 1 .4. Particle and fluid properties 1 .5. Slugging 1 .6. Distributor design 1 .7. Bubbling and solids circulation 2. Types of fluidisation 2. 1 . General description of group behaviour 2. 1 . 1 . Group B 2.1 .2. Group A 2 . 1 .3. Group G 2.1 .4. Group D 3. I nterparticle forces 3.1 . Van der Waals forces 3.2. Liquid bridges 3.3. Sintering 4. The effects of cohesive forces 4. 1 . Effects of "natural" cohesion - Van der Waals forces 4.2. Effects of liquid bridges 4.3. Sintering 5. Conclusions Acknowledgements References
1 04 1 1 04 1 1 043 1 044 1 046 1 047 1 048 1 049 1 05 1 1 056 1 056 1 057 1 057 1 058 1 058 1 058 1 059 1 06 1 1 062 1 062 1 063 1 065 1 067 1 068 1 068
1 . BASIC ASPECTS OF FLUIDISATIO N 1 . 1 . I ntroduction
A fluidised bed is formed by passing a fluid, usually a gas, upward through a bed of particles supported on a distributor (Fig. 1 ). As the fluid velocity is increased, *Corresponding author. E-mail:
J . P. [email protected]
Granulation
Edited by A.D. Sa/man, '
M.J.
Hounslow and J. P. K. Seville
(' 2007 Elsevier B.V All rioht� ",�"rv"rl
1 042
J. Seville
Bed weight per unit area, W/A Minimum fluidisation velocity , Umf
Pressure difference across bed, M' U
Fig. 1 . A basic fluidised bed and determination of the minimum fluidising velocity.
the pressure drop aeross the bed also inereases until it equals the weight per unit area of the bed. At this point (the point of ineipient or minimum fluidisation) the bed is said to be fluidised. In gas-fluidised beds, at gas veloeities in exeess of the minimum fluidisation velocity, Umf, some of the fluidising gas passes through the bed in the form of moving voids, whieh resemble (in some respeets) bubbles in a viseous liquid. At mueh higher gas velocities still, these clearly identifiable bubbles are no longer seen, and the predominant struetures are par tiele clusters. In general, a fluidised bed exhibits the following useful properties: (a) It behaves like a liquid of the same bulk density - particles ean be added or withdrawn freely, the pressure varies linearly with depth, heavy objeets will sink and light ones float. (b) Particle motion is rapid, leading to good solids mixing - henee little or no variation in bed temperature with position. (e) A very large-surfaee area is available for reaetion and mass and heat transfer - 1 m 3 of 1 00 l!m partieles has a surfaee area of about 30,000 m 2 . There are, however, some disadvantages, whieh should be eonsidered in any application. In the context of fluidised-bed agglomeration, these include the following: (a) Gas and solids motion may not scale easily, so that seale-up ean be difficult. (b) Particle entrainment can oceur, espeeially with wide size distributions, prefer entially removing fine particles from the bed. (c) Particle attrition andjor surfaee erosion ean occur. The favourable properties listed above have given rise to many applications of fluidised beds in industry, some of which are listed in Table 1 [1]. Gas-fluidised
1 043
Fluidisation of Cohesive Particles
Table 1 . Classification of fluidised bed applications according to predominating mecha
nisms [ 1 ]
Industrial processes
Heat and/ar mass
Heat and mass
Heat transfer
Gas/gas reactions
transfer bctween
transfer between
between
in which solid
in which so lids are
ga�/particles
particle/particle
bedisurface
aets as catalyst or
transformed
heat sink
or partie leIsurface
'Solids drying -Absorption 01' solvents -Cooling of fertilizer prills -Pood freezing
•
Plastic coating
of surfaces
·Coal combustion -Heut treatment of textile fibrcs, wire, rubber,
-Coating of
glass. metal
pharmaceutical
components
tablets -Granulation eMixing 01'
Gas/solid reactions
·Constant temperature baths
solids -Dust filtration
Oil cracking, reforming
-Caal gasification eRoasting of nickel
Manufacture of:
and zinc sulphides
eAcrylonitrile
elncineration of
'Phthalic
liquid and solid waste
anhydride
·Production of
'Polyethylene
titanium terachJoride
'Chlorinated
·Catalyst regeneration
hydrocarbons
·Decomposition 01' l imestone ·Production uf UFo' AlF, ·Production of UO:!, uo,
beds are in wide use for agglomeration and also for drying of agglomerates made in other types of equipment. As indicated earlier, most industrial uses are for gas-fluidised beds, although liquid-fluidised beds are also found, particularly in biochemical engineering separation processes. The remainder of this chapter refers to beds which are fluidised by gas,
1 .2. Pressu re d rop through packed beds
When a fluid passes through a fixed bed of solid partie/es, a pressure drop results, It is best to describe this in terms of the manometrie pressure drop: the manometrie pressure difference between two points is the total pressure differ ence minus the hydrostatic pressure difference arising when a stagnant fluid is present between the two pOints, 1 1 In other words, the manometrie pressure differenee is the pressure differenee whieh results solely from the motion of the fluid. The distinetion between total and manometrie pressure differenee is only of praetieal importanee if the density of the fluid is signifieant, Le, in liquid-fluidised beds but not usually in gas-fluidised beds,
1 044
J. Seville
The most popular result used to estimate pressure drop in paeked beds is that due to Ergun [2f (1 ) where I1P is the manometrie pressure differenee between two points in the bed, a distanee H apart in the direetion of flow and U the superfieial fluid veloeity (the total fluid flow rate divided by the eross-seetional area of the bed). The void fraction in the bed is denoted by 8. This includes interstitial voids (i.e. voids between the particles) but not interparticle voids (i.e. voids within the particles). A typieal value of 8 for closely sized particles of near-spherieal shape at the point of minimum fluidisation might be in the range 0.40-0.45; dp is the particle diameter. Note that the form of equation ( 1 ) indieates that in general the fixed bed pressure drop rises non-linearly with inereasing gas veloeity. (Figure 1 shows a linear inerease, whieh is the ease only for fine particles - see below.) Fluid flow is often deseribed in terms of dimensionless groups, the most eom mon of whieh is the Reynolds number, pUd/ll, where p is the fluid density and 11 its viseosity. The value of the Reynolds number provides a simple indieation of whether flow behaviour is dominated by fluid viseosity or density - that is by viseous or inertial effeets. In the eontext of fluidised beds, the form of the Reynolds number to be used is the particle Reynolds number, Rep or pUdp/ll, where dp is the particle diameter. The first term on the right of equation ( 1 ) dominates in ereeping flow, i.e. when the particle Reynolds number, Rep, is small so that drag is dominated by fluid viseosity and not affeeted by its density; thus I1Poc U. The seeond term dominates at relatively high Rep, i.e. when drag is dominated by the inertia of the fluid and is therefore affeeted by p but not 11 ; thus, at high Rep, I1Poc U2 . 1 .3. Minimum fluidisation velocity
When a fluid passes upwards through a paeked bed, the manometrie pres sure gradient inereases as U inereases. When the pressure drop is just sufficient to support the immersed weight of the particles, then the partieles are sup ported by the fluid and not by resting on neighbouring particles. Therefore, at this point, the particles beeome free to move around in the fluid, and are said 2 At low Reynolds numbers, the second term in the Ergun equation disappears and the equation then becomes virtually the same as the well-known "Carman-Kozeny equation". The simple result that the pressure gradient is proportional to the flow rate (which is only true at low Reynolds numbers) is generally credited to Darcy ( 1 846). For a more extensive explanation ofthe basics of particies in fluids, see Seville et al. [3], Chapters 2 and 6.
1 045
Fluidisation of Cohesive Particles
to be "fluidised" (see Fig. 1 ). ApjH = ( 1 - Gmf)(Pp - p)g
(2)
where the subscript "mf" is used to denote minimum fluidisation conditions. Using equation (1 ) to evaluate APjH leads to an equation for the minimum fluidisation velocity, Umf, which rearranges to - p)g _ 1 50(1 - Gmf) pd 1 .75 p2 cP p cF (pp 0---'-; -Umf + -3- - 2- u2mf 3 Gmf G mf fl 112 fl -
(3)
Each individual term in equation (3) is dimensionless. It is therefore convenient to rewrite it in terms of a dimensionless diameter, d*, and the particle Reynolds number at minimum fluidisation, Remf (4) In these terms, and combining the numerical constants with the voidage terms as suggested by Wen and Yu [4] , equation (3) becomes (d*)3 = 1 650 Remf + 24.5 Re�f
(5)
which is widely used for estimation of minimum fluidisation velocities. For low d*, such that the viscous term in equation (5) dominates (6) For high d* , where the inertial term dominates
[
]
_ d(Pp _ P)g
Umf -
24.5p
1 /2
(7)
The different dependencies on particle size and fluid praperties should be noted. Figure 2 shows some numerical values, calculated fram equation (5), to illustrate these effects. In the context of batch-type fluidised-bed agglomeration, where the particle size may increase fram < 1 00 to �1 000 Ilm, the implication is clear: the operating velocity must remain weil above Umf at all times. However, too high an operating velocity at the start of the process may cause excessive elutriation. The form of the pressure drop curve with increasing gas velocity is affected by size distribution, pre-preparation of the powder bed and other factors, as in dicated in Fig. 3.
1 046
J. Seville
Umf
m/s 0.1
0.01
1 00 d 1 m 1 000 c 1 Fig. 2. Superficial gas velocity of air at minimum fluidisation, for spherical particles of density 2500 kgjm3 [ 1 ] , continuous line 25°C and 1 bar, - - - line 1 00o-C and 1 bar, chainline 1 000°C and 1 0 bar.
Pressure difference across bed, �P
'Overshoot' due to fluidisation in a narrow tube or of a compacted bed ,�
- - - - �J/- �X� ; " � \
....
Narrow range, weIl mixed bed
-
I ;I � I "', Ir'" Same mean
" I I /
I /
t. '/
size, increasing spread
: Umf I
Fixed bed
Fig. 3. Varieties of pressure drop i ncrease as a function of gas velocity (after [1 ]).
1 .4. Particle and flu id properties
As regards fluidisation behaviour, the most important particle properties are den sity, size, and size distribution. The density of interest is the true solids density, Pp, for whieh a range of pyenometers is available. For beds eontaining a range of sizes, the question arises of whieh mean dia meter to use to eharaeterise the partieles. For purposes of eomparison between different materials, the appropriate diameter to use is the surface- vo/urne rnean,
1 047
Fluidisation of Cohesive Particles
also known as the "Sauter mean" or the weight-harmonic mean: (8)
where the particles contain a mass fraction f; in size range i, the mean particle size in this range being di . If the size analysis is carried out by sieving with the usual logarithmic progression of sieve sizes, the di should be taken as the geo metrie mean of the sieve opening which retains cut i and the next larger sieve. The significance of dsv is that it gives the particle size whose surface area per unit mass or per unit solids volume is the average value for the whole particulate. It is therefore the best single measure of particle size for processes controlled by the interfacial area between gas and solids; this includes mass transfer proc esses and, to a first approximation, fluidjparticle drag at low particle Reynolds numbers. The relevant properties of the gas in a fluidised bed are its density p and viscosity f.1 . For virtually all practical purposes, the density of a gas or gas mixture can be estimated from the ideal gas laws; it is proportional to absolute pressure and inversely proportional to absolute temperature. To a good first approximation, the viscosity of a gas or gas mixture is independent of pressure but increases with increasing temperature: the variation is as T1 j2 according to elementary kinetic theory, and is usually somewhat stronger in practice. The effects of temperature and pressure on gas properties explain most of the effects of T and P on the behaviour of fluidised beds in Geldart's groups B and D (see Section 2. 1 ). How ever, as shown later, the behaviour of finer particles is influenced by cohesive interparticle forces; in their case, therefore, the effects of temperature and pres sure cannot be predicted solely in simple hydrodynamic terms. -
1 .5. Slugging
If the bed diameter is relatively small and the bubbles grow sufficiently to fill the column, then the bed will be in eontinuous slug f1ow, as shown schematically in Fig. 4. Bubbles formed at the distributor grow by coalescence until they form slugs. In this flow regime, which is usually regarded as undesirable, the bed surface fluctuates widely, collapsing sharply with each slug eruption. A bed will show slug flow if (a) the bubble diameter exceeds about 60% of the column diameter; (b) the gas velocity is high enough; (c) the bed is sufficiently deep.
1 048
J . Seville
A ..... -�..,...,,,.J- _ , A I I I I I I I
I
I I I I I I I B
L_
I I I I I I I
tt t
_ -1 8
Fig. 4. Bubble and slug growth [ 1 ] .
Condition (a) depends on the gas and particle properties. Conditions (b) and (c) are combined in a criterion developed by Baeyens and Geldart [5], which gives the minimum superficial velocity for slugging as Umsl = Umf + 0. 1 6(1 . 340°· 1 75 Hmf)2 + 0.07(gO)0.5 (9) -
where Hmf is the bed depth at minimum fluidisation. The second term on the right, which allows for the fact that the bed must be sufficiently deep for slugs to develop, is omitted if Hmf > 1 .340°. 1 75 , and equation (9) then becomes identical to a result derived for deep beds by Stewart [6]. 1 .6. Distributor design
Many types of gas distributor are in common use, including woven or sintered polymers and metals, simple drilled plates and complex directional pressings. Considerations which apply when designing a distributor include: •
•
•
•
pressure drop (must be above a certain minimum value necessary to fluidise the bed uniformly, but not so great as to give rise to excessive gas compression costs); the height of the region of high gas and particle velocities adjacent to the distributor (this region is associated with both attrition and erosion of in-bed surfaces); mechanical strength (which must be sufficient to support the bed weight when the bed is not fluidised); orifice size (which must be small enough to prevent the particles running back into the wind-box).
1 049
Fluidisation of Cohesive Particles
The fractional free-area of a multi-orifice distributor is given by F = najA (1 0) where n is the total number of orifices, a the area of each orifice and A the total area of the distributor. The pressure drop across the multi-orifice distributor is then f...PD = p 2 d.d F2
U2
(1 1 )
where Cd is the orifice discharge coefficient. (This derivation, and other aspects of distributor design are considered in detail by Geldart and Baeyens [7].) Qureshi and Creasy [8] concluded, from a review of published data, that the minimum distributor pressure drop required for satisfactory operation is
�lJ.PpDs = 0.01
+
0.2[1
-
exp( - 0j2H)]
(1 2)
where f...po is the pressure drop across the bed. Thus, the minimum distributor pressure drop depends on the aspect ratio, the ratio of bed diameter, 0, to bed height, H. For large beds, f...P o/f...Ps must be at least 0.2 and up to 0.3 is rec ommended if the bed is "sticky". This is an aspect which is insufficiently con sidered in some fluidised-bed agglomerators, which tend to suffer from gas maldistribution because the particles are cohesive. 1 .7. Bubbling and solids circulation
Solids motion in fluidised beds is strongly associated with bubble flow, since the bubbles transport solids in their wakes and drifts (Fig. 5). The bubble flow rate in a fluidised bed, Ob, is defined as the rate at which bubble volume crosses any level in the bed. A first estimate for Ob is given by the "two-phase theory of fluidisation" [1 ], which conceives the bed as consisting of two "phases": (a) a dense "phase" in which the gas flow rate is equal to the flow rate at incipient f1uidisation, i.e. the 0.3 r------, 0.25 0.2
Wake
0. 1 5 0.1 0.05
0.05
0.1
0. 1 5
Fig. 5. Bubble wake and drift; particle motion driven by rising bubbles. Left - schematic;
right - discrete element simulation.
1 050
J. Seville
voidage is constant at the minimum fluidisation value and (b) a bubble "phase" that carries the additional flow of fluidising gas. The bubble flow rate is then estimated as (1 3) where U is the superficial fluidising velocity and Umf the value at minimum flu idisation. In words, the simple two-phase theory can be stated as: "the excess gas flow above that which is necessary for minimum fluidisation passes through the bed in the form of bubbles". Many features of fluidisation, notably the partieIe circulation time and the mixing rate, depend on the "excess gas velocity", U - Umf. When a bed of partieIes is fluidised at a gas velocity above the minimum bubbling point, bubbles form continuously and rise through the bed, which is said to be "freely bubbling". Bubbles coalesce as they rise, so that the average bubble size increases with distance above the distributor (see, for example [9]) until the bubbles approach the maximum stable size. Thereafter, splitting and re-coalescence cause the average bubble size to equilibrate at a value elose to the maximum stable value. For large particles ( ;G 1 mm), the maximum stable bubble size may be many metres, so that bubbles can grow to occupy the entire bed cross-section. For partieIes of 20-1 00 11m, however, the maximum stable size at ambient conditions is in the range 1-20 cm, so that bubbles in beds of sub-1 00 11m particles are typically constant in size over much of the bed height. Bubble coalescence can also have an influence on circulation of the dense phase. The effect is shown schematically in Fig. 6(a). Bubbles usually coalesce by overtaking a bubble in front (Fig. 6(b)(i)) and may move sideways into the track of a leading bubble (Fig. 6(b)(ii)). Thus coalescence can cause lateral motion of bubbles. Bubbles near a bed wall can only move inwards, while bubbles weil away from the walls are equally likely to move in any horizontal direction. As a result of this preferential migration of bubbles away from the wall, an "active" zone of enhanced bubble flow rate forms at a small distance from the wall. In this zone, coalescence is more frequent so that the bubbles become larger than at other positions on the same horizontal plane. Because the region between the "active" zone and the wall is depleted of bubbles, coalescence continues to cause preferential migration towards the bed axis. Eventually, if the bed is deep enough, the "active" zone comes together to form a "bubble track" along which the lean phase rises as a stream of large bubbles. On the other hand, if the bed is wide and shallow, it may divide into several mixing "cells", with relatively little exchange between them (Fig. 7). Because of the transport of partieIes by the bubbles, the solids tend to move up in regions of high-bubble activity and down elsewhere. In the upper levels, the motion is up near the bubble tracks and down near the walls. At lower levels, the partieIe motion is down near the axis and outwards across the distributor; this motion can in turn enhance bubble activity near the walls elose to the distributor.
1 05 1
Fluidisalion of Cohesive Particles
( a ) Overall bubbl ing pattern circulation Sol ids
_ .
-.- . _
A
1 f f t t
(b) ( i )
0
6
( ii )
0
o
Fig. 6. (a) Bubble and solids flow patterns (b) bubble coalescence modes in fluidised beds
[1].
All of the comments above apply regardless of the shape of the bed. In many agglomeration applications, the bed walls are conical for at least some of the bed height This serves to enhance the concentration of bubble flow towards the centre of the bed, and therefore to increase the overall solids circulation, up in the centre and down at the walls.
2. TYPES OF FLUI DISATIO N
As the fluid flow upwards through a settled bed of particles is increased, the pressure drop across the bed also increases, but a simple force balance shows that it is not possible for this pressure drop to exceed the buoyant weight of the
1 052
J. Seville 35
35
30
30
25
25
20
20
15
15
10
10
/�__ 'I ?�
1W:\�IJJ�� ____ \
5
o , 0
5
,
10
15
5
5
10
15
Fig. 7. So lids circulation i n beds of different heights (DEM simulation).
particles. At higher fluid velocities, therefore, either the bed voidage must increase so as to maintain the pressure drop at or below this level, or not all the fluid can flow interstitially. The following types of behaviour are now possible (see Fig. 8): • •
• •
•
bubbling and slugging; uniform expansion, which is found over a certain range of gas flows for "group A" particles (see below); jetting (where gas jets from the distributor penetrate significantly into the bed); spouting (where the gas is deliberately added over a limited central area of the distributor and a lean "spout" penetrates the entire bed height to the free board [ 1 0]); channelling ("rat-holing").
All of these types of behaviour, with the exceptions of spouting and channel ling, can be described as fluidisation, because both the bed and the individual particles within it are wholly supported by the pressure drop. Spouting and chan nelling cannot, because, in general, the pressure drop during these types of behaviour is less than that required to support the bed. There have been several attempts to devise theoretical and empirical classi fications of these behavioural types. Of these, the most widely used is the empirical
1 053
Fluidisation of Cohesive Particles A
8
0
0
D 0
Cl C
° D O 0 " •
0
. _ _
0 . .. • •
'!_ _ '!.
u
Bvbbltng
0
D
0°
p C:>
u
SllI9ging
(
o
c::I
� ""
u
u
u
Ä##ing
Fig. 8. Types of fluidisation [ 1 ] .
c1assification of Geldart [1 1 ], who divides fluidisation behaviour according to mean particle size and density difference between the solids and the fluidising gas (Fig. 9). Geldart recognises four behavioural groups, designated A, B, C and D. Typical fluidisation behaviour of groups A-C is illustrated in Fig. 1 0. Group B particles fluidise easily, with bubbles forming at or only slightly above the minimum fluidisation velocity. Group C particles are cohesive and tend to lift as a plug or channel badly; conventional fluidisation is usually difficult or impossible to achieve. Group A particles are intermediate in particle size and in behaviour between groups B and C, and are distinguished from group B by the fact that appreciable (apparently homogeneous) bed expansion occurs above the minimum fluidisation velocity but before bubbling is observed. There is now much experimental evi dence (see Section 3) that group A particles are also intermediate in cohesive ness between groups B and C, their interparticle cohesive forces being of the same order as the single particle weight. Group 0 particles are those that are "Iarge" andjor abnormally dense. Such particles show a tendency to "spout", rather than fluidise. Other properties of the groups are summarised in Table 2 and are discussed further below. It should be emphasised that the Geldart diagram (Fig. 9) is applicable only to particles fluidised by air under ambient conditions, and in the
1 054
J. Seville 7 6 5 4
r-..
3
"'e u
2
Q.Q.
Aerotoble
/ I
......
.!? � .
A
J
I
i\
ß
0.5 f- C
Cohesive
/
i
I
1\ \
B 1\
f\
Sond - like
�
"
iJ utoble
0
\
1\ � \
"'
I IJ
"1\
� \
",
20
100
50
5
\
\
1,000
Fig. 9. Geldart diagram for classifying powders according to their fluidisation behaviour in air at ambient conditions [1 1 ].
6P
AP
H
H
�A .
uf
AP
H
1-----:,
: �u�t..!.t«;. _
.... I ....
u
f
BEHAVIOUR ERRA Tl C AND IRREPRODU5,l8lE
I , EXPANDING I I
u
u
Fig. 1 0. Typical f1uidisation behaviour in Geldart's groups B, A and C (from left to right). Note that the scales are different for each group [24].
1 055
Fluidisation of Cohesive Particles
Table 2. Charaeteristie features of Geldart's ( 1 973) classifieation of fluidisation behaviour
(after Geldart [1]).
Typieal examples
Flour, eement
Craeking eatalyst
Building sand, table salt
Crushed limestone, eoffee beans
Bed expansion
Low when bed ehannels; ean be high when fluidised Can be very slow Channels
H ig h
Moderate
Low
Siow
Fast
Fast
Splitting and eoaleseenee predominate Maximum size Large wake H igh H ig h Axi-symmetrie; breakdown to turbulent fluidisation Shallow beds only
No limit on size
No known upper size Small wake
Moderate Moderate Asymmetrie
Low Low Horizontal voids Solid Slugs Wall Slugs Yes, even in deep beds
De-aeration rate Bubble properties
Solids mixing Gas baek-mixing Slug properties
Very low Very low Solid slugs
Spouting
No, exeept in very shallow beds
Shallow beds only
absence of artificially enhanced cohesive interparticle forces, due to the presence of liquid layers on the particles, for example. A more recent c1assification due to Grace [12] is shown in Fig. 1 1 . This uses the dimensionless particle diameter introduced in equation (4) and dimensionless gas velocity, U* , where U* _
U -
[_p'-2_--- p ] )g I1(Pp
1 /3
(14)
-
Figure 1 1 also shows the various processing options which might be con sidered for particles of various sizes and gases of different properties. Grace's classification successfully accounts for the effects of variation in gas properties due to operation at elevated temperature and pressure but there is, as yet, no satisfactory c1assification that also takes into account interparticle forces, which in many practical situations may be of considerable importance.
1 056
J. Seville Group C powder
I I i i
j 1( / /
,
bed I �\Spouted .
,'
i.
Movlng
bed
I
Fixed bed
10
{
}1I3
Dimensionless porticle diameter 2 113 1/3 (3,44 � Re I :Ar : d g ( pp -PQII/
Fig. 1 1 . Regime/processing-mode diagram for grouping systems according to type of powder and u pward gas velocity used [12].
2.1 . General description of g roup behaviour 2. 1. 1. Group B
Many commonly encountered experimental particles lie in group B, which, for a particle density of about 3000 kgjm 3 , encompasses the particle size range from about 75 to 600 11m. In group B, as mentioned above, bubbles form at about the minimum fluidisation velocity. Bed expansion is smalI, and the bed col lapses rapidly when the gas supply is cut off. Bubble rise velocity depends on bubble size, but most bubbles travel faster than the interstitial gas velocity, Umt/8mf, so that gas tends to circulate within the bubble, except during coales cence and splitting. There is no evidence of a maximum bubble size (so that bubbles will continue to grow by coalescence until their size is limited by the size of the apparatus) .
1 057
Fluidisation of Cohesive Particles
2. 1 . 2. Group A
As mentioned earlier, group A particles are those which exhibit a region of non bubbling expansion for gas velocities above the minimum fluidisation velocity. (In earlier literature, non-bubbling expansion is known as "particulate" fluidisation, by contrast with "aggregative" bubbling fluidisation.) Geldart [1 1 ] defines a minimum bubbling velocity, Umb , and designates group A particles as those for which Umb/ Umf > 1 . The non-bubbling expansion of a group A bed can be characterised in terms of the Richardson and Zaki [1 3] equation. U - = cn Ut
( 1 5)
where UI is the particle terminal velocity in an infinite medium and n a function of the particle Reynolds number at the terminal velocity, normally taking values between 2.4 and 4.65. As the superficial gas velocity exceeds the minimum bubbling velocity, the pas sage of bubbles breaks up the expanded structure, causing a decrease in bed height (Fig. 1 0) as the dense phase voidage is reduced to somewhere between C mf and C mb ' When the gas supply is suddenly cut off, the bed initially collapses rapidly as the bubbles leave and then continues much more slowly, at a rate which is similar to the superficial velocity of the gas in the dense phase. This property of slow deaeration is responsible for the ease with which fluidised group A solids are maintained in a fluidised state, but is also responsible for their tendency to "flood" on discharge from hoppers [14]. In bubbling group A beds, all bubbles travel faster than the interstitial gas, but a tendency towards bubble splitting limits the size to which they can grow by coalescence. Circulation and mixing are rapid, bed-to-surface heat transfer is favourable, and gas exchange between the bubbles and the dense phase is high due to frequent splitting and coalescence. All of these factors, together with a larger solid surface area per bed volume than for groups B and D, favours the use of group A particles in many applications. 2. 1 . 3. Group C
Group C powders will readily form stable channels from the distributor to the surface, and may aiso litt as a cohesive plug, particularly if the apparatus is small. The pressure drop across the bed usually remains below the bed weight per unit area, and mixing and heat transfer are poor. Fluidisation can sometimes be made possible by increasing the gas velocity to break up the cohesive struc ture, or by mechanical stirring or vibration. Fluidisation can also sometimes be promoted by adding a small proportion of fumed silica or some other sub-micron powder; these reduce the interparticle forces by modifying the contact geometry.
1 058
J. Seville
2. 1.4. Group D
The distinction between groups B and D concerns the rise velocity of the bubbles, which is, in general, less than the interstitial gas velocity in group D beds, so that gas flows into the base of the bubble and out of the top. Because of the size and density of the particles, the permeability of the bed is high, so that the minimum fluidi sation velocity is also high. Gas and solids mixing is low, but cohesive solids can be fluidised because the greater momentum of the particles on impact and fewer particle-particle contacts per unit area reduce the tendency towards agglomeration. Introduction of a liquid spray may then lead to coating rather than agglomeration. If gas is introduced over a small part of the distributor, group D particles can be made to spout [1 0] . In practice, it is often advantageous to exploit this tendency and to use a spouted bed rather than a fluidised bed when processing or handling them.
3. INTERPARTICLE FORC ES
By definition, a state of fluidisation exists when the force of gravity on a set of particles is balanced by the drag arising from the flow of the fluidising gas. It folIows, therefore, that small interparticle forces, which may not be noticeable in other circumstances, may have observable consequences at the point of fluid isation and beyond. Interparticle forces can occur due to a variety of causes; those of interest here are van der Waals interactions, liquid bridges and sintering. 3.1 . Van der Waals forces
"Van der Waals forces" is a collective term taken to include the dipole/dipole, dipole/non-polar and non-polar/non-polar ("dispersion") forces arising between molecules [1 5]. Though other intermolecular forces can occur, such as hydrogen bonding, these are related to the specific chemical nature of the materials; van der Waals forces always exist. Although intermolecular forces decay with mo lecular separation, a, as a-7 , when the pair potentials are integrated between macroscopic bodies, such as spherical particles, the resulting force is much less sensitive to separation, decaying as a-2 in the case of sphere-sphere interaction.
AR Fvw = 1 2 a 2
( 1 6)
where R is the sphere radius, A the Hamaker (materials-related) constant and a the surface separation, which takes a minimum value of the order of the inter-molecular spacing. Suitable values for the variables give the lines plotted in Fig. 1 2. It will be apparent that intermolecular forces depend more on the particle
1 059
Fluidisation of Cohesive Particles
1 0-5
g GI () ... 0 u.. GI
1 0-6
U 1:
111 Q. ... GI
�
Force - ----ra:�:e�:��::e Capillary
(Max)
------------
--
a l
1 0-8
--------
a=4_ A
---0 ---10
----100
1 000
Particle Diameter (11m)
Fig. 1 2. Comparison of the magnitude of sphere-to-sphere cohesive forces (dashed lines indicate asperity-to-plane contact) _ Quartz/water system [30].
surface properties than on the bulk, so that it may be more plausible to assume (or measure) a surface roughness and use this to determine the curvature. The van der Waals force then depends on this local curvature and is independent of R. This result is also plotted in Fig. 1 2, and suggests, for the set of variables chosen here, that spherical particles of diameter of order 1 00 �m should exhibit interparticle van der Waals force to equal their single particle weight. If the gross particle radius is taken as the controlling factor, as in equation ( 1 6), the corre sponding diameter is 1 mm, which is less plausible. Particles of 1 00 �m are commonly found adhering to surfaces and resisting the force of gravity; 1 mm particles are not! 3.2. Liquid bridges
Liquid bridges are more interesting than van der Waals forces from a practical point-of-view, since their magnitude can be adjusted by altering the amount of
1 060
J. Seville
free liquid and its properties, particularly surface tension and viscosity. They are of practical importance in agglomeration processes, driers, and in some types of reactors and bioreactors. They are also more complex than van der Waals forces in that they exhibit both dynamic and static forces and are dissipative of energy. Their behaviour is considered in detail in Chapter 28; only a brief summary will be given here. The static liquid bridge force arises from the sum of the surface tension force and the force arising from the pressure deficit in the liquid bridge [3] (Fig. 1 3).
!:lP
(17) where is the reduction in pressure within the bridge with respect to the sur rounding pressure and y the surface tension. The magnitude of this force is difficult to compute exactiy, even for spheres, because the bridge forms a gas-liquid interface of constant curvature in order to satisfy the Laplace equation.
!:lP = Y [�r1 - �r2]
(1 8)
This results in a bridge shape (Fig. 1 3(a)) in which r1 is a variable for a given bridge volume, so that r2 must also be a variable. However, the toroidal approximation (2 ), in which r1 is taken as constant, enables a simple and rea sonably accurate result to be obtained. At contact, the maximum static liquid bridge force is ( 1 9) F[s,max = 2nRy which is plotted in Fig. 1 2 and again compared with the force which would arise if the contact were dominated by surface asperities of dimensions independent of gross particle diameter. For water, the static liquid bridge force is rather larger than the maximum van der Waals force. It is generally assumed that the static (or low-relative velocity) liquid bridge force is conservative, but Willett et al. [1 6] have shown, both experimentally and theoretically, that this is not the case. If the contact angle is non-zero and the surface is "rough", both of which are often true, the contact line may be "pinned"
Fig. 1 3. (a) Liquid bridge between two spheres, (b) sinter bridge between two spheres.
