Filled Polymers: Science and Industrial Applications

Filled Polymers Science and Industrial Applications

Filled Polymers Science and Industrial Applications Jean L. Leblanc

Boca Raton London New York

CRC Press is an imprint of the Taylor & Francis Group, an informa business

CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2010 by Taylor and Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S. Government works Printed in the United States of America on acid-free paper 10 9 8 7 6 5 4 3 2 1 International Standard Book Number: 978-1-4398-0042-3 (Hardback) This book contains information obtained from authentic and highly regarded sources. Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint. Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers. For permission to photocopy or use material electronically from this work, please access www.copyright.com (http://www.copyright.com/) or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400. CCC is a not-for-profit organization that provides licenses and registration for a variety of users. For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com

Contents Preface.......................................................................................................................xi Author Bio...............................................................................................................xv

  1. Introduction....................................................................................................1 1.1. Scope of the Book...................................................................................1 1.2. Filled Polymers vs. Polymer Nanocomposites...................................3 References........................................................................................................8   2. Types of Fillers............................................................................................ 11   3. Concept of Reinforcement......................................................................... 15 Reference........................................................................................................ 19   4. Typical Fillers for Polymers...................................................................... 21 4.1 Carbon Black......................................................................................... 21 4.1.1 Usages of Carbon Blacks.......................................................... 21 4.1.2 Carbon Black Fabrication Processes....................................... 21 4.1.3 Structural Aspects and Characterization of Carbon Blacks....................................................................... 24 4.1.4 Carbon Black Aggregates as Mass Fractal Objects..............30 4.1.5 Surface Energy Aspects of Carbon Black..............................44 4.2 White Fillers.......................................................................................... 49 4.2.1 A Few Typical White Fillers.................................................... 49 4.2.1.1 Silicates......................................................................... 49 4.2.1.2 Natural Silica............................................................... 52 4.2.1.3 Synthetic Silica............................................................ 53 4.2.1.4 Carbonates...................................................................54 4.2.1.5 Miscellaneous Mineral Fillers................................... 56 4.2.2. Silica Fabrication Processes..................................................... 56 4.2.2.1 Fumed Silica................................................................ 56 4.2.2.2 Precipitated Silica....................................................... 58 4.2.3 Characterization and Structural Aspects of Synthetic Silica.......................................................................... 62 4.2.4 Surface Energy Aspects of Silica............................................ 68 4.3 Short Synthetic Fibers.......................................................................... 69 4.4 Short Fibers of Natural Origin........................................................... 72 References...................................................................................................... 79

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Appendix 4.................................................................................................... 82 A4.1 Carbon Black Data............................................................................ 82 A4.1.1 Source of Data for Table 4.5............................................... 82 A4.1.2 Relationships between Carbon Black Characterization Data........................................................84 A4.2  Medalia’s Floc Simulation for Carbon Black Aggregate.............85 A4.3  Medalia’s Aggregate Morphology Approach............................... 86 A4.4  Carbon Black: Number of Particles/Aggregate............................ 89   5. Polymers and Carbon Black...................................................................... 91 5.1 Elastomers and Carbon Black (CB).................................................... 91 5.1.1 Generalities................................................................................ 91 5.1.2 Effects of Carbon Black on Rheological Properties............. 95 5.1.3 Concept of Bound Rubber (BdR).......................................... 108 5.1.4 Bound Rubber at the Origin of Singular Flow Properties of Rubber Compounds.......................... ............... 112 5.1.5 Factors Affecting Bound Rubber.......................................... 114 5.1.6 Viscosity and Carbon Black Level........................................ 121 5.1.7 Effect of Carbon Black on Mechanical Properties.............. 125 5.1.8 Effect of Carbon Black on Dynamic Properties.................. 140 5.1.8.1 Variation of Dynamic Moduli with Strain Amplitude (at Constant Frequency and Temperature)............................................................. 141 5.1.8.2 Variation of tan δ with Strain Amplitude and Temperature (at Constant Frequency)...................142 5.1.8.3 Variation of Dynamic Moduli with Temperature (at Constant Frequency and Strain Amplitude)..................................................... 142 5.1.8.4 Effect of Carbon Black Type on G′ and tan δ.................................................................... 144 5.1.8.5 Effect of Carbon Black Dispersion on Dynamic Properties................................................. 146 5.1.9 Origin of Rubber Reinforcement by Carbon Black............................................................................ 148 5.1.10 Dynamic Stress Softening Effect.......................................... 151 5.1.10.1 Physical Considerations........................................... 151 5.1.10.2 Modeling Dynamic Stress Softening as a “Filler Network” Effect............................................ 152 5.1.10.3 Modeling Dynamic Stress Softening as a “Filler–Polymer Network” Effect........................... 168 5.2 Thermoplastics and Carbon Black................................................... 172 5.2.1 Generalities.............................................................................. 172 5.2.2 Effect of Carbon Black on Rheological Properties of Thermoplastics........................................................................ 173

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5.2.3 Effect of Carbon Black on Electrical Conductivity of Thermoplastics........................................................................ 175 References.................................................................................................... 179 Appendix 5.................................................................................................. 185 A5.1 Network Junction Theory.............................................................. 185 A5.1.1 Developing the Model...................................................... 185 A5.1.2 Typical Calculations with the Network Junction Model.................................................................. 188 A5.1.3 Strain Amplification Factor from the Network Junction Theory................................................................. 190 A5.1.3.1 Modeling the Elastic Behavior of a Rubber Layer between Two Rigid Spheres................................................... 190 A5.1.3.2 Experimental Results vs. Calculated Data................................................ 191 A5.1.3.3 Comparing the Theoretical Model with the Approximate Fitted Equation.. .. ............ 192 A5.1.3.4 Strain Amplification Factor............................ 193 A5.1.4 Comparing the Network Junction Strain Amplification Factor with Experimental Data............. 194 A5.2 Kraus Deagglomeration–Reagglomeration Model for Dynamic Strain Softening............................................................. 196 A5.2.1 Soft Spheres Interactions................................................. 196 A5.2.2 Modeling G′ vs. γ0............................................................. 197 A5.2.3 Modeling G″ vs. γ0............................................................ 198 A5.2.4 Modeling tan δ vs. γ0........................................................ 200 A5.2.5 Complex Modulus G* vs. γ0............................................. 202 A5.2.6 A Few Mathematical Aspects of the Kraus Model...................................................................... 204 A5.2.7 Fitting Model to Experimental Data.............................. 206 A5.2.7.1 Modeling G′ vs. Strain.................................... 207 A5.2.7.2 Modeling G″ vs. Strain.................................... 209 A5.3 Ulmer Modification of the Kraus Model for Dynamic Strain Softening: Fitting the Model.............................................. 212 A5.3.1 Modeling G′ vs. Strain (same as Kraus)......................... 213 A5.3.2 Modeling G′′ vs. Strain..................................................... 215 A5.4 Aggregates Flocculation/Entanglement Model (Cluster–Cluster Aggregation Model, Klüppel et al.)............... 218 A5.4.1 Mechanically Effective Solid Fraction of Aggregate...................................................................... 219 A5.4.2 Modulus as Function of Filler Volume Fraction........... 220 A5.4.3 Strain Dependence of Storage Modulus........................ 221 A5.5 Lion et al. Model for Dynamic Strain Softening........................222 A5.5.1 Fractional Linear Solid Model.........................................222