1 06 1
Fluidisation of Cohesive Particles
and the force/separation curves on approach and departure follow different paths, leading to hysteresis and energy dissipation. The liquid bridge also dissipates energy by viscous flow, away from the contact area on approach and vice versa. The viscous force always opposes relative movement, unlike the surface tension force. During separation, the reduction in pressure around the point of e/osest approach may easily lead to cavitation in the liquid [1 7]. The force is given, to a first approximation, by Reynolds' lubrication equation [1 8, 1 9]. (20) where v is the separation velocity, J1 the viscosity and a the separation distance. This equation implies a singularity at contact; in practice, the surfaces are rough , so that there exists a non-zero minimum separation, ao, and/or they deform. In practice, therefore, the interpartie/e force due to the viscous contribution (equa tion (20)) will exceed the static force at higher relative velocities. For the partie/es of interest for fluidisation, this velocity is in the approximate range 1 cm/s to 1 m/s [3]. To a first approximation it is permissible to superimpose the static and the dynamic forces, since the former depends mainly on the shape of the gas-liquid interface while the laUer depends mainly on fluid motion near the point of e/osest approach. A third energy dissipation mechanism is the stretching and eventual rupture of the bridge; in a wet-fluidised bed, bridges can be imagined to be continually rupturing and reforming. The energy thus dissipated depends on the rupture distance, which takes the very simple form [20]. 13 a a x = (0.5 + 0.25 > Vp). From a numerical point of view however it is sometimes desirable to use small computational cells in order to resolve all relevant details of the gas flow field and to obtain a grid-independent solution. Unfortunately, the method by Hoomans et al. [6] generates problems once Vcell approaches Vp . That is, computational cells can be fully occupied by a particle, which leads to numerical problems. In order to overcome these problems, we suggest a new method to calculate the porosity. In this revised method the particles are represented as porous cubes. The diameter of the cube depends on the particle diameter and a constant factor a, which defines the ratio between the cube and particle diameter and consequently the volume, where interaction between the fluid and the particle under consideration occurs: (22) dcube = adp The volume of the cube should be larger than or equal to the volume of the particle, resulting in 1 /3 (23) a � 6" � 0.8
(n)
The porosity of a porous cube representing a particle can now easily be calculated as ccube
=
\I, = 6n3
Vp cube
a
(24)
Finally, the porous cube representation can be used to calculate the gas fraction in a computational cell in a manner analogous to equation (21 ): (25) cg,cell = 1 - ccube L f;ell 'tiEcel!
where f;ell is the volume fraction of the cell under consideration that is occupied by cube i. Contrary to the real particles, the cubes representing the particles are allowed to overlap. By representing the particle as a porous cube, its presence is feit only relatively weakly in a larger portion of the flow domain. Consequently, grid refinement will
Multi-Level Computational Fluid Dynamics Models
1 079
not lead to local extremes in the gas-fraction around the centre of mass of the particle. The force balance for a single particle, wh ich is used in our model to calculate the acceleration of the particle, is given by equation ( 1 ). Most of the variables in this equation are only available at distinct positions in space (i.e. the Eulerian grid). The acceleration of the particle should however be available on the Lagrangian position of the particle. In order to calculate the acceleration of the particle, these variables need to be mapped to the position of the particle. In order to satisfy Newton's third law, a consistent mapping technique should be used for the calculation of the momentum exchange coefficient ß. Hoomans et al. [6] used a volume-weighing technique for the mapping. Unfortunately, this technique yields a porosity that depends on the numerical grid size. Since the momentum exchange coefficient is non-linear with respect to porosity, the overall calculated momentum exchange is also grid-dependent. Furthermore, numerical problems should be prevented, by circumventing that the local porosity becomes close to zero in case the size of the computational cells approaches the volume of the particles. For a proper treatment of the drag force, the control volume used in the calculations should match the control volume for which the drag relation was derived. Generally, the control volume will be much larger than the particle size (i.e. a = 3-5). For the calculation of the acceleration of the particle, we suggest a method similar to the one presented for porosity mapping. A general variable
0.8. Minimum model: the minimum of the relations by Wen and Yu [1 8], and Ergun [1 7] is used. Koch and Hili model: equation (4) is used.
Table 2. Physical properties and numerical settings for the granulation simulation
Parameter
Symbol
Gase 1
Gase 2
Gase 3
Unit
I nitial particle diameter Particle density Number of particles Droplet diameter Droplet density Droplet flow rate Gas density Gas viscosity Background gas velocity Gas velocity in the spout Number of celis in the X-direction Number of cells in the Y-direction Number of celis in the Z-direction Time step particles Time step droplets Time step gas
dp Pp Np dd Pd Fd Pg f.i.g Ubg Ujet NX NY NZ
4.0 2526 44,800 n.a. n.a. n.a. 1 .2 1 x 1 0�3 1 .5 30 15 1 200 1 x 1 0�4 n.a. 1 X 1 0�4
4.0 2526 44,800 n.a. n.a. n.a. 1 .2 1 x 1 0�3 3.0 20 15 1 200 1 x 1 0�4 n.a. 1 x 1 0�4
3.0 ± 0.2 2526 39,667 200 2526 2.2 x 1 0�6 1 .2 1 X 1 0�3 3.5 40 30 1 240 1 X 1 0�4 1 .6 x 1 0�5 1 X 1 0�4
mm kg/m3
Li tp Li td Li tg
pm kgjm 3 m /s kg/m 3 kg/(m s) m/s m/s
s s S
1 082
M . van Si nt Annaland et al.
/
/
2000
.�
/
x
/
.�
YL 70 10 70 x
Fig. 3. Schematic representation of the geometry of the pseudo-2D bed, dimensions are given in millimeters.
3� r-----, - Exp.
3500
,-----------
3000
Cii'
�
- Kochand
- mln(Ergun. Wen and Yu)
- Koch 800 Hili
3000
2500
--,
__ __ __ __ __
-ErgurvWen and Vu
- ErgunIWen and Yu
Hili
-mln(Ergun, Wen and Yu)
� 2500
2000 1�
1�
�--�
1� � -1 1 .0
�
__ __ � __ � __
1 1 .2
1 1 .4
1 1 .6
1 1 .8
I [sJ
Case 1 ,
spollt-tlllidization
12.0
----�----�
__ � ____ �
1�� 18.0
18.5
19.0
1 [8J
19.5
20.0
Case 2. jel-in-f1uidized-bed
Fig. 4. Measured and computed pressure drop fluctuations over the entire bed for two different regimes using several drag c1osures.
For spout-fluidization (Gase 1 in Fig. 4) a periodically fluctuating pressure drop is obtained for the model of Koch and Hili, the minimum model and the experiments, while the conventional model displays a less regular pattern. These results are also reflected in the power spectra for Gase 1 , which are presented in Fig. 5. That is to say that, except for the conventional model, a dominant frequency between 5 and 6 Hz is found. The jet-in-fluidized-bed case (Gase 2 in Fig. 4) shows that the differences between the drag models are less pronounced resulting in similar frequency spectra for Gase 2, which are given in Fig. 5. Each of the drag closures predicts a randomly meandering spout, which leads to an irregular pressure drop signal.
1 083
Multi-Level Computational Fluid Dynamics Models 100,000
, ,000, 000,--, -Koch and H ili - Exp.
100.000
_
�
';
""
[
!!:.
1 ,000
c.
- ErgurvWen and Yu
- mln(Ergun, Wen and Yu) - - Koch and Hili
10,000
N� 10,000 "
,::-....,.,.,-,-:-:----,
�
'00
1 ,000
1 00
10
6
9
12
frequency (Hz]
12
15
15
frequency [Hz]
Case I, spout-nuidization
Case 2, jet-in-nuidized-bed
Fig. 5. Measured and computed pressure drop fluctuations over the entire bed for two different regimes using several drag c1osures.
�E
'ä;
900
600 ,------,
600
400
e
=:
-600
-900 0.00
,�
., ,
=��(g;�� X'edn��d Yu) , •
200
=;; -200
0
� -300
�
Ni
300
Exp.
0
•
' -400
- -Koch and Hili
0.05
x [m]
0.10
Case I, spoul-fluidization
0.15
Exp.
- ErgunIWen and Yu - min(Ergun, Wen and Yu) - - Koch and Hili
-800 .J..:-----� 0.15 0.10 0.05 0.00 x [m] Case2, jet-in-fluidized-bed
Fig. 6. Frequency spectra of the measured and computed pressure drop fluctuations over the entire bed for two different regimes using several drag c1osures.
In Fig. 6, Gase 1 displays a relatively narrow peak in the vertical time-averaged particle flux profile, which is captured rather weil by both the Koch and Hili model and the minimum model. The conventional model however, produces a broader peak. The deviating results obtained from the conventional model can be attributed to the discontinuity in the drag relation at = 0.8. In this case, the relation of Wen and Yu [1 8] is used in the spout region, whereas the relation of Ergun [1 7] is used in the annulus. The system will therefore display behaviour, which resembles the situation with a higher background velocity and a lower spout velocity, and will consequently resemble the results for Gase 2. Figure 6 shows that for Gase 2 all drag models predict similar particle flux profiles. The agreement with the experimental results is very good. The conventional drag model is less suitable for modelling fluid beds with stable high-velocity jets, as encountered in spout(-fluid) beds. The minimum of the relations of Ergun [1 7], and Wen and Yu [1 8], as weil as the relation proposed by Koch and Hili [3] are more suitable, although the computed frequency of the pressure drop fluctuations is somewhat too high. 39
1 084
M . van Sint Annaland et al.
2.3. Example of a simulation of a g ranulation process
With the use of the DEM the interaction between droplets and particles and the evolution of the particle size distribution as encountered in granulation processes, can be modelIed in a deterministic fashion. Results of a sam pie calculation are discussed in this section. In this example a pseudo-2D flat bed was filled with particles with a size distribution around 3 mm. A schematic representation of the bed can be found in Fig. 3. The particles in the bed are fluidized through background fluidization gas streams, which enter the bed alongside the spout. The droplets are introduced to the bed through the spout. The interaction between the droplets and the gas phase is handled through one-way coupling. That is to say that the droplets are assumed to enter the bed at their terminal velocity and thereafter follow the gas stream. The effect of the droplets on the phase fractions and the feedback effects from the droplets to the gas phase are neglected. The properties of all the phases, along with the numerical settings are presented in Table 2. An impression of the particles dynamics can be obtained from Fig. 7, which shows an instantaneous snapshot of the particle velocity field along with the particle positions and their sizes. The air originating from the spout moves through the bed in a meandering fashion. It can be seen that particles are entrained in the spout stream from both si des of the bed. Most particles move down along the side walls and return to the spout region. When the particles enter the spout stream, they impact with droplets and grow accordingly. Figure 7c shows that most particle-droplet collisions take place in a very small region just above the spout mouth. It is stressed that the DEM can be used to deduce growth kerneis for the particle phase or alternatively sink terms for droplet transport equations, which can be used in higher level models, such as the multi-fluid model (MFM) or the discrete bubble model. In order to investigate the particle growth rate as a function of the particle size, the particles were split into four particle size groups. Figure 8 shows the partial density functions of the growth rate of each of the different particle c1asses during a simulation period of four seconds. The particles outside the spout region hardly come in contact with droplets. It is these particles that show a large peak in the partial density function around zero growth. A second peak is observed for each of the particle c1asses around 0.1 5-0.25 mm 3/s. This peak results from the particles that have travelled through the spout region and have been hit by droplets. It is seen that the position of this peak on the x-axis (i.e. the growth rate) scales with the mean surface area of the particles. Furthermore it is observed that the fraction of particles that grows in the spout region is larger for small particles than for large particles. That means that the number of encounters with droplets is relatively larger for small particles as compared to large particles. This can be explained from the fact that small particles that return to the spout region are able
Multi-Level Computational Fluid Dynamics Models
1 085
... 2.0 mI!l
( a)
Fig. 7. Close-ups of the instantaneous particle velocity field (a), instantaneous snapshot of
particle positions and sizes (b), and cumulative density function of the number of deposited droplets for a period of 4 s (c) predicted by the DEM.
to move closer to the bottom plate, due to their smaller size. Consequently, they have a higher probability to be hit by droplets as compared with the larger particles, which are partly blocked by the small particles. 2.4. Conclusions A hard-sphere DEM was developed, which takes into account all relevant
interfacial interactions in a deterministic manner. It was shown that for systems with relatively large particles subject to high velocities as experienced in spout fluid beds the conventional drag model (the equation of Ergun [1 7] when n represents the rate of change of property 4>n due to collisions with particles of species p, which is decomposed in a collisional source Xnp(4)n) and collisional flux 8np(4)n) term:
nnAp4> n = Xnp(4)n) - 8,ßnp(4)n) 8
(44)
(46) The conservation equations for mass, momentum and fluctuating kinetic energy for each species n can be obtained from the Maxwell transport equation by substituting for the particle property 4>n: mn , mncn and �mn� respectively. The mixture conservation equations are obtained by summing over all species n and are listed in Table 3 . The external forces acting on the particles that are relevant for gas-fluidized beds are gravity, buoyancy and drag exerted by the gas phase: 1 ßng Fn (47) 9 - - VPg + -- (cg - cn)
mn
- =
-
nnmn
Pn
-
In the mixture granular temperature equation the correlation between the fluctuating velocities of the gas and particulate phases (CgCn) (turbulence Table 3. Conservation equations
Species continuity equations: Mixture continuity equation: Mixture momentum equations:
ft (önPn) + v pn + 8nPnusl where Jn
önPn(Cn)
ft(ösPs) + V(ösPsus) =
0
ft (ösPsus) + V(ös Psusus)
0
-
-ös VPg - VPs - VTs + L ßng(Ug un) + ösPs9 Np
=
n�1
t (nnmn(Cn Cn) + p�1t Onp(mncn») 1 - (Psi"0 + es= ) .. VUs - Vqs l; 3 ßng On [c(nsos) 2 --;;r- + V(nsOsus)
where psi + Ts Mixture granular temperature equation:
=
=
3
where Cis and Ys
=
Np
-
=
=
(
-
n�1
-
=
_
� � nnmn(�Cn) + n
L L Xnp G mn c;) Np
Np
n�1 p�1
-
-
;E OnpG mn�)) Np
Np
mn
-
,
Ys
1 09 1
Multi-Level Computational Fluid Dynamics Models
modulation) has been neglected, which is allowed when modelling dense fluidized beds. For the evaluation of the transport coefficients defined in Table 3 explicit functions for the individual particle velocity distribution function fn and the pair distribution function fnp(2) are required. 3. 2. 3. Particle velocity distribution function
In order to determine the collisional terms in the balance laws, the pair distribution functions at contact �� (C1 n ' (1 ; C2p' (2 ; t) d(1 d(2 dC1 n dC2p are needed. Following Enskog, assuming binary interactions and 'molecular' chaos, i.e. information on the particle velocity of a certain particle is lost after only a few collisions, the pair distribution function can be approximated by the product of two single-particle velocity distribution functions and the radial distribution function gnp (( - �O"npk, r + �O"npk) that corrects the probability of a collision for the volume occupied by the particles: ( - 1 -. - - 1 - _ - 1 - 1 fnp2) C1 nJ - "2 O"npk, C2pJ + "2 O"npk,. t - gnp r - "2 O"npkJ + "2 O"np k fn
(
(
-
C1 n , r -
; O"npk; t) fp (
C2 , ( + p
)
; O"npk; t)
(
)
(48)
In order to avoid conflicts with irreversible thermodynamics that arise for multi-size particle mixtures when the radial distribution function is evaluated at a specific point on the line joining the midpoints of the two colliding particles at contact, Van Beijeren and Ernst proposed the so-called Revised Enskog Theory (RET) [30]. According to this theory a non-Iocal functional of the particle density field is taken for the radial distribution function, which give rise to gradients of the chemical potential of all species n present in the particle mixture instead of the gradient of the radial distribution function that appears in the standard Enskog theory. The RET was also employed by L6pez de Haro et al. [27] and Jenkins and Mancini [29], whose results have been used to derive detailed expressions for the particle velocity distribution functions for multi-component mixtures of inelastic spheres. The particle velocity distribution function for particles of species n can now be obtained by solving the generalized Boltzmann equation. Here the Chapman -Enskog solution method of successive approximations is applied [26]: fn = f�O ) + f� 1 ) + f�2 ) + . . . (49) where in this work terms up to the second approximation fn( 1 ) have been included. The first approximation to the velocity distribution is the velocity distribution of a non-dissipative system at equilibrium. The effects of energy dissipation in particle-particle collisions and spatial gradients in the state variables are taken into account in the second approximation by the coefficients of normal restitution
1 092
M. van Sint Annaland et al.
enp and a perturbation function vmax , t) volume of a granule that can exist. 5
=
0, where vmax is the maximum
Population Balance Modelling of Granulation
1 1 19
structure of each granule in the course of a granulation process, PBEs can werk only there, when the error that is made by this assumption is not significant [33].) I nstead , the equation only describes some average behaviour of the underlying mechanisms through the coalescence kernel. The idea is that the details of the local motion and local coalescence rule, which arise from the physics of what is being modelled, are subsumed into the coalescence kernel. The model assumes that the system is diluted so that merging of two particles into one is not influenced by the presence of other particles and they merge without failure as soon as they meet [34]. The multiplication of n(v, t) by n(u, t) approximates the number density of two collided, adhering particles of sizes v and u, instead of introducing an unknown pair density into the PBE. This approximation is known as the mean-field closure hypothesis. Basically, the above closure approximation is tantamount to neglecting any correlations in the pair density, which may arise either due to the slowness of spatial mixing that results in segregation or correlation effects or due to the smallness of populations [35]. A basic assumption of the Smoluchowski equation is that each particle with the same properties and in the same environment behaves in the same manner. When equation (7) is applied, several more assumptions have to be made: • it is a batch process, • the particles in the device are randomly mixed, coalescence occurs by the combination of two particles, • coalescence is the only mechanism acting in size enlargement, • growth or shrinkage along a size axis can be disregarded, • breakage and attrition can be disregarded, and • no nuclei are formed. •
3. 1 . 1 . 3 . The discrete form
The equivalent discrete form of equation (7) is
(8) Although only one single equation is given, the population balance approach makes use of a series of coupled discrete PBEs, one for each size interval, into which the PSD is divided. Fundamentally, the whole PSD is divided into small intervals, and the PBE follows the evolution of the particle growth due to aggregation, allowing the computing at each time of the number of particles existing in each size interval. The size intervals, i, j, 6 are specified as a linear 6 It is common to use the subscripts i and j in discrete notation.
1 1 20
T. Abberger
volume-based progression, such that Vi = iV1 , where V1 is the volume of a single particle of the starting distribution (size class 1 )7 and where Vi+j = Vi + Vj. Equations (7) and (8) are referred to jointly as the Smoluchowski equation [1 1 ] in the literature. 3 . 1 . 1 .4. The stochastic model related to the Smoluchowski equation
The assumption that the modelIed process is a Markovian process is implicit in the PBM [36]. The number density n(v,t) is Iimited in time, its time derivative describes an irreversible process. Equations, which describe linear, irreversible Markovian processes, such as the Smoluchowski equation, have been very successful in the codification of large quantities of experimental data in different systems [37]. 8 The standard stochastic model related to the Smoluchowski equation is a Markov jump process where the two different clusters of size x and y coalesce to a single cluster of size x + y with rate ß(x, y). This model is ca lied Marcus-Lushnikov process [39]. In the Marcus-Lushnikov process, ML(N) (x, f) denotes the (random) number, N, of mass-x particles at time t. A weak law of large numbers, saying that as N 00 (9) N- 1 ML(N) (x, f)-+P n(x, f), x � 1 , t � 0 �
where n(x, t) is the solution of the Smoluchowski equation with n(x, 0) = 1 (x = 1 ) is expected [40]. Aldous [40] described the solution of the Smoluchowski equation as the deterministic limit of the Marcus-Lushnikov process. A deterministic model and solution require that particles are sufficiently numerous to approximate a continuum and that time evolution is continuous. The assumption of sufficiently large particle numbers is necessary in a deterministic model because the fluctuations relative to the mean become unimportant and the mean number of particles of any given size is a suitable state variable. Inherently, a deterministic model disregards the fluctuations of the number of particles of any given size. Issues of stochastic aggregation models are important in systems with low numbers of particles, when not only an average behaviour but the fluctuation about the average behaviour is also of interest and are treated in detail [14,41] or briefly in the literature [23]. The relationship between stochastic particle systems and the Smoluchowski equation was discussed in detail in a review by Aldous [42].
3 . 1 . 1 . 5 . Adaptation of the Smoluchowski equation for the modelling of
granulation
Following the argument of Kapur and Fuerstenau [1 2], regarding the collision frequency in a granulator (see Section 3.2.2), the right-hand side of equation (7) 7 This progression is particularly suited for the modelling of polymerization, where polymers are made up of monomers. 8 Consequently, an attempt to predict the size distribution of an agglomeration process using the Fokker-Planck equation directly has been made [38].
Population Balance Modelling of Granulation
1 1 21
has to be divided by the total number of particles, Ntot , to describe the population balance in a granulating device [43-45]. Sastry and Gaschignard [46] presented a more versatile form, which is in agreement to Ouchiyama and Tanaka's argument [47], regarding the collision frequency in a granulator an(v, t) 1 ß(v, u)n(v, t)n(u, t) du -- at Nrtot 0 1 ß(v - u, u)n(v - u, t)n(u, t) du ( 1 0) 2Wtot 0 where r is the degree of restriction, as defined by Ouchiyama and Tanaka [47]. For r = 1 , this reduces to the PBE as applied by Sastry and Fuerstenau [43], which has been extensively applied in the modelling of granulation. Sastry and Fuerstenau [43] discussed the effect of restriction on granules motion on the agglomeration process. They showed that the degree of restriction has an influence on the rate of the agglomeration process, but does not affect the shape of the PSD.
+
100
lv
3. 1 . 2. The general population balance equation
3 . 1 .2 . 1 . I ntroduction
The Smoluchowski equation was expanded to a general PBE in order to account for more mechanisms, or processes, than coalescence causing an accumulation of particles in a size interval, account for the distribution of more properties other than size alone, be able to deal with particulate processes that do not support the implicit restriction on spatial homogeneity over the entire process volume, and overcome the restriction on a batch process. •
•
•
•
The first general formulation of PBEs in the chemical engineering literature [48] was based on a statistical mechanics equation describing the Markov processes. Ramkrishna [1 4,20] used Reynolds' transport theorem as a starting point, and other authors applied continuum mechanics [1 7]. 3. 1 . 2. 1 . 1 . Development of the microdistributed form. The deterministic PBE of Randolph and Larson [1 7] was derived as a conservation equation for the number of particles in a population. An expanded particle distribution function n( S, t) was defined in an (m + 3)-dimensional space S consisting of the three external or spatial coordinates and m independent so-ca lied internal coordinates, such as size, binder content, composition, porosity, etc. , which are required to completely specify the state of the particle. The total number of particles in a finite subregion, R, of particle state space, S, is N(R) =
j� n(R, t) dR
(1 1 )
T. Abberger
1 1 22
R1,
The population balance in an arbitrarily chosen fixed subregion, of particle state space S is Accumulation Input - Output Net Generation (1 2) The input (output) term accounts for the physical inflow (outflow) of particles to (from) the system as weil as to growth into (out of) that subregion. The net generation is the difference between the birth and death of particles. The birth term represents an increase in the number of particles due to aggregation, nucleation, or breakage of larger particles. Similarly, the death term represents a reduction in the number of particles owing to aggregation to a higher size or breakdown to a lower size. Although birth and death of particles are physically discrete events, they become rate processes when averaged over sufficient volume, which includes the birth or death of many particles. The discrete events, which occur at the particle scale, provide the mechanistic interpretation for the rate events [49]. When no fluxes or growth across the boundaries of this subregion take place, then the time derivative of equation ( 1 2) may be stated as [ 1 7]
=
+
( 1 3) :t JR1r n(R, t) dR = JR1r (B - D) d R where B(R, t) is the birth rate and D(R, t) is the death rate. To account for fluxes
(external coordinates) and growth (interna I coordinates), the former term is expanded
:t�1 n(R, t) d R = �1 �� dR + (n �D I R1 = �1 �� d R + �Jv . (n �D ] d R r [8otn + v . (n ddXt) ] dR (14) JR1 =
x
is the set of external and internal coordinates comprising the phase space Equation ( 1 5) describes the velocity of movement of particles in the phase space
R.
R,
( 1 5) By substituting the extreme right-hand side of equation (14) into equation ( 1 3), the differential micro-distributed population balance was obtained as equation ( 1 6), because the region is arbitrary
R1 �� + v . (nvi) + v . (nVe) - B + D = O
(1 6)
or, in terms of the m + 3 coordinates,
m 0 on 0 0( ) 0 ) ( ) � + ot + ox nvx + oy nvy + o/nvz (OXi)j [n(vi)j] - B + 0 = 0
(1 7)
Population Balance Modelling of Granulation
1 1 23
The partial derivative with respect to time represents the accumulation rate of particles. The population is changed by four separate mechanisms. The divergence term is divided into two because it recognizes that the particle has external and internal coordinates. The partial derivatives with respect to the spatial coordinate axes represent the convective transport term, the physical flow of material. The partial derivatives with respect to the property coordinate axes represent the continuous generation term, this term always includes particle size (e.g. growth of particles along a size axis), but the summation sign recognizes that there may be more than one property of interest. B and 0 constitute the net generation term by birth and death [17]. The microdistributed form is suited for systems that are not weil mixed; the number density of particles is then considered to be a function of time and of the spatial position of the particles; for a mathematical perspective on this issue, see Ref. [50]. 3. 1 . 2. 1 . 2. Development of the macrodistributed form. There are many examples in population balance modelling where the spatial variation may be neglected, and where interest is in studying the global behaviour of the system. With the assumption that neither n, B nor 0 are dependent on the spatial coordinate. A macroscopic version of the PBE, equation (1 8), has been developed by integrating the microdistributed form over the three spatial coordinates [1 7] d(log V) an n = B _ 0 " Qk k nv.I n ( 1 8) at dt � V
+v + .
_
where V is the volume of the device, and k are the input and output streams to the volume V. The macroscopic PBE is the most useful form for practical applications. This equation can be applied to weil-mixed systems, where no spatial dependency of n, B or 0 exist, or averaged values are applied. The general form of the PBE must, in any case, be adapted to suit the particular problem. The PBE for a given problem is composed of those terms that describe the mechanisms of interest, such as coalescence, breakage, growth, attrition, and nucleation or processes, namely fluxes into or out of the device, which are active in this particular problem. The number density of particles is a function of all those particle properties that are considered to be relevant to the problem, and of time. 3 . 1 .2.2. One-dimensional population balance equations
One-dimensional PBEs are a simplified version of the general PBE, because they regard a single internal property, the size, as the independent, distributed property.
1 1 24
T. Abberger
3. 1 . 2. 2. 1 . The general PBE for granulation. The general PBE for modelling granulation processes is [51 ]
on(v, f) Qin . ( o(G(v, f) - A(v, f»)n(v, f) n1n ( v) Qou! nou! v) V ot V ov + Bnuc (v, f) + BcoaI(v, f) - DcoaI (v, f) _
_
_
( 1 9)
The first two terms on the right-hand side represent the flow into and out of a continuous process. Qi n and Qou! are the inlet and outlet flow rates from the granulator. V is the granulator volume. G(v, t) and A(v, t) are the growth or layering and attrition rates, respectively. Bnuc (v, t) is the nucleation rate of new granules of size v owing to the liquid binder addition of the bed. Where necessary, additional terms can also be added to include the appearance and disappearance of granules due to breakage. The general PBE allows the modelling of all rate processes including nucleation or breakage, however, population balance modelling of granulation is usually limited to the granule growth phase. Growth, nucleation and breakage term are not included in many working models of granulation, such as equation ( 1 0). Often the pure aggregation form of the PBE is applied in the modelling of granulation processes. This simplification can be acceptable. The wetting and nucleation phase, including the liquid distribution stage, is both difficult to characterize [52] and to model. In fluid-bed granulation, it is common practice to spray the binder liquid continuously onto the bed. This practice makes it difficult to differentiate adequately between the liquid distribution and granule growth stages of granulation. In comparison to the growth phase, Iittle progress has been made in modelling the nucleation phase and introducing it into a PBE. 3. 1 . 2. 2. 2. The pure growth form. Although a distinction between coalescence and layering is arbitrary, depending on an arbitrarily selected cut-off size, a pure layering form of the PBE is mathematically convenient. For a batch process, the PBE for growth along a size axis (Iayering) only becomes on(l, f) oG(I, f)n(l, f) _ 0 (20) ot + 01 where G(I, t) is the growth rate dljd t. The use of length as particle size is suitable when growth is the dominant mechanism. A PBM for the layering mechanism occurring in the granulation of iron ore fines was proposed by Kapur and Runkana [53]. Abberger and Henck [54] investigated fluid-bed melt granulation of fine lactose and PEG 4000 as meltable binder in an instrumented laboratory scale fluid-bed granulator STREA- 1 . The PEG was added as coarse flakes (d1 ,3 579 J.lM) and molten by the heated inlet air. Motivated by an interest in the quality (hardness
Population Balance Modelling of Granulation
1 1 25
and dissolution behaviour) of tablets compressed from melt granules, we performed experimental series with increasing concentrations of PEG from 9% to 29%. A PBM was applied for simulation of the PSD with an increasing concentration of binder. The model was based on the following assumptions: the mechanism of nucleation is immersion [55], each PEG flake greater than a partition size is a seed for a granule, granule growth occurs by layering of the lactose, PEG flakes which are smaller than the partition size melt and act as binder in the porous layer, the seed melts, molten PEG is sucked by capillary forces into the porous layer, where it acts as binder, the rate of pick up of fine particles is proportional to the surface of the granules, where a constant fraction of the surface is sticky enough to enable layering, thus a layer is formed whose thickness, h, is the same irrespective of the seed size, and coalescence does not occur. •
•
• •
•
•
•
A kinetic constant was obtained by parameter fitting to the sieve analysis data. It allowed to calculate the layer thickness and to estimate the fraction of lactose remaining as fines after the ending of the granulation process. Using the relationship (see Section 3.3.2) n(d, t) = n(d- h(t)), n( d, t) of the granules could be calculated from the seed size distribution. After a transformation of the number distribution into a mass distribution, and taking the calculated fraction of fines and their size distribution into account, the mean size d1 , 3 was calculated and compared to sieve analysis data (Fig. 2). Electron microscopy of sections of granules confirmed the nucleation mechanism to be immersion [56]. In conclusion, the results were found to be in qualitative agreement with the assumptions in the model. 3. 1 . 2. 2. 3. The pure breakage form. The kinetics of breakage is described by two functions, the selection function, S(u), which describes the rate at which particles u are selected to break, and the breakage function, b(u,v), [21 ] . The selection function (or breakage kernei) is the rate constant i n the foliowing expression: D(u)
( rate of breakage Of ) particles of size u
=
S(u) x ne u)
( concentration of ) particles of size u
(21 )
Therefore, S(u) i s a rate constant of a first-order process with the dimension of reciprocal time. To account for non-first-order breakage kinetics, a time dependent breakage kernel S(u,t) was introduced [57,58].
T. Abberger
1 1 26 1 200 1 000 E
2� �
"0
800 600 400
•
•
:+/;/�r=-r=
/ V o
200
.
•
o
•
I
/
15 20 10 mass fraction PEG %
5
25
30
Fig. 2. Simulated (line) and experimental (symbols) mean granule sizes in fluid-bed melt granulation of fine lactose and coarse PEG 4000 flakes [54].
The breakage function is the probability density function for the formation of particles of size v from particles of size u. It describes the number of particles of size v formed once a particle of size u has been broken. By inspecting the values of the breakage function, the breakage mechanism (attrition, fracture into two or more large pieces, and shatter, where an agglomerate is broken down into the primary particles) can be elucidated. To include breakage in the population balance, expressions for the birth and death rates owing to breakage are required. From the definition of the selection function, the death rate is as follows Dbrea(v) = S(v)n(v)
(22)
The birth rate at size v must be the weighted sum of death rates of larger particles that give fragments of size v. The fraction of deaths at u that gives birth at v is b(u,v) Bbrea(v) =
100 b(u, v)S(u)n(u) du
(23)
100 b(v, u)S(u)n(u, f) du - S(v)n(v, f)
(24)
The combination of equations (22) and (23) leads to Bbrea(v, f) - Dbrea(V, f) =
The theory concerning breakage is not as developed as that for aggregation and the expressions for breakage kerneis and breakage distribution functions are usually semi-empirical [59]. A list of breakage distribution functions can be found in [30] and three frequently applied breakage kerneis are described by Vanni [59].
Population Balance Modelling of Granulation
1 1 27
The PBE for breakage in discrete notation is [59] dN.
�I
dt
= '""' 6 M
1.=1+1
S(x1.) b (x1x1 ) N.1 - S(x1·) N.1
(25)
If the shear force in a granulator is low (drum or fluid-bed) and the particles are wet enough, breakage can be assumed as insignificant. Using high-shear mixers, however, experimental evidence for occurrence of significant breakage has been reported, and breakage should, therefore, be included in a PBM [60-62]. Sanders et al. [7] investigated the dependence of the agglomeration rate constant on the impeller speed in a high-shear granulator. Their results indicate as weil that breakage should be considered in a PBM of high-shear granulation. Hounslow and co-workers [22,63] included breakage into PBMs and could extract mechanisms and kinetic parameters of breakage in high-shear granulation. The addition of coloured tracer granules was shown to be a useful technique in the investigation of breakage. Tan et al. [64] investigated breakage in fluid-bed melt granulation. Glass ballotini were granulated by spraying PEG 1 500 onto them, in the presence of 1 % (m/m) coloured granules previously produced in three different sizes. In a second type of experiments, these mixture was fluidized without spraying binder in order to investigate breakage in the absence of agglomeration. Three different fitting experiments were performed to the data of the growth experiments, where the same coalescence kernel in all the fitting experiments was applied. In the first series, breakage was disregarded. Despite this, the mass-based PSD could be described fairly weil, however, the agglomeration only model failed to describe the number-based PSD. This was to be expected since bigger granules are more likely to break. In the second series, the agglomeration frequency extracted from the first series was used but breakage was additionally taken into account to improve the fit to the obtained PSDs. Three different breakage mechanisms (see above) were considered. The breakage model that induced the best improvement of the fit was random binary breakage with a size independent selection rate constant. The mean size was slightly overestimated, because the same aggregation frequency as in the first series was used. The apparent agglomeration rate extracted from the first series is in fact a net process made up of agglomeration and breakage. In the third series, agglomeration and breakage rates were extracted simultaneously. The extracted breakage mechanism was a combination of random binary breakage and attrition. Such a combination of mechanisms was supported by micrographs. Each of the three approaches was suited to model the evolution of the mass-based PSD. When comparing the evolution of the mean size, it was revealed that the third approach produced the best estimation, as expected. This work again showed, however, the difficulties in modelling the nucleation phase of granulation.
T. Abberger
1 1 28
3 . 1 .2.3. Multi-di mensional population balance equations
As discussed by Iveson [33], one-dimensional PBEs regarding particle size alone as independent granule property that significantly controls granule growth and thus being the only property that is modelled, are a simplification that leads to limited applicability. Although size is a key property of granules, it is weil known, however, that other internal properties of granules, such as porosity and granule binder content strongly influence the growth of granules and their quality. All such properties can vary significantly between granules [33]. Multi-dimensional PBEs allow the modelling of the time evolution of the distributions of such properties. There seems little doubt that models allowing particles to be described by multiple properties will become the norm [27]. When the advantages of multi-dimensional PBEs shall be exploited, this requires knowledge of the initial distribution and the boundaries of all the properties included in the equation, as weil as rate expressions for their development in the course of time. A coalescence kernel that is applied in a multi-dimensional PBE has to take into account the effects of all the independent properties included in that PBE on granule agglomeration (see Section 3.2.4). Porosity is a controlling factor of coalescence owing to its effect on deformability and liquid saturation. Liquid saturation is a key controlling factor for granule growth [65,66]. Annapragada and Neilly [60] showed that both the particle size and the porosity evolve during the process. They were the first to suggest that both, size and porosity, should be included in a population balance model. 9 A two-dimensional PBE for pure agglomeration accounting for size and porosity as independent parameters can be easily developed (equation (26), compare [33]). A granule with volume v - u and porosity ev- u coalesces with a suitable granule of size u and porosity eu to produce a new granule of volume v and porosity ev. The PBE requires a term for the evolution of porosity and a double integration over both the independent properties in the birth and death terms. an(v, ev, f) at
100 l"u,max ß(v, u, ev, eu, f)n(v, ev, f)n(u, eu, f) deu d u "u,minmax rl"u, + 2Ntotr Jo0 "u,min ß(v - u, u, ev-u, eu, t) 1
-Ntrot 0 1
X
n(v - u, ev-u, t)n(u, eu, t) deu d u
(26)
9 A two-dimensional PBE for coagulation of a binary mixture has already been described by Lushnikov [67].
Population Balance Modelling of Granulation
1 1 29
The porosity is not additive: GV -# GV- U + GU, but the pore volume is, as a first approximation, assumed to be additive. Therefore, for a given granule of properties v U, Gv- u, the porosity of the second granule with size U to produce a granule with properties v, Gv can be calculated by -
GU =
VGV - (v u)Gv- u -
U
(27)
Binder content has been the subject of many experimental investigations on the factors influencing granule growth. Almost all investigations showed that granule growth increases with increasing binder content for a wide range of materials in many different types of granulators. Increasing granule binder content increases the amount of liquid available to form bonds between granules and also improves granule surface plasticity [51 ]. It is now recognized that in many systems the binder is not uniformly distributed [33,68]. The homogeneity of the binder content, reflecting the liquid distribution in a device, has been shown to influence the resulting PSD [69]. Iveson [33] proposed a four-dimensional PBE for pure agglomeration considering four independent granule properties: the granule solid-phase mass, m; the binder content, expressed as mass ratio, w; the porosity, G; and the composition, expressed as mass fraction, x, of a second component. an(m, G, w, x, t) = Bcoal (m, G, W, X, t) - 0coal (m, G, W, X, t) at + C(m, G, W, X, t) + Wem, G, W, x, t)
(28)
Terms for the evolution of the distribution owing to consolidation, C, and wetting, W, are included. These terms describe the evolution of the porosity and of the binder content, respectively. Other terms could be added easily. Ramkrishna and Mahoney [23] have assessed common methods of solving one-dimensional PBEs for their ability to solve multi-dimensional PBEs. Because the solution of multi-dimensional PBEs is exceedingly difficult [20], attempts at simplification have been made. Verkoeijen et al. [31 ] facilitated the approach regarding size, porosity, and binder content as properties of interest. To obtain the facilitation, they regarded three different volumes as independent, distributed properties: the volume of solids, the volume of liquids, and the volume of air of a single granule; these volumes have additive properties. In their approach, the time evolution of these volumes instead of particle numbers is being modelled. The measured properties of interest that are the particle porosity, the moisture content, and the pore saturation, which are not additive, can all be derived from these three volumes. An extension of the approach of Verkoeijen et al. [31 ] was made by Darelius et al. [70] to account for initial non-uniformly distributed moisture and air content.
T. Abberger
1 1 30
Biggs et al. [71 ] regarded size and liquid fraction as independent, growth controlling properties, whereby each granule comprises three phases, solid, liquid, and air. The simplifying approach of Biggs et al. [71 ] was to model the granulation with a set of n number density functions of one variable each, either the volume of solid or liquid, instead of regarding one single number density function in n variables. 3. 1 . 3. The population balance equation in moment form
Sometimes knowledge of the complete PSD is unnecessary and some average quantities may be sufficient to represent it. These average quantities can be expressed as moments of the distribution function. The moment form of PBEs is widely applied in the crystallization literature, owing to its potential to create reduced order models. The procedure to form moment forms of the PBE, however, very often leads to terms that may not reduce to moments, to terms that include fractional moments, or to an unclosed set of moment equations [72]. Kerneis applied in granulation are often complex, which enforces this difficulty. There exist moment forms of the general PBE, for pure growth and for pure aggregation. Because the general PBE and the pure growth form in moment transformation do not seem to be applied in the modelling and simulation of granulation, nor to be relevant for the development of the approach, they will not be presented in this chapter; the reader is referred to Ref. [ 1 7]. 3 . 1 . 3. 1 . Moment representation of a particle size distribution
1000
We define the nth moment of n(x, t) as Mn =
� n(x, t) dx,
n? 0
(29)
Usually, only the first few moments are tracked because they contain the information about • the total particle number, Mo, • the number-based mean particle size, M1/Mo (d1 •0, when x is a length), and the coefficient of variance, (J, to express the width of the PSD as (J = 1, 1 which is sufficient in many practical applications. •
3 . 1 . 3 . 2 . The pure aggregation form
JM��2
-
The pure aggregation form of the PBE in moment form is obtained by multiplying both si des of equation (7) by � and integrating over the entire range of v; this
Population Balance Modelling of Granulation
1 1 31
yields an ordinary differential equation, ODE, dMn - O -- =
(30) Bn - n where Bn and On are given as Bn = Jooo v n B(v) d v and On = J: v n O(v) d v,
dt
respectively. Equation (31 ), which was given by Drake [73], follows from equation (30) dMn (t) __ _ 1 00 00 [(u + vt - u n - v n] ß(U, v)n(u, t)n(v, t) dv du (31 ) 2 0 0 dt This immediately shows that the total number of particles i n the system decreases in the course of time and that the total mass or volume is conserved , Jooo vn(v, t) d v i s constant in t, which i s expected from the descriptive model, however the sum of square of masses, M2 , increases. =
_
11
3.2. The coalescence kernel 3. 2. 1. Introduction
The establishment of the coalescence kernel for granulation processes is still ongoing research. A single kernel unifying all theories and considering all governing factors and their relationship does not yet exist. The determination of the appropriate kernel remains a difficult problem in the simulation of granulation or when solving an inverse problem (see Section 3.4). The experimental results described in the literature vary widely, are sometimes contradictory and many growth regimes exist. Experimental observations are offen unique to a given class of material and processes. A complex relationship exists between feed size distribution, granule properties, apparatus geometry, operating conditions, and the mechanisms of granulation, leading to the proposal of a variety of coalescence models and growth regimes [74]. This had two consequences: the development of a variety of different kerneis, and that the current approaches to kernel development tend to recommend different kerneis for different granulating systems and/or materials [75]. Kernel development started with empirical kerneis considering granule size as distributed property governing granule growth. Owing to their long history, many such kerneis exist. Such kerneis contain adjustable parameters, and their numerical value is extracted by data fitting. The insight gained into the process by such kerneis is not sufficient and the numerical value extracted might not be transferable to another experimental setup. The choice of the empirical kernel providing the best fit is a trial and error approach. Despite all their disadvantages, as discussed by Wang and Cameron [8], these authors stated that the empirical coalescence kerneis have played an important historical role in the study of the population balance and for many practical
1 1 32
T. Abberger
granulation processes, a properly selected empirical kernel may provide an acceptable level of model prediction. More generalized, physically based models are highly demanded by the granulation industry for further research and development [8]. If the coalescence kernel is based on a physical coalescence model, the PBE ideally should allow predictions of PSDs without any need for parameter fitting from experimental granulation data. Although several recently proposed kerneis have a theoretical basis, a need to include empirieal, adjustable constants even in such kerneis can remain. This may be attributed to the still limited knowledge of the influences of process parameters and material properties. Coalescence kerneis based on theoretical models should be more fundamen tally sound than the empirical kerneis, because the granule physical properties, the binder properties, as weil as the collision velocities of the granules are included in theoretical models [76]. The key for successful application of these models is to correlate the model parameters to measurable process and material parameters. Therefore, difficulties exist in application of the theoretical coalescence models. Limited application of theoretical coalescence models can be attributed by two factors [76]. Firstly, most models are based on the collision mechanisms of two isolated granules. In coalescence models, the particle pair must act indepen dently of the remainder of the dispersed phase. This is a limitation of such models [28]. In a granulator in which many granules interact with each other, the theoretical models based on binary co-linear collisions may not be applied [76]. Furthermore, few models consider angular collisions [33]. Secondly, there is still very limited knowledge on the granule-collision velocity distribution and collision frequencies in different types of granulators (see Section 3.2.2). In consequence, using a kernel or a combination of kerneis that provide the best fit to the experimental data is still the most common method [76,77]. 3. 2. 2. The physical implication of a coalescence kernel
As mentioned, the coalescence kernel describes the local motion and coalescence rules. This statement is described in greater detail below. 3 . 2 . 2 . 1 . The aggregation frequency
As can be seen from equations (3) and (4), the number of particles formed or lost in a size range between v and v+ dv owing to coalescence of two granules with diameters u and v is determined by a coalescence rate, or aggregation frequency. The aggregation frequency is usually derived by analysing the relative motion between particles culminating in their aggregation in isolation from the population balance. This approach is based on the assumption that the local motion does not compromise the spatial homogeneity of the population and on the assumption that motion of particles is faster than the rate of particle aggregation [50].
Population Balance Modelling of Granulation
1 1 33
The aggregation frequency is composed of two terms [78] Aggregation frequency = Collision frequency x Aggregation efficiency (32) Because collision of granules is necessary but not sufficient for coalescence, it is necessary to associate an efficiency of aggregation for a complete characterization of the aggregation frequency. The aggregation efficiency can be interpreted as the probability that two collided particles will aggregate to form a single particle, that is the coalescence probability [14]. Equation (32) is valid under the assumption, that collision is the step, which determines the velocity of the whole aggregation process. 3.2.2.2. The col lision frequency 3. 2. 2. 2. 1. General collision theory. A particle A moves in the course of time M through a "collision cylinder", which contains a collection of particles B (Fig. 3). The volume, V, of the collision cylinder is given as (33) where (J is the "collision cross-section" and collision frequency, fc, can be calculated as
< v)
the velocity of particle A. The (34)
where [B] is the number concentration of particles B. The velocity < v) has been replaced by the relative velocity, < Vrel ) because the particles B are not stationary. The frequency of collisions between particles A and B per unit volume, fc, is given as fc fdA] = (J ( vrel ) [A][B] (35) 3. 2. 2. 2. 2. The collision or loading frequency in a granulator. Sastry and Fuerstenau [43] divided the aggregation processes into two basic classes, "free-in space" and "restricted-in-space" aggregation. The distinguishing property between ,
=
dA+dB 2
1
-
miss
----
__ _
d B/2
hit
Fig. 3. Collision cylinder. Reprinted with permission from Prof. Thomas Bally, Department of Chemistry, University of Fribourg, Switzerland.
T. Abberger
1 1 34
the two types of aggregation is the number concentration (Iow or high) of particles in a unit volume. When the number concentration is low, each particle can collide with any other particle in the unit volume. When the number density is high, the movement of a particle is restricted and it can encounter only the particles that immediately surround it. No clear demarcation between the two classes exists. For aggregation in a diluted system, in a free-in-space system, the rate of collisions is proportional to the product of the number concentrations of the two species (compare equation (35)) (36) [Collisionslj ni(t)nit) Kapur and Fuerstenau [12] postulated that the concentration of agglomerates in a loosely packed granulating bed is more er less fixed by the packing constraints. In this situation, the movement of an agglomerate is restricted. It is likely to encounter and coalesce with its nearest neighbours, which form a cage around it. The agglo meration occurs under a restricted-in-space environment. For a restricted-in-space system, the number of random collisions between particles belonging to any two size groups, i and j, under the constraint of perfect mixing is proportional to the product of the number of species of one type with the number fraction of the second type oe
[Collisions]ij
oe
niet)
::a;it)
(37)
In deriving equation (37), Kapur and Fuerstenau [12] argued that in a randomly mixed bed in which the range of sizes is not large, the collision frequency will be approximately the same for all granules present. The normalization by Ntot(t) means that the population is averaged over a region containing that number of particles; this can be the whole granulator but may aiso be applied to separate regions [77]. Recently, Kapur and Runkana [53] modified the random collision model and, therefore, equation (37), in order to incorporate the size dependence of the coordination number of granules. In a simulation performed to compare both the collision models, random and coordination, however, similar results were produced despite the differences in the collision model. Size segregation will alter the frequency and velocity of collisions between granules of different sizes. Granules in the stationary regime of a drum, pan, or mixer will also have lower collision velocities than granules in other regions [33]. Ouchiyama and Tanaka [47] divided the granulating spaces into two types and introduced two different frequencies, the collision frequency for the free-in-space system and the loading 1 0 frequency for the restricted-in-space system. In one type of granulating spaces, most of the granules are separated from each other and in the other type the granules are in contact with their neighbours. Denoting the volume ratio of the former by �, then the collision and the loading 10 Loading means an application of force through the neighbours to the contact point between two granules which are in contact with each other.
Population Balance Modelling of Granulation
1 1 35
frequency in each space are represented by equation (38) for the collision and by equation (39) for the loading (38) [Collisions]jj , njnj n (39) [Loadinglj cx ( 1 - Onj N j tot By introducing a new parameter, the degree of restriction, r, which is equal to zero for the granulator in which most of the granules are separated from each other, e.g. a fluid-bed granulator, and equal to unity for that in which they are in contact with the neighbours, e.g. pan or drum, they could express the collision or loading frequency in a unified expression cx
:!
(40)
�t�(6 n(d, t) dO dd
(42)
[Collisions or Loading]jj cx nj
tot
In order for two granules to coalesce, it is necessary that a collision occurs when granules are separated from each other, Iike in a fluid bed. No c1ear single collision event exists in applications, where the granules are constrained in contact with one another for significant time intervals, as in the rising section of a tumbling drum, or in the quiescent zones of a fluid-bed. Here, all the granules are constantly in contact with their neighbours [79]. The collision frequency may be replaced in these cases by the loading frequency per unit volume, fL, that is the product of the total number of contacts between the two granules of sizes 0 and d per unit volume, n(O,d) dO dd, and the frequency of experience of a force leading to adherence of a pair, the loading frequency, ", according to h = n(O, d) dO dd x " (41 ) According to Ouchiyama and Tanaka [80,81], n(O,d) i s the contact number function of sizes 0 and d in a completely mixed packing. The total number of contacts between particles of the size fractions O,O + dO and d,d + dd at time t can be expressed in a restricted-in-space environment as neO, d) dO dd =
C C(O, d)
C and C(O,d) have been defined from a packing model [82] as the packing parameter and the contact number between one granule of diameter 0 and the surrounding granules of diameter d. Huang and Kono [83] assumed that the total number of collisions per unit time can be expressed as the product of the total number of contacts and the packing renewal frequency in a granulating device. Because little is known about the collision or loading frequency, several authors [81 ,83-86] resorted to a dimensionless time, defined as fC,L t, where fC,L is the collision or loading frequency and t the real time to solve the PBE. A shortcoming of this approach is that at present the function = f(t) can be obtained by data fitting only. T,
T
"-'
T
1 1 36
T.
Abberger
In order to describe the collision rate in a fluid-bed, Goldschmidt (cf. [87]) was able to develop a proportionality factor, a collision rate constant, Gij, for introduction into equation (36) as
mj
Gjj = ncJtgjj
2 1 / [4 (0smi+mj ) 2mjmj _ ] djj
n
2( - "3 \7 u)
(43)
where djj is the inter-particle distance between two particles on collision, gjj a radial distribution function for mixture, Os the mixture granular temperature, mj and the mass of particles, and ü the ensemble average particulate velocity. 3 . 2 . 2 . 3 . The aggregation efficiency
To predict the aggregation efficiency, or coalescence probability, from the properties of the granules and the binder, and the operating conditions, a large number of coalescence models have been developed, making a wide range of different assumptions about the formulation and the process characteristics. Key properties in which the models differ are the deformation behaviour of the granules, binder viscosity or other binder properties influencing bond strength, and the acting separation forces. The methods used in developing the models are either energy or force balances, and most of the models [88-92] are able to predict whether the granules will stick together (successful collision) or rebound upon collision. 3. 2.2.4. The relationship between the coalescence kernel and the aggregation frequency
From equations (3) and (4), it can be easily checked that the aggregation frequency of particles of sizes u and v is proportional to the product of the total numbers of such particles, and that the coalescence kernel is a proportionality factor in the aggregation frequency. The coalescence kernel ß(u,v) expresses • •
•
the aggregation efficiency of two particles of sizes u and v, and either the "collision cross-section" and the velocity of the particles in the free-in-space environment or the contact number between one granule and the surrounding granules and the loading frequency in the restricted-in-space environment. In conclusion, the kernel has to describe the influence of
•
• •
granule size on the aggregation efficiency and either the collision or loading frequency, other granule properties except size on the aggregation efficiency, operating conditions on collision or loading frequency and the aggregation efficiency.
Population Balance Modelling of Granulation
1 1 37
The kernel is in principle measurable and because its physical properties include a probability, it is positive everywhere. The dimension of the kernel is reciprocal time. In a granulation process, the kernel cannot describe the motion and coalescence rule owing to a dependence on u and v alone. Furthermore, the assumption, that there is no influence of other particles, can be challenged in a granulation process. In order to express that the kernel has to account for a variety of influencing properties and conditions, time has been introduced as a third variable, ß(u, v,t). The time dependence of the kernel is a manifestation of the dependence of the kernei on other particles in the system or on the state of the distribution [28]. The time dependence allows to account for a shift in the granulation regime during the course of a granulation process. 3.2.2.5. The design of kerneis
3.2. 2. 5. 1 . The traditional design. The coalescence kernel is traditionally split into two parts [44] ß(u, v, f) = ßo (f)ß*(u, v) (44) where ßo ( t) is the aggregation rate term and ß*(u, v) describes the dependence of the coalescence kernei on the sizes of the agglomerating granules. The aggregation rate term ßo (t) is size-independent and includes various system parameters such as the granulator geometry, the operating conditions (e.g. drum or impeller speed), and formulation properties (e.g. binder viscosity, wettability or moisture content [45]). The variable t is, therefore, in part a dummy variable for other properties such as binder or moisture content, or operating parameters, which can, but need not change in the course of time. The relationship between the time dependence of a kernel and the granule properties has been discussed by Pearson et al. (cf. [68], see also Ref. [63]). Provided that the binder content and operation conditions remain the same, ßo (t) is generally assumed to remain constant throughout the experiment [33]. If, however, the aggregation rate term is, contrary to this assumption, not constant in the course of an experiment this could be due to invalidity of the underlying assumptions in the kernel (see Ref. [22]). Moreover, as stated by Iveson [33], it is insufficient to model the effect of parameters that show a significant distribution, such as binder content of granules, by just varying the aggregation rate term ßo (t) as an average value, as has been done in the traditional approach using the empirical kerneis. This may explain, in part, why this approach had limited success. The aggregation rate term controls the rate of change of the mean of the granule size distribution [93]. In many kerneis, the second term, ß*(u, v), expresses the influence of granule size on the collision frequency, where the assumption that each collision leads to coalescence is implicit. In some kerneis, ß*(u, v) expresses as weil the size
1 1 38
T.
Abberger
dependence of the likelihood of coalescence. The term ß*(u, v) determines the shape of the resulting PSD [75]. 3. 2. 2. 5. 2. The design suited for physical models. With this design, a kernel consists of a rate term describing the collision or loading frequency and a term describing the aggregation efficiency, P(u, V, Z1 , Z2), where Z1 and Z2 stand for all the other relevant properties besides size of the two colliding granules. This design differs considerably from the traditional design of a kerne!. A coalescence model that predicts whether two granules will coalesce or not, can be transformed into an aggregation efficiency by applying a test function 1 if test is true aggregation efficiency = P(u, V, z1 , Z2) = (45) . . o If test IS false This can lead to a high computational load. Instead of performing this test for each pair of colliding granules, where each granule has many different properties, the calculation can be facilitated by using average values for properties such as binder content, kinetic energy, or porosity. Furthermore, mostly the distribution of such properties is not known. Such a distribution of influencing properties leads to a corresponding probability distribution of P(U,V,Z1 ,Z2) according to P(u, V, Z1 , z2 ) = Pr{test is true} (46) Within a granulation regime, an increase of parameters such as moisture or binder content can lead to an increase of Pr{test is true} and, therefore, to a higher aggregation frequency. In the traditional approach, an increase of the mean value of Pr{test is true} manifests itself in an increase of the aggregation rate term. Different granulation regimes can produce different mean values of Pr{test is true} as weil. The shift from one granulation regime to another during the course of a granulation manifests itself again as a different value of the aggregation rate term. Although the collision or loading frequency is size-dependent, in many working models a separate term such as (U1 /3 + V1 /3) 2 to express this dependence has not been incorporated, because the whole collision frequency has been obtained as an average value by parameter estimation. In some PBMs of a granulation in a restricted-in-space environment [80,81 ,84,85], such a term, however, has been included.
{
3. 2. 3. Homogeneity of kerneIs
3.2.3. 1 . Definition
A separable kernel satisfying the condition
ß( cu, CV) = dß(u, v),
i s called homogeneous with exponent A.
'v'c> O
(47)
Population Balance Modelling of Granulation
1 1 39
Many kerneis of practical relevance 1 1 satisfy equation (47) [42]. The exponent A, the homogeneity degree, expresses the strength of the dependence of ß(U, v) on its arguments. It reflects the tendency of large particles to aggregate preferentially with other large particles [94]. The behaviour of the solution of the PBE depends critically on the homogeneity degree Je [95]. It is the mainstream of the literature that the homogeneity degree divides the pure aggregation process into two regimes: • •
A < 1 non-gelling and leading to a self-preserving size distribution, and A > 1 gelling.
It seems that most authors consider A = 1 as non-gelling and leading to a self preserving size distribution. 3.2.3.2. Self-preserving size distributions
Definition. Homogeneity of the kernel is the formal statement that the aggregation process does not have a characteristic scale, i.e., aggregation of particles at different scales is assumed to happen similarly except for a possible change in the rate of the process [96]. A self-preserving or self-similar size distribution is characterized by a distribution function with a maximum and a similar shape that increases in peak position with time but retains the shape of the distribution curve. By normalization a general time-invariant distribution function can be determined for the self-preserving distribution associated with a kernel. By normalization all graphs of the self-preserving distribution collapse into one single graph. The size can be normalized by the mean volume of a particle, V, where v = M;+ 1 /M;, i = 0,1 ,2, . . . , and the distribution function, 'P(I]) = 'P (vIv(t)) , is dimension less. The new independent variable I] is the dimensionless normalized particle volume. The concept of self-similarity was described comprehensively by Wright and Ramkrishna [28]. In the broadest sense, the term similarity implies a reduction in the number of independent variables in the problem as a result of some invariance relationships. Physically, the process harbours some behavioural symmetry that manifests in some quantitative manner [97]. Many pure aggregation processes lead to self-preserving size distributions [14]. This simplifies the analysis of experimental data (see Section 3.4). Numerous evidence of self-preserving size distributions in granulation was reported. 3. 2. 3. 2. 2. Similarity transformation of the population balance equation. A similarity transformation transforms the PBE into an ODE for 'P of 1], thus reducing the number of independent variables from two to one. The well-known 3. 2.3. 2. 1.
11
For a list of relevant kerneis applied in the physical chemistry literature, see Ref. [94].
1 1 40
T. Abberger
similarity transformation introduced by Swift and Friedlander [98] is as folIows: n(v, t) t1 and Ssat :( Serit for t > t1 and Ssat > Serit where ß 1 and ß2 are the aggregation rate terms, obtained by parameter estimation, t1 the transition time between the two stages of granulation, Ssat the saturation of the voids, and Serit the critical saturation, a characteristic void saturation necessary for the onset of the second granulation stage, as the second stage relies on plastic deformation of colliding granules. The first stage was within a non-inertial regime where growth occurred by random coalescence. The probability of successful collisions depended only on 16 In the physical chemistry literature, a kernel of this type with a Brownian motion [1 1], see also Ref. [1 1 1].
=
b
=
1/3 has been based on
Population Balance Modelling of Granulation
1 1 45
binder distribution, with all collisions involving binder being successful. The PSD narrowed during this first stage and an equilibrium size distribution was reached at t1 . The extent of granulation within the first stage, given by ß1 t, was found to be linearly proportional to Ssat and to increase with binder viscosity. Changes to the initial size distribution affected ß 1 t by changing granule porosity and, therefore, liquid saturation. When Ssat remained below Scrit, which means the second stage of granulation did not occur, the PBE solved for f> t1 gave the equilibrium granule size distribution for coalescence in the non-inertial regime only. When Ssat exceeded Scrit, the granules were sufficiently deformable for further growth. The second stage of granulation broadened the PSD. Scrit decreased with increasing binder viscosity. Hoornaert et al. (cf. [1 1 0]) investigated the granulation of an enzyme powder and inorganic fillers with an aqueous binder solution using a high-shear mixer. Several stages of growth were observed. Following the approach of Adetayo et al. [93], they proposed a sequential kernel to model the stages of nucleation, densification, and growth of the form ß( u, v, f) =
{
ßn (u + v) for f < t1 0 for t1 < f < t2 ßc ( u + v) for f> t2
(6 3)
where the subscripts n (c) denotes nucleation (coalescence), and the time of densification is from t1 to t2· Wauters et al. [77] made an aUempt to develop a PBM for a high-shear granulation, which can be applied to simulate three stages of granulation: nucleation, induction, and growth by coalescence. Owing to the complex mechanisms of nuclei formation, they could not find a kernel for the nucleation stage. They could find a joint kernel for both the induction and the growth stage, however: ß( u, v, t) =
{0
A e -Bt
for Ssat < 1 --- 1 for Ssat ?
(64)
This kernel predicts that the induction period with no growth proceeds as long as the void saturation is below unity. When the surfaces get wet, a discontinuity with onset of coalescence occurs, where the growth is independent of granule size. The term in the kernel describing the growth stage for Ssat � 1 was found empirically. The ratio of the empirical constants A and B, AlB, was found to be directly proportional to the solution phase ratio derived by Sherington. Experimental validation was performed with previously published data from a high-shear mixer. The PSD at the end of the nucleation stage was used as starting size distribution for the simulation of the induction and growth stages. In a comparison of the sum kernei, the kernel of Adetayo and Ennis [75] (see this
1 1 46
T. Abberger
section) and their own kernei, the latter produced the best fit to the experimental data. The reason for this better performance could not be c1arified. 3.2.4.3. Model-based kerneis 3.2. 4. 3. 1 . Coalescence models accounting for plastic deformation 3.2. 4. 3. 1 . 1 . A model of plastic deformation for surface-dry granules.
Plastic deformation leads to energy dissipation and creates an enlarged area of contact that helps to hold the granules together [1 1 3]. Ouchiyama and Tanaka [1 081 considered surface-dry, deformable granules in a drum granulator (Fig. 4). They assumed that in the constant-angular-velocity region of the drum, an axial compressive force acts on each pair of granules with diameters 0 and d. This deforms the granules and creates a contact zone between them with a cohesive strength proportional to the area of the contact, S. In the tumbling region of the drum, each granule pair is then exposed subsequently to pairs of forces, F1 and F2 , perpendicular to a tangent common to the contacting granules that tend to separate the granules. The compressive forces were assumed to be independent of granule size, whereas the tangential separating forces were assumed to be proportional to the volumes of the granules in contact. At the contact point, the bending moment exerts a tensile stress. Successful coalescence occurs when this tensile stress is smaller than the tensile strength of the bond. In other words, the compressive force has to be greater than the force creating the tensile stress. The coalescence probability, P(D,d), was described by Ouchiyama and
s
TUMBLING DRUM
Fig. 4. Ouchiyama and Tanaka's model of coalescence. Reprinted from Iveson et al. [1 1 3]. with permission from Elsevier.
Population Balance Modelling of Granulation
Tanaka [1 08] as P(D, cf)
,n - )0
_
[ -{ 1
}]
2 ' (Dcfy-3ry/2 / «D + cf) / 2)2Y_4_ 3ry/ 2 /3 64-3ry/2
1 1 47
n
(65)
where 6 is a characteristic limiting size that makes the coalescence probability equal to zero between granules of the same size, because the separating forces owing to the kinetic energy exceed the binding forces. For simplification, it is assumed that no coalescence occurs between granules having sizes larger than 6. That is [80] P(D, cf) = 0 for D ?:. 6; cf ?:. 6 Equation (65) requires five constants, namely y, lJ , ,1" �, and n. Two of these constants, lJ and �, are related to the elastic and plastic behaviour of the colliding particles. The surface area of contact, S, between two colliding particles is given by [1 08] (66) where Q is the compressive force between two colliding granules. According to the theory of Hertz, values of lJ = 0 and � = 1 describe plastic behaviour (cf. [1 08]), and values of lJ = � = 2/3 describe elastic behaviour [1 14]. The parameter ,1, is given as ,1, = Qmax /( Qmax - Qmin ) . The limiting size, 6, is related to the tensile strength, (Jst , and the deformability, K, of a granule as [1 1 5] 6 = A1 K2/3 (Jst (67)
(
f
where A1 and are constants independent of the granule size and K = S/Q . K is related to both the yield strength of the material and the ability of the surface to be strained without rupture of the granules or degradation [1 1 6]. From equation (67), Kristensen et al. [1 1 6] obtained equation (68) by geometric considerations (1':,.1/ D) 3 62/a = A1 (68) (Je where (Je is the compressive strength. The nominator expresses the normalized strain produced by the impact. The strain depends primarily on the packing of the particles and the liquid saturation. Significant strain arises when the liquid saturation is increased to the limit where the cohesive strength of the agglomerate is governed by the strength of mobile liquid bondings. From equation (68), Kristensen et al. [1 1 6] concluded that the rate of growth by coalescence between agglomerates is controlled primarily by the saturation degree of the agglomerate, because it is the liquid saturation that controls the strain behaviour. Kristensen et al. [1 1 6] concluded furthermore that a high rt
1 1 48
T.