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A5.5.2 Modeling the Dynamic Strain Softening Effect...........223 A5.5.3 A Few Mathematical Aspects of the Model.................. 226 A5.6 Maier and Göritz Model for Dynamic Strain Softening........... 227 A5.6.1 Developing the Model...................................................... 227 A5.6.2 A Few Mathematical Aspects of the Model.................. 229 A5.6.3 Fitting the Model to Experimental Data........................ 230 A5.6.3.1 Modeling G′ vs. Strain.................................... 231 A5.6.3.2 Modeling G″ vs. Strain.................................... 232   6. Polymers and White Fillers..................................................................... 235 6.1 Elastomers and White Fillers........................................................... 235 6.1.1 Elastomers and Silica.............................................................. 235 6.1.1.1 Generalities................................................................ 235 6.1.1.2 Surface Chemistry of Silica..................................... 236 6.1.1.3 Comparing Carbon Black and (Untreated) Silica in Diene Elastomers....................................... 237 6.1.1.4 Silanisation of Silica and Reinforcement of Diene Elastomers...................................................... 239 6.1.1.5 Silica and Polydimethylsiloxane............................. 246 6.1.2 Elastomers and Clays (Kaolins)............................................ 257 6.1.3 Elastomers and Talc................................................................ 260 6.2 Thermoplastics and White Fillers.................................................... 262 6.2.1 Generalities.............................................................................. 262 6.2.2 Typical White Filler Effects and the Concept of Maximum Volume Fraction.................................................. 266 6.2.3 Thermoplastics and Calcium Carbonates........................... 280 6.2.4 Thermoplastics and Talc........................................................ 291 6.2.5 Thermoplastics and Mica...................................................... 297 6.2.6 Thermoplastics and Clay(s)...................................................300 References.................................................................................................... 302 Appendix 6..................................................................................................308 A6.1 Adsorption Kinetics of Silica on Silicone Polymers...................308 A6.1.1 Effect of Polymer Molecular Weight..............................308 A6.1.2 Effect of Silica Weight Fraction....................................... 310 A6.2 Modeling the Shear Viscosity Function of Filled Polymer Systems............................................................................. 312 A6.3 Models for the Rheology of Suspensions of Rigid Particles, Involving the Maximum Packing Fraction Φm........................... 315 A6.4 Assessing the Capabilities of Model for the Shear Viscosity Function of Filled Polymers......................................... 319 A6.4.1 Effect of Filler Fraction..................................................... 320 A6.4.2 Effect of Characteristic Time λ0...................................... 320 A6.4.3 Effect of Yasuda Exponent a............................................ 321 A6.4.4 Effect of Yield Stress σc................................................... 321

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A6.4.5 Fitting Experimental Data for Filled Polymer Systems.............................................................. 322 A6.4.6 Observations on Experimental Data............................ 323 A6.4.7 Extracting and Arranging Shear Viscosity Data.................................................................. 324 A6.4.8 Fitting the Virgin Polystyrene Data with the Carreau–Yasuda Model.................................................. 324 A6.4.9 Fitting the Filled Polystyrene Shear Viscosity Data................................................................................... 326 A6.4.10 Assembling and Analyzing all Results........................ 332 A6.5 Expanding the Krieger–Dougherty Relationship...................... 335   7. Polymers and Short Fibers...................................................................... 339 7.1 Generalities......................................................................................... 339 7.2 Micromechanic Models for Short Fibers-Filled Polymer Composites..........................................................................................344 7.2.1 Minimum Fiber Length.........................................................344 7.2.2 Halpin–Tsai Equations...........................................................345 7.2.3 Mori–Tanaka’s Averaging Hypothesis and Derived Models...................................................................................... 351 7.2.4 Shear Lag Models.................................................................... 353 7.3 Thermoplastics and Short Glass Fibers........................................... 358 7.4 Typical Rheological Aspect of Short Fiber-Filled Thermoplastic Melts.......................................................................... 368 7.5 Thermoplastics and Short Fibers of Natural Origin..................... 370 7.6 Elastomers and Short Fibers............................................................. 375 References.................................................................................................... 383 Appendix 7.................................................................................................. 389 A7.1 Short Fiber-Reinforced Composites: Minimum Fiber Aspect Ratio..................................................................................... 389 A7.1.1 Effect of Volume Fraction on Effective Fiber Length...................................................................... 389 A7.1.2 Effect of Matrix Modulus on Effective Fiber Length...................................................................... 390 A7.1.3 Effect of Fiber-to-Matrix Modulus Ratio on Effective Fiber Length/Diameter Ratio......................... 391 A7.2 Halpin–Tsai Equations for Short Fibers Filled Systems: Numerical Illustration.................................................................... 391 A7.2.1 Longitudinal (Tensile) Modulus E11............................... 392 A7.2.2 Transversal (Tensile) Modulus E22. ................................ 393 A7.2.3 Shear Modulus G12............................................................ 393 A7.2.4 Modulus for Random Fiber Orientation........................ 394 A7.2.5 Fiber Orientation as an Adjustable Parameter. ......................................................................................394