Abberger
value of 6 is associated with a high coalescence probability, and therefore a high growth rate. Ouchiyama and Tanaka [81 ] carried out simulations of a batch granulation using their model of aggregation efficiency, where the evolution of the mean diameter in the course of the simulation showed an S-shape, corresponding to the three granulation regimes of nucleation, transition, and ball growth, as previously described by Kapur and Fuerstenau [1 1 7]. Experimental validation, however, was not provided. The uncertainty of the bond strength (Tst is a main drawback for a quantitative application of this model [1 1 3]. Contrary to many other models, this model does not consider collision velocities, because it assumes that in a restricted-in-space environment granules are permanent in contact to each other. 3.2. 4. 3. 1 . 2. Modification of the model for surface-wet granules. The modifi cation of Ouchiyama and Tanaka's model by Huang and Kono [83] has been based on the existence of a liquid bridge between two granules, which causes the adhesive force between the colliding granules. The probability of coalescence is treated as the probability that the liquid bridge can withstand the separation forces imposed on the colliding granules in the granulator. The force creating the tensile strength, here the force of the liquid bridge, h, has to be greater than the force creating the tensile stress, which is the net force acting on the granule resulting from granule-granule collision in the granulator. The probability for coalescence of two granules, PrcoaJ, is (69) where (Tt is the tensile stress, crst the adhesive stress, Mo the critical bending moment with respect to the contact point 0 of the colliding granules, and R the radius of the liquid bridge. Because only very low-viscosity binding liquid was considered in the development of the model, only the static phenomena surface tension and pressure difference forces were supposed to contribute to the bridge strength. The tensile strength is then a function of the surface tension of the liquid, its contact angle to the powder material, the particle diameters, and the volume of the liquid bridge. This volume is the result of the granule collision intensity, the local deformability (defined as the ability for local porosity reduction), and the moisture content of the feed, because these factors determine the amount of liquid, which is squeezed to the surface during a collision. For an ideally liquid bridge, the probability for coalescence for two granules of diameter 0 and d, P(O,d), was derived as
[
P(O, d) = 1
-
( 0d)r- 1 62 « 0 + d) /2)2r-4
ln
(70)
Population Balance Modelling of Granulation
1 149
where (j is the maximum limiting size for pair formation and n a parameter to enable mathematical adjustability. The probability of coalescence in a real system, P(D, d, Ci, Pi), was given as (71 ) The non-ideality of the coalescence probability is represented by a function of the operating conditions, Ci, and material properties, Pi, as h(Ci, pJ The model was validated in the granulation of pre-wetted aluminium hydroxide and rehydratable alumina powders in a spouted fluid-bed granulator. 3.2. 4. 3. 1 . 3. Applications of the model in the calculation of the aggregation efficiency. Although formulated for surface-dry granules, Ouchiyama and Tanaka's coalescence model was applicable to simulate the aggregation efficiency in fluid-bed spray granulation. Watano et al. [84,85] investigated the granulation of a mixture of lactose, corn starch, and hydroxypropycellulose by spraying purified water onto the powder bed using an agitation fluid-bed granulator. In this device, the granules were fluidized by air and tumbled by agitator rotation. Because the movement and flow pattern of granules were claimed to have many similar features to those in the tumbling granulator, Ouchiyama and Tanaka's coalescence model was applied. The idea of Watano et al. [84,85] was to correlate the deformation behaviour of the granules with their moisture content. With the formulation used, granulation was feasible with moisture contents ranging from 0% to 20% before blocking or defluidization occurred. The two parameters 17 and � were taken to be functions of the moisture content in the range of 0% to 20%, therefore. The parameters n and y were empirically determined as exponential functions of the moisture content by data fitting. Abberger investigated fluid-bed spray granulation of lactose and corn starch with an aqueous solution of polyvinylpyrrolidone in an instrumented laboratory scale fluid-bed granulator STREA-1 [86]. Two series of experiments were performed using lactose in order to investigate the effect of free moisture. The first series was with a target content of 5% free moisture. According to calculations of the free moisture from the operating conditions based on a thermodynamic model [1 1 8, 1 1 9], 44 ml of the granulating liquid was added at a rate of 30 ml/min to obtain a 5% free moisture level. The spray rate was reduced to the equilibrium value [1 1 8] of 1 1 .9 ml/min, and then increasing volumes were sprayed continuously onto the powder bed. The second series was with target content of 1 0% free moisture. In this case, 78 ml of liquid was added at a rate of 30 ml/min. Then again, increasing volumes were sprayed onto the powder bed at a rate of 1 1 .9 ml/min. For each granulation, sampies weighing about 5 9 were taken after the addition of the first 44 or 78 ml, respectively, and after the addition of the total volume of granulating liquid. These sampies were dried, and the free moisture was calculated from the loss on drying.
T. Abberger
1 1 50
Using corn starch, two experimental series were also performed. With the first series, increasing volumes of granulating liquid were sprayed onto the powder bed at a rate of 20 mljmin. With the second series, 200 ml of pure water was sprayed at a rate of 20 mljmin on each batch. Subsequently, increasing volumes of binder liquid were sprayed at a rate of 20 mljmin onto the batch. Ouchiyama and Tanaka's coalescence model [1 08] was applied to simulate the evolution of the PSDs. In each of the lactose series, the first granulation with an R2 value to the log-normal distribution of at least 0.99 was used as the starting PSD for the simulation. The applied values for the constants as weil as the value for the required limiting size (5 were obtained by data fitting. Figure 5 shows the evolution of the cumulative number distribution with time for the 1 0% series and Fig. 6 for the 5% series with lactose as powder. Figure 7 shows the evolution of the cumulative number distribution for the starch granulations without any previously added water, and Fig. 8 shows the evolution of the cumulative number distribution for the starch granulations with a previous addition of 200 ml of pure water. With the assumption that the granules underwent plastic deformation, the evolution of the size distribution could be modelled weil for both materials. With lactose, the evolution could be mode l ied weil independent of the statistical distribution that existed between 5% and 1 0% of the free moisture content within
0.9 0.8
:g 0.7 � 0.6 c 0
Q; E
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Population Balance Modelling of Granulation
. = i I --- � .� -1 --+ t -L -t- I -f-- J:- �- \� I -t. � I T l- I --- ---tI�I _I , -i' ----rI - ----rI I ' t-f 1 --1 -1 ---+ ----L -
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Simulated and experimental cumulative n umber distribution of the lactose 5 % series. Reprinted from Abberger [86], with permission from Elsevier.
F i g . 6.
. dfb Dp > dre D,. > dfb Dp =dfb
t
dre =d", dre = dpc dfb > dpc dre > d",
0. 160
0. 147
0. 146
0. 1 46
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=d",
Dp
> dfb dre =d",
Fig. 6. Representative projections of five composite granules (a) composed of the binary
mixture of CaC03 and SiC powders and of the SiC agglomerates contained within it (b and c) using image analyser. (Adapted from Sugimoto et al. [ 1 8].) (Reprinted with permission from Elsevier.)
Models of composite structure
Coagulum of SiC-agg lomerates
o
Fig. 7. Estimated composite structure models of a granule. In the models. the white part denotes the CaC03 component and the black denotes and agglomerate of SiC particles. (Adapted from Sugimoto et al. [ 1 8].) (Reprinted with permission from Elsevier.)
•
•
To separate the SiC particles from the granule, the CaC0 3 was dissolved with a HCI solution. The SiC agglomerates are named b-agglomerates. Further treatment applied attempted to break up clusters of SiC that had been formed during the treatments by using EDTA · · · 2Na in order to break bonds due to the presence of calcium silicate (Ca 2 Si04) which might be produced by heating the granule composed of SiC and CaC03 . The solution added did not have any effect on agglomerates of pure SiC that had been formed in the granulation process. These SiC agglomerates contained in the b-granules are named c-agglomerates.
The structure of the binary composite granules made of CaC0 3 and SiC powders is discussed in terms of the size distributions of SiC agglomerates
1 1 98
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(c-agglomerates) contained in the granules. They grouped the structure into three classes (A, B and C) according to the characteristics of the dispersion of Sie agglomerates in a single granule. Each of these groups was further divided into two-subgroups according to the mean diameters of the a, b and c-granules (sizes Dp , dpb and dpc, respectively). 5. I MAGING TECHNIQUES
Following the definition of structure as the spatial arrangement of the basic components of a granule [1], a technique capable of measuring it should give the spatial arrangement inside the granule either in two or three dimensions. Some of the techniques that can provide this kind of information are (from Kohlus [1]): •
•
•
•
SEM (scanning electron microscopy): standard tool to image microstructures. It has a high spatial resolution and good material contrast, therefore allowing the identification of different phases present in a granule. It is only a two-dimen sional technique though, and in order to image internal structures they have to be exposed, requiring slicing of the specimen to be analysed. An example of the application of SEM in characterizing agglomerate morphology can be seen in Ref. [ 1 9]. I R (infrared) microscopy: in this case infrared signal can be used for material identification. It presents the same disadvantages as SEM, and its spatial reso lution is much lower. MRI (magnetic resonance imaging): non-destructive three-dimensional tech nique. Uses nuclear magnetic resonance properties of the material. High spatial resolution but its success depends on the nature of the specimen to be analysed. XRT (X-ray tomography): non-destructive three-dimensional technique. Utilizes the X-ray absorption properties of the material. It has the highest spatial reso lution and if the X-ray source is of sufficient quality, the contrast between different materials is sufficient to be able to identify them and analyse the agglomerate structure (Fig. 8).
5.1 . Quantification of g ranule structure
A segmentation step is necessary in order to quantify granular structure from images, meaning that each point in the image has to be classified as part of one of the defined phases [1]. In the segmentation process, the main area of uncertainty arises when partial voxeling happens. This effect happens when two or more phases occur in a single voxel. When only one phase is present in a voxel the signal intensity will be characteristic of that phase, but when more than one phase is present the signal
1 1 99
Granule Structure
(a)
(h)
Fig. 8. Comparison of MRI and XRT images of single granules. (a) Cross section through a single granule using MRI, nominal resolution 35 x 35 x 50 11m (from Sochon [20]); (b) cross section through a single granule using XRT, nominal resolution 4.25 x 4.25 x 4.25 11m.
will be a combination of the contributions of the different phases. The quantitative limitations imposed by the partial voxeling effect have been subject to study in fields like medical imaging, and different approaches have been used in order to quantify and correct for this problem (e.g., [21 ]). Most research into this topic has been done in the field of medical imaging using MRI as the technique. A set of five key descriptors in order to quantify granule structure are proposed in [1 ] using imaging techniques as the basis for this analysis and include the amounts of the phase volumes, their sizes and a homogeneity measurement. 5.2. XRT (X-ray tomography)
X-ray tomography was initially developed by Hounsfield and Cormack [22-24]. For developing computer-assisted tomography both Hounsfield and Cormack shared a Nobel Prize for medicine in 1 979, a field in which this method was most likely to prove useful. XRT has been primarily used in medical applications, and further developed and applied in other areas of research, such as geosciences [25,26] or materials sciences [27]. This has been possible due to the fast technical development of its basic components (X-ray source, detector, specimen holder). The main advantages of XRT over other imaging techniques is that it allows for a non-destructive, three-dimensional evaluation of the internal structure of objects, with a continuously increasing special resolution as its physical components develop (it is claimed that features in the nanometre scale can be resolved).
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XRT measures variations in material density generating images of different cutting planes of the material, and three-dimensional maps of density and ele mental distributions can be obtained with high resolution and short scanning time. A more detailed description of how the technique works can be obtained in Refs. [28,29,30]. Owing to its origin weil outside the powder technology area, its applications are only starting to be explored in this area, but the potential of the technique is immense after the selection of the most appropriate scanning configuration, the use of the most suitable X-ray sources and detectors, selection of an appropriate X-ray energy, possible calibration and minimization of the artefacts created by the technique. A very interesting application of XRT to particle technology can be seen in Ref. [31]. XRT is used to characterize the internal structure of agglomerates. Two "test" granules were created with two different binders and two different primary powders, by dropping a single droplet of binder onto a bed of powder. XRT showed different structures: loosely packed for non-cohesive powders that let the binder disperse through the powder surrounding the nuclei and densely packed with cohesive powders with which the nuclei contract towards themselves. Further work was done on the potential of XRT to characterize granular struc ture that would then be used as an input for DEM modelling to verify and validate existing models [32]. A model granule was created and XRT used to characterize the three-dimensional location of the primary particles and their respective dia meters (Figs. 9 and 1 0). Simulations of a spherical-shaped granule produced within the DEM code were compared to those of the XRT characterized granule, showing different behaviour between the two different agglomerates, due only to structural and shape differences. XRT has also been used to calculate the total porosity, pore size distribution and geometric structure of pores in pharmaceutical granules and compare the results to data obtained with more conventional methods (mercury porosimetry and gas adsorption) [1 1]. Results showed that XRT is less precise in the deter mination of total porosity than the more conventional methods, but on the other hand the main advantage of XRT is that it provides detailed information about the true pore geometry and distribution within the granules in a non-destructive man ner. It also accounts for internal occluded pores, although its resolution may not yet resolve narrow pore channels. In this work, the granule is considered as a two component system: air and solid matter, with no differentiation between binder and primary particles. This way, the images resulting form XRT analysis had to be transformed to binary ones, hence the need to find a threshold value (Fig. 1 1 ). The effect of the amount of binder in the structure and behaviour of granules under stress has also been studied using XRT [ 1 0]. For this analysis the cross sections provided by the XRT analysis of the sampies had to be transformed into binary images by choosing a threshold value. As before, this transforms the
1 20 1
Granule Structure 1.0 Onwn Z-2.87Omm
(a )
3.0
2.0
4.0
1.0 •
2.0
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(b) Onwn 1.0 Z·2.323rnm
2.0
3.0
4.0
1.0 Z·'.mrnm
1.0
1.0
2.0
2.0
3.0
3.0
".0
(c)
4.0
2.0
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Fig. 9. X-ray microtomographs o f model granule. (a) Side view, (b) t o ( d ) cross sections at different heights (from Golchert et 81. [32]). (Reprinted with permission from Elsevier.)
(b) Fig. 1 0 . Model granule. (a) DEM reconstruction based on XRT characterization and (b) original X-ray image of granule (from Golchert et 81. [32]). (Reprinted with permission from Elsevier.)
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Fig. 1 1 . Reconstructed cross-section images fram XRT analysis of two different granules done under different granulation conditions, showing the difference in structure. (Adapted fram Farber et al. [1 1 ].) (Reprinted with permission fram Elsevier.)
(b) Fig. 12. Reconstructed cross-section images fram XRT analysis of granules at two dif ferent granulation times: (a) 1 80 s and (b) 900 s (fram Bouwman et al. [ 1 0]). (Reprinted with permission fram Elsevier.)
1 203
Granule Structure
1 mm
/ (a)
Fig. 1 3. Shadow image (a) of a single granule with three reconstructed slices through it at different cutting planes. The light areas correspond to materials that attenuate X-rays less (white corresponding to the background air), the darker areas correspond to more atten uating materials.
sam pie in a two-component system: air and solid, without differentiating between solid and binder (Fig. 1 2). On a scale bigger than single-granule analysis, XRT has been used in the powder technology area to measure density variations in tablets [33] and on an even bigger scale to characterize powder mixing [34]. As it can be seen, not much work has been done using XRT to resolve the structure of single granules. However, the application of this technique to the powder technology area offers great potential to develop physical insight on the single-granule scale, which would offer a great deal of information about how the agglomeration process works. Current work using XRT is focused on how different processing conditions affect the structure of agglomerates [35], and different methodologies to extract as much information as possible from XRT analysis on agglomerates are being developed [35] (Figs. 1 3-1 5). With the increasing availability of high-quality X-ray sources (synchrotron ra diation) and the development of the physical instruments that compose an XRT scanner (detectors, specimen holders, X-ray sources and computing power) this non-destructive technique has the potential to become an extremely useful tool in power technology, aliowing the resolution of each individual phase within a single agglomerate.
1 204
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1
mm
1
1
mm
Barrera-Medrano et al.
mm
1
mm
2
3
(a)
(b)
(c)
(d)
Fig. 14. Central cross sections of sampies at different impelier speeds, taken after 1 0 min of granulation time: (a) 200 rpm, (b) 400 rpm, (c) 600 rpm and (d) 800 rpm.
(b)
Fig. 1 5. Central cross sections of sampies at different granulation times (constant impelier speed of 200 rpm): (a) 2 min, (b) 4 min, (c) 6 min, (d) 1 0 min and (e) 1 5 min.
5. 2. 1 . XRT sampIes of different materials and granulation conditions
The following figures show different structures obtained by using X-ray tomo graphy to visualize the internal structure of agglomerates made up of different materials and obtained under different granulation conditions.
Granule Structure
1 205
1 mm Fig. 1 6. Example o f three cross sections through a typical high-shear granule made of CaC03 and polyethylene glycol (PEG). An X-ray shadow image of the corresponding granule is shown in (a).
(a )
1
•
mm
Fig. 1 7. Example of three cross sections through a typical fluidized-bed granule made of glass ballotini and PEG. The corresponding X-ray shadow image is shown in (a).
Figures 1 6 and 1 7 show the typical structures of granules made under high shear conditions and in fluidized beds. High-shear granulation agglomerates are typically compact and rounded whereas fluidized-bed granules tend to show a much more opened structure, giving the products very different properties. Figure 1 6 shows three cross-sectional images of a typical high-shear granule made using calcium carbonate primary powder and polyethylene glycol as binder. Figure 1 7 shows cross sections of a typical fluidized-bed granule made using glass ballotini primary particles bound together using a malten polyethylene gly col spray in a fluidized bed. The structure is much more porous compared with that shown by the high-shear granule. Figures 1 8-22 correspond to cross section of granules manufactured from different materials and under different granulation conditions, showing some of the different internal structures that XRT has discovered within single granules. The linear attenuation coefficient of the materials plays a key role in being able to identify different phases within an agglomerate. The bigger the difference in the linear attenuation coefficient, the better the contrast that can be obtained. The
1 206
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D. Barrera-Medrano et al.
(b)
Fig. 1 8 . Central cross sections of granules made with: (a) Na 2 C0 3 and zeolite as primary particles, bound together using LAS acid (proportions 63:23 : 1 4) in a food mixer; (b) pol ystyrene particles and a water binder which is subsequently evaporated off (binderless g ranule).
(a)
(b)
Fig. 1 9. Central cross sections corresponding to two granules extracted from the same batch. The g ranules were manufactured in a high shear mixer using calcium carbonate as primary particles and a mixture of polyethylene glycol and H PC as binder (liquid to solid ratio of approximately 0. 1 3). As it can be seen, the same conditions create two completely different structures.
linear attenuation coefficient for the different materials depends on the voltage applied to the X-ray source, hence the XRT scan can be tuned in order to obtain the best results. Figure 23 iIIustrates the different linear attenuation coefficients as a function of voltage for some materials commonly used in granulation.
1 207
Granule Structure I.'
,..
'.0
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1.0
'.0
..•
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Cross section of a polyethylene glycol (PEG) flake. PEG is commonly used as a binding agent, either added as a liquid or as a solid flake that melts during the granulation process. Fig. 20.
(a )
(b)
1 mm Fig. 2 1 . Central cross sections of high-shear granules after 30 s of granulation time. The granules are made of CaC03 and PEG added as solid flakes. In both cases, the gran ulations conditions are identical except the temperature, wh ich is of 60°C for the cross sections in (a) and of 80°C in (b).
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Central cross sections corresponding to two granules extracted trom the same batch. The granules were manufacture in a high shear mixer with lactose and starch as primary particles and a mixture of H PC and water as binder. As it can be seen, the same conditions create two completely different structures. Fig. 22.
CaC03 CaS04 Na2S04 NaOH Na2C03 K2C03 polyethylene ZnO
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.
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5. 2. 2. Application of X-ray tomography to the description of single granules: method development
XRT analysis on single granules provides a great deal of data in the form of a stack of adjacent cross-sectional images showing the internal microstructure of the sampie. A method developed to analyse these images to extract information about the structure of the granules can be found in Ref. [35] and is summarized here. The XRT images can be understood as a group of spatial coordinates (position vectors Xij, k = (ij,k)) with an associated greyscale intensity value, gij, k, which provides information on the material attenuation coefficient which is a function of the material density. Therefore, every pixel belonging to the granule can be ex pressed as a pair of position vectors with an intensity value, as seen in Fig. 24. The centre of mass of the particle, g, can be calculated by averaging the greyscale and the coordinates for every pixel within the granule for each of the cross sections obtained after XRT (equation (1 )) Once the centre of mass is known a scalar defining the position of all the granule pixels referred to it can be calculated (equation (2)). L: gij.kK x ij,k = --== (1) - L: gij.k ij,k .
_ _
(2)
y
[(K. Y- .l), g]
o
o
0 '------0---' 0
24. Schematic diagram showing a stack of XRT slices of a granule as a three-di mensional array of spatial coordinates and greyscale i ntensity values.
Fig.
1210
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i+1
Bin i+1
Fig. 25. Schematic representation of the binning procedure. The binning of the d ata con sists on dividing the radial axis in bins. The average greyscale value of all the pixels included in each bin is calculated and assigned to a radial distance corresponding to the middle point of the bin. This process is carried out in the three dimensions, by constructing spherical shells around the calculated centre of mass.
Once the scalar is known for each of the pixels in each image that belong to the granule all the images are transformed into pairs of greyscale intensity and radial distance to the centre of mass. The data is then binned by radius (see Fig. 25) and results can then be analysed in the form of radial distributions of greyscale intensity values. After the binning is done the data is in the form of pairs that can now be plotted. Many details have to be taken into account when carrying out this process, such as beam hardening, or the normalization of the radial distances. Details can be found in Ref. [35]. This method interprets the data from XRT in the form of radial dis tributions of greyscale intensities in within the granule as an indication of structure. As an example of the results obtained, Fig. 26 shows the radial profiles cor responding to the scans shown in Fig. 1 5. The granules used for this experiment were manufactured in a Zanchetta Roto Junior laboratory scale mixer, with a capacity of 1 0 L and a diameter of 30 cm. The unit contains a vertically mounted three-blade impeller which was set at a speed of 200 rpm and a lid-mounted chopper set at a speed of 1 400 rpm. Temperature is controlled through a water filled jacket and set to 60 oG. Granules were produced from Durcal 40 (an industrial form of comminuted calcium carbonate) as primary particles and po lyethylene glycol f1akes (PEG) as a binder. The PEG had an average molecular weight of 1 500 Da and a melting point of approximately 45 °G. This grade of Durcal (D40) has an Xso size of approximately 24 Jlm (volume basis). The binder was added using the melt-in technique, whereby the powder is preheated to the
121 1
Granule Structure
80 Cl
70
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40
2min 4min - - - - 6min
30
. .. .. .. .. ���:�
20 0.0
0.2
0.6
0.4
0.8
1 .0
rls Fig. 26. Radial profiles corresponding to the scans shown in Fig. 1 5. Each line represents five granules of the same characteristics.
desired temperature at a low impeller speed, and the binder is then added at once as a solid at room temperature at the start of the experiment. Each of the Iines in Fig. 26 corresponds to the average of five granules per sampling time and the x-axis has been normalized by dividing the radial distance by the radius of gyration. High-greyscale intensities correspond to higher ab sorption of the X-rays. As it can be seen, there is a consolidation towards the edge of the granules (higher density areas towards the edge), as weil as in creased density with increasing granulation time. This can be understood by looking at the cross sections, as they show a core of binder that decreases as granulation time goes, although it is still present even after 1 5 min of granulation time (due to the low shear at which the experiment was carried out).
REFERENCES [ 1 ] R. Kohlus, U nilever R & D, Vlaardingen, The Netherlands, presented at the 4th World Congress in Particie Technology, Sydney, 2002. [2] D.E. Fonner, G.S. Banker, J. Swarbrick, J. Pharm. Sei . 55 ( 1 966) 1 81-1 86. [3] G.K. Reynolds, CA Biggs, AD. Salman, M.J. Hounslow, Powder Technol 1 40 (2004) 203-208. [4] P.J. Rue, H. Seager, J. Ryder, I. Burt, I nt. J. Pharm. Tech. Prod. Manuf. 1 ( 1 980) 2-6. [5] H . Seager, P.J. Rue, I. Burt, J. Ryder, J . K. Warrack, I nt. J. Pharm . Tech. Prod. Manuf. 2 ( 1 981 ) 4 1 -50. [6] H. Seager, I. Burt, J . Ryder, P. Rue, S. Murray, N . Beal, J . K. Warrack, I nt. J . Pharm. Tech. Prod. Manuf. 1 ( 1 979) 36-44. [7] H . Seager, Manuf. Chemist Aerosol News ( 1 977) 25-35.
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[8] A. Samini, M . Ghadiri, R Boerefjin, A Groot, R Kohlus, Powder Techno! . 1 30 (2003) 428-435. [9] P.C. Knight, Powder Technol. 1 1 9 (2001 ) 1 4-25. [1 0] A M . Bouwman , M.J. Henstra, D. Westerman, J .T. Chung, Z. Zhang , A Ingram, J.P.K. Seville, HW. Frijilink, I nt. J. Pharm. 290 (2005) 1 29-1 36. [1 1 ] L. Farber, G . Tardos, J . N . Michaels, Powder Technol 1 32 (2003) 57-63. [ 1 2] M . H . Rubinstein , K. Ridgway, J. Pharm. Pharm. 26 ( 1 974) 24-29. [ 1 3] K. Ridgway, M . H . Rubinstein, J. Pharm. Pharm. 23 (Supp!.) ( 1 97 1 ) 1 1 S-1 7S. [ 1 4] K. Ridgway, M.H. Rubinstein, J . Pharm. Pharm. 23 ( 1 97 1 ) 587-589. [ 1 5] M . E. Aulton, M. Banks, I. Davies, Drug Dev. Ind. Pharm. 4 ( 1 978) 537-539. [ 1 6] M . J . Gamlen, H. Seager, J . K. Warrack, I nt. J. Pharm. Tech. Prod. Manuf. 3 ( 1 982) 1 08-1 1 4 . [ 1 7] M . Sugimoto, D. Tojima, K . Yamamoto, S. Rengakuji, J . Soc. Powder Techno!. Japan 36 ( 1 999) 685-691 . [ 1 8] M . Sugimoto, I. Takehiko, Y. Ken-Ichi, M. Tosihiaki, Powder Techno!. 1 30 (2003) 442-449. [ 1 9] L. Rodriguez, C. Cavailari , N. Passerini, B. Albertini, M.L. Gonzalez-Rodriguez, A Fini, I nt. J. Pharm. 242 (2002) 285-289. [20] R Sochon, MEnG Research Project, The University of Sheffield, 2005. [21 ] MA Gonzalez-Bailester, AP. Zisserman, M. Brady, Med. Image Anal. 6 (2002) 389-405. [22] G . N . Hounsfield, A method and apparatus for examination of a body by radiation such as X-ray or gamma radiation, Patent Specification 1 2839 1 5, 1 972. [23] A.M. Cormack, J. Appl. Phys. 34 ( 1 963) 2722-2727. [24] A M . Cormack, J. Appl. Phys. 35 ( 1 964) 2908-291 3. [25] RA. Ketcham, WD. Carlson, Comput. Geosci. 27 (2001 ) 381-400. [26] A Macedo, S. Crestana, Soil Tiilage Res. 49 ( 1 998) 249-253. [27] L. Salvo, P. Cloetens, E. Maire, S. Zabler, J.J. Blandin, J .Y. Buffiere, W. Ludwig, E. Boiler, D . Bellet, C. Josserong , Nucl. Instru m . Meth. Phys. Res. B 200 (2003) 273-286. [28] B . P. Flannery, H W. Deckman, w.G. Roberge, K.L. D'Amico, Science 237 ( 1 987) 1 439-1 444. [29] ASTM, ASTM designation E 1 44 1 -92a, Annual Book of ASTM Standards, Section 3, ASTM, Philadelphia, 1 992, pp. 690-7 1 3 . [30] J . Barruchei, J .Y. Buffiere, E . Maire, P. Merie, F. Peix, X-ray tomography in material science, Hermes Science Publications, Paris, 2000. [31 ] D.J . Golchert, L. Farber, L.X. Uu, J D. Uster, N.W. Page, Proc. World Congress of Particle Technology 4, Sydney, Australia, 2002. [32] D.J. GOlchert, R Moreno, M. Ghadiri , J. Utster, Powder Techonol . 1 43-144 (2004) 84-96. [33] I.C. Sinka, S.F. Burch, J.H. Tweed, J . C. Cunningham, Int. J. Pharm. 271 (2004) 2 1 5-224. [34] C.Y. Yang, X.Y. Fu, Powder Technol. 1 46 (2004) 1 0-1 9. [35] D . Barrera-Medrano, PhD Thesis, The University of Sheffield, 2007.
CHAPTER 26 M o r p h o l ogy a n d Stre n gth Deve l o pm e n t i n Sol i d a n d Sol i d ify i n g I nterparticle B ri d ges i n G ra n u les of P ha rm a ce utical P owders G . I . Tardos, 1 , * L. Farber, 2 D . B i ka 2 and J . N . M ichaels2
1 The City College of the City University of New York, New York, NY 10031, USA 2Merck and Co. Inc., West Point, PA 19456, USA Contents
1. 2. 3. 4. 5.
Introduction The key issues Background and literature review Extended summa ries of the contribution Experimental 5. 1 . Materials 5.2. Solutions 5.3. Bridges 5.4. Bridges between tablets 5.5. Granule formation 5.6. Granule strength measurement 5.7. Polymer films 5.8. Optical microscopy 5.9. X-ray powder diffraction 6 . Theoretical 6. 1 . Crush strength model 6.2. Re-crystallized bridge model 6.3. The auto-adhesion model (JKR theory) 7. Strength of solid bridges and dry granules: results and discussion 7. 1 . Slightly soluble systems: ethanol-based granulating solutions 7.2. Soluble systems: aqueous granulating solutions 8. Evolution of drying material bridges: results and discussion 8. 1 . Lactose bridges 8.2. Mannitol bridges 8.3. Granules 9. Conclusions 1 0. Forward look Acknowledgements Appendix: Prediction of dry bridge strength References
*Corresponding author. E-mail: [email protected]
Granulation Edited by A D. Salman, MJ. Houns/ow and J. P. K. Seville ( 2007 SV '
Elsevier
All rights reserved
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G . 1 . Tardos e t 8/.
1 . I NTRODUCTION
Granulation is used extensively in industry to produce larger granules from fine powdery particles to improve flowability and appearance, reduce dustiness and to ensure thorough mixing of different ingredients. This last application is a very important unit operation in the pharmaceutical industry to produce non-segre gating mixtures of dry powders that would otherwise strongly segregate due to differences in size, shape, density and surface properties. The so-ca lied "wet" granulation process uses liquids that are dripped, sprayed or poured into a shearing mass of powder. The granulating fluid is typically composed of water and/or alcohol and may contain surfactants and polymeric binders such as hydroxypropyl cellulose (HPC) or polyvinylpyrrolidone (PVP). The process by which large dry granules are formed from fine powders by using liquid binders is quite complex. An accepted view holds that the liquid solution wets and spreads in the interstices between primary particles, forming liquid bridges that hold them together by capillary and viscous forces. These wet or "green" granules are subsequently dried and liquid eva po rates from the bridges to leave behind solid bridges or "necks" that impart mechanical strength to the dry granule. The process of solid bridge formation from pendular liquid bridges between particles is not unique to granulation and in fact plays a significant, albeit un wanted role in powder caking. In this case, liquid (water) is extracted from the surrounding atmosphere and condenses in the interstices between particles to form liquid bridges that subsequently dry. The result is the formation of large, strong lumps in the otherwise free-flowing powder that have to be broken to ensure powder flow. There is very little in the open literature that describes the morphology and properties of solid bridges that are formed between primary particles during granule formation and/or powder caking. While the strength of solid bridges has been recognized by Pietch [1] to have a strong influence on the tensile strength of agglomerates (granules and lumps), the intrinsic strength of the bridge itself was not studied in detail. To simplify the problem, the solid bridge is assumed, in most cases, to be non-porous and of similar chemical composition and physical prop erties as either the primary powder particles or the polymeric binder material used. This, however, is an overly simplistic view of a very complex problem especially if the original fine powder is itself soluble in the binder solution. In this case, the liquid partially dissolves some solid powder and forms liquid bridges of a very complex composition. Upon drying, these bridges exhibit intricate patterns of crystallization that are both time and composition dependent. This behaviour imparts complex morphology to the drying bridge as weil as time-dependent strength to the forming dry granule.
Interparticle Bridges in Granules of Pharmaceutical Powders
1 21 5
2 . THE KEY ISSUES
Figure 1 shows a schematic of a dry granule produced with granulating fluid containing a polymeric binder. Assuming some solubility of primary particles in the fluid, the liquid bridges are multi-component solutions that may form solid bridges of complex microstructure when dried. A few scenarios are shown in the figure. The bridge on the left consists of filaments of polymer, while the bridge on top contains both the polymer and a solidified crystalline bridge formed by re crystallization of the base powder. The bridge on the right is pure re-crystallized base powder. The bridge at the boUom is a combination of a small primary particle embedded in re-crystallized base powder. Clearly, these are only some of a large variety of combinations that could exist in reality. The questions that need to be answered are (i) what kind of solid bridge will actually form inside the granule as liquid eva po rates and further, (ii) what will characterize its strength, and (iii) where will it break when subjected to a mechanical load? Will it break by fracture of the body of the bridge or by adhesive failure at the interface with the primary particle? Answers to the above questions are central to the strength of formed dry granules since it impacts all further down-stream operations such as pneumatic transport, fluidization, comminution, tabletting, dissolution, etc. Knowledge of dry granule strength is also very important because it is a measure of the quality of bonding of various components inside the granule. Intimate bonding and good mixing of ingredients are both reflected in high dry strength. Since granule strength measurements are relatively simple, one gains a straightforward meas ure of important intrinsic granule properties that would otherwise require very sophisticated instrumentation and procedures to obtain. We describe in this chapter extensive work to study, on one hand, the strength and morphology of solid bridges inside dry granules of complex composition, and Solid Particles
� Polymer (binder) � bridge
C----.J
� �
Solidified bridge from saturated solution Dry particle (crystalline) bridge
Fig. 1 . Schematic of dry inter-particle bridges formed by co-precipitation of base powder and polymer.
1216
G . 1 . Tardos e t al.
on the other, the evolution in time of drying bridges made of complex solutions of binder and base powder. In the first part, we measure the strength of dried mannitol and lactose granules and characterize them with X-ray tomography and microscopy to shed light on the morphology, composition and attachment of the solid bridges to particles inside the granules. We also pro pose a theoretical framework based on crack-propagation theory to explain the findings. The sec ond part is a mostly experimental, micro-Ievel study of bridge solidification. It is weil known from previous work (see, for example, Ref. [2]) that it is very difficult to identically reproduce bridges formed between two small grains of powder due to variability in local shape and surface properties. For this reason, we describe model bridges with well-defined geometries to investigate the solidification kinetics and phase composition of drying bridges. The model geometries used in the present work are drying of a droplet on an inert substrate and evaporation from a solution stretched in the form of a pendular bridge between two flat plates. Further, evidence is given to show that real bridges between small particles actually exhibit similar behaviour as the model geometries mentioned above. 3. BACKGROUN D AND LITERATURE REVIEW
Wet granulation is an intermediate step in processing that leads to the manu facture of tablets. The process is used intensively in pharmaceutical applications because it assures homogeneous mixing of different powdery ingredients that otherwise would tend to segregate. It is also used in many other applications including the sOlid-detergent industry, to produce chemically active powders of several different ingredients that are free flowing and have pleasant appearance. The process of wet granulation entails the introduction of a liquid binder into a continuously moving and deforming powder bed of small particles contained in a processing vessel. Coalescence and growth of the initial powder feed results in the formation of "wet" or so-ca lied "green" granules [3-5]. Strong solid bridges that hold the granule together develop from liquid bridges during a subsequent drying step. In traditional granulation theory it is assumed that a binder such as a polymer is required to hold particles together once granules form in the granulator and are dried. It has been also suggested that even though some base powders may be somewhat soluble in the granulating liquid, the polymeric binder is still required to assure appropriate granule strength. Ongoing work performed in our laboratory shows however that base powders that are strongly soluble in the liquid binder play a major role in the formation and strength of solid bridges inside a granule [6]. Formation and strength of liquid bridges between fine particles has been stud ied extensively (see, for example, Ref. [2]. More recently, Pepin and co-workers [7] applied the knowledge gained from the study of these bridges to the strength
Interparticle Bridges in Granules of Pharmaceutical Powders
1217
of moist agglomerates such a s "green" granules. Solid bridges, o n the other hand have been studied to a much lesser extent. Shinohara's chapter in the Handbook of Powder Technology, Chapter 4 [8] dedicates to the subject a short subsection where the basic assumption is that the material in the solidified bridge has iden tical properties as the material of the particles that it holds together. Pietch [1] in his monograph on agglomeration processes takes a very similar approach. How ever, it has been shown by Tardos and Gupta [9] that solid bridge properties strongly depend on the composition and drying rate of the bridge itself. In the work described here (see also Ref. [1 0]) we measure the strength of granules containing bridges made of several ingredients such as binders and dissolved base powders and observe the microstructure of individual solid bridges and their time evolution directly in an effort to understand the factors that determine inter particle bridge strength. The choice of base powders used during the work described herein was dictated by funding and was justified by their extensive use in many pharma ceutical formulations employing wet granulation. Use of lactose and mannitol base powders for this investigation does not take away from the generality of the results since these materials exhibit overly complex structures and behaviour that may be generalized to other complex systems. Mannitol is a compound that can exist in several crystalline polymorphie forms and is soluble in water. Lactose is also water-soluble and exists in two anomeric forms (IX and ß); it can crystallize from aqueous solution into stable andjor unstable monohy drate or anhydrous forms or remain amorphous. Moreover, conversion from one anomer andjor crystal form of lactose to another may occur spontaneously even at room temperature depending on relative humidity (RH). It is also known that the source of lactose, even of the same grade but produced by different suppliers, can strongly affect the granulation process, suggesting that variability in phase purity between suppliers and form stability during processing may be significant. Hence, we also present results for these different materials to show that slight variations in composition can have a major impact on specific results. 4. EXTENDED SUMMARIES OF THE CONTRIBUTION
Work described in the first part of this chapter is an experimental study of solid bridges formed between particles inside granules of several pharmaceutical base powders such as lactose and mannito!. Particles are held together in the granule by re-crystallized bridges of the base powder and by several polymerie binders such as HPC and PVP. We studied an ethanol-based system where base pow ders were only slightly soluble in the binder and where the main binding agent was the polymer. We found that in this system bonds are very strong when the
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G . I . Tardos e t al.
polymer is present and compare to the strength of individual polymerie films. In the absence of polymer, dry bridges between particles attain the strength of the theoretical base powder crystal (Griffith strength). In a second, more complex aqueous system, both base powders and polymers were highly soluble. Bonding between particles in this case was due to a com bination of base powder-polymer bridges. We found that the bridge strength is a direct funetion of the total amount of liquid present in the original liquid bridge, i.e., large liquid bridges form stronger dry bridges. This is mainly due to the total amount of (solid) material present in the bridge upon drying. Compatibility be tween the polymerie binder and the base powder also strongly influences the strength of the bridge. When the polymer is ineompatible with the solid powder such as for example PVP and mannitol, the bond strength is decreased some times by as much as 50%. This is due to the fact that upon drying and re crystallization, the polymer and powder separate into different phases and the final bridge is weakened. This is especially true for the PVP film which in itself is brittle and therefore makes a weak bridge. When polymer and powder are com patible such as in the case of H PC and both base powders are used (lactose and mannitol), the bridge strength is increased when the polymer exceeds a certain eoncentration but does not reach either the strength of the pure polymerie film or the strength of the theoretical crystal. In part two of the work, an experimental procedure was developed to study directly the process by which liquid bridges between small particles in a granule form and solidify. The evolution of saturated solutions of lactose and mannitol in a liquid bridge was studied on a system situated on a microscope slide. Solidifi cation and crystallization kinetics and phase composition during and immediately following bridge formation were observed directly. It was shown that bridges on the mieroscope slide and in the granule behave very mueh the same regardless of the different length and diffusion-scales of the two systems. We found that solid bridge formation takes plaee in several eonsecutive but distinet steps. In the case of lactose, considerable shrinkage of the initial liquid bridge takes plaee prior to the onset of crystallization. Further bridge solidification at ambient conditions oceurs via simultaneous crystallization and vitrification within minutes. As a result, a "solid" or "green" bridge usually contains both a crystalline and a non-crystalline phase, the erystalline phase being predominately a-Iactose monohydrate. Most of the non-crystalline phase eventually converts to crystalline ß-Iactose but the process may take many hours or even days. Results for this process are compared for sam pies obtained from different manufacturers of eommercially available lactose. In the case of mannitol, different polymorphie forms erystallize as the dryingjcrystallization process progresses. A formed "solid" bridge usually eontains several polymorphs of mannitol. The relevance of the behaviour of the two model systems to a real granulation and tabletting process is discussed.
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Interparticle Bridges in Granules of Pharmaceutical Powders
5 . EXPERI MENTAL 5.1 . Materials
All materials used during this experimental program are described in Table 1 . Lactose monohydrate from three different manufactures, spray-dried lactose and the anhydrous lactose were used in different phases of this study in addition to one grade of mannito!. So me of their physical characteristics are given in Tables 1 and 2 where base powder (sugar) characteristics and polymer and surfactant properties are given, respectively. Granules for strength measurements were prepared from lactose (Meggle) or mannitol powders with ethanol (HPLC grade, Aldrich #27,074-1 ) or water (USP) as granulating fluids. In several experiments, Table 1 . Properties of mannitol and lactose
Powder Mannitol Lactose (monohydrate)
Lactose (spray dried) Lactose (anhydrous)
Origin SPI Polyols Roquette DMV Pharma Meggle Foremost Farms Foremost Farms Quest
Trade name/ grade SD-200 Roquette 35 Pharmatose 200M Granulac 200 NF Lactose 312 Spray dried Sheffuke Brad Lactose NF
Solubility in water es (g/ml) 0.18 0. 1 8 0.21
Solubility in ethanol Cs (g/ml) 0.01 0.01 0.0001
0.21 0.21
0.0001 0.0001
0.21
0.0001
0.21
0.0001
Table 2. Properties of H PC and PVP
Polymer
Grade
Molecular weight
Saturation concentration in water (%)
Polyvinylpyrrolidone (PVP) Hydroxypropyl cellulose (HPC)
K29/30
50 K
43
Klucel EXF
80-1 00 K
5-7
1 220
G.I.
Tardos et al.
hydroxypropyl cellulose (HPC) and polyvinylpyrrolidone (PVP) were used as polymerie binders (see properties given in Table 2). In a few experiments surfactants such as sodium lauryl sulfate, Polysorbate 80 and Triton X were also dissolved in the granulating fluid. 5.2. Solutions
Solutions were prepared using corresponding amounts of powder (lactose and mannitol, respectively) and H PLC grade water. Powder to water ratios were 1 :5.6 and 1 :4.6 for mannitol and lactose, respectively, i.e., the saturation limits for the excipients at 22°C [1 1 ]. Typically, the solution cleared after 1 5 min of stirring with magnetic stirrers, suggesting that the solutions were not completely saturated. These solutions are however referenced in the text as "saturated". In most cases, freshly prepared solutions were used within 30 min after mixing of the powder in water. In some cases, the same solutions were used after several days. No visual changes in the solution were observed during that period. 5.3. Bridges
Two different bridge geometries were investigated: (i) a single droplet on a flat glass slide and (ii) a liquid droplet stretched between two glass slides situated a small distance apart. The two geometries are depicted schematically in Fig. 2. For the first geometry, a droplet of saturated solution was dropped from a syringe from approximately 1 cm distance on a conventional microscope glass slide that had been cleaned by dipping it into a soap solution followed by rinsing in de ionized water and drying with compressed air (Fig. 2(a)). In some cases, several solid particles of either the same excipient or microcrystalline cellulose (Avicel PH1 01 ) were placed on the slide; these were added to study the effect of seeding the crystallization of the bridge. This situation is represented in Fig. 2(b). In the case of the bridge between two slides, a droplet was placed on a clean micro-
a
,
J
.
�
:2dZ ;{0J 4r c
glass silde
Fig. 2. Schematic representation of model inter-particle bridges: (a) droplet on a slide; (b) droplet on a slide with several grains of the original powder used as nucleating agents; and (c) bridge between two microscope glass slides.
1 22 1
Interparticle Bridges in Granules of Pharmaceutical Powders
scope slide with a syringe, and a second glass slide was brought into contact with the droplet. This resulted in immediate redistribution of the liquid and formation of a liquid bridge between the two glass slides. I mmediately after the contact and formation of the bridge, slides were pu lied slightly apart and fixed, so that the distance between the slides was constant through each drying experiment. Bridge geometry is shown schematically in Fig. 2(c). Overall, the distance bet ween slides va ried in a range 0.6-1 mm. The bridge microstructure was moni tored as it dried in each of these geometries using optical microscopy. Typical ambient conditions of these experiments were 23°C and 65% RH. 5.4. Bridges between tab lets
To investigate the microstructure and strength of inter-particle bridges directly, we produced macroscopic bridges between tablets of lactose or mannito!. The tablets, approximately 1 0 mm in diameter and about 6 mm thick, were com pressed in a manual tablet press at approximately 9.2 MPa to produce smooth surfaces with minimal change in porosity. A schematic representation of the formation process of liquid bridges between tablets is shown in Fig. 3. The tablets were fixed in a vertical position on two holders, and the bridge was formed by filling the gap with granulating fluid and several particles of base powder to ensure saturation. After drying at room tem perature and 25% RH for 48 h (at similar conditions as the granules themselves) the pair was broken in three-point bending mode using the Texture Analyzer as described below. The doublet made of two tablets with the solidified bridge between them was laid flat on its side and broken with the force applied on the middle of the bridge. Both X-ray tomography and microscope images were taken of the tablet pair before and after breaking and an example is shown in Fig. 4. One can easily see the measured, delimited area of the broken bridge in the figure; this value was used in the calculation of the bridge strength (Tables 3 and 4). Binder solution Liquid bridge
/
Double stick tape Holder
Tablets Fig. 3.
Holder
Grains of powder
Procedure to form macroscopic bridges between two base powder tablets.
1 222
G.I.
Tardos et al.
Photograph of broken bridge between two tablets showing the method of meas uring the area of the broken bridge used to determine its strength.
Fig. 4.
5.5. Granule formation
"Granules" produced with ethanol as the granulating fluid were prepared by compressing a bed of partieIes in a rectangular die as shown schematically in Fig. 5. Binder solution was added in an amount to ensure complete liquid saturation after consolidation. The consolidation pressure used ( 1 .5 MPa) was sufficient for liquid distribution and particle consolidation, but not enough for par ti e1e deformation. The advantage of this method is the formation of a single "granule" in the shape of a beam whose strength can be measured reproducibly [1 2 , 1 3] . The sam pie was dried at room temperature and 25% RH. Granules produced with aqueous granulating fluids were prepared by drop granulation in a unit specially constructed to produce very low shear during granule formation. The low-shear environment was required for these granules, since shear forces during agglomeration can overwhelmingly control granule properties. Granules produced under low shear more e1early exhibit the material factors that control their properties such as wetting and spreading of binder and the solubility of the primary partieIes in the granulating fluid. The "very low-shear granulator" (VLSG) used during this work was a horizon tally rotating bowl filled with powder to a specified level. The binder was fed to the bowl through a loss-of-weight system, a peristaltic pump and a straight copper tube of inner diameter of 1 /8 inch. During granulation, the granulating fluid drop lets gently fell onto the surface of the powder and were partially buried into the
Table 3 . Strength of dry granules formed in slightly soluble systems (ethanol-based granulating solutions)
Powder O"ta blet (Mpa)
Polymer
Mannitol (Roquette 35)
None PVP
H PC Lactose
None PVP HPC
Polymer concentration (wt.%)
0.7 1 .6 2.8 4.4 0.7 1 .4 0.75 1 .5 3.0 0.73 1 .5
a Back-calculated using equation (6) with b
(equation 6 ) a O"cr
Cs (g/g)
(h q
0.010 0.01 7 0.026 0.038 0.054 0.01 7 0.024 0.000 0.0075 0.01 5 0.030 0.0073 0.01 5
0.32 0.32 0.32 0.32 0.32 0.32 0.32 0.37 0.37 0.37 0.37 0.37 0.37
=
0.288 and c
=
0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.40 0.40 0.40 0.40 0.40 0.40
O"G (MPa) (equation 7)
O"sb
(MPa)
(MPa)
0.47 3.10 3.40 3.40 4.50 2.00 2.80 0. 1 6 1 .00 1 .64 1 .81 2. 1 1 2.87
5.87 34.0 31.2 26.6 30.4 1 9.7 26.6 1 6.7 20.4 1 6.8 35.6 35.7
4.43
O"film
(MPa)
20--40
1 0-20 20--40 1 0-20
1 1 .5
0.42.
->.
N N VJ
Table 4. Strength of dry g ranules formed in very soluble systems (water-based g ranulating solutions)
Powder Mannitol ( SD200 )
Polymerl surfactant None Triton X SLS Polysorbate 80 PVP
HPC
Lactose
Polymer concentration (wt.%)
None PVP HPC
1 .0 1 .0 1 .0 3.0 3.0 3.0 5.0 7.0 1 0.0 30.0 3.0 3.0b 5.0 5.0b 30.0 5.0
Cs (gIg)
rl i q
(Jsb (MPa) (equation (MPa) (measured) (measured) 6) a
0. 1 8 0.18 0.18 0.1 9 0.1 9 0.19 0.21 0.21 0.21 0.23 0.25 0.28 0.48 0.21 0.21 0.23 0.23 0.21 0.51 0.26
0.19 0.23 0.28 0.212 0.207 0.2 1 8 0.19 0.24 0.31 0.31 0.32 0.31 0.37 0.33 0.22 0.42 0.34 0.12 0.38 0.45
0.69 0.69 0.69 0.69 0.69 0.69 0.65 0.65 0.65 0.65 0.65 0.65 0.60 0.70 0.70 0.64 0.70 0.60 0.60 0.64
8
a Back-calculated using equation (6) with b = 0.717 and b Granulating solution pre-saturated with mannito!.
c = 0.5.
(Jer
0. 1 2 0.14 0.17 0.057 0.083 0.075 0.095 0.12 0. 1 3 0.1 5 0.20 0.24 0.43 0.21 0. 1 5 0.54 0.24 0.13 2 . 03 1 .12
1 .14 1.10 1.10 0.46 0.69 0.59 0.65 0.61 0.54 0.57 0.68 0.75 0.54 1 .03 1 .09 1 .45 1 .06 1.11 2.32 2.49
(JG (MPa) (equation
7)
(MPa) (measured)
(Jfilm
(MPa) (measured) (Jta blet 0.80
4.98
20-40
0.73 1 0-20
0.93 2.25
4.70
1 .03 20-40 1 0-20
1 .47 G) :-
-l tIl a. 0 (f) C1l ..... Q) :-
I nterparticle Bridges in Granules of Pharmaceutical Powders
1 225
I F = 50 kg .. 0.01 mmls v =
Fig.
5. Procedure to form beam-shaped granules (test specimens).
Fig. 6.
Typical granules produced in the very low-shear granulator (VLSG).
powder with a metallic plough. The liquid tended to wet a region of the powder and spread radially to form a spheroid-shaped granule approximately 5-8 mm in diameter. Upon the formation of up to 1 00 granules, the remaining ungranulated powder was separated by sieving from the granules, and the granulated material was then dried in an oven at 50°C. Pietures of granules produeed in this manner are shown in Fig. 6, while an X-ray miero-tomographie seetion of a granule is shown in Fig. 7. The granules are quite homogeneous but not very dense, with porosities of the order of about 70%. Granule moisture eontent was measured direetly by weighing the wet and dry granules, and also by using an automatie gravimetrie moisture analyzer (Sartorius LabServe MA-40).
1 226
G . I . Tardos et al.
Fig. 7. X-ray tomographie eross-seetion of a granule produeed in the VLSG.
5.6. Granule strength measurement
To measure the dry strength of the beam-shaped granule bars, three-point bending measurements were performed using the TA-XT2i HR Texture Analyzer (Texture Technologies Corp., Scarsdale, NY). The pracedure is described in more detail in Bika e t 81. [6]. The crush strength was determined fram Ref. [14]: (Jcr =
3LFmax 2fw
(1)
where L i s the distance between the fulcrums, Fmax the load at breakage, t the thickness of the beam and w its width (see Ref. [1 5] for more in-depth analysis). The crush strength of spheroidal granules formed fram the VLSG were meas ured by compression between parallel platens. Prior to measurement, granules were maintained in a humidity-contralled box at room temperature and 25% RH for 48 h. Dry granules were crushed at 25% RH and ambient temperature using the Texture Analyzer. During each measurement, the total force, F at breakage and the diameter of the granule, dg, were determined. Assuming the granule
Interparticle Bridges in Granules of Pharmaceutical Powders
1 227
cross-sectional area to be circular in the plane of the punch, the crush strength is calculated by 4F (2) (Jer = ndg2 -
The crush strength can also be a function of the contact area between the particle and the platen of the instrument. In the present application, however, it was assumed that the granules are very brittle and relatively weak and failed by crack initiation caused by tension in a diametrical plane parallel to the applied force. This assumption was supported by the fact that most granules were seen to split into two halves and no plastic impressions were observed on the fractured granules. 5.7. Polymer films
Mechanical testing of the polymers used in this study was conducted on free standing films. To produce an H PC film, about 1 0 mg of 5% by weight polymer solutions in water was poured into the dish and allowed to dry at ambient tem perature and 1 5% RH. After drying, films were conditioned at ambient temper ature and 1 5% RH prior to testing. This procedure resulted in semi-transparent, macroscopic crack-free, freestanding films with thickness ranging from 0.05 to 0.5 mm. The final moisture content was measured by loss on drying at 50°C for 48 h to be about 1 .2% by total weight. The films were removed from the casting surface, cut into strips or dumb-bell specimens of standard sizes and subjected to tensile testing. All sampies were tested using the Texture Analyzer according to ASTM and ISO standards [1 6, 1 7]. All tests were performed at room temperature and 1 5% RH. The elongation force was recorded as a function of the displacement. The film stress was calculated from the relationship: F (3) (Jf = A
where F is the measured peak force preceding breakage, and A the initial cross sectional area of the specimen. The reported film strength values are averages of 1 0 tensile measurements. PVP films were cast on plastic weighing boats laid with Teflon paper as a substrate. 50% wjv PVP solutions were poured into the dish and allowed to dry and equilibrate at room temperature and 1 5% RH. The resulting freestanding films were from 0.3 to 0.6 mm in thickness, yellow, transparent and fragile. During drying numerous cracks developed throughout the film. The moisture content was found to be 6-7% by loss on drying at 50°C for 48 h. To perform tensile testing of these sampies, smalI, non-cracked pieces were isolated and tested under three-point
G . 1 . Tardos et al.
1 228
bending using the Texture Analyzer. Average values of 1 0 tests are reported for the tensile (bend) strength calculated using equation (1 ). 5.8. Optical m icroscopy
An Olympus SZX 1 2 stereomicroscope and an Olympus BH1 2 microscope equipped with standard image acquisition cameras and software were used for "Iow-magnification" and "high-magnification" observations, respectively. 5.9. X-ray powder d iffraction
Powder X-ray diffraction (PXRD) measurements were made with a Bruker Siemens D5000 using Cu Ka radiation (tube operated at 40 kV/40 mA). The hardware included a parallel beam mirror, 1 and 0.6 mm diverging beam splitters and a graphite monochromator. The powder sam pie was lightly packed into the standard sam pie holder and the top surface was smoothed using a glass micro scope slide. Data were collected in a 20 range from 5 to 45° under lock-coupled scan mode with a step size of 0.02° and a step time of 1 s. To study the granule's crystalline structure and to identify the crystalline phases present in the dry body, some granules were kept either in a humidity-controlled dry box (1 5% RH/23°C) or on a bench top (�65% RH/23°C). After several days they were hand ground with a mortar and pestle and analysed by XRD.
6. THEORETICAL 6. 1 . Crush strength model
We reproduce here the equation to predict crush strength of a granule (Jcr from the knowledge of the solid bridge "neck" strength between particles (Jsb, which is derived in the appendix (equation (A.7)): (Jcr = nb2
1
-
I:
--
I:
[ ] Cs Vb
�
ppop/8
2c
(Jsb
(4)
here is the porosity, es the total dissolved solids concentration in the liquid bridge and Vb the liquid bridge volume. The quantities Pp and dp are the primary particle density and diameter, and b and c are numerical coefficients given in Table A 1 . The basic assumptions in the above equation are that particles forming the agglomerate are spherical and the solid bridge is formed by evaporation of a liquid bridge that conserves its shape as it shrinks and precipitates its dissolved I:
1 229
I nterparticle Bridges In Granules of Pharmaceutical Powders
solids. We rewrite the above equation by using the "liquid ratio" defined as P Vb V liiq = Pb Vp = Pnb b/6 p pp �
(5)
where P b is the binder density. With this, equation (4) becomes 2c 1 2 c C = nb 8- :3 Lliiq O"sb O" r _
where CL
=
[4n ]
I::
(6)
Cs /Pb is the solid concentration in the binder solution expressed in gIg.
6.2. Re-crystal lized bridge model
If the base powder has appreciable solubility in the granulating fluid, the solid bridges will be formed by re-crystallization (or precipitation) of the base powder as the bridge dries. An upper limit to the strength of this bridge can be calculated assuming that the final bridge is a non-porous brittle solid with the same mecha nical properties as the base powder. In this case, the bridge tensile strength is described by the Griffith model [1 5]: O"G
=
2EOY J ne
e
-
( 7)
here Eo is the Young's modulus, y the surface energy and a characteristic defect size. In calculating the ideal lactose and mannitol solid bridge strength, we used Young's moduli of compacts tabulated by Rowe and Roberts [1 8]. These values were extrapolated to zero porosity using the expression developed by Boccaccini [ 1 9], = Eo(1 - cf, where is the compaci's porosity and k = We also assumed that the characteristic flaw size equals the primary particle size. The values of Eo and y used to calculate the mannitol and lactose bridge strengths are listed in Table 5 .
E
Table 5.
2.
Surface energy and Young's modulus for mannitol and lactose
Material Mannitol Lactose monohydrate (Meggle)
a Values
[;
y
(mN/m)
2
67 7
1 7.5 1 9.0
from Rowe a n d Roberts [ 1 8] a t zero porosity and corrected for particle size according to the expression E 1 /E2 = (dp2/dp1) 1 /3 as proposed by Kendall et al. [20] . Par ticle size used, dp = 30 Jlm for both powders.
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G . I . Tardos et 81.
6.3. The auto-adhesion model (JKR theory)
In the absence of dissolved solids in the liquid bridge (no polymeric binder or evaporative re-crystallization), dry granules are held together by auto-adhesive forces and the compact's strength can be calculated by [21 ] : (Je
y
= 24.7z(8) (j p
(8)
assuming that the interfacial fracture energy is equal to the surface energy, y, and the characteristic defect size equals the primary particle size, C = dp . The porosity function in equation (8) can be taken as either z(s) = 1 3.3(1 - 8)4 (according to Kendall et al. [20]) or Z(8) = (1 - 8)/8 (according to Rumpf [22]). We used in this study the second expression but it can easily be shown that for accepted values of the porosity the two expressions give values that are almost identical. 7. STRENGTH OF SOLID BRI DGES AND D RY GRANU LES: RESULTS AND DISCUSSION 7. 1 . Slightly soluble systems : ethanol-based g ranulating solutions
We consider first the granules made with ethanol-based granulating fluids. Since lactose is essentially insoluble and mannitol is only sparingly soluble in ethanol, we expect primary particle solubility to have little or no effect on dry bridge strength. The bend strengths of these granules are plotted in Fig. 8. For all systems, the strength increases with polymer concentration in the granulating fluid. The dry bridge strength corresponding to each point in Fig. 8 was calculated using equa tion (6) and tabulated in Table 4. In these calculations, we assumed that the primary particles were in contact (a = 0), which is consistent with the way that the beam-shaped granules were made under compression in a die; according to Table A 1 , this gives b = 0.288 and C = 0.42. The liquid ratio (liq was estimated from the measured porosity of the compact and the respective densities of the liquid and powder, according to equation (5). We assumed complete saturation of the liquid bridges with mannitol or lactose at the start of drying and took the solid concentration es to include all dissolved solids present in the liquid bridges. Also given in the table is the theoretical Griffith strength of solid bridges in the mannitol beam made with pure ethanol calculated from equation (7), the tensile strength of pure H PC and PVP films, and the strength of a macroscopic bridge containing PVP and lactose between two lactose tablets. The Griffith model is inappropriate for lactose granulated with pure ethanol, because lactose is essentially insoluble and therefore does not re-crystallize to
Interparticle Bridges in Granules of Pharmaceutical Powders
1 231
6 �======�----1 Binder: PVP
�
:iE
5
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s::.-
4
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m
1
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4 ,------, -+- Mannitol 3.5 � :iE --*- Lactose 3 s=
,& 2.5
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2
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m
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O .-----r----,---.--� o 0 .0 1 5 0.02 0.005 0 .0 1 0 .025 0.03 Binder concentration (g polymer/g solution) F i g . 8 . Bend strength of beam-shaped granules formed from ethanol granulating solutions of H PC and PVP.
produce solid bridges. For this reason, we calculated the theoretical compact strength using the JKR model employing equation (8). This yielded a value of 0 . 1 MPa, in good agreement with the measured strength of 0 . 1 6 MPa and sup ports the assumption used in the calculation of bridge strength that the primary particles were in contact. The bend strength of mannitol granulated with pure ethanol was 0.47 M Pa, approximately three times larger than the JKR strength. This indicates that this granule is held together by dry mannitol bridges. The strength of the bridge is calculated with equation (6) to be 5.87 MPa, in reasonable agreement with the theoretical ("Griffith") strength of 4.43 MPa. In the lactose granules made with ethanol-based polymer solutions, the dry bridges consist of pure polymer, and the bridge strength should be independent of polymer concentration. The increase in granule strength with polymer con centration shown in Fig. 8 should be simply due to an increase in the volume of the dry bridge as more polymer is avaifable. As seen in Table 4, the bridge
1 232
G . I . Tardos et al.
strengths of the lactose granules made with HPC and PVP show no consistent variation with polymer concentration. This supports the validity of the crush strength model, i .e., the result in equation (6). The bridge strengths of the man nitol granules made with polymerie binders also do not vary consistently with polymer concentration, suggesting that these bridges also behave Iike pure poly mer bridges. This is consistent with the low mannitol solubility in ethanol. The bridge strength of the PVP bridges in the mannitol and lactose granules lies within the range of values measured for free films and macroscopic bridges between tablets. This indicates that the microstructure of the granule bridges does not differ significantly from either that of the model bridge between tablets or that of the freestanding films. The strengths of the HPC bridges are consist ently larger than that of the free films. The reason for this difference is not understood. Interpreting the above results in view of the schematic of bridges in Fig. 1 , it is Iikely that in the granules made with ethanol-based polymer solutions, the bridges that form between particles are of the polymerie filament kind. The filaments may not be as thin or disconnected as in the figure, but their strength is essentially that of the polymer film. In this case, the mechanical properties of the polymers control the strength of the dry granules. 7.2. Soluble systems: aqueous granulating solutions
We now consider lactose and mannitol granules made with water and aqueous polymer or surfactant solutions. Mannitol and lactose both exhibit significant sol ubility in water; therefore, re-crystallization of each sugar may be expected to contribute to the strength of bridges in the dry granules. Dry crush-strength data obtained for granules made with mannitol are plotted in Fig. 9 as a function of the liquid ratio, 'iiq . Aside from the very strong granules obtained with 5% H PC and 30% PVP, bridge-strength values cluster around a straight line through the origin. As shown, addition of PVP to the granulating fluid reduces the dry bridge strength especially at the lower concentrations of polymer of 3-7%. Similarly, granules made with aqueous surfactant solutions fall con sistently below this line, indicating that the dried granules are weaker than those made without surfactant, regardless of the type of surfactant used. As shown by the black dia monds in Fig. 9, the crush strength of mannitol granules made with water in the VLSG increases Iinearly with 'iiq . This is con sistent with assuming a value of 2c = 1 in the crush-strength model, equation (5). Referring to Table A1 , this corresponds to values of a = 2% and b = 0.7 1 7. The non-zero value of the dimensionless separation distance between primary par ticles, a, is consistent with the granules being formed at low shear, e.g. , not fully consolidated. Bridge strengths, ()sb, corresponding to all points in Fig. 9 for all
1 233
I nterparticle Bridges in Granules of Pharmaceutical Powders 0.6 . water
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-
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.-. 111
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•
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Fig. 9. Crush strength of granules produced i n the VLSG with aqueous granulating solution.
granules made in the VLSG were computed using these model parameters and are tabulated in Table 5. Also included in the table are values of the tensile strength of pure polymer films and bend strengths of macroscopic bridges bet ween mannitol tablets. As seen in Table 5, there is generally good agreement between the bridge strength calculated from equation (6) and the bend strength of macroscopic bridges between mannitol tablets. This indicates that the macroscopic bridge is a good model of the microseopie bridges between primary particles in the granules. All dry bridge strengths are, however, much smaller than the measured strength of pure polymer films or the theoretical Griffith strength. The discrepancy between the theoretical (Griffith) and measured strength of pure mannitol bridges can be understood by considering the micrograph of a macroscopic bridge shown in Fig. 1 0. The Griffith strength was calculated assuming that a bridge is a single crystal of mannito!. As shown by the micrograph, the microstructure is much more complex, and it seems likely that the polycrystalline nature of the bridge signifi cantly reduces its tensile strength. The dry bridge strength of mannitol granules made with a 3-wt. % HPC granulating solution was equal to that of granules made with pure water, 1 . 1 M Pa. These bridges are an order of magnitude weaker than the pure H PC films. This indicates that co-precipitation of HPC and mannitol forms a dry bridge with the mechanical strength of a pure mannitol bridge. This would be consistent with a solid bridge in which the H PC and mannitol are fully separated, with the
1 234
G . I . Tardos et al. Ungranulated mannitol particles
Fig.
Recrystallized mannitol bridge between particles
1 0. Scanning electron micrographs of mannito!.
mannitol part dominating the bridge strength. Increasing the H PC concentration to 5% by weight increases the bridge strength by 0.4 MPa, suggesting that the HPC part of the bridge begins to confer additional strength at this concentration. Consistent with this, the bend strength of the macroscopic bridge between man nitol tablets also increases with increasing HPC concentration. This suggests that HPC filaments form between primary particles that are sufficiently strong to reinforce the underlying mannitol bridge. Pre-saturating the 3-wt. % HPC granu lating solution with mannitol had no impact on dry bridge strength suggesting that the liquid bridges become saturated with mannitol in situ during granule formation. Granulating with aqueous PVP solutions produced dry bridges that were con sistently weaker than the pure mannitol bridges. The bridge strength exhibited no consistent variation with PVP concentration between 3 and about 30 wt.% . The tensile strength of the bridge was similar to that of a macroscopic bridge between mannitol tablets but 40 to 80 times smaller than that of a pure PVP film. These results indicate that co-precipitation of PVP and mannitol produces dry bridges that are significantly weaker than pure mannitol bridges. This could reflect poor adhesion between mannitol and PVP in the heterogeneous bridge. Surprisingly, addition of surfactants to the granulating solution also produced dry bridges that were substantiaily weaker than the pure mannitol bridges. Triton X 1 00, SLS and Polysorbate 80 each reduced bridge strength (relative to pure water) by 40-50%. This indicates that improving the wetting of primary particles by reducing the interfacial tension of water, which is expected to allow the granulating fluid to distribute more effectively between the primary particles [23], does not translate into higher strength solid bridges.