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A7.2.6 Average Orientation Parameters from Halpin–Tsai Equations for Short Fibers Filled Systems.................................................................... 394 A7.2.6.1 Longitudinal (Tensile) Modulus E11.............. 395 A7.2.6.2 Transversal (Tensile) Modulus E22. ............... 396 A7.2.6.3 Orientation Parameter X................................. 396 A7.3 Nielsen Modification of Halpin–Tsai Equations with Respect to the Maximum Packing Fraction: Numerical Illustration........................................................................................ 396 A7.3.1 Maximum Packing Functions......................................... 397 A7.3.2 Longitudinal (Tensile) Modulus E11............................... 398 A7.3.3 Transverse (Tensile) Modulus Ey.................................... 398 A7.3.4 Shear Modulus G.............................................................. 398 A7.4 Mori–Tanaka’s Average Stress Concept: Tandon–Weng Expressions for Randomly Distributed Ellipsoidal (Fiber-Like) Particles: Numerical Illustration............................. 399 A7.4.1 Eshelby’s Tensor (Depending on Matrix Poisson’s Ratio and Fibers Aspect Ratio Only).............................. 399 A7.4.2 Materials’ Constants (i.e., Not Depending on Fiber Volume Fraction)...............................................................400 A7.4.3 Materials and Volume Fraction Depending Constants............................................................................ 401 A7.4.4 Calculating the Longitudinal (Tensile) Modulus E11. ...................................................... 402 A7.4.5 Calculating the Transverse (Tensile) Modulus E22....... 402 A7.4.6 Calculating the (In-Plane) Shear Modulus G12............. 403 A7.4.7 Calculating the (Out-Plane) Shear Modulus G23..........404 A7.4.8 Comparing with Experimental Data.............................404 A7.4.9 Tandon–Weng Expressions for Randomly Distributed Spherical Particles: Numerical illustration...................................................... 406 A7.4.9.1 Eshelby’s Tensor (Depending on Matrix Poisson’s Ratio Only)....................................... 406 A7.4.9.2 Materials’ Constants (i.e., Not Depending on Filler Volume Fraction)......... 406 A7.4.9.3 Materials and Volume Fraction Depending Constants..................................... 407 A7.4.9.4 Calculating the Tensile Modulus E...............408 A7.4.9.5 Calculating the Shear Modulus G.................408 A7.5 Shear Lag Model: Numerical illustration.................................... 409 Index........................................................................................................... 411

Preface This book is an outgrowth of a course I have taught for several years to master and doctorate students in polymer science and engineering at the Université Pierre et Marie Curie (Paris, France). It is also based on around 30 years of interest, research and engineering activities in the fascinating field of so-called complex polymer systems, i.e., heterogeneous polymer based materials with strong interactions between phases. Obviously, rubber compounds and filled thermoplastics belong to such systems. If one considers that, worldwide, around 40% of all thermoplastics and 90% of elastomers are used as more or less complicated formulations with so-called fillers, it ­follows that approximately 100 million tons/year of polymers are indeed “filled systems.” Quite a number of highly sophisticated applications of polymers would simply be impossible without the enhancement of some of their properties imparted by the addition of fine mineral particles or by short fibers, of synthetic or natural origin. The idea that, if a single available material cannot fulfill a set of desired properties, then a mixture or a compound of that material with another one might be satisfactory is likely as old as mankind. Adobe, likely the oldest building material, is made by blending sand, clay, water and some kind of fibrous material like straw or sticks, then molding the mixture into bricks and drying in the sun. It is surely one of the oldest examples of reinforcement of a “plastic” material, moist clay, with natural fibers that was already in use in the Late Bronze Age, nearly everywhere in the Middle East, North Africa, South Europe and southwestern North America. In a sense, the basic principle of reinforcement, i.e., to have a stiffer dispersed material to support the load transmitted by a softer matrix, is already in the adobe brick. Therefore, the “discovery” of natural rubber reinforcement by fine powdered materials, namely carbon black, in the dawn of the twentieth century surely proceeded from the same idea. At first, mixing rubber and carbon black was pragmatic engineering, it gave a better and useful set of properties, and the technique could be somewhat mastered, thanks to side developments, such as the internal mixer. The very reasons for the reinforcing effect remained unclear for a long time and the question only started to be seriously considered by the mid ­t wentieth century. Today, some light has been shed on certain aspects of polymer reinforcement, as will be reviewed through the book. But the story is surely not complete because any progress in the field is strongly connected with either the availability of appropriate experimental and observation techniques or theoretical views about polymer–filler interactions, or (and most likely) both. xi

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One of the starting points of my deep interest for filled polymers is the simple observation that, whilst having different chemical natures, a number of filled polymers, either thermoplastics or vulcanizable rubbers, exhibit common singular properties. This aspect will be thoroughly documented throughout the book but a few basic observations are worth highlighting here. Let us consider for instance the flow properties of systems that are as (chemically) different as a compound of high cis-1,4 polybutadiene with a sufficient level of carbon black and a mixture of polyamide 66 with short glass fibers. They share the same progressive disappearance with increasing filler content of the low strain (or rate) linear viscoelastic behavior. Regarding the mechanical properties, the effect of either fine precipitated calcium carbonate particles or short glass fibers on the tensile and flexural moduli of polypropylene are qualitatively similar but by no means corresponding to mere hydrodynamic effects. So, many filled polymer systems are similar in certain aspects and different in others. Understanding why is likely to be the source of promising scientific and engineering developments. The possibilities offered by combining one (or several) polymer(s) with one (or several) foreign stiffer component(s) are infinite and the just emerging nanocomposites science is an expected development of the science and technology of filled polymers, once the basic relationships between reinforcement and particle size had been established. For reasons that are given in Chapter 1, nanofillers have been excluded from the topics covered by the book, whose objectives are to survey quite a complex field but by no means offer the whole story. As stated above, teaching the subject is the origin of the book. In my experience, nothing must be left in the shadow when teaching a complex subject and all theories and equations found in the literature must be carefully checked and weighed, particularly if engineering applications are foreseen. I am not a theoretician but an experimentalist with an avid interest for any fundamental approach that might help me to understand what I am measuring. Therefore, whilst theoretical considerations that lead to proposals such as “property X is proportional to (or a function of) parameter Y,” i.e., X∝ Y or X∝ F(Y), may be acceptable in term of (scientific) common sense, they are of very little use for the engineer (and less so for the student) if the coefficient of proportionality (or the function) is not explicitly given. This is the reason why all equations displayed in the book have been carefully tested, using (commercial) calculation software. When one loads theoretical equations with parameters expressed in the appropriate units, then either the unit system is inconsistent and the software gives no results because the unit equation is considered, or the right units are used and the results of the theory can be weighed, at least in terms of “magnitude order.” If the results have the right order of magnitude, then the theoretical considerations are likely acceptable. If not… Such an exercise is always useful and I am grateful to my editor for having accepted, as appendices, a selection of calculation worksheets (obviously inactive in a printed book) that offer numerical illustrations of