Interparticle Bridges in Granules of Pharmaceutical Powders
1 235
Table 5 also contains a much more limited set of data for lactose granules. This shows that the bridge strength of the pure lactose bridges is also about 1 . 1 M Pa. This value is approximately five times smaller than the theoretical (Griffith) strength but equal to the bend strength of a macroscopic bridge between lactose tablets. In contrast to mannitol, bridges formed from 5% H PC and 30% PVP granulating solutions are both approximately twice as strong as the pure lactose bridge. While these are significantiy weaker than the corresponding pure polymer films, they do show that the polymers augment the strength of the solid bridges holding the lactose granules together. Referring back to the schematic picture of the granule in Fig. 1 , we observe that bridges in the aqueous system, where both polymer and base powder are highly soluble in the liquid, are of the kind depicted on the right. These are re-crystallized bridges that contain both base powder and polymer, intermixed to some degree both physically and spatially. Morphology, strength and attachment to the original base powder particle result from a complex combination of wetting and crystal lization characteristics of the new material formed between the particles. Micro graphs of fracture surfaces of polymer films, depicted in Fig. 1 1 , show clearly that each of the aqueous systems studied in this work produces bridges with sub stantially different microstructure. The aqueous surfactant-mannitol and PVP-mannitol systems differed quantita tively from the other aqueous systems in that the presence of surfactant and polymer reduced the tensile strength of the dry inter-particle bridges. This sug gests that it might be useful to categorize polymers and surfactants in terms of their "compatibility" with the base powder(s) when the base powder solubility in the granulating solution is appreciable. H PC can be considered to be compatible with both lactose and mannitol as adding it to the granulating solution yields dry bridges of equal or greater strength than that of the pure sugar (lactose or mannitol) bridge. In contrast, PVP is incompatible with mannitol since all dry mannitol bridges con taining PVP were substantially weaker that pure mannitol bridges. Similarly, Triton X 1 00, SLS and Polysorbate 80 are each incompatible with mannitol.
8. EVOLUTION OF DRYIN G MATERIAL BRIDGES : RESULTS AND DISCUSSION 8.1 . Lactose bridges
Figure 12 illustrates a typical evolution of a saturated lactose monohydrate (Meggle - Granulac 200, see Table 1 ) bridge between two glass slides upon drying at room temperature and medium conditions of RH ('"'- 50%). The glass slides are situated perpendicular to the li ne of view and the black rings apparent in the figure represent the outer edges of the liquid bridge. The rings occur due to
1 236
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5% HPC/water films
Tardos et al.
30% PVP/watcr films
Mannitol
Lactose
Fig. 1 1 . Scanning electron micrographs of fracture surfaces produced from saturated so lutions of mannitol or lactose with H PC or PVP.
the curvature of the air/liquid interface at the centre of the bridge and as it touches the glass slide. The liquid material inside the bridge is totally transparent. The liquid bridge initially shrinks considerably during the first 60 min. The ratio of the bridge diameters measured at the beginning and at the end of this step varies from about 33% for the central (transparent) cross-section to about 48% for the top or boUom of the bridge (shown as black rings in the figures). Crystallization starts at the liquid/substrate interface close to the outer diameter of the bridge as indicated by arrow "1 " in the image taken after 1 60 min. This crystalline region grows relatively rapidly (see images taken at 2 1 0 and 260 min). Crystallization also starts at other locations at the liquid/substrate interface close to the outer diameter of the bridge (see points "2", "3" and "4"). Typically, several such clusters grow at the interface. Their growth occurs relatively fast (of the order of tens of minutes). However, the central part of the bridge remains crystal free. To illustrate this, the glass slides were pulled apart from each other after 260 min; this resulted in some necking in the middle of the bridge followed by separation in
Interparticle Bridges in Granules of Pharmaceutical Powders
• •
Fig. 1 2.
1 237
•
Solidification of a lactose liquid bridge (starting material: spray-dried lactose).
the middle of the bridge, see side view on the image taken at 1 0,OOO min, ro tated). An image of the boUom part taken at 265 min (immediately after sepa ration) demonstrates that the central part of the bridge is non-crystalline. Finally, this central part also crystallizes, although the timescale for this process is sev eral days. To study the process in more detail, the "droplet on a slide" configuration was employed with the same grade of lactose and under similar ambient conditions as used before and this can be seen in Fig. 1 3. The droplet undergoes the same major changes as the bridge described above. First, the liquid droplet shrinks due to loss of water through evaporation. Typically in this case however, the droplet height and not its outer diameter decreases (this is due to the absence of ad hesion to the top slide that in the previous case keeps the bridge height constant).
1 238
Fig. 1 3.
G . 1 . Tardos et al.
Solidification of a droplet on a slide (starting material: spray-dried lactose).
This can be seen from the change in shadows in the pictures of the droplet taken at 0 and 1 0 min. At so me point, crystals nucleate at the interface close to the outer perimeter of the droplet as shown by the arrows. These crystals grow and serve as nucleation centres for other crystals, which grow as a cluster and form a
1 239
I nterparticle Bridges in Granules of Pharmaceutical Powders
crystalline region: Fig. 1 3 shows a few of these regions after 30 min. Several such clusters can be observed to grow at the interface. The growth of such crystalline regions occurs relatively fast (of the order of minutes). Further crystallization proceeds much slower, as shown in the droplet images taken at 30 min and 1 5 h. Moreover, the central part of the droplet remains crystal free for a much longer time. In the end, it also crystallizes as seen in Fig. 1 3, which shows an image of a dried drop after 20 days. Typical XRD patterns for droplets at different stages of solidification are shown in Fig. 14. The upper pattern corresponds to the initial powder that consists of crystalline a-Iactose monohydrate and amorphous lactose. After the rapid crys tallization at the drop perimeter (1 h), the majority of crystals are a-Iactose mono hydrate. Also notable is the high background in the range of 1 8-22° 28 that indicates the presence of amorphous lactose. After 6 h, the peaks at 1 0.5 and 21 ° corresponding to anhydrous ß-Iactose are weil detected in the spectra. After six days, the ß-Iactose peaks increase considerably while the peaks of a-Iactose remain practically constant. Additionally, the background decreases, confirming some conversion of amorphous phase to ß-Iactose. The typical evolution of a nucleated crystal at the drop periphery is shown in Fig. 1 5. A single plate-like crystal nucleates in the region of the outer diameter and starts to grow. Eventually, its shape evolves, and other crystals nucleate in a space adjacent to this crystal and grow further. The cluster grows very fast as can be inferred from the time depicted, in minutes, on the micrographs in Fig. 1 5. We used XRD to compare the crystalline content of solidified droplets formed from solutions of several different powders. These powders contained either well defined initial crystalline forms (either a-monohydrate or ß-anhydrous) or mixtures
initial powder
c '00
2c
1 hour r---�_..-I '-�--'
6 hours
6 days
5
10
15 28, deg
20
25
Fig. 1 4. Evolution of powder XRD patterns of a solidifying droplet (starting material: Meggle lactose monohydrate).
1 240
Fig. 1 5 .
G . I . Tardos et al.
Solidification of a lactose droplet on a slide (starting material: spray-dried lactose).
of crystalline and amorphous forms (such as spray-dried lactose). We found, as c1early depicted in Fig. 1 6, that the initial crystalline forms present in the powder do not affect the final composition of the dry droplets since all crystallized droplets contained the same mixture of ß-anhydrous and a-monohydrate phases. We were initially concerned that different phases would nucleate differently in liquid bridges between real particles than in droplets on a glass surface. To test this, we studied the effect of seeding the droplet with lactose or microcrystalline cellulose particles (another common pharmaceutical excipient used in binder granulation). Insertion of particles of a-Iactose or microcrystalline cellulose (Avicel PH 1 0 1 ) into the centre of the droplet did not have any effect on the nucleation
I nterparticle Bridges in Granules of Pharmaceutical Powders
5
15 20, deg
10
20
1 241
25
Fig. 1 6. XRD pattems of a-monohydrate (am) and ß-anhydrous (ß) lactose powders and of re-crystal lized bridges made from the solutions of these powders (am-r and ß-r, respectively).
process. Nueleation always started at the edge of the droplet, and the crystalline clusters grew there first. If a partiele of either of the solids was placed elose to the edge, nueleation usually started at this point simultaneously with one or several other places at the outer boundary. This suggests that neither lactose mono hydrate nor microcrystalline cellulose partieIes promote crystallization of the sat urated liquid bridge. Since the glass substrate also serves as a nueleation site for heterogeneous nueleation, the major factors determining nueleation appear to be the solution concentration and the curvature of the liquid/air interface. Comparison of the solidification of three droplets prepared from a-Iactose monohydrate obtained from different manufacturers is shown in Fig. 1 7. Figures 1 7(a)-(c) are micrographs obtained under polarized light at different time points. Crystalline matter appears white. It can be seen, that after 1 0 min all the periphery in the Foremost lactose droplet and most of the periphery in DMV lactose droplet are crystallized, whereas only several crystals are present in the Meggle droplet. The central part of the droplets remains crystal free in all droplets. After 35 min, the DMV droplet has the most crystalline material, while the Meggle has the least. Additionally, some crystals are seen in the central portion in the DMV droplet. As was shown before, the majority of the crystalline material at this point is a-Iactose monohydrate. The morphology of crystalline regions is similar in the DMV and Foremost droplets. In contrast, only isolated crystalline regions are present in the Meggle droplet, similar to what was observed for spray-dried lactose. Moreover, the amount of crystalline material in Meggle is much smaller than in the other two droplets at this point in time, indicating that the crystallization rate is persistently slower in the Meggle droplet. After days, XRD analysis reveals that the amor phous regions in all droplets crystallize such that they contain approximately the same amount of anhydrous ß-Iactose. However, the crystallization rate of
4
1 242
G.1.
Tardos et al.
(a)
(b)
(c) Fig. 1 7. Solidification of lactose liquid bridges produced with lactose from different man ufacturers (F, Foremost; M, Meggle; D, DMV).
ß-Iactose in the Meggle drop was also slower. It can be concluded from these experiments that the crystallization kinetics of both (X-monohydrate and an hydrous ß forms as weil as the morphology of developing crystalline regions are clearly different for lactose from Meggle and from two other manufacturers. These results demonstrate that formation of inter-particle bridges from lactose solutions is a multi-step process that continues for extended periods of time and results in formation of a bridge of complex phase composition and microstructure. This is shown schematically in Fig. 1 8. During the first step, Le., shrinkage, the saturated liquid solution of lactose in water becomes supersaturated. Volume changes during the first step were measured using changes in the bridge dia meter since the bridge height was kept constant. If a bi-conical shape of the
Interparticle Bridges in Granules of Pharmaceutical Powders
1 243
Lactose: schematic of the solidifying bridge
o Non-crystalline (liquid)
(X-lactose monohydrate
• ß-Iactose, althydrous Fig. 1 8 .
Schematic representation of lactose bridge evolution.
bridge is assumed as a first approximation, the bridge contains only about 1 7% of the initial volume at the end of the shrinkage step. Assuming that the loss is caused by water evaporation, 88% of the initial water is lost during this step. Thus, at the end of the first step, the bridge loses most of its water and becomes a highly supersaturated lactose solution. This supersaturated solution appears to be a very viscous, plastic body. The properties of this plastic bridge strongly affect and may even control the mechanical properties of granules at this stage. The next step in the solidification process is crystallization of thermodynami cally stable a-Iactose monohydrate from the supersaturated solution. Only part of the bridge volume crystallizes during this step. Typical crystallization times range from minutes to a few hours. The rest of the material remains amorphous. Finally, during the next step, the amorphous part of the bridge crystallizes as anhydrous ß-Iactose, producing a bridge that contains both crystalline anomers. However, the timescale of this last conversion is days and sometimes even weeks. It is known that a-Iactose monohydrate is the thermodynamically stable cry stalline form of lactose at room temperature in air. ß-Iactose anhydrous is meta-stable below 96°C in air, although it is quite stable kinetically at room tem-
1 244
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perature. 80th a- and ß-Iactose are thermodynamically stable in water at room temperature, and the equilibrium a-to-ß ratio is 65/35. Hence, when a-Iactose is dissolved in water, part of it converts to ß-Iactose and both anomeric forms are present in the solution. Similarly, when ß-Iactose is dissolved in water, part of it converts to a-Iactose. Typical a-to-ß conversion and equilibration times vary from seconds to a few hours depending on the presence of impurities in water. If water is allowed to eva porate very slowly so that the equilibrium is maintained in the solution, only a-Iactose crystallizes. In this case, crystallization is controlled by thermodynamics. Unlike the process described above, bridge solidification does not occur at equilibrium since both a- and ß-Iactose phases are detected in the solidified bridge. Evaporation of water results in a solution in which lactose exists at very h igh degree of supersaturation before it starts to crystallize. The fact that nu c1eation agents do not play any significant role in growth of a-crystals suggests that its crystallization kinetics are fast only at a high degree of supersaturation. The presence of ß-Iactose crystals suggests that the high supersaturation affects either the a-to-ß equilibrium ratio in the solution or the kinetics of ß-to-a muta rotation, so that ß does not transform into a during/after a crystallization but rather crystallizes itself. Additionally, the high supersaturation level of the solution means a lack of available water that may make crystallization of anhydrous ß-Iactose favourable over crystallization of the hydrate. Crystallization kinetics of ß-Iactose are however much slower than those of a. As a result, the amorphous part of the bridge transforms slowly into crystalline ß-Iactose. Thus, initial solidification of lactose bridges occurs on a timescale comparable to that of granulation and drying, and then continues for relatively long periods of time, causing changes in bridge microstructure and, potentially, to its physical and chemical properties. It is known that a- and ß-Iactose have different physical properties and different affinity to water vapour (see, for example, Ref. [1 1 ]). Thus, the phase composition in a lactose bridge may affect not only the mecha nical properties of granules, but also dissolution, stability and mechanical prop erties of tablets made of these granules. Since compression of tablets is often completed within hours after the granulation process is completed, crystallization of ß-Iactose may occur in the tablets weil after their fabrication. Thus, the cry stallization processes in the bridge may affect the granulation process and, po tentially, milling, compression, and the mechanical and dissolution performance and stability of tablets. That the kinetics of crystallization and the morphology of developing crystalline regions are c1early different for lactose from different manufacturers may be ex plained by the fact that the crystallization process is often sensitive to the pres ence of even minor quantities of impurities. It can be expected therefore, that lactose from d ifferent manufacturers contain different impurities and/or different levels of those impurities.
I nterparticle Bridges in Granules of Pharmaceutical Powders
1245
8.2. Mannitol bridges
The "droplet on a slide" configuration was studied first. After several minutes from the time the droplet of a saturated solution was deposited on a slide, the first man nitol crystal nucleated and started to grow (see Fig. 1 9(a)). Apparently, a relatively low supersaturation level is required at room temperature to provide nucleation and growth of mannitol crystals. Similar to lactose droplets, nucleation of mannitol takes place at the periphery of the droplet (see images taken at 1 5 and 20 min). Initially, relatively narrow plate-like crystals nucleate and grow from a nucleation site in different directions along the droplet surface. Typically, the fastest growing crystallites were the ones that grew along the perimeter of the droplet, with a rate of up to several millimetres per minute. Eventually, the habit of the newly nucle ated crystals changes from plates to needles. These grow as a bunch, along the liquid droplet surface towards the centre of the droplet. Finally, after practically no free liquid is left on a slide, white agglomerates start to grow vertically on top of the bunches, closer to the periphery of the droplet. They grow "out of plane" of the droplet, normal to the surface. It is interesting to note that they start growing after most of the liquid has evaporated and only some residual liquid is observed be tween the needles. The solidification process is typically complete after 30--40 min. A typical image of the solidified droplet at higher magnification is shown in Fig. 1 9(b), in which different crystalline morphologies are clearly revealed. It is known that at least three crystalline polymorphs of D-mannitol (IX, ß and b) exist [1 11. It was reported by Kim et al. [241 that each form has a distinct mor phology when produced by evaporation of an aqueous solution: needle-like crys tals (b), parallelepiped-like (ß) and large (up to several millimetres) lichen-like crystals growing normal to the solution surface (IX). The presence of these crystal forms in the solidified droplet was confirmed by XRD. Crystals with similar morph ologies were extracted from several solidified droplets, grouped, gently hand milled and analyzed by X-ray powder diffraction. Corresponding XRD patterns are shown in Fig. 20. Three morphologies exhibit distinct diffraction patterns. The phase that forms at the beginning of the process is ß-mannitol, the same crystal form as the mannitol powder itself. However, both the needles and agglomerates that form subsequently have different diffraction patterns, corresponding to predominantly b and IX-mannitol, respectively. Thus, all the three forms of mannitol are formed sequentially in the water droplet during solidification. As a result, a bridge formed from mannitol solution consists of all three polymorphs and has a very complex microstructure. We estimated that the b- and IX-polymorphs constitute, at the end of the process, a larger volume of the crystallized droplet than the initial ß-polymorph. The formation of a solid bridge from a mannitol solution between two glass slides is shown in the Fig. 21 . Initially, the liquid bridge shrinks. Then, similar to the case of the "droplet on the slide", ß-crystals nucleate and grow at the periphery of the bridge (Fig. 21 (c), arrow #1 ). Their growth, however, is limited to the outer perimeter
1 246
G.I. Tardos et al.
a.
I -plates; 2-needles; 3-agglomerates
b. Fig. 1 9. Solidification of a mannitol droplet on a slide.
of the bridge/glass interface. At some point, bunches of needle-like o-crystals (see Fig. 21 (e), arrows #2) also nucleate at the glass/bridge interface and start to grow. However, they grow mainly along the liquid surface from one glass slide to another,
1 247
Interparticle Bridges in Granules of Pharmaceutical Powders
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Powder XRD patterns of crystals with different habits in a solidified mannitol
contacting the upper slide as they grow. Finally, a hollow solid bridge forms. It consists of several bunches of needles which are b-mannitol (Fig. 21 (g), arrow #2). Also at some later point, white agglomerates form and start to grow at the periphery of the foothold of the bridge (see Fig. 21 (e) and (g), arrow #3). It Can easily be seen from the above that, similarly to lactose, formation of inter particle bridges from mannitol solutions is a process that results in bridges of complex composition and microstructure. Apparently, the supersaturation level of the solution controls what polymorph will nucleate and which will grow faster. It is likely that the phase composition of the bridge as weil as the size of the crystallites and their interconnection depends on drying kinetics, although this needs to be investigated further. It can be expected that the phase composition and micro structure of the bridge will control its mechanical properties. Lastly, different polymorphs may have different behaviour when exposed to various environmental conditions. It was reported during some earlier work in our laboratory, for example, that water suspensions of Pearlitol (an rx/ß mixture) result in rapid conversion of rx into ß. Thus, if a bridge is composed of several polymorphs, transformations may occur if the bridge is exposed to different environmental conditions. This may affect not only the mechanical properties of the bridge, but also the physical and perhaps chemical properties of tablets made of the granules containing these bridges. 8.3. Granules
To verify that the "glass slide approach" used during this study is relevant to solid bridges formed in real agglomerates, granules were fabricated from ß-mannitol and DMV (X-lactose monohydrate using saturated solutions of the initial materials
1 248
G . I . Tardos et al.
Fig. 21 . Solidification of a mannitol liquid bridge: (a)-(f) top view of the bridge during solidification, (g)-(h) top and bottom glass slides separated after solidification, respectively.
as granulating fluids. XRD patterns of initial and granulated material are shown in Fig. 22. XRD confirms that anhydrous ß-Iactose appears after granulation in the (X-lactose monohydrate granules. Similarly, 6-mannitol is present in the dried ß-mannitol granules. Thus, although the typical bridge dimensions/diffusion
Interparticle Bridges in Granules of Pharmaceutical Powders
1 249
6000
5000
4000 V; C
8 3000 :l 0 c
:.J
2000
1 000
O �������TT��rr�� 5
6
7
8
9
10 1 1 1 2 1 3 14 1 5 1 6 1 7 1 8 1 9 20 21 22 23 24 25 2-Theta -Scale
3000
�
.l!l
c :l 0
8
2000
c
:.J
1 000
O ���=rrrrrTT���rrpr���� 5
Fig. 22.
6
7
8
9
10 1 1
1 2 1 3 14 1 5 1 6 17 1 8 19 20 21 23 22 24 25 2-Theta -Scale
Powder XRD patterns of crushed granules.
distances in granules are in the range of microns and not hundreds of microns as in the model experiments on the glass slide, the composition of the dried bridges is similar. The fact that the newly re-crystallized material in granules differs in crystalline form (mannitol) or in both the crystalline form and the anomeric form (lactose) from the initial material confirms earlier conciusion from the experiments
1 250
G.I.
Tardos et 8/.
with bridges on a glass slides that nueleation on the surfaees of the primary partieles does not dominate erystallization in the drying liquid bridge. 9. CONC LUSIONS
From the study of the ethanol-based system, where base powders were only very slightly soluble in the binder, we found that the main binding agent was the polymer. I n this system, bonds between partieles are very strong when the poly mer (HPC or PVP) is present and eompare to the strength of individual polymerie films sinee there is no interferenee to the film formation from the base powder. In the absence of polymer, dry bridges between particles attain the strength of the theoretieal erystal (or Griffith strength) sinee in this ease there is no interferenee from the polymer to the erystal formation of the base powder. In the more eomplex system where both the base powders and polymers were highly soluble in the binding solution, bonding between particles was due to a eombination of base powder-polymer bridges. The strength of these bridges is eharaeteristie for eaeh system and depends mainly on the total amount of liquid present in the original liquid bridge, i.e., large liquid bridges form stronger dry bridges. Compatibility of the polymerie binder with the base powder strongly influenees the strength of the bridge. When there is ineompatibility as in the ease of mannitol with PVP, the bond strength is deereased sometimes by as mueh as 50%. When the polymer is eompatible with the base powder, the bridge strength is inereased but does not reaeh either the strength of the pure polymerie film or the strength of the theoretieal erystal . A simple theoretieal model based o n the assumption that solid bridges formed by evaporation of liquid bridges between particles maintain their shape, proved to be quite accurate in predieting solid bridge neck strength in both ethanol and water-based systems. It was also shown that a good measure of the strength of the bridge eould be obtained experimentally from solid bridges made between two tablets of similar base powders. This is important sinee such measurements in this case are relatively simple and the strength measurement is straightforward and unambiguous. From the second part of the study it was found that solidification of liquid bridges and formation of dry bridges from saturated solutions of lactose and mannitol is a complex, multi-step proeess. Dry solid bridges contain polymorphs andjor anomeric forms that differ from those of the starting material. Lactose bridges that form from an aqueous solution of IX-lactose monohydrate consist of IX-lactose monohydrate and anhydrous ß-Iactose. A very viscous su persaturated solution is formed as an intermediate step, but eonverts slowly into the crystalline anhydrous ß-Iaetose. The crystallization processes in the liquid bridge start to oeeur within several minutes but then continue for several weeks,
I nterparticle Bridges in Granules of Pharmaceutical Powders
1 25 1
causing slow changes in bridge composition and microstructure. Significant differences in crystallization kinetics were observed in bridges made from lactose produced by different manufacturers. Similar conclusions can be drawn for man nitol bridges formed from an aqueous solution of crystalline ß-mannitol. These consist of three polymorphs and have complex microstructure. 1 0. FORWARD LOOK
The approach proposed in this work allows the study of the micro-kinetics of bridge development as weil as its phase composition and morphology at different stages of solidification. It can be used in further studies with more complex bridges. The effect of polymeric binders such as PVP and H PC on the micro structure and evolution can be undertaken using similar tools. The study of the presence of surfactants or alcohol in the solution on phase composition and crystallization kinetics should also be undertaken. The effect of drying conditions on crystallization kinetics and bridge phase composition should also be studied, since we have observed that drying conditions can have a strong effect on both crystallization kinetics and bridge phase composition. To complete the picture of drying bridges between particles, mechanical prop erties of individual bridges must also be measured. This is an ongoing compli mentary study where, in addition of observing bridges between two microscope slides, we also measure their strength in situ as the bridges evolve in time. The correlation of strength development and morphology as the bridge dries and crystallizes is also being studied. ACKNOWLEDGEMENTS
The authors wish to thank Dr Jim Zega and Dr Larry Rosen for fruitfuI discussions. APPENDIX: PREDICTION OF DRY BRI DGE STRENGTH
Dry, solid bridges may form between particles as a result of a multitude of proc esses such as sintering, melting, dissolution, evaporation and re-crystallization of the material. During bridge formation, particles' surfaces deform, melt, dissolve and/or re-crystallize and therefore the initial shape of the particles at the contact point changes while a new solid with distinct properties is formed. The force required to separate two particles after a bridge has formed between them can be calculated from (A.1 )
1 252
G.I. Tardos et al.
where rsb is the radius of the narrowest portion of the bridge or "neck" and (Jsb its strength. The assumption in equation (A. 1 ) is that the bridge has a cylindrical shape and breaks at its narrowest point (and not at the interface with either partieIe). The force and the corresponding stress can be either tensile (com pression or tension) or shear. To calculate the strength of an agglomerate (J, from the knowledge of the inter partieIe force F, one usually uses the well-known correlation proposed by Rumpf [25]: (A.2) Here Z is a porosity dependent function given as Z(8) = (1 -8)/8 by Rumpf and Z(8) = 1 3.3(1 -8)4 by Kendall [26]. The difficulty in this computation is the prediction of the "neck" size rSb, and assigning a value to its strength (Jsb. For the case of a solid bridge formed between two spherical particles from the evaporation of a liquid bridge, simple considerations of conservation of mass yield a correlation between the initial volume of the liquid bridge Vb, the volume of the dry bridge, GSVb and the size of the dry "neck". Here Gs is the solid concentration in the liquid. Pietsch and Rumpf [22], gave a semi-analytical solution to this problem (see also Ref. [27]). Their result can be rewritten in the following form: (A.3)
where b and c are coefficients given in Table A 1 as a function of the partiele-par tiele separation distance a/dp• These values were obtained by assuming that the bridge volume is small (as would be the case for solid bridges formed by evap oration) and the meniscus of the bridge surface is circular. A simple analytical solution can also be developed [28] by considering the bridge between partieIes to remain cylindrical during evaporation, i.e., the meniscus remains straight. This yields a somewhat over-predicted solid Table A 1 .
Coefficients b and c i n equation (A.3)
a* = a/dp
b
c
0 1% 2% 3%
0.288 0.381 0.717 1 .1 7
0.21 0.326 0.494 0.68
1 253
I nterparticle Bridges in Granules of Pharmaceutical Powders
bridge neck size: (A.4) Equation (A.4) gives for a/dp = 0 an exponent of c = 0.25 and a coefficient b = 0.44 or only slightly higher then the more precise equation in Table A 1 . This is demonstrated in Fig. A 1 , where equations (A.3) and (A.4) are plotted for a/dp = O.
The difference is due to the shape of the bridge that neglects the concave part of the outer meniscus and assumes this to be linear. A further correlation between the size of the neck rSb/dp is obtained from an experimental result by Pepin et al. [7]. Rewriting their result (from their Fig. 9) gives: (A. 5) Comparison of the results from equations (A.3) and (A.5) is given in Fig. A2. It can be seen that for bridge volumes larger than 0. 1 , equations (A.3) and (A.5) give values that are quite close, but at sm aller bridge volumes the dimensionless distance a* = a/dp, starts to have an influence. In a different approach by Kudoh et al. [29], the ratio of the solid bridge neck diameter and the particle diameter, dp, is given by
0: 0 2. � u (]) Z (/) (/) (]) c 0 ·00 c (])
E (5
Analytical Solution _ _+--_ 1
y=0.446 x /4
0.1
I
y 0.288 X 021 R2 0.987 =
=
0.01 -j---t----+---+--,---i 1 E-06 0.00001 0.0001 0.001 0.01 0.1 10 Dimensionless Bridge Volume, VS/[( Dp3)/8)] Fig. A1 .
Neck radius vs. bridge volume for touching particles.
1 254
G.I.
Tardos et 81.
1 0 ,----,--�--_.--�
-- a*=O
..J::
�
ü)
� () Q) z
-- a*=0.01 -- a*=0.02 � a*=0.03
-
- Simons et al. [2002]
0.1 +----+�����--�--�
h*=0.421 Vb*1/3 ---+---t---+---j--j 0.01 +0.1 0.0001 0.001 0.01 10 1 00 Bri d ge Volume. b* Fig. A2.
Analytical solution for bridge neck radius.
(sb
dp
=
[ ] X12x X
1 .64 eS vb
pp�/8
(A.6)
here es is the solid concentration in the liquid, Vb the initial volume of the liquid bridge as above, Pp the density of the particle and the dimensionless ratio of the rate of drying over the dissolution rate constant. One has to note that none of the equations above give a linear dependence of the bridge neck radius on the total bridge volume as in equation (A.6), casting some uncertainty on the accuracy of this correlation. Using equations (A. 1 ) and (A.3) in (A.2) (Rumpfs equation ) yields a direct dependence of the granule strength on the volume of the liquid bridge and the solids concentration as folIows: O"cr
1 - [; = nb2 [;
[
es Vb
] 2C
�
pp u p/8
O"sb
(A.7)
We can use equation (A. 7) as written to evaluate O"cr or we can use it to calculate the bridge strength O"sb from the measured granule strength O"cr since the crush strength is usually easier to measure. Plotting the granule strength as a function of the dimensionless bridge volume yields the best fit for b and c, as suming the total porosity of the granules remains constant. The model can, then, be validated by comparison of the calculated bridge strength with independent measurements of the strength of the materials involved in bridge formation.
Interparticle Bridges in Granules of Pharmaceutical Powders
1 255
Nomenclature
c
CL Cs
dp
dg E
Eo
F k L
rliq
t
Vb w
Crack or defect size (m) Dimensionless solid concentration in binder solution (gIg) Solid concentration in binder solution (g/cm 3) Particle diameter (m) Granule diameter (m) Young's modulus (MPa) Zero porosity Young's modulus Load to failure (N (or g)) Numerical exponent Distance between fulcrums in three-point bending (m) Liquid ratio defined in equation (4) Thickness of bending object (m) Liquid bridge volume (cm 3) Sam pie width (m)
Greek y
60
0
40
6
�
A theor. -D A exp. A B theor o B exp.
20 0 0.500
e
�
1 .000
A
A
0
&
0
A
0
8
0
8
1 .500
0
0
2.500
2.000
a * [-] Fig. 23. Evolution of measured and calculated contact angles versus normalised sepa ration distance for the case of the experiment shown in Fig. 1 3. A and B refer to the two particles, of which B is silanised.
1 60 ,----1 40 +-----����---__ L 234.6E __ L 272.7E __ L 301.4E
�----��----�60 t-��----��-
-+-- L 375.3E
80
L-----r-----' O+-�+_�������_r�_r�_+�� �----� 40 ��----
:
Ö
60
.2 e:
40
.9 15 ä> t:: 0 u
i 20 '"
(c)
o L-���--�--� o 4 rotation angle [radian)
08 0.0 0.4 0.2
. '
. .
. . . . .
and a "repulsive", vrep, component. The attractive vector is oriented from the centre of mass of the incoming object to the centre of the simulation box and its magnitude is set to[vatt[ = 1 . The repulsive vector is the sum of vectors oriented from the collision points (i.e., voxels in which the incoming object is in contact with the existing structure in the simulation box) and its magnitude is ° ;( [vrep [ ;( 1 , calculated as the ratio of the overlap volume to the maximum allowed fraction of the volume of the incoming object. The algorithm stops when [vtet [ = 0, i .e., when the incoming object has found a stable position, which represents a local min imum of potential energy with respect to the centre of the simulation box. Note that the ballistic deposition algorithm represents a limiting case of a DEM sim ulation with perfectly inelastic collisions and zero friction. 2.2.3. Binder spreading and solidification on partic/e assemblies
The spreading and solidification steps are both modelled using the volume-of fluid (VoF) method for interface tracking - solid-liquid interface in the case of solidification and gas-liquid interface in the case of spreading. During binder spreading, the three-phase contact Iines are propagated at a velocity, ULG, de pendent on the local value of the instantaneous contact angle, (J, according to the constitutive equation = I1( (cos (Ja - cos (J) (J
ULG
(6)
where (J is surface tension of the liquid binder, 11 the viscosity, ( the "friction coefficient" [1 6] (a binary liquid-substrate interaction parameter), and (Ja equi librium advancing contact angle. Other constitutive relationships for the contact-line velocity as function of the instantaneous contact angle can of course be used if they are found to describe the spreading dynamics of a particular binder-substrate combination more ac curately than equation (6). The local contact angle is calculated from the solid, "s, and liquid, "L, interface normal vectors (7)
1 363
Sub-Granule Scale Modelling
which are obtained from the gradient of the corresponding "mollified" [1 7] phase volume function:
(8) At each time step, the three-phase contact lines are propagated according to equation (6) and the two-phase (gas-liquid) interfaces are then allowed to relax to a shape constant mean curvature. The local relaxation velocity at each l iquid in terface point is proportional to the difference between the local curvature and the average curvature of the liquid cluster to which that point belongs, ( ) until I( = The interface curvature is calculated from the normal vector according to (9) A VoF simulation of the spreading of a liquid-binder droplet on an assembly of a few primary solid particles in the absence of solidification is iIIustrated in Figs. 9a * K -K ,
1(
*
.
(� - -
Fig. 9. Volume-of-fluid simulation of the elementary steps of granule microstructure for mation: (a) liquid droplet spreading; (b) spreading with deposition of additional primary particles (indicated by arrows); and (c) spreading with binder solidification (adapted from ref. (9]).