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several of the theoretical considerations discussed in the book. Readers who are familiar with the calculation software I use will have no difficulties in implementing these appendices in their own work. As a last word, it is worth noting that writing a science book on an active field is (by essence) a never ending task since new interesting contributions are published every day. But working with an editor forces the scientistwriter to accept a deadline, in other words to make choices, to develop more certain subjects and drop other ones, and eventually to bring an end point, not final but temporary as always in science and industrial applications. Jean L. Leblanc Bois-Seigneur-Isaac

Author Bio Born in 1946, Jean L. Leblanc studied ­physico-chemistry at the University of Liège, Belgium, with a special emphasis on polymer science and received his PhD in 1976, with a thesis on the rheological properties on SBS bloc copolymers. He then joined Monsanto Company where, from 1976 to 1987, he held various positions in the rubber chemicals, the AcrylonitrileButadiene-Styrene plastics (ABS), and the santoprene• divisions. He left Monsanto in 1987 to join the italian company Montedison as manager, technical assistance and applied research, then moved to the position of manager applied research when Enichem took over Montedison in 1989. In 1988, he became fellow of the Plastics and Rubber Institute (U.K.) and in 1993 he qualified as European Chemist (EurChem). In 1993, he was elected Professeur des Universités in France and joined the Université Pierre et Marie Curie (Paris, France), as head of the then newly developed polymer rheology and processing laboratory, in collaboration with the French Rubber Institute. He is still in this position today and, since 1997, also teaches polymer rheology and processing at the Free University of Brussels (Belgium), as a visiting professor. He has written two books and more than 100 papers.

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1 Introduction

1.1  Scope of the Book This book deals with the properties of filled polymers, i.e. mixtures of ­macromolecular materials with finely divided substances, with respect to established scientific aspects and industrial developments. So-called (polymer) composites, that consist of long fibers impregnated with resins, such as glass fibers reinforced polyesters or carbon fibers reinforced epoxy resins, are not within the subject of this book. Filled polymers discussed hereafter are heterogeneous systems such that, during processing operations, the polymer and the dispersed filler flow together. In other words, filled ­polymers are macroscopically coherent masses that exhibit interesting physical, mechanical, and/or rheological properties, often peculiar, but always resulting from interactions taking place between a matrix (the polymer) and a dispersed phase (the filler). It follows obviously that filled polymers have to be prepared through mixing operations, generally complex and requiring appropriate machines, in such a manner that a thorough dispersion of filler particles is achieved. Why does one prepare filled polymers? There are many reasons, all of them related to engineering needs. Generally one mixes fillers into polymers in order to modify properties of the latter, either physical properties, such as density or conductivity, or mechanical properties, for instance modulus, stiffness, etc., or rheological properties, i.e., viscosity or viscoelasticity. Occasionally, fillers are also used for economical reasons, as cheap additives that reduce material costs in polymer applications. Table 1.1 gives the relative volume costs of a few common mineral fillers in comparison with several polymers, using polypropylene (PP) as a reference. Clearly, only grinded calcium carbonate and finely divided clays can be considered as “economical” fillers; in all other cases, specific property improvements are sought when mixing the filler and the polymer. A few numbers allow underlining the economical importance of filled polymers. According to recently published market research reports (2007), the worldwide consumption of fillers is more than 50 million tons with a global value of approximately €25 billion. Many application areas are concerned, 1

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Filled Polymers

Table 1.1 Relative Cost of Mineral Fillers and Polymers Type of Filler or Polymer Grinded calcium carbonate Grinded clays Polyvinyl chloride Carbon black Polypropylene Talc Polyethylene Calcined clays Wollastonite (not treated) Natural rubber Ethylene-propylene rubber Treated calcined clays Styrene-butadiene rubber Silica Precipitated CaCO3 Polyamides

Relative Weight Cost (Polypropylene = 1.0) 0.3–0.6 0.4–0.7 0.7 0.7–1.2 1 1.1–1.4 1.1 1.5–1.7 1.6 1.6 1.6–1.9 1.7–1.9 1.7 1.7–1.9 1.9 3.0–6.0

Note: Table assembled using prices and quotations on the European market during the first sem­ester of 2008.

such as paper, plastics, rubber, paints, and adhesives. Fillers, either synthetic or of natural origin are produced by more than 700 companies all over the globe. In Western Europe, 17 millions tons of thermoplastics were consumed in 2005 with a significant part in association with 1.7 millions tons of mineral fillers. Polyvinyl chloride (PVC) and polyolefins (polyethylene PE, PP) are the main markets for mineral fillers, with calcium carbonate CaCO3 accounting for more that 80% of the consumption (in volume). In rubber materials, more that 90% of the applications concern “compounds”, i.e. quite complex formulations in which fillers are used at around 50% weight (some 30% volume). The Western Europe consumption of rubbers was 3.79 millions tons in 2006 (1.28 MioT natural rubber; 2.51 MioT synthetic elastomers) and some 2.25 millions tons carbon black were used in the interim. Preparing and using filled polymers is consequently a well established practice in the polymer field, particularly in the rubber industry where the first use of carbon black as a reinforcing filler can be traced back to the early twentieth century. There are consequently a number of pragmatic engineering aspects associated with the preparation, the development and the applications of filled polymers, not all yet fully understood, despite considerable progresses over the last 50 years. As usual, scientific investigations on filled polymer systems started later than empirical engineering (trial-and-error)

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and it is only the recent development of advanced investigation means that really boosted research and development work in this area, obviously connected with the contemporary physico-chemistry research on interfaces and interphases. Polymers, either elastomers or thermoplastics, offer a great variety of chemical natures, as well as the fillers, but curiously common effects and properties are (at least qualitatively) observed whatever is the chemistry of the polymer matrix and of the filler particles. This striking observation is the very origin of this book that intends to offer a survey of a quite complex field, with the objectives to highlight what most filler–polymer systems have in common, how proposed theories and models suit observations and, eventually what are the specificities of certain filled polymers.

1.2  Filled Polymers vs. Polymer Nanocomposites A filled polymer system is thus a polymer in which a sufficient quantity (volume) of a small size foreign rigid (or at least less flexible) material, e.g., powdered minerals, short glass fibers, etc., has been well dispersed in order to improve certain key properties of engineering importance, for instance modulus, stiffness, or viscosity. The reinforcing effect of carbon black in rubber is known for one century (1907, Silvertown, UK) and the mastering and understanding of its scientific aspect has led to the development of many high engineering performance products, for instance the automobile, truck, or aircraft tires. Starting in 1984, a series of patents obtained by Toyota1 described the use of organoclay additives for plastics as well as various plastic structures that could replace traditional components (e.g., ­aluminium parts) in automotive applications. Typically U.S. patent No. 4,810,734 described a production process for a composite material by firstly treating a layered smectite mineral having a cation exchange capacity (e.g., a phyllosilicate) with a swelling agent having both an onium ion and a functional group capable of reacting with a polymer and secondly forming a complex with a molten polymer. U.S. patent No. 4,889,885 described a composite material made with at least one resin selected from the group consisting of a vinyl-based polymer, a thermosetting resin and a rubber, and a layered bentonite uniformly dispersed in the resin. The layered silicate has a layer thickness of about 0.7–1.2 nm and an interlayer distance of at least about 3 nm, and at least one polymer ­macromolecule has to be connected to the layered silicate. Such patents prompted, over the last 20 years, a kind of cult research area for so-called polymer nanocomposites, whose origin of reinforcement is on the order of nanometers, but with the capability to deeply affect the final macroscopic properties of the resulting material. In certain cases, such materials exhibit properties not present in the pure polymer resin, whilst keeping the processibility, the other mechanical

4

Filled Polymers

polymer properties and the specific weight. Several types of polymeric nanocomposites can in principle be obtained with different particle nanosize, nature and shape: clay/polymer, carbon nanotubes, and metal/polymer nanocomposites. Let us consider the case of clay/polymer nanocomposites. The key aspect is obviously the successful formation of suitable clay/polymer nanostructures, essentially through an intercalation process. In the case of hydrophilic ­polymers (typically polyamides) and silicate layers, pretreatment is not necessary; but most polymers are hydrophobic and are not compatible with ­hydrophilic clays. Complicated and expensive pretreatments are thus required. For instance organophilic clays can be obtained from normally hydrophilic clay by using amino acids, organic ammonium salts, or tetra organic phosphonium solutions, to name a few reported techniques. Established methods are: solution induced intercalation, in situ polymerization, and melt processing. Solution induced intercalation consists of solubilizing the polymer in an organic solvent, then dispersing the clay in the solution and subsequently either evaporating the solvent or precipitating the polymer. Such a technique is obviously expensive, raises a number of environmental, health, and safety problems (common to all organic solution techniques), and in fact leads to poor clay dispersion. In situ polimerization consists of dispersing clay layers into a matrix before polimerization, i.e., mixing the silicate layers with the monomer, in conjunction with the polymerization initiator and/or the catalyst. This technique is obviously limited to polymers whose ­monomers are liquids, and therefore excludes most of the general purpose (GP) resins, namely polyolefins. In the melt processing technique the silicates layers, previously surface treated with an organo-modifier, are directly dispersed into the molten polymer, using the appropriate equipment and procedure. A priori, this technique would be the preferred route with most GP polymers, providing mixing/dispersion problems are mastered. In theory, extraordinary improvements of material properties are expected with polymer nanocomposites but, in reality, the overall balance of usage properties (i.e., mechanical, hardness, wear resistance, to name a few) in the best clay/polymer nanocomposites are much lower than in conventional fiber reinforced composites, or even in certain traditional filled compositions. It is indeed only in the low filler range, typically 4–5 wt%, and providing the dispersion of nanoparticles is nearly ideal, that nanocomposites show better mechanical performances, but at the cost of major difficulties in mass fabrication. At higher loading, the surface area of the silicate-filler increases, which leads to insufficient polymer molecules adsorbed on the clay surface. One may consider that polymer nanocomposites combine two concepts: composites (i.e., heterogeneous systems) and nanometer-size ­materials; the hope that manufacturing composites polymer material could eventually be achieved with a tight control at molecular level (i.e., the nanometer range) surely justifies fundamental research in this area, even if large scale industrial applications are not yet in sight. Certain thermoplastics, filled with nanometer-size

Introduction

5

materials, have indeed different properties than systems filled with conventional mineral materials. Some of the properties of nanocomposites, such as increased tensile strength, are routinely achieved by using higher conventional filler loading, but of course at the expense of increased weight and sometimes with unwanted changes in surface aspects, i.e., gloss with certain polymers. Obviously other typical properties of certain polymer nanocomposites such as clarity or improved barrier properties cannot be duplicated by filled resins at any loading. One may indeed consider that polymer nanostructured materials represent a radical alternative to the conventional filled polymers and polymer blends, because the utility of inorganic nanoparticles as additives to enhance polymer performance has been well established at laboratory level. The incorporation of low volume (1–5 wt%) of highly anisotropic nanoparticles, such as layered silicates or carbon nanotubes, results in the enhancement of certain properties with respect to the neat polymer that are comparable with what is achieved by conventional loadings (15–40 wt%) of traditional fillers.2 In principle the lower loadings would facilitate processing and reduce component weight, and in addition, certain value added properties not normally possible with traditional fillers are also observed, such as higher stiffness, reduced permeability, optical clarity, and electrical conductivity. But the chemical and processing operations to disrupt the low-dimensional crystallites and to achieve uniform distribution of the nanoelement (layered silicate and single wall carbon nanotube, respectively) continue to be a challenge. Most commercial interest in nanocomposites has so far focused on thermoplastics, essentially because certain polymer nanocomposites allow the substitution of more expensive engineering resins with less expensive commodity polymer nanocomposites, to yield overall cost savings. But such favorable cases are rare and restricted to very specific applications. A recent study by a market research company claims that, by 2010, nanocomposites demand will grow to nearly 150,000 tons, and will rise to over 3 million tons with a value approaching $15 billion by 2020.3 So far however the market for these new materials has not developed as expected and if, indeed, exfoliated (or surface treated) nanoclays are commercially available,4 their uses seem restricted to very specific cases. Packaging and parts for motor vehicles are nevertheless expected to be key markets for nanoclay and nanotube composites. With respect to the improved barrier, strength and conductive properties that they can offer, polymer nanocomposites should somewhat penetrate certain food, beverage, and pharmaceutical packaging applications, as well as specific parts for electronics. In motor vehicles, automotive manufacturers are expected to consider polymer nanocomposites either as replacement for higher-priced materials, or to increase the production speed of parts and to reduce motor vehicle weight by lightening a number of exterior, interior, and underhood applications. The future will weigh such expectations. Over the last decades, a considerable number of research papers have been published whose main subject is so-called polymer nanocomposites,5 i.e.,