1 364
F. Stepanek
and 9b. Binder solidification can be approached in two principally different ways, depending on the solidification mechanism. If binder solidification occurs as a well defined phase transition (e.g., re-crystallization of a solution binder, solidification of a melt binder, or the formation of a solid phase fram a reactive binder), the un derlying problem is also that of a moving interface, the solid-liquid interface velocity being calculated from the drying rate, heat-transfer rate, or reaction rate depending on the solidification mechanism [9]. This case is illustrated in Fig. 9c. On the other hand, binder solidification often occurs as a gradual increase of viscosity (e.g., for polymer-based solution or some melt binders), rather than in the form of a sharp phase transition. In that case, the effect of solidification is mode lied by gradually increasing the viscosity in equation (6) as function of concentration (drying) or temperature (cooling) and stopping the spreading simulation when a threshold value is reached at which the binder is effectively solid. 2.3. Characterization of granule m icrostructure
Once the 3D model of granule structure is constructed, it is often desirable to reduce the information about the spatial distribution of the constituent phases into volume-averaged morphological measures, such as porasity, etc., which can then be correlated with effective macrascopic properties. Several classes of morphological descriptors for disordered media are available [6, 1 8] ; only the most commonly used ones will be briefly reviewed here. The phase volume fraction of a phase j in the granule is defined by
rPj = � !fjd V
( 1 0)
where 0 is the VoF function of that phase and the sampling volume of the granule (typically, a sphere located in the centre of mass of the granule and covering 90% of its volume - so that the external shape of the granule does not affect the volume-averaged quantities). Porasity is the phase volume fraction of the gas phase. The characteristic length-scale of a phase is typically defined in one of four ways: (i) as the correlation length calculated fram the auto-correlation function of that phase; (ii) as the mean chord length calculated fram the chord-Iength dis tribution; (iii) as the ratio of phase volume to phase surface area of that phase; (iv) as the mean covering sphere diameter calculated fram the distribution of covering spheres. Let us now define some of these terms mathematically. The auto-cor relation function of phase j is defined (similarly to equation 5)
V
(1 1 )
1 365
Sub-Granule Scale Modelling
The correlation length Lc,j is defined as the zero-th order moment of the auto correlation function, i.e., Lc,j =
100 Rj(z)dz
(12)
The second above-mentioned measure of the characteristic length-scale, the mean chord length, is simply the mean of the chord-Iength distribution function i.e., the length distribution of line segments passing through the phase of interest. The third measure of the characteristic length-scale is defined by j� fjd V ( 1 3) LA, J. = --"--"--'-- --,;-;O ü . 5� r dA 2 [f(1 f)] J .J v J --
-
In the specific case of the phase j being the gas phase, LA,) is directly related to the equivalent hydraulic diameter up to a multiplication constant. The fourth above-mentioned measure of the characteristic length-scale of phase j within the granule structure is the mean covering diameter. The covering radii distribution function is generated by first constructing the distance function [1 9,20] that de termines the maximum possible radius of a sphere that fits entirely into the phase j as function of the position of its centre, and then finding the distribution of sphere radii that entirely cover the phase of interest. In the specific case of the gas phase, the distance function can be used for the calculation of simulated mercury intrusion curve [6]. Higher-order moments of each of the above-mentioned distribution function can of course also be used for the characterization of the microstructure, though the zero- (phase volumes) and first-order (character istic lengths) measures tend to be most useful for correlation with macroscopic properties. 2.4. Calculation of macroscopic properties from microstructure 2.4.1. Effective transport properties
As al ready mentioned in the introduction, the effective transport properties diffusivity, permeability, and thermal conductivity - of granules are important parameters in a number of applications. The aim of the calculation procedure is to obtain the values of these transport properties from the knowledge of the granule microstructure [6,7,21 ,22]. Let us iIIustrate the principle of the calculation on the case of effective thermal conductivity [ 1 5] (Fig. 1 0). A macroscopic temperature gradient ( T2- T1 )/f:.Z is imposed on a computa tional unit cell containing a statistically representative sampie of the multi-phase medium of interest. The steady-state heat conduction problem (Fourier's law) V (lc/vT) = 0
(14)
1 366
F. Stepanek
I 1
öL
Fig. 1 0. Calculation of effective thermal conductivity by imposing a temperature gradient across a unit cell containing a statistically representative sampie of the microstructure of interest, and solving the Fourier's law (from ref. [1 5]).
is then solved on the multi-phase medium using the local values of thermal conductivity of each phase, Aj, subject to the temperature gradient in the z direction and periodic boundary conditions in the x- and y-directions. The overall heat flux across the simulation box, 0', is then used for the calculation of the effective thermal conductivity from the macroscopic Fourier's law, Le., Aeff
=
Ci
I1Z
- A T2 - T1
( 1 5)
where A is the cross-section area of the simulation box perpendicular to the macroscopic temperature gradient. The effective thermal conductivity as function of the composition (phase volume fractions, rfJ), thermal conductivities of the phases, Aj, and microstructure can then be systematically calculated and corre lations derived, as has been done recently for the case of partially liquid-saturated particle assemblies of various shape by Kohout et al. [1 5]. The calculation of effective diffusivity proceeds in a similar manner as that of thermal conductivity, except that a macroscopic gradient of concentration (cr c1)/I1Z is imposed and the steady-state diffusion problem (Fick's law) is solved V (Dj VC)
=
0
( 1 6)
where Dj is the diffusivity in phase j. The effective diffusivity Deff is obtained from the macroscopic diffusion flux analogous to equation (15). Finally, the calculation of
1 367
Sub-Granule Scale Modelling
permeability [7] is based on imposing a macroscopic gradient of pressure (P2 -P1 )/ cell and solving the Stokes equation in the pore space ( 1 7) where I] is the dynamic viscosity, v the velocity, and P the pressure. Permeability is then evaluated from the converged velocity field according to the macroscopic Darcy's law V' I1Z = - 1] ( 1 8) A (P2 - P 1 ) where V' is the total volumetric flow-rate across the simulation box in the z-direction and A the cross-section area of the simulation box in the direction perpendicular to the pressure gradient. An example of calculated effective diffusivity and permeability of wet particle assemblies as function of relative saturation and particle size and shape can be found, e.g., in ref. [23]. The special case of multi-scale porous media is described in ref. [6]. I1Z across the computational
K
K
2.4.2. Effective dissolution rate
The effective dissolution rate of a granule can be determined from the knowl edge of granule microstructure and morphology by modelling the convec tion-diffusion transport of dissolved components from the granule surface and locally eroding the surface at a rate corresponding to the local mass fluxes. The single-granule dissolution methodology has been described by Stepanek [1 0], based on similar methodology for the dissolution of porous media, developed originally by Bekri [24]. An input to the simulation is a 3D granule structure encoded in a computational unit cell by the phase volume functions as de scribed in Section 2. 1 . The simulation proceeds iteratively in three steps: First, the velocity field in the surrounding liquid phase is calculated by solving the Stokes and continuity equations, i.e., r,.'v2 v
(1 9) 0 where I] is the viscosity, v the velocity, and P the pressure. Typically, periodic boundary conditions are applied in all the three directions for the velocity, and a macroscopic pressure gradient is imposed in one direction. Once the velocity field is calculated, the convection-diffusion equation aCi at
-
=
=
Vp;
Vv
=
-vVcI + DI V2 c·I
(20)
(where Ci is the concentration of component i, t the time, and Di the diffusion coefficient of component I) can be integrated for a short period of time. The granule structure is eroded (i .e., the values of the phase volume functions updated) simultaneously with the solution of equation (20) according to mass
F . Stepanek
1 368
Fig. 1 1 . Simulation sequence showing the erosion of a granule during diffusion-limited dissolution. (The granule skeleton is grey, the concentration profile of one the components in the fluid phase is shown by the contour map.)
fIuxes at the solid-liquid interface. The surface erosion rate is related to the local mass flux by dfi Mi dt = p; (-D;VCi + VCi)nS (21 ) -
where � is the phase volume function of component i, Mi the molar mass of component i, Pi the density of component i, and ns the solid interface normal vector (oriented from solid to the surrounding liquid phase). The evolution of a granule during dissolution simulation is shown in Fig. 1 1 . As the phase volume functions are updated, the geometry of the domain on which equation ( 1 9) is solved, is changing. However, it is usually sufficient to update the velocity field only after the volume of the granule changes by a significant amount (e.g., 5% of the original volume) rather then after every time step, and in the meantime obtain the velocity vector in newly formed liquid-phase points by interpolation. During the simulation of granule dissolution, the connectivity of the granule skeleton is also periodically checked. If a disconnected solid-phase cluster is detected (typically a partially dissolved primary solid particle whose binder bridge has already dissolved completely), it is removed from the simulation unit cell . The "shrinking core" and the "break-up" dissolution mechanisms can thus be distin guished (under shrinking core, the granule remains as a single entity during the dissolution, under break up, fragments detach from the granule during dissolu tion). In either case, the dissolution curve (i.e., the amount dissolved vs. time) is obtained from the dissolution simulation by integrating equation (21 ) .
3 . APPLICATION EXAMPLES
In this section, several works in which the above-described methodology of sub granule-scale modelling has been applied for the calculation of granule micro structure and macroscopic properties, are reviewed. The first two examples are concerned with the computation of granule porosity as function of formulation and
1 369
Sub-Granule Scale Modelling
process variables and its experimental validation. The latter two examples deal with the calculation and experimental validation of effective transport properties and dissolution rate.
3. 1 . Dependence of granule porosity on binder solidification rate
The granule formation algorithm described in Section 2.2 has been used for the calculation of granule porosity as function of the binder solidification and spread ing rate, and the frequency of droplet and particie deposition on the surface of a growing granule in the limiting case of low-shear granulation (negligible contri bution of external deforming forces) and granule growth by the layering mech anism [9]. The characteristic times of binder spreading, binder solidification, and surface deposition have been introduced in order to reduce the dimension of the parameter space to be investigated. The characteristic time of spreading, has been defined as the time required for the three-phase contact line to cover a distance equal to the droplet diameter. The characteristic time of solidification, has been defined as the time required for the solidification front to cover the has been chosen as same distance, and the characteristic time of deposition, the mean time between particie collisions in the granulation equipment. Granule porosity as function of the ratio / for several values of the ratio / and a fixed ratio of primary particies and droplets depositing on the growing granule surface is plotted in Fig. 1 2. The cross-sections of representative microstructures corresponding to three different t/ ratios are also shown. Let us discuss the observed trends by first examining the limiting cases of t/ -> 0 and t/ -> x . In the former case, the solidification time is much longer than the spreading time, i.e., there is sufficient time for the binder to completely spread within the granule structure before it solidifies (cf. also the cross section). The porosity in that case is determined by the available pore volume fraction within a ciose-packed structure of the primary particies saturated by the binder to a degree dependent on the binder/solids ratio. In this particular case, the binder/solids ratio is high so that the asymptotic porosity for t/ -> 0 is zero. The other asymptotic limit ( / -> oc ) corresponds to a situation where the binder droplet solidification is very rapid. The porosity of the granule then corresponds to that of a random ciose packing of primary solid particies and "frozen" binder droplets. The intermediate cases around t/ 0.1 lead to granule structures where the binder is partially distributed within the structure and a layer of solidified binder of varying thickness separates the primary particies. In this intermediate range, the porosity is also most sensitive to the collision frequency (the ratio t/ ) At a fixed solidification rate, increasing the particie deposition rate gene rally leads to a higher porosity - a liquid binder droplet that would Twet.
Tso!>
Teol ,
Twet Tsol
Twe
Twe
Tsol
Twet Teol
Tsol
Twe Tsol
Twe
Tsol
Twet Tsol
Twe
Twe
Teol '
Tsol
�
1 370
F. Stepanek
. �
.,"
/n.
- �.J:�--�-_:: : :'
//
OL---����----�--�
0.001
0 . 01
'wer''tsol [-] 0.1
10
Fig. 1 2. Dependence of granule porosity on the characteristic times of spreading, solid ification, and deposition, with three typical corresponding granule microstructures (from ref. [9]).
otherwise penetrate into the granule structure by capillary flow will be retained in place if a new solid particle is deposited on the surface. 3.2. Dependence of g ranule porosity on composition
In the previous case, it has been mentioned that granule porosity in the limiting case of slow solidification should only depend on the packing density of the primary solid particles and the binder content. This hypothesis has been tested in [25) both computationally and experimentally. Granules were prepared by fluid bed granulation of sugar spheres (Suglets, NP Pharm, France) with in situ melt binder (PEG-8000, mp 61 °C). Sugar spheres of two different size ranges have been used: Sl with dp = 250-355 j..lm and S2 with dp = 1 80-250 j..l m . The gran ulation was carried out in three steps: (i) mixing and heating-up of a mixture of primary solid and binder particles; (ii) granulation period, during which the tem perature was raised above the melting point of the binder and granulation oc curred; and (iii) cooling-down period during which the temperature was reduced to ambient and binder solidified. The binder/solids ratio and S2ISl mixing ratio were systematically va ried and the porosity of the resulting granules has been determined by measuring their envelope density (the composition and the density of the primary solids and the binder were known). At the same time, virtual granules of the same composition (S2/S1 ratio and binder/solids ratio) have been generated computationally for the limiting case of asymptotic spreading 0). (rwetlrsol --*
Sub-Granule Scale Modelling
1---.--
1 371
I
0.40 -,------,
Z.
0.35
�
..!...
'iii 0 ....
16 Ci
0 Q.
�
0.30 0.25 0.20
.,.
�" " " " ,. � .
-*-
Simulations Experiments
0 . 1 5 +-----,----,--1 0.20 0.25 0.00 0.15 0.05 0.10
Binder ratio [w/w]
F i g . 1 3. Granule porosity as function of binderjsolids ratio (by mass) for granules made of
S1-type primary particles (from ref. [25]).
0.35 -,------,
�
..!...
0.30
>:t::
�5 0.25
16 Ci
•. .. - - - - - - ...
-- -- --
Q.
�
0.20 - -
-11
--
Simulations
--- Experiments
0 . 1 5 +-----,----,.---1 0.6 0.0 0.9 0.3 1 .2 52/51 ratio [w/w] Fig. 1 4. Granule porosity as function of small to large primary particle mixing ratio (by mass) for constant binder ratio (from ref. [25]).
Computed and experimentally measured porosity of granules as function of the binder ratio for Sronly granules is plotted in Fig. 1 3. Porosity is a decreasing function of the binder ratio - the packing density of the partie/es is fixed and the pore space becomes increasingly saturated by the binder as the binderjsolids ratio is increased. A small difference between sim ulated and measured porosity is apparent; in the simulations, the primary par tie/es were regarded as mono-sized spheres, while in fact the Suglets are slightly aspherical and the size is dispersed over a small interval. Figure 14 shows granule porosity as function of the mixing ratio between large (Si ) and small (S2) primary solid partie/es for a fixed binder ratio. The packing density of a binary
1 372
F. Stepanek
mixture of unequal partieIes is known to go through a maximum [26], and there fore the porosity of granules can be controlled by the partieIe size distribution of the primary partieIes. This phenomenon has been reproduced both computa tionally and experimentally - both sets of data show a e1ear minimum of porosity as function of the mixing ratio. 3.3. Dependence of g ranule d issolution rate on composition and porosity
The dissolution rate of granules as function of granule porosity, binderjsolids ratio, solubility and diffusivity of primary partieIes, and binder has been system atically investigated in [1 0] by using the methodology described in Section 2.4.2. A population of virtual granules with varying binderjsolids ratio and porosity has first been generated by means of the algorithm described in Section 2.2. The region in the granule composition space occupied by these granules and the correlation between porosity and binderjsolids ratio are plotted in Fig. 1 5. Each granule has then been subjected to a virtual dissolution test under eight different conditions: two hydrodynamic regimes (diffusion-Iimited dissolution in a stagnant liquid and dissolution under relative liquid-partiele velocity equal to the terminal settling velocity) and four combinations of material properties (high- and low solubility binder, and fast- and slow-diffusing binder). Examples of the dissolution curves for three different granules (porosity of 7%, 1 2%, and 21 % and binderj solids ratio of 0.41 , 0.35, and 0.1 7, respectively) under terminal settling velocity and a situation where the primary solid partieIes have both higher solubility and diffusivity than the binder (case "E" from ref. [1 0]) are shown in Fig. 16. The dissolution rate is e1early increasing with increasing porosity. The jumps on the radius VS. time plot correspond to fragments breaking off from the mother gran ule, and are an indication of the disintegration mechanism. Notice that the granule with lowest porosity (7%) dissolves practically only by the shrinking core mech anism, while for the high-porosity granule (21 %) the break off is most significant. 3.4. Effective transport properties of wet particle assemblies
The effective thermal conductivity [1 5] and the permeability [23] of primary par tiele assemblies partially saturated by a liquid have been determined computa tionally and compared with experimental measurements. The system used for the experiments consisted of glass spheres with narrow size distribution as model solid partieIes with water and n-hexane as high- and low-thermal conductivity liquid, respectively. A range of volume fractions of the solid phase has been realized by mixing large- and small-diameter glass spheres at varying ratios (the
Sub-Granule Scale Modelling
1 373 Primary Sol i ds
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0.7
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. ,
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porosity
15
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:
20
25
Fig. 1 5. CompOSltlon ot granules used tor virtual dissolution tests, shown in the triangular diagram and as correlation between porosity and binderjsolids ratio (from ref. [1 0]).
240 "
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.,
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I
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., Ul 'ö .,
o L.---'-_��'----'-_��_"""" 14 o 2 4 6 8 10 12 time [51
Fig. 1 6. Dissolution curves for three granules with different values of porosity (as indi cated) plotted as amount dissolved (lett) and equivalent radius (right) as function of time (from ref. [ 1 0]).
F . Stepanek
1 374
same principle as the S2/S1 mixing described above). The sizes used were 68 11m (code name AH), 200 11m (AC), and 628 11m (BL). The effective thermal conduc tivity has been measured by the transient hot-wire method; permeability was determined by measuring the flow-rate and pressure drop of gas flowing through a column containing the partially saturated particle layer. The simulations were performed according to the procedure described in Section 2.4. 1 . Selected results are illustrated i n Figs. 1 7 and 1 8 for effective thermal con ductivity and permeability, respectively. The effective thermal conductivity is for AC-type particles with a varying degree of pore-space saturation ranging from 0 (dry system) to 1 (complete saturation). Owing to the relatively high thermal conductivity of water, the effective thermal conductivity of the saturated system is more than seven times higher than that of the dry system. The knowledge of thermal conductivity as function of liquid content is crucial for quantitative de scription of processes such as drying. An equally important parameter for drying and other applications (e.g., adsorption or catalysis) is permeability. Permeability as function of liquid saturation has been calculated [23] for a range of granular microstructures, such as mono-sized and poly-dispersed spherical, cubic, and rectangular particles, both hydrophilie and hydrophobie. A power-Iaw function for permeability, valid over a wide range of compositions and particle shapes, has been found [23]. A direct comparison of measured and computed permeability as function of porosity for a mixture of spherical particles is shown in Fig. 1 8. There is small offset between the experimental and computed values, due to slight over prediction of packing density in the simulations. 0.9
...... "";"
� "";"
E
�
..l
AC + water simulations fit
0.7 0.5
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0.3 0.1
0
.. ..... . .
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O
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H .
. ..
0.2
0.4 XL'
[-]
0.6
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Fig. 1 7. Effective thermal conductivity of an assembly of 200 J.lm glass spheres as function pore space saturation by water - simulations and measurements (from ref. [1 5]).
1 375
Sub-Granule Scale Modelling 0.006
0.005 �
N
GI
-0 ....... z.e
ex p AH + BL fit simulations " '-" -'"
,..-----�---r--�-_, • -
0.004 0.003
0.002 0.001
o � 0.25
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porosity XG [-]
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-J
____ �_____ �_____
Fig. 1 8. Measured and computed permeability of granular media realized by mixing large (BL) and small (AH) particles at varying ratio (fram ref. [23]).
4. FORWARD LOOK 4.1 . Computer-aided g ranule design
Let us now consider the integration of the sub-granule scale modelling methods described in this chapter into an overall design process for granular products. As already mentioned in the introduction, rational design of structured chemical products requires that two functional relationships be established: the so-called process function, relating a set of raw material properties and processing pa rameters to the granule microstructure; and the so-called property function, re lating the microstructure to the effective macroscopic properties of the product. Schematically these relationships are shown in Fig. 1 9, which has been derived from the general "product design" diagram proposed in [27]. The functional relationships can be established through experiments, theory or simulation, or their combination. Product design can be defined as a systematic activity whose aim is to find the inverse of these functions, i.e., to determine product composition (formulation) and processing conditions that result into a product with specified end-use properties. The term "computer-aided product design" then refers to a situation where mathematical modelling or computer simulations are used at least in some parts of this process. The computational methods described in this chapter cover all aspects of the design cycle - sim ulation of granule microstructure formation for the process function, granule dis solution and transport properties calculation for the property function, and granule
1 376
F. Stepanek
Formulation
I} -------n [ r-I GranuIe m-ic-ro-st-ru-c-tu-re--'I } Processing
1
n
process function property function
End-use properties
Fig. 1 9. Formal representation of the computer-aided granule design process.
microstructure characterization for both - and can be used either individually or in combination with experiments. 4.2. Virtual prototyping
The term "virtual prototyping" refers to a situation where new products are not only designed but also tested using computer models - by simulating the product end use, or other process in which the product performance is of interest. A physical prototype is then only manufactured in order to confirm predictions of the virtual prototyping activity, but not as part of the design loop. Virtual prototyping is already applied, e.g., in the automotive or aerospace industries, where the achieved savings are most significant in particular when the physical tests are destruetive in nature (crash tests). In the context of granular products, the sim ulation of granule dissolution that was described in Section 3.3 is an example of virtual prototyping. Two conditions have to be met for virtual prototyping to be a viable alternative to physical prototyping: one technical and other economic. The technical con dition is that the computer models have to be sufficiently aceurate so that their outputs can be treated with the same confidence as the results of physical tests. Referring again to the automotive industry, computational fluid dynamics (CFD) models for aerodynamics tests, and finite element analysis (FEA) models for crash tests are already reaching that level of accuracy. In principle, there is no reason why this should not also be the case for virtual prototyping of granules studies have shown that both the calculation of transport properties [1 5,23] and of granule porosity [25] can be rather accurate. The second condition is related to the availability of material properties required as input parameters into the models. If reliable property estimation methods exist for all required material properties (e.g., solubility, diffusion coefficients, ete.), these properties can be calculated from the knowledge of the molecular structure and fed into virtual prototyping models. If material properties have to be
Sub-Granule Scale Modelling
1 377
measured due to the absence of good property estimation methods and a group of materials is repeatedly employed in the products being virtually tested, then their properties can be measured once, maintained in a material property da tabase, and readily recalled each time they are required in a virtual prototyping model. However, if each new product also contains a new material (e.g., a new active in a granule) which is very different from any previously characterized substance and the experimental effort required to fully characterize, the new material is comparable to the effort required for the preparation and physical testing of the complete product, then of course the application of virtual proto typing would not bring any overall time saving. With this caveat in mind, computer-aided design and virtual prototyping of chemical products are rapidly developing areas with applications not only in granulation but also polymers [20], catalysis [6], and materials engineering. REFERENCES [1] [2] [3] [4] [5] [6] [7] [8] [9] [ 1 0] [1 1 ] [ 1 2] [ 1 3] [ 1 4] [ 1 5] [1 6] [1 7] [1 8] [1 9] [20] [21 ] [22] [23] [24] [25] [26] [27]
M. Hili, AIChE J . 50 (2004) 1 656-1 661 . J . N . Michaels, Powder Technol. 1 38 (2003) 1-6. M.F. Edwards, T. Instone, Powder Technol. 1 1 9 (200 1 ) 9-1 3. E.M. Holt, Powder Technol. 1 40 (2005) 1 94-202. L. Farber, G . I . Tardos, J.N. Michaels, Powder Technol. 1 32 (2003) 57-63. J. Kosek, F. Stepanek, M. Marek, Adv. Chem. Eng. 33 (2005) 1 37-203. P . M . Adler, Curr. Topics Phys. Fluids 1 ( 1 994) 277-306. N. Losic, J .-F. Thovert, P.M. Adler, J. Coll. Interf. Sci. 1 86 ( 1 997) 420-433. F. Stepanek, M A Ansari, Chem. Eng. Sci . 60 (2005) 401 9-4029. F. Stepanek, Chem. Eng. Res. Des. 82 (2004) 1 458-1 466. E.J. Garboczi , Cem. Conc. Res. 32 (2002) 1 62 1 -1 638. C. Thornton, M .T. Ciomocos, M.J. Adams, Powder Technol. 1 05 ( 1 999) 74-82. D. Coelho, J.-F. Thovert, P.M. Adler, Phys. Rev. E 55 ( 1 997) 1 959-1 977. X. Jia, R.A Williams, Powder Technol. 1 20 (2001 ) 1 75-1 86. M. Kohout, AP. Collier, F. Stepanek, Int. J . Heat Mass Trans. 47 (2004) 5565-5574. A Clarke, TD. Blake, K. Carruthers, A. Woodward, Langmuir 1 8 (2002) 2980-2984. w.J. Rider, D.B. Kothe, J. Comput. Phys. 1 4 1 (1 998) 1 1 2-1 52. C.H. Arns, M A Knackstedt, K.R. Mecke, Coll. Surf. A 241 (2004) 351-372. S.M. Sweeney, C.L. Martin , Acta Mater. 51 (2003) 3635-3649. Z. Grof, J. Kosek, M. Marek, P.M. Adler, AIChE J. 49 (2003) 1 002-1 0 1 3. E.J. Garboczi, D.P. Bentz, N.S. Martys, P.Z.Wong (Eds. ), Experimental Methods for Porous Media, Academic Press, New York, 1 999. M . E . Kainourgiakis, E.S. Kikkinides, A Galani, I . N . Tsimpanogiannis, Y.C. Yortsos, Transp. Por. Media 58 (2005) 43-62. M . Kohout, A.P. Collier, F. Stepanek, Powder Technol. 1 56 (2005) 1 20-1 28. S. Bekri, J .-F. Thovert, P.M. Adler, Chem. Eng. Sci . 50 ( 1 995) 2765-2791 . MA Ansari, F. Stepanek, Optimisation of binder and porosity distribution in granules. Proc. 8th Int. Symp. Agglomeration , Bangkok, Thailand, March 1 6-1 8, 2005, pp. 1 79-1 85. S. H utin, P. Accart, D . Oulahna, JA Dodds, Polym. Int. 52 (2003) 581-585. E. Favre, L. Marchal-Heusler, M. Kind, Trans. IChemE Part A 80 (2002) 65-74.