6

Filled Polymers

mixtures or preparations involving macromolecular materials and small particles with dimensions in the nanometer range, with however a great deal of confusion in the author’s opinion. Indeed, a careful reading of published papers reveals that for certain authors, nanoparticles are entities with (equivalent) diameters up to a few tens nanometers, whilst others title their works with the heading nanocomposites but consider mixtures with particles in the micron range. It is also worth underlining that nanoparticles technology implies that individual representatives particles (i.e., spheres, platelets, etc.) are ideally dispersed in the polymer matrix, without agglomeration or flocculation. This aspect of polymer nanocomposites appears thus in sharp contrast with conventional filled polymer technology where elementary particles must be suitably clustered in complex tri-dimensional structures called “aggregates” to yield reinforcing properties. As will be extensively described in this book, this is the key aspect of the reinforcement of rubber with carbon black and high structure silica. In many published papers this ideal dispersion of nanoparticles is neither documented nor granted by the preparation (mixing) process, and therefore the reference to polymer nanocomposites is dubious. Despite the lack—so far—of significant industrial applications, polymer nanocomposites seem to be a fashion subject for fundamental research, with sometimes an unfortunate lack of reference to earlier works on more classical filled polymer systems, namely filled rubber materials, surely the oldest class of complex polymer materials of industrial importance. There are a number of recent books, reviews, and treatises on so-called polymer nanocomposites6–8 and elastomer nanocomposites.9,10 The present book is definitely not addressing the same subject, but rather so-called “filled polymer systems” that are nowadays used yearly in quantities of hundred thousands to million tons worldwide. In order to avoid confusion it is thus necessary to clearly define what are filled polymer systems, the very subject of the present book, in contrast with polymer naonocomposites. It is clear that industrial use is not a sufficient criterion to distinguish both classes of materials. Whilst mainly concerned with rubber reinforcement, Hamed offered recently quite a clear and wellsupported proposal to distinguish filled polymer systems, with respect to the smallest size d of the dispersed phase.11 The characteristic smallest dimension d depends of course of the actual geometry of the particles, the diameter for spheres and rods, the thickness for plates and scales. There are a number of available materials whose characteristic particle dimension is in the 1–100 nm range and therefore the prefix nano is ambiguously used in the literature. We will consequently somewhat follow the Hamed’s proposal: when the characteristic dimension d of the dispersed phase is between 1 and 10 nm, then one is dealing with nanocomposites, when 100 nm > d > 10 nm, then mesocomposites are involved, with d above 100, composite materials are referred with the prefix micro, and the prefix macro when very gross  (d > 104  nm) rigid “entities” are dispersed in a polymer. Further to this basic characterization, Hamed considers that the dispersed entities can be structured, either a priori

7

Introduction

by their nature or through their manufacturing process, or as a result of the kinetics and thermodynamics of phase separation that may occur during the preparation of the complex polymer system. The proposal is further elaborated in Table 1.2., with typical examples of concerned materials. With respect to Table 1.2, all filled polymer systems discussed in this book are either meso or microcomposites, and most of them have a considerable industrial importance. The proposal by Hamed is based on well sounded arguments on the mechanical properties of filled rubbers and is further reinforced by very recent observations on the likely origin of the unusual properties of (true) nanocomposites. Indeed as demonstrated by a number of authors, so-called anomalous rheological and mechanical properties of polymer nanocomposite systems are observed when the characteristic dimensions of (ideally) dispersed particles are in the 1–10 nm range, in fact commensurable with some typical dimensions of polymer dynamics, namely the reptational tube diameter (a few nanometers), as considered when modeling the behavior of entangled polymers. In fact polymer nanocomposites are distinguished by the convergence of length scales corresponding to the radius of gyration of the polymer chains, a dimension of the nanoparticle and the mean distance between the nanoparticles.12 It was therefore hypothesized that, when nanoparticles have such small dimensions, they have the capability to participate in the local polymer dynamics.13 Filled polymer systems of industrial importance, e.g., filled rubber compounds, filled thermoplastics are thus meso or microcomposites, ­possibly with a structuration (of the dispersed phase) at the nano or meso scale. Whilst no sizeable commercial application yet exist for nanocomposites rubbers or thermoplastics (to the author’s knowledge), considerable research has been made since 1984 with so-called ex-foliated layered silicate “nano-clays.” Exfoliation means that individual clay sheets, of around 1 nm thickness, have been separated and adequately dispersed in the matrix. Some reinforcement has indeed been demonstrated with such exfoliated nanoparticles but, generally with very specific rubber systems and/or at a cost of preparation that is hardly compatible with reasonable chances of commercialization.

Table 1.2 Classification of Filled/Composite Polymer Systems Designation

Characteristic Dimension (nm)

Nanofiller/particle composite

1–10

Mesofiller/particle composite

10–100

Microfiller/particle composite

100–10,000

Macrofiller/particle composite

 > 104

Example Polyamide/exfoliated montmorillonite Rubber compounds with highly reinforcing carbon blacks Polypropylene/grinded calcium carbonate Polymer concrete

8

Filled Polymers

It can further be commented that the level of reinforcement obtained in such systems is not even comparable with what is practically achieved with conventionally filled mesocomposite polymers, namely rubbers. No amorphous vulcanized rubber reinforced only with exfoliated clay has been reported to have a tensile strength in the 30 MPa range, as currently obtained with conventional carbon black filled compounds. One can nevertheless expect that, owing to their special geometries (plates or scales), properly dispersed exfoliated clays might enhance certain properties, such as gas impermeability, through barrier effects, or thermal or electrical conductivity, through appropriate orientation effects, and therefore find niche markets.