S U BJ ECT I N D EX 3-A, 575-577, 579 Abrasion technique, 1 1 92 Adhesion, 325, 330, 333, 342-343, 345, 351 , 354 Adhesion forces, 605 Adhesive failure, 832 Adhesive force, 1 259, 1 308, 1 31 0, 1312 Adjunct, 691 Admix, 675, 678, 682 ADPI, 575-576 Agglomerates, 4 1 8, 69 1 , 8 1 5 Agglomeration, 1 99, 208, 2 1 0-21 1 , 325, 332, 336, 34 1 , 344, 347-351 , 353, 356, 358, 366-371 , 4 1 8 Aggregation efficiency, 1 1 33, 1 1 36, 1 1 38, 1 1 42, 1 1 48-1 1 49, 1 1 56-1 1 57, 1 1 59 Aggregation rate constant, 1 027 Akkermans number, 685-686 Area rupture criterion, 1 288 Atomization , 336, 35 1 , 357-358, 364, 455, 465, 856, 859, 886, 890 Attenuation coefficient, 1 205, 1 208 Attrition, 453, 853, 856, 859, 870-87 1 , 887-889, 898, 980 Attrition constant, 1 028 Axial circulation , 1 2 Axial stress, 744 Bacteria, 555-559, 580, 583 Barium sulphate, 205 Base powder, 673, 675, 682-684, 686-687 Batch , 443, 853-854, 858, 872-879, 882, 884, 889-893 Batch fluidized-bed, 445 Beam testing, 764 Benbow-Bridgwater analysis, 202 Bentonite ciay, 21 1 Beverage powders , 656 Bifidobacterium, 557
Binder, 853-857, 859-887, 889-893 Binder deposition , 1 308 Binder solidification, 1 353, 1 357, 1 363-1 364, 1 369 Binder spreading, 1 353, 1 357-1 358, 1 362, 1 369 Binder surface tension, 1 0 Binder viscosity, 9 Binder viscosity, drum granulation, 232-233 Binderless, 29 1 , 294 Binders, 834 Bleach, 675, 678, 687 Bleeding, 680, 689 Bond formation, 957-961 Bond number, 1 345 modified, 1 348 Bonding forces, 995 Bonding mechanisms, 341 Bottom-driven high shear granulator, 470 Bottom-spray processing, 428 Brazilian test, 688, 763, see also Diametral compression test Bread improvers, 569 Breakage, 453, 700, 853, 857, 859, 864, 868-872, 882, 884, 886, 889, 893, 898-899, 979, 1 1 1 9, 1 1 22-1 1 27, 1 1 42, 1 1 63, 1 1 65, 1 1 67, 1 1 70-1 1 74, 1 1 76-1 1 78, 1 1 80 Breakage selection rate constant, 1 028 Breakfast cereals, 664 Bridge volume, 1 263, 1 265, 1 268, 1 27 1 , 1 284, 1 294, 1 301 , 1 3 1 4 Brittle, 995, 1 0 1 0 Brittle material, 763 Bubble size and shape, 1 098 Bubbling, 1 049-1 050, 1 052-1 053, 1 057, 1 062-1 063, 1 067 Buckingham's theorem, 7 1 2 Builder, 678, 683, 687 Bumping, 1 4
1 380 Caking, 665 Calcium carbonate, 209, 21 1 Calcium phosphate, 21 1 Capillary, 1 2 1 0, 1 26 1 , 1 265, 1 267-1 270, 1 273, 1 284, 1 287, 1 298, 1 300-1 301 Capillary bridge 1 3 1 7 Bond number 1 345 buoyancy force 1 346 contact angle 1 324 draining 1 348 effect of gravity 1 31 8, 1 344 effect of wetting hysteresis 1 31 8, 1 340-1 344 rupture 1 332-1 334, 1 339-1 340, 1 346-1348 volume 1 327-1 329 Capillary force 8 1 8, 1 321 c1osed-form approximation 1 334-1 335, 1 338 Derjaguin radius 1 338 effect of gravity 1 344-1 349 equal spheres 1 334 experimental data 1 332-1 334, 1 34 1 -1 342, 1 346-1347 hysteresis 1 340-1 344 Israelachvili's approximation 1 328 Laplace-Young equation 1 3 1 9, 1 345 surface tension 1 321 toroidal approximation 1 323 unequal spheres 1 336 Capillary number, 936-938, 974 Capillary pressure, 826 Capsules, 4 1 8 Cascading velocity, 377, 400-402, 405, 4 1 1 Catenoid, 1 258 Centre of mass, 1 209-1 2 1 0 Centripetal, 853, 879, 882-885 Cereal bars, 664 Certification, 555, 576, 579, 582 CFD, 377, 380, 397-398, 4 1 3-41 4 Chopper speed, 6 Chord length, 690, 698-699 Clamp, 579-580 Classifying discharge, 449 Classifying particle discharge, 21-22, 53-54, 59, 77, 79, 1 8 1
Subject Index Cleaning, 676-677 Coalescence, 853, 856, 859, 861 , 864, 867-870, 872, 874-878, 882, 884, 890, 893, 898-899 Coalescence kernei, 238-240, 1 1 09, 1 1 1 4, 1 1 1 7, 1 1 1 9, 1 1 27-1 1 28, 1 1 31 -1 1 32, 1 1 36-1 1 37, 1 1 42, 1 1 58, 1 1 70, 1 1 72, 1 1 77-1 1 79 Coalescence models, 947-956 Coalescence probability, 1 1 1 0, 1 1 33, 1 1 36, 1 1 46-1 1 49, 1 1 52, 1 1 80 Coater disc coater, 364-366 fluidised-bed coater, 337, 347, 355, 358-360, 364 pan coater, 364-366 rotating drum coater, 364-366 spouted bed coater, 360-362 Wurster coater, 362-364 Coating, 23, 79, 81 , 84-90, 1 58, 1 73, 1 8 1 , 685, 687 coating efficiency, 338, 348, 35 1 , 352, 355, 357, 367 coating quality, 338, 372 dry coating, 330-33 1 , 333 melt coating, 331 , 337 modelling of coating, 366-372 wet coating, 330, 335-336 Coating variability, 377, 379-380, 382, 385, 387, 389-390, 392, 394-395, 397-399, 412, 4 1 4 Co-extrusion, 2 1 4 Cohesion, 1 041 , 1 062-1 064, 1 067 Cohesive failure, 8 1 8 Cohesive forces, 1 041 , 1 053, 1 059, 1 062-1 063, 1 067 Cohesive stress, 707 Cohesivity, 8 1 7 Collision frequency, 1 1 1 0, 1 1 20-1 1 2 1 , 1 1 33-1 1 35, 1 1 37-1 1 38, 1 1 42, 1 1 58, 1 1 80 Collision model, 1 076 Collision rates, 983 Compact, 736-737 Compact strength, 277 Compaction, 425, 982 Compaction equations Cooper and Eaton, 748-749 Heckei, 750-751
Subject Index Kawakita, 749-750 Walker, 748 Compaction mechanisms, 744-755 Compaction problems, 766 binding, 770 chipping, 770 cracking, 766-769 disintegration, 772 dissolution, 772 mottling, 772 picking, 769 pitting, 770 tensile strength, 771 weight control, 771 -772 Compaction simulator, 761 -762 Compressibility factor, 265-266, 268, 275 Computer simulation, 1 030, 1 353, 1 357, 1 375 Concave toroidal model, 1 278 Cone-and-plate shearing device, 820 Confectionery, 660 Consolidation, 1 98, 200, 208, 853, 856, 859, 86 1-862, 866-867, 870, 872, 875-877, 88 1-882, 884, 886, 889-89 1 , 893, 929, 938-940 Consolidation rate constant, 944-945 Contact angle, 904, 1 01 7, 1 258, 1 263-1 268, 1 272, 1 278, 1 280, 1 284-1 287, 1 289, 1 294, 1 301 , 1 304, 1 307, 1 324, 1 362 advancing, 1 342 hysteresis, 1 342 receding, 1 340 Contact angle hysteresis, 1 264, 1 284 Contact area, 1 0 1 3 Contact line, 1 32 1 pinning, 1 340 slipping, 1 340 Continuous, 443, 853-855, 858, 861 , 869, 872, 876, 878, 885, 887-888, 890-893 Continuous fluidized-bed, 448 Continuous operation, 99, 1 04 Continuous processing, 451 Continuous product discharge, 448 Control, 466, 854, 856-857, 862-864, 869-870, 872, 874, 876, 879, 887-888, 890-892 Convenience foods, 648
1 38 1 Convex toroidal model, 1 280 Conveying, 680-682 Cracks, 1 0 1 3 Critical impact velocity, 993 Critical separation distance, 1 265 Critical stress intensity factor (Kid, 766 Cross section, 1 1 99-1 201 , 1 204-1 209, 121 1 Cross-linking, 569 Crystallisation, 594-595, 647 Cultures, 558-559, 580 Dairy powders, 644 Damage ratio, 1 0 1 3 De-aeration, 258, 262, 278 Deformation, 980 Deformation of particles, 229 Degree of wetting, 22, 1 00, 1 08, 1 1 1 , 1 1 3-1 1 4 , 1 1 6-1 1 8, 1 20-1 2 1 , 1 23-1 24, 1 26-1 29, 1 3 1-1 32, 1 34-1 35, 1 40-142, 1 79, 1 83 Delivery number, 853, 872, 885-886 DEM (Discrete Element Modeling), 377, 380, 397, 398, 4 1 4 , 1 020, 1 030, 1 200-1 201 Densification, 5, 674, 680, 683 Densities bulk, 1 98, 2 1 3 tapped, 1 98, 2 1 3 Density, 674, 678-680, 684, 687, 689-690, 692, 694, 700, 855-856, 859, 865, 867, 870, 872-874, 886, 891-892 Density distribution, 753-754 Derjaguin radius, 1 338 Detergent, 673-679, 681-683, 685-691 , 693-695, 697, 699 Detergent enzymes, 567, 572, 574 Dewetting, 1 289, 1 291 , 1 3 1 2 Diagenesis, 1 357 Diagnostic and guidance systems, 543 abnormal situation management (ASM), 504 expert system G2, 543 Failure Mode Effects Analysis (FMEA), 544 fault trees, 543 HAZOP, 543-544,547,552 hierarchical coloured Petri net (CPN) approach, 544
1 382 Kaiman filters and extended Kaiman filters, 543,548 operator guidance systems (OGS), 544 pattern recognition techniques, 45 root-cause analysis, 45 Diametral compression test, 762-764 Die, 1 89-1 90, 1 92-1 93, 1 96 , 200-201 , 205, 207, 2 1 2 , 2 1 4 Die fill, 74 1 -743 Diffusion, 1 366-1 368, 1 372, 1 376 Dimensionless analysis, 7 1 0 Dimensionless flow stress, 937 Dimensionless groups, 7 1 2 Dimensionless nucleation number, 91 0 Dimensionless spray flux, 908-909 Direct pelletization, 780, 782, 784, 789-790, 792, 794, 799-800 Discharging, 443 Discrete element, 270 Discrete element model, 1 074 Discretization, 1 1 65-1 1 70, 1 1 75 Discretized population balance, 1 1 09, 1 1 66 Disintegration, 1 0 1 1 Disintegration time, 772 Dispensing, 679-68 1 , 689 Dispersion , 686, 8 1 5, 853, 855-856, 859-865, 872, 874, 886, 888-889, 893 Dispersion map, 848 Dispersive mixing, 81 6 Dissolution, 209, 2 1 3 , 673-674, 678-680, 686, 688-690, 692, 694-695, 697-698 1 353-1 354, 1 367-1 369, 1 372-1 373, 1 375-1 376 Distribution of binder, 1 1 93 Distributive mixing, 8 1 6 Distributor design, 1 04 1 , 1 048-1 049 Dosage form design, 725-726 DPI, 3 1 3, 3 1 8, 32 1 Drop penetration time, 906, 920 Drop size distribution, 455 Drum coaters, 420 Drum critical speed, 248 Drum flight arrangement, 248 Drum granulation, 2 1 9-251 Drum granulation models, 249-250 Drum rotational speed, 225-227 Dry granulation, 289-291 , 308-309, 3 1 2 , 32 1
Subject Index Dry material handlingjrecirculationj production of seeds, 453 Dry powder inhalation, 289, 3 1 3-31 4 Dry product treatment, 464 Drying, 853, 856-857, 859-861 , 866 fluidised bed, 1 90, 1 99 freeze, 1 99 Drying liquid bridge, 1 250 Ductile, 995, 1 0 1 0 Dumb-bells, 1 96, 1 99, 205-207 Dynamic mechanical thermo analysis, 603 Dynamic strength, 1 006 Dynamic-yield strength, 1 002 EHEDG, 575-577, 579-582 Elastic, 995 Elastic deformation, 745, 752 Encapsulation, 325-326, 329, 331 Ennis coalescence model, 948 End-point, 477-480, 494 Enzoguard, 565-566 Enzymes, 555-557, 559-565, 567-575, 577, 579-581 , 583, 585, 587, 675, 687 Eötvös number, 1 345 Equipments, 4 1 8 Erosion, 8 1 8 Erosion kinetics, 83 1 , 840 Excipient, 1 99, 209, 21 1 -2 1 2 , 2 1 4 External seed production, 454 Extrudates, 1 90-1 9 1 , 1 95-1 97, 1 99-200, 203-207, 2 1 0 Extruder gear, 1 92 ram, 1 94-1 95, 2 1 3 , 2 1 4 screen, 1 93-1 94, 1 96 , 2 1 2 screw, 1 90, 1 92, 1 95, 202, 204 Extrusion, 1 89-2 1 5, 425, 627, 651 , 665 Extrusion pressure, 486-489 Extrusion spheronisation, 571 Fabric, 676-677 Fat bridges, 6 1 0 FDA, 575, 578 FDA's PAT initiative, 730 Feeding systems, 26 1 Fermentation, 557, 560, 580, 583 Fermipan, 557 Fertilizer granulation, 241 -243 Filtermat, 586-588
Subject Index Finite element, 269, 1 1 60, 1 1 64-1 1 65 Flange, 579 Flow field , 853, 872, 879, 882, 889 Flow pattern , 853, 875, 878-879 , 882-884, 888-890, 893 Flow regime, 879-880, 882, 884-885, 1 080 Fluid bed agglomeration, 6 1 9 Fluid-bed coating, 564, 576 Fluid bed granulator, 780, 785, 802 Fluidisation, 685, 1 04 1 -1 059, 1 06 1 -1 065, 1 067-1 068 Fluidized bed, 21-27, 29, 3 1 , 33--43, 45-59, 6 1 -65, 67-69, 71-75, 77, 79-85, 87, 89-9 1 , 93-95, 97, 99-1 03, 1 05, 1 07-1 09, 1 1 1-121 , 1 23-1 29, 1 31 -1 37, 1 39, 1 4 1 , 1 43-1 81 , 1 83-184, 291 , 294, 296, 298-299, 301 -302, 308-309, 3 1 3 , 3 1 8-31 9, 32 1 , 1 1 93, 1 1 95, 1 204-1 205 Fluidized-bed equipment, 424 Fluidized-bed granulation, 674, 684-686 Fluidized-bed granulators, 426 Flux number, 700 Food, 555, 558, 574-579, 581 , 583-585 Food protection, 575 Food safety, 574-575 Force feed, 26 1 Force-displacement, 753 Force-feeding, 261 Forces, 1 259, 1 269-1 270, 1 273, 1 276, 1 293-1 294, 1 297, 1 299-1 301 , 1 304, 1 307, 1 3 1 2 Fracture, 994 Fracture mechanics, 765-766, 997 Fracture pattern, 1 032 Fragmentation, 749, 752-753, 8 1 8, 983, 1 008 Frequency analysis, 479--480 Friction forces, 1 293, 1 301 Froude number, 71 1 , 7 1 3, 858, 872-874, 878, 883-886, 889 Fungi , 556 Gas distributors, 439 Gas handling, 430 Geldart's group, 1 047, 1 054 Glass transition, 578, 595 Glycerol monostearate, 2 1 0
1 383 Grains, 4 1 8 Granular flow, 874, 879-880, 882, 888, 891 Granulating liquid, 7 1 2 , 7 1 5 , 7 1 9 , 72 1-722, 727, 729 Granulating liquid requirement, 72 1 Granulation, 21-25, 27, 29, 3 1 , 33, 35, 37, 39, 4 1 , 43, 45--47, 49-51 , 53-55, 57, 59, 6 1 , 63, 65, 67, 69, 71 , 73, 75, 77, 79-81 , 83-85, 87, 89-9 1 , 93, 95, 97-1 03, 1 05, 1 07-1 09, 1 1 1-1 1 3, 1 1 5-1 1 7, 1 1 9, 1 2 1 , 1 23, 1 25, 1 27, 1 29, 1 3 1 , 1 33, 1 35, 1 37, 1 39, 1 4 1 , 1 43-1 8 1 , 1 83, 1 90-1 9 1 , 207, 209-2 1 0 , 220, 673-679, 681-687, 689-693, 695, 697, 699-700, 1 2 1 3-1214, 1 2 1 6- 1 2 1 8 , 1 222, 1 240, 1 244, 1 248 Granulation endpoint detection, 7 1 0 Granulation growth models, 235-237 Granulation index, 690 Granulation kinetics, 244-246 Granulation performance, 1 273, 1 302-1 303, 1 3 1 3 Granulation process control, 705, 7 1 3 , 7 1 7, 7 1 9 Granulation systems control of, see Process control diagnosis of, see Diagnostic and guidance systems dynamic analysis of, 5 1 0,549 future challenges, 549 mathematical modelling of, see Population balance models measurement of, see Process measurement operational aspects of, see Process optimization regime separated devices, 549 steady state analysis of, 51 1 Granule, 673, 675, 679-681 , 683, 686-692, 694-699 Granule design, 737-738 Granule flow, 739-741 Granule friability, 1 304 Granule growth, 2 1 , 53, 59-60, 1 79 Granule impact energy, 992 Granule strength, 1 2 1 3, 1 2 1 5- 1 2 1 6 , 1 226, 1 231 , 1 254 Granule T, 562-563, 567, 572
1 384 Granule TX, 567 Gravitational distortion, 1 260 Gravity feed, 26 1 , 275 Greyscale, 1 208- 1 2 1 1 Growth, 333, 335-336, 338, 341 , 347-350, 352-353, 356-358, 362, 366, 368-372, 683, 685-686, 700, 853, 856-857, 859-870, 874-875, 877, 889, 892, 929-930, 946, Growth regime map, 233-235, 933-934 Half-filiing angle, 1 263, 1 265, 1 271 Hamaker constant, 8 1 8 Handling, 673, 68 1 -682, 697 Hard metal, 289, 300, 306-308, 3 1 0, 3 1 2 Hardness, 1 1 93, 1 270, 1 293-1 295, 1 297-1 301 Heat and mass transfer, 22-24, 26, 85, 1 00, 1 08, 1 1 9-1 20, 1 23, 1 56 High shear granulation, 3, 563 High shear granulators, 42 1 , 469 High-shear granulation mixer, 674, 676, 678, 683-684, 687 High-pressure, 425 High-shear, 1 204-1 205, 1 207 Horizontal axis, 4 Horizontal axis ploughshare mixers, 1 1 Horizontal fluidized-bed, 450 Hydrodynamics in spout fluidized beds, 1 079 Hydrophobie nucleation , 922 Hygiene, 575, 577-578 Hygienic design, 555, 574, 576-578 Hygroscopicity, 598, 682 Hygrosensitivity, 599 IAFIS, 575 IAFP, 575 I D FA, 575 I mage processing, 477-478, 489-495 Imaging techniques, 1 1 89, 1 1 98-1 1 99 I mpact tests, 1 007 I mpact, wear, 982 Impelier speed, 6 In process computer program, 7 1 4 Induced particie drift, 1 098 Induction behaviour, 931
Subject Index I nfiltration, 820, 825 Infiltration Kinetics, 826 infrared (IR) moisture sensor, 481 , 483-484 I n-process control, 7 1 0 , 722, 726 I nstant yeast, 557 Instrumentation, 466 Interparticie forces, 1 04 1 , 1 047, 1 055, 1 057-1 058, 1 062-1 063 I nterparticie forces, 340-345 Inverse problem, 1 1 09-1 1 1 0, 1 1 1 5, 1 1 31 , 1 1 76 IR, 1 1 98 JOhanson, 264, 268, 276 Kawakita, 688 Kinetic energy, 1 259, 1 272, 1 293 Kinetic theory of granular flow, 1 087 Kinetics, 982 Lactic acid bacteria, 556 Lactobacilii, 557 Lactose, 1 94, 203, 206, 209, 2 1 1 Laplace-Young equation, 1 3 1 9, 1 345 Laundry, 675, 688 Layering of seeds, 782 Life cycie concept, see Systems perspective Likelihood of erosion, 845 Liquid bridge force, 707 Liquid bridges, 606, 8 1 8, 1 04 1 , 1 058-1 059, 1 063, 1 258-1 260, 1 264, 1 266- 1 267, 1 270, 1 272, 1 276, 1 284, 1 286, 1 289, 1 291-1 292, 1 294-1 295, 1 301 , 1 303, 1 305-1 307, 1 3 1 1 , 1 31 3, 1 3 1 7 see also capiliary bridge; capiliary force Liquid carrying capacity, 677, 685 Liquid feed system, 460 Liquid handling, 455, 465 Liquid phase migration , 1 92, 1 94, 204-205, 21 1 , 2 1 3 Liquid to solid ratio, 5 , 675, 677, 690, 693, 697 Load transmission, 995 Loss angle, 605 Loss modulus, 604 Low-pressure extruders, 425 Lubricant, 2 1 0 , 737-738, 744, 754, 765, 769
Subject Index Macrostructure, 689-690 Marumerizer, 560 Marumerization, 1 89-1 90, 1 95 Material charging, 443 Material properties, 262, 267 Mathematical modeling, drum granulation, 235-241 Mathematical modelling, 1 375 Matrix granule, 568 Maximum granule pore saturation, 931 Mechanically fluidized bed, 624, 650 Mechanisms, 982 Mechanisms of granule growth, 235-237 Melt pelletization, 801-809 coalescence, 804-805, 808, 809 distribution, 804-805 immersion, 804-805, 808, 809 layering, 804-805, 808 Melting, 5 Meniscus, 1 26 1 , 1 265, 1 267, 1 270, 1 278-1 280, 1 282, 1 307, 1 3 1 4 Mesostructure, 686 Method of binder addition, 5 Method of Lines, 1 1 09, 1 1 65 Method of moments, 1 1 63-1 1 64 Micelles, 2 1 3 Micro organism, 556-557 Microcrystalline cellulose (MCC), 1 94, 200 Micro-Force Balance (MFB), 1 273-1274, 1 276, 1 304-1 305 Micromanipulation, 1 272-1 273, 1 277, 1 305, 1 3 1 2 Microstructure, 689, 700, 1 353-1 357, 1 363-1 368, 1 375-1 376 Minimum fluidisation, 1 042, 1 044-1 046, 1 048, 1 050, 1 053, 1 056-1 058, 1 062, 1 064 Mixer, 420, 857-858, 860, 868-869, 872-886, 888-893 high shear, 1 91 -1 92 planetary, 1 91-1 92 Mixer load, 9 Mixing, 8 1 6 Mixing behaviour, 22, 1 2 1 , 1 81 Mixing rule, 687 Modelling, 775, 98 1 , 1 258, 1 284, 1 286 Modelling for granulation, 506-509 black-box, 520,530 hybrid models, 5 1 2
1 385
population balance models, see Population Balance Models reduced order models, 5 1 7 role of, 5 1 0 , 5 1 2-5 1 3 , 5 1 9 Moisture content, drum granulation, 223-225 Moisture measurement, 477, 481 Molten binder, 780, 784, 802, 804-808 MOM, 562, 564 Moments, 1 1 09, 1 1 30, 1 1 40, 1 1 42, 1 1 62-1 1 64, 1 1 67-1 1 68, 1 1 70-1 1 7 1 , 1 1 73, 1 1 78 Morphology of re-crystallized material, 1 234 Monte Carlo, 377, 380, 384-390, 393, 396-397, 399, 4 1 2 Monte Carlo simulation, 1 1 09, 1 1 75 MRI, 1 1 98-1 1 99 MSD, 569-570 Multi stage drying, 570, 574 Multi-dimensional population balance, 1 1 1 0, 1 1 28, 1 1 59, 1 1 79 Multi-fluid model, 1 086 Multi-level mOdeling, 1 072 Multi-scale, 853, 887-888, 894 Multiscale, multitask perspectives, 506-5 1 0 length and time scales, 506 scale map for granulation processes, 508 multiscale integration frameworks, 509
Nataphos, 570-572, 574 Nauta blender, 560 Neural networks, 271 Neutral angle, 258, 269, 276 Nip, 258, 261 , 265, 268, 277, 281 Nodoid configuration, 1 266 Nozzle arrangements, 459 NSF, 575, 577, 579 NUcieation, 2 1 , 59-60, 63, 853, 859, 86 1 -864, 869, 886, 889-890, 899 Nucleation area ratio, 9 1 0 Nucleation formation mechanism, 901 Nucleation process, 902 Nucleation ratio, 926 Nucleation regime map, 920-922 Nucleation regimes, 903
1 386 Number density, 1 1 1 4, 1 1 1 9-1 1 20, 1 1 23, 1 1 30, 1 1 34, 1 1 64, 1 1 66-1 1 67, 1 1 70, 1 1 72-1 1 74 Numerical techniques for population balance models, 5 1 3-51 4 Hounslow's discretization methods, 5 1 4-51 6 I mmanuel and Doyle I I l's finite element method, 5 1 5 Kumar and Ramkrishna's fixed and moving pivot methods, 5 1 4 Monte Carlo methods, 5 1 4 wavelet methods, 5 1 4 Nusselt number, 71 1 One-dimensional population balance, 1 1 23 Operating principles, 4 1 8 Oscillatory shear device, 820 Oversized grains, 453 Overspray, 453 Packed beds, 1 04 1 , 1 043-1 044 Packing, 1 9 1 , 1 98, 204, 208, 21 1 Packing density, 822 Pan coating, 379, 381 , 385, 403 Parabolic approximation, 1 265, 1 267, 1 273, 1 278, 1 282-1 283, 1 285, 1 287, 1 289-1 290, 1 297 Paracetamol, 1 304-1 309, 1 3 1 1-1 3 1 2 Partial voxeling, 1 1 98-1 1 99 Particle morphology, 1 355, 1 359-1 361 Particle packing, 1 353, 1 357, 1 36 1 -1 362 Particle size and shape, 1 0 1 9 Particle size distribution, 1 90, 1 94, 202, 205, 209, 21 1 , 2 1 4 Particle size distribution, drum granulation, 222-229 Paste, 1 97, 1 99-200, 202, 204-205, 2 1 0, 2 1 2-21 4 Peak pressure, 266, 268, 276-277 Pellet properties aspect ratio, 781 dissolution profile, 785 shape parameter, 781 Pelletization, 4 1 9 , 422-423 Pelletization aid, binder, 790-794 crystallite-gel model, 790, 791 microcrystalline cellulose (MCC), 783, 790-794, 799 sponge model, 790-79 1
Subject Index Pellets, 557, 570 Pendular, 1 258, 1 278, 1 282, 1 289, 1 293, 1 301 Pendular liquid bridge, 1 3 1 7 see also capillary bridge; capillary force Penetration time, 904 Percolation theory, 728 Pertume, 675-676, 678, 682, 687 Permanent plastic deformation, 954 Permeability, 826, 1 354, 1 365, 1 367, 1 372, 1 374-1 375 Pharmaceutical granules, 1 303 Phase ratio, 243 Phase volume, 675-676, 689-690, 693, 698-699 Plastic deformation, 745-746, 752-753, 766, 995, 1 1 44, 1 1 46, 1 1 50, 1 1 52, 1 1 54-1 1 55, 1 1 58 Pneumatic behaviour, 21 , 24, 47, 49, 1 00, 1 79 Pneumatically fluidized bed, 6 1 9, 650, 659 Polyethylene glycol, 801 , 803, 808-809 Population balance equation (PBE), 367-371 Population balance mOdelling, 237-238, 1 024 Population balance models (PBM), 51 3-52 1 , 537,544 birth rate, 5 1 3-51 5 coalescence kerneis, 5 1 7-51 8, 521-523,541 control relevant models, 523-525, 538 death rate, 5 1 3-51 5 growth rate, 51 1 , 51 3,523-524 linear models, 51 0,51 8-51 9 liquid mass balance, 524 multi-dimensional population balances, 518 multiple model approach, 5 1 8 population balance models, 5 1 3,51 5, 52 1 ,537 powder mass balance, 524 Pore size, effective, 906 Porosity, 673, 680, 684, 688-694, 697, 699-700, 854-856, 859, 861 , 870, 882, 1 0 1 9, 1 1 89, 1 200, 1 353, 1 357, 1 364, 1 368-1374, 1 376
1 387
Subject Index Porosity of tablets, 738, 745, 747, 772 Porous particie, 923-924 Positron emission particle tracking (PEPT) , 1 1 Post hardening, 668 Pouring , 5 Powder caking, 1 21 4 Powder coating, 289, 3 1 5 Powder flux, 908 Powder layering, 4 1 9 Powder motion , 1 1 Power consumption, 477-480, 489, 494 Power consumption method, 709, 7 1 3-71 5, 720, 722, 724-726 Power consumption profile, 709, 71 7-720, 722 Power-draw, 853, 872, 874 Pre-compressed, 1 1 90, 1 1 95 Pressure agglomeration, 627 Pressure swing granulation, 29 1 -292, 32 1 Prilling , 560-56 1 , 564, 568 Primary particle, 688-689, 692, 694-695 Primary particle size, 1 1 Principle of similarity, 7 1 0 Probiotics, 556-559 Process analytical technology (PAT), 775 Process control feedback/feed-forward control, 530-531 fuzzy logic control, 530 model predictive control (MPC) based on linear models, 532-535 multi-level, non-linear model predictive control (ML-NMPC), 522,533-537 multi-level control under uncertainty, 538-540 relative gain array (RGA), 5 1 1 Process measurement, 51 9-52 1 indirect minitoring parameters, 52 1 ,530-532 measurement of particle size distribution, 520 measurement of solid moisture, 520 soft sensors, 5 1 3 Process optimization, 52 1 algorithm of, 525-526 dynamic optimization (optimal control), 512,525-526 mini-max optimization, 540-542
objective functions for optimization, 525-526 simulation results and discussion, 526-530 steady state optimization, 521 -527 Process time, 8 Processing gas handling, 464 Processing options, 428, 442, 461 , 472 Product design, 1 375 Product examples, 22, 24, 1 56 Product forms, 4 1 8 Product properties, 4 1 8 Properties, 1 1 90, 1 1 92-1 1 95, 1 1 98, 1 204 Quality by design , 731 Quality control (tablet), 775-776 Quantification, 1 1 89, 1 1 98 Radial distributions, 1 209 Rate of liquid addition, 6 Rate processes, 899 Reaction , 853, 856, 860-86 1 , 879 Recycie, 854, 857, 887-888, 892 Reduced order models, 5 1 7-51 8 lumped regi mes i n series, 5 1 8 model reduction for multi-dimensional population balances, 5 1 8 reduced order models using the method of moments, 5 1 8 Relaxation time, 602-603 Release, 258-259, 324-328, 331 , 364 Residence time, drum granulation, 227-229 Resistance, 991 Reynolds number, 71 1 Robust formulations, 726 Roll compaction , 256 Roll pressing, 255 Roll speed, 276 Roller compaction , 629, 652, 1 1 94 Roll-gap, 280 Roping, 1 4 Rotary fluid bed processor, 780, 781 fluidizing air temperature, 807 particle movement, 781 , 795, 807 rotating friction plate, 781 , 785, 803, 806 rotor speed, 788, 795, 797, 80 1 , 807 spray nozzle, 780, 787, 795, 806 Rotating drums, 420
1 388 Rotational frame, 1 7 Rotor-processing (tangential spray), 428 Rumpf Model, 842 Rupture, 8 1 8, 1 334, 1 339-1 340, 1 346-1348 Rupture distance, 1 258, 1 265, 1 271 , 1 284, 1 287, 1 289 Rupture energy, 1 259, 1 271-1 272, 1 276 Saturation, 5, 853, 861-862, 870, 874-875, 890, 893 Scale-up, 24, 1 79, 289, 305-308, 289, 303, 306, 307, 32 1 , 705, 7 1 0, 7 1 2, 7 1 7, 853-859, 861 , 863-865, 867-869, 871-894, 9 1 9 Scale-up invariant, 7 1 0 , 71 1 , 7 1 7 , 722 Scale-up precision, 72 1 Schmidt number, 71 1 Screw feeder, 277 Sealing, 262 Seals, 578-579 Seeds (nuclei), 453 Segmentation, 1 1 98 Segregation, 1 1 0 1 Self-agglomerating, 291 Self-preserving, 1 1 39, 1 1 4 1 , 1 1 62, 1 1 77 Self-similar, 1 1 39, 1 1 4 1 -1 1 43 Self-similarity, 1 1 39, 1 1 4 1 S E M , 1 1 94, 1 1 96, 1 1 98 Semi-brittle , 995, 1 0 1 0 Semi-brittle granules, 967 Separation distance, 1 264-1 265, 1 268, 1 271 , 1 277, 1 283-1 285, 1 287, 1 290, 1 297, 1 3 1 4 Shape reconstruction, 1 36 1 Shear, 995 Shear rate, 859-860, 868-869, 879-880, 883-885 Shear strength, 1 003 Shear stress, 857, 864, 866, 868, 871 , 875, 883-884, 890 Sherwood number, 71 1 Similarity criteria, 71 1 Simulation of a granulation process, 1 084 Single particle, 4 1 8 Sintering, 608, 1 041 , 1 058, 1 061-1 062, 1 065-1068
Subject Index Size distribution particle size distribution, 520, 530-532, 537, 550 binder size distribution, 544 Size enlargement, 4 1 9 Slip, 258, 265, 280 Slugging, 1 04 1 , 1 047-1 048, 1 052 Smoluchowski equation, 1 1 09, 1 1 1 6, 1 1 1 9-1 1 21 , 1 1 4 1 , 1 1 75 Solid bridges, 607, 1 202, 1 21 4-1 2 1 7 , 1 229-1 231 , 1 234-1 235, 1 247, 1 250-1252 Solids circulation, 1 04 1 , 1 049, 1 05 1 -1 052 Solvent extraction, 1 1 89, 1 1 93-1 1 96 Specific energy, 853, 872, 875-878 Spray angle, 455 Spray area, 385-386, 388, 390, 393-395, 4 1 2 Spray coating, 4 1 9 Spray crystallization, 453 Spray dryers, 461 Spray drying, 423, 453, 559, 570, 572, 576, 6 1 3 , 646, 657 Spray flux, 853, 860, 872, 874, 886, 889-890 Spray granulation, 4 1 9 Spray nozzle, 455 Spray pattern , 455 Spray shape, 385-386, 388, 390, 393-394, 4 1 2 Spray systems, 455 Spray-coated, 1 1 92 Spray-dried, 1 1 9 1 , 1 1 95 Spray-drying, 674, 676, 68 1 , 684 Spraying , 5 Spreading, 856, 859, 863, 889 Spreading coefficient, 1 304-1 305 Spray flux, 9 1 5-9 1 6 Stareh , 555-556, 564-565, 568-569, 571 -574 Steady growth , 929, 931 Steady-state, 22, 53, 70, 78, 1 09, 1 25, 1 27, 1 31 -1 33 Steam jet agglomeration, 6 1 6 , 657 Stickiness, 569-570. 584-586, 588 Sticky region, 584-585 Stokes, 853, 858, 863-868, 876, 891 Stokes deformation number, 932, 1 022 Stokes number, 684, 1 1 53, 1 1 55-1 1 58
1 389
Subject Index Storage modulus, 604 Strain rate, 1 003 Strength, 675-678, 680, 683, 688, 689, 697 Stress, 688, 755 Stress amplification, 834 Structural characteristics, 1 1 90, 1 1 92, 1 1 95 Structure, 673, 675, 678, 680, 686, 688-700, 853, 855, 86 1 -863, 867, 870, 875, 89 1 , 893, 1 01 9, 1 1 89-1 1 95, 1 1 97-1 205, 1 207-1209 Structure-property relationships, 1 353-1354, 1 365-1 368 Superheated steam granulation, 1 35 Superposition, 603 Supra molecular structure, 593 Surface energy, 1 258, 1 276 Surface tension, 945, 1 0 1 7, 1 259, 1 266-1 267, 1 270, 1 273, 1 277, 1 293-1294, 1 298, 1 301 , 1 306, 1 3 1 0-1 3 1 2 , 1 321 Surfactant, 676-677, 679-680, 683-684, 686-687, 691 Swept volume, 853, 872, 877-879, 886, 889 Synchrotron, 1 203 Systems perspective, 500-509 accomplishments, 506 definition, 500 impact of Iife cycle perspective, 503-504 importance of systems approach, 504-505 ISOj1 EC1 5288, 502 life cycie activities, 502 life cycie concept, 502-504 life cycle phases, 503 systems framework, 501-502 Tablet, 377-380, 382, 385-390, 392, 394-397, 403, 406-4 1 4, 688, 690, 737, 745, 753, 756-758, 760-76 1 , 767-768, 770-773 Tablet ejection, 758-759 Tablet presses, 758-760 Tablet shape, 377, 406, 409-4 1 0 Tablets, 4 1 8 Tabletting, 425, 637, 654, 661
Tensile strength, 708, 996, 1 000 Tensile strength measurement, 7 1 6 , 724-725 Tensile strength , 708 Tensile strength, tablet, 771 Three-phase contact line, 1 294 Throughput, 256, 261-262, 264, 276, 278, 281 Tip speed, 869, 872-875, 879, 882-883, 885, 891 , 893 Tomography, 673, 695-697, 1 1 89, 1 1 98-1 1 99, 1 203, 1 206 Top-driven high shear granulator, 472 Top-spray processing, 428 Toroidal approximation, 1 258, 1 265, 1 271 , 1 278-1 279, 1 28 1 , 1 283-1 284, 1 287, 1 323 Toroidal vortex motion, 1 4 Torque, 477-478, 480, 489, 494, 853, 872-875 Tracer experiments, 985 Transformation, 858-860, 864, 866-867, 869-870, 875, 887, 891 , 893 Transport properties, 1 353-1 354, 1 365, 1 369, 1 372, 1 375-1 376 Triaxial testing, 774 Undesired agglomeration, 665 Uniaxial compression, 268 Unsteady operation, 22, 1 28 USDA, 575 Validation, 555, 579, 581 , 1 1 1 0, 1 1 45, 1 1 48, 1 1 58-1 1 60, 1 1 78-1 1 80 Van der Waals Forces, 6 1 1 , 996 Variables, 987 Variables affecting granule strength, 1016 Vertical axis, 4 Video-imaging, 377, 38 1 , 385-388, 390, 401-402, 404, 4 1 2 Viscoelasticity, 601 Viscosity, 1 270, 1 272, 1 277, 1 293-1294, 1 298, 1 3 1 2 Viscous contribution, 1 270 Viscous forces, 1 293 Viscous Stokes number, 940 Voidage, 906
1 390 Volume-of-fluid method, 1 362 VTF equation, 603 Wall friction, 258, 266, 276 Washburn equation, 904 Weil-mixed fluidized bed, 452 Wet granulation, 4 1 9 Wet granulation process, 7 1 2 , 7 1 7 , 723 Wet granulators, 420--421 Wet granule breakage, 962-964, 968 Wet pelletization, 786-801 moisture content, 787-788, 798, 800-801 required granulation liquid, 782, 792 spray rate, 787, 796, 798 Wet-massed, 1 1 9 1 , 1 1 95-1 1 96 Wettability, 338-340, 1 264, 1 276-1 278, 1 284-1 285, 1 29 1 , 1 293 Wetting, 338-340, 350, 853, 856-857, 859-86 1 , 863, 889, 900, 1 258, 1 268, 1 272-1 273, 1 289, 1 296-1297, 1 303, 1 305, 1 307, 1 309, 1 3 1 2
Subject Index Wetting hysteresis, 1 258, 1 289, 1 294, 1 340 WLF equation , 603 Work of compaction, 752-753 Wurster-processing, 428, 442 X-ray computed tomography, 741 X-ray tomography, 904 XRT, 1 1 89, 1 1 98-1 203, 1 205-1 206, 1 208-1 209 Yeast, 555-557, 580-581 , 583-588 Yeast extract, 555, 580-581 , 583-588 Yield , 688 Yield stress, 752 Young-Laplace, 1 258-1 260, 1 262-1 264, 1 266, 1 284, 1 287 Young's modulus, 752, 765-766, 1 021 Zeolite, 676, 678, 682 Zig-zag-sifters, 450