References







1. U.S. Patents: 4,472,538 (Composite material composed of clay mineral and organic high polymer and method for producing the same, September 18, 1984); 4,739,007 (Composite material and process for manufacturing same, April 19, 1988); 4,810,734 (Process for producing composite material, March 7, 1989); 4,889,885 (Composite material containing a layered silicate, December 26, 1989); 5,091,462 (Thermoplastic resin composition, February 25, 1992). 2. Q. Yuan, R.D.K Misra. Polymer nanocomposites: current understanding and issues. Mater. Sci. Technol., 22 (7), 742–755, 2006. 3. Nanocomposites. The Freedonia Group, Inc., Cleveland, OH, 2006. 4. For example, Nanomer® nanoclays from AMCOL Intern. Corp., Arlington Heights, IL; Cloisite® and Nanofil® from Southern Clay Products, Inc., Gonzales, TX; Bentone® from Elementis plc, Hightstown, NJ. 5. See for instance the following recent reviews: S.S. Ray, M. Okamoto. Polymer/ layered silicate nanocomposites: a review from preparation to processing. Prog. Polym. Sci., 28 (11), 1539–1641, 2003; H. Fischer. Polymer nanocomposites: from fundamental research to specific applications. Mater. Sci. Eng. C, 23 (6–8), 763– 772, 2003; Wang, Z.-X. Guo, S. Fu, W. Wu, D. Zhu. Polymers containing fullerene or carbon nanotube structures. Prog. Polym. Sci., 29 (11), 1079–1141, 2004; J. Jordan, K.I. Jacob, R. Tannenbaum, M.A. Sharaf, I. Jasiuk. Experimental trends in polymer nanocomposites—a review. Mater. Sci. Eng. A, 393 (1–2), 1–11, 2005. 6. P.M. Ajayan, L.S. Schadler, P.V. Braun. Nanocomposite Science and Technology. Wiley, New York, NY, 2003. ISBN: 9783527303595. 7. Y.-W. Mai, Z.-Z. Yu Ed. Polymer Nanocomposites. CRC Press, Baton Roca, FL, USA; 2006. ISBN 9780849392979; a review by an international team of authors with 13 papers on layered silicates/polymer compositions and eight papers on nanotubes, nanoparticles and inorganic-organic hybrid systems. 8. J.H. Koo. Polymer Nanocomposites. McGraw-Hill Prof., New York, NY, 2006. ISBN 13: 978-0071458214.

Introduction





9

9. S.D. Sadhu, M. Maiti, A.K. Bhowmick. Elastomer-clay nanocomposites. Chapter  2, 23–56. In Current Topics in Elastomer Research, A.K. Bhowmick Ed. CRC Press, Taylor & Francis Group, Boca Raton, FL, 23–562008. ISBN-13: 978-08493-7317-6. 10. M. Maiti, M. Bhattacharya, A.K. Bhowmick. Elastomer nonocomposites. Rubb. Chem. Technol., 81, 384–469, 2008. 11. G.R. Hamed. Rubber reinforcement and its classification. Rubb. Chem. Technol., 80, 533–544, 2007. 12. R. Krishnamoorti , R.A.Vaia. Polymer nanocomposites. J. Polym. Sci. Part B. Polym. Phys., 45 (24), 3252–3256, 2007. 13. M.E. Mackay. Anomalous rheology of polymer-nanoparticle suspensions. XVth International Congress on Rheology, Monterey, CA, August 3–8, 2008. Paper KL.11.

2 Types of Fillers In polymer technology, there are essentially two major classes of fillers, either extracted or fabricated. Minerals such as talc and clays (Al2O3, 2SiO2, 2H2O) are extracted, grinded, and possibly treated and therefore belong to the first class. Calcite (CaCO3) belongs to both classes, as it can be either extracted and grinded or obtained through a chemical process that involves precipitation. Carbon blacks result from the incomplete combustion of hydrocarbon feedstock, and are consequently fabricated fillers, as well as synthetic silica that are obtained through more or less complex chemical operations. Short fibers made either of glass, or of carbon, are fabricated products, and we arbitrarily include cellulose fibers also in the second class, because quite complex treatments are required before they can be used as a polymer reinforcing material. Moreover, many types of natural fibre have been considered for use in polymers as reinforcing materials including flax, hemp, jute, straw, wood flour, rice husks, sisal, raffia, green coconut, banana, and pineapple leaf fibre to name a few, but technical problems such as moisture absorption and low impact strength have sometimes restricted their development. Wood flour nowadays used to prepare so-called wood– polymer composites (WPC), which represents a growing market over the last decades,* can also be considered as a fabricated filler with respect to its preparation mode. Fillers for polymers exhibit in fact a stunning variety of chemical natures, particle sizes and shapes. Essentially three basic shapes can be distinguished: either spheres, or plaques (disks, lamellas) or rods (needles, fibers), as illustrated in Figure 2.1. Such basic shapes can be further combined to result in quite complex geometrical objects to which specific (reinforcing) properties can be associated. Carbon black aggregates offer typical examples of complex tri-dimensional structures whose shape specifically affects the reinforcing properties, as will be discussed hereafter. Most fillers, either extracted or fabricated, have a mineral origin, with the notable exception of carbon blacks that result from the thermal degradation of hydrocarbons. There are also a * In North America the WPC market amounts today to around 300,000 tons/year, essentially for building and garden applications, particularly decking and associated products. Estimated over $600 Mio in 2002, the USA and Canada segment is nowadays worth over $2 billion and worldwide estimates are in the $3 billion range. Market growth is slower in West Europe with a consumption of around 140,000 tons in 2002, over 200,000 tons in 2005 and estimated to reach some 270,000 tons in 2010 (source: A. Eder. WPCs – an updated worldwide market overview including a short glance at final consumers. 3rd Wood Fibre Polymer Composites Symposium, Bordeaux, France, March 21–27, 2007).

11

12

Filled Polymers

Spheres

Scales, flakes lamellas

Cylinders, rods, needles, fibers

Partial fusion elementary particles => aggregates Complex tri-dimensional object => structural effect of the filler

Figure 2.1 Fillers basic shapes and structure.

number of filler materials that have a vegetal origin, for instance wood flour, sisal, coco, or jute fibers. It is tempting to consider a classification scheme for polymer fillers but no overall system is available and the analysis of existing proposals reveal that their validity and interest strongly reflect the application considered. We will nevertheless consider a few logical possibilities, which underline certain specific aspects of the common property considered. Considerations based on the refractive index allow to draw a clear distinction between a filler and a pigment, whilst if certain fillers can be used to modify the color of a polymer (e.g., carbon black in polyolefin), not all pigmenting materials have reinforcing capabilities. Let us consider various materials and their respective refractive indices (Table 2.1). The refractive index of vacuum is (by definition) equal to 1, and most polymers exhibit indices around 1.5. One would consider that any given material has no capability to modify the color of another one if the respective refractive indices of both materials do not differ by more than 0.2. It follows that materials with refractive indices either above 1.3 or below 1.7 have practically neither clearing nor darkening effects on polymers. Consequently, a mineral whose refractive index is above 1.7 can potentially be used as a pigment (but can also have reinforcing capabilities), whilst materials whose refractive index is below 1.7 would be essentially considered as fillers.* A logical and broader approach would associate the origin, the production process and the reinforcing capabilities (Figure 2.2). In this manner, essentially four types of filler are considered: organic fillers of natural origin (liege, wood flour, vegetal fibers), organic fillers obtained by chemical * One notes however that such a classification makes no sense for “dark” fillers, such as carbon blacks, which do not refract light.

13

Types of Fillers

Table 2.1 Distinguishing Between Filler and Pigment with Respect to Refractive Index Material

Refractive Index

Vacuum Water Chalk Polymers Silica BaSO4 ZnO ZrO2 ZnS Diamond TiO2, Anatase TiO2, Rutile

1.00 1.33 1.35 1.50 1.55 1.64 2.08 2.17 2.37 2.42 2.55 2.75

Filler Organic

Inorganic

Natural

Synthetic

Natural

Synthetic

- Inactive - Semiactive - Active

- Inactive - Semiactive - Active

- Inactive - Semiactive - Active

- Inactive - Semiactive - Active

Liege Wood flour Fibres (jute, sisal,...)

Synthetic resins Minerals Cellulose derivatives (CaCO3, talc, clays,...)

Carbon blacks Silicas (fumed, precipitated) Metal oxides (TiO2, ZnO,...) Metal salts (BaSO4,...)

Figure 2.2 Classifying fillers with respect to fabrication process and reinforcing activity.

synthesis (synthetic resins, cellulose derivatives), mineral fillers of natural origin (essentially all extracted fillers) and mineral fillers obtained through chemical processes in the broad sense (carbon blacks, fumed and precipitated silica). Furthermore, for each type, one might distinguish materials as active, semiactive, or inert filler, depending how they boost, improve or do not affect certain mechanical properties of interest, for instance stiffness, tensile or flexural strength, and abrasion resistance, to name a few. Another approach, maybe less subjective, consists of paying attention to particle size because, as illustrated in Figure 2.3, there is a clear relationship between this characteristic and the reinforcing capabilities. Essentially

14

Filled Polymers

105

104

103

Degradative fillers Dilution fillers Semireinforcing fillers

102 Reinforcing fillers 101 Particle size (nm)

Grinded CaCO3 mica, talc

Clays Precipitated CaCO3 TiO2, ZnO Si aluminates Ca silicates Hydrated silica Anhydrous silica Carbon blacks

Figure 2.3 Classifying fillers with respect to particle sizes.

no reinforcement is obtained when particles are larger than 103 nanometer (nm) and too large particles deteriorate mechanical properties of polymer materials. The wide range of particle sizes (and structures) offered by the manufacturing of carbon blacks and synthetic silica clearly reflect in the  semireinforcing and reinforcing character of these fillers. The general relationship between reinforcing capabilities and particle size suggests obviously that a poorly dispersed mineral, whatever its ultimate particle size, is likely to deteriorate ultimate mechanical properties, for instance by reducing the elongation at break of vulcanized rubbers and thermoplastics. Indeed, large and badly dispersed particles are fracture initiation sites.

3 Concept of Reinforcement Whilst they can be added to polymers for other purposes, it is mainly for their reinforcing capabilities that certain fillers offer the largest interest. When compared to polymers, any mineral exhibits mechanical properties, such as modulus, stiffness, hardness, that are several order of magnitudes larger. Therefore, one may reasonably expect that mixing the latter with the former will result in a heterogeneous mixture that exhibits macroscopic mechanical properties, at least intermediate between those of the polymer and those of the filler. Reinforcement of elastomers by carbon black, discovered in 1907 in Silvertown, UK, is likely the most significant example of this effect, that really permitted the development of the emerging tire technology, strongly connected of course with the automotive industry. Essential in rubber technology, the concept of reinforcement is however very complex, even if relatively easy to capture at first sight. Indeed, when a filler is added to a polymer, practically all properties are affected, some in a positive manner, others negatively with respect to a given application. There has been much debate about which particular property should be considered as the most expressive in terms of reinforcement. In this respect, it is worth quoting here the opinion expressed by G. Kraus:1 A precise definition of the term «reinforcement» is difficult because it depends somewhat on the experimental conditions and the intended effects of the filler addition…it appears preferable to regard reinforcement broadly as the modification of the viscoelastic and failure properties of a rubber by a filler to produce one or more favorable results…

The reinforcing capabilities of a filler must consequently be appreciated with respect to a balance of properties, whose choice depends on the application considered. Let us consider the general trends exhibited by a rubber compound in which increasing quantities of active (e.g., carbon black) or inert (e.g., finely divided clay) have been added. As shown in Figure 3.1, certain properties will only either increase or decrease, for instance viscosity, hardness, but other ones will pass through extremes in the case of the reinforcing filler. This immediately suggests that there will be optimum loadings, for a given filler, in a given polymer, for a specific application. To establish the optimum filler level is therefore the most important task for the compounder, further complicated by the obvious requirement that the compound must remain processible at reasonable 15

Inert

Filler level (phr)

Inert

Active

Tensile strength

Filler level (phr)

Active

500

1000

50

60

70

80

90

Inert

Inert

Filler level (phr)

Active

Elongation at break

Filler level (phr)

Active

Hardness

Figure 3.1 Relative variation of rubber compound properties as imparted by active (reinforcing) or inert filler.

5

10

15

20

20

40

60

80

100

ML(1+4) at 100°C

MPa

Shore A %

400

500

10

20

30

40

50

% 100

200

300

mm3

(Mooney) viscosity

Active

Filler level (phr)

Inert

Abrasion

Filler level (phr)

Inert

Active

Compression set

16 Filled Polymers

17

Concept of Reinforcement

energy and labor costs; sometimes the excessive viscosity increase imparted by very active fillers, either limits their practical level in certain elastomers or requires additional modification in formulation, for instance higher  levels of processing oils, or plasticizers, which generally have a penalizing effects on certain mechanical properties of the vulcanized part. In general, the reinforcing activity of a filler depends on at least four criteria: • • • •

The particle size (always smaller than 100 nm) The structure (i.e., the spatial organization) The specific area The surface (chemical) activity.

The structure of the filler material refers to the fact that, during their manufacturing process, reinforcing fillers develop very complex tri-dimensional shapes, which are called aggregates in the case of carbon black. Aggregate structure appears thus as one of the most important aspect of reinforcement and is obviously related with the specific area. The quantification of structure and the measure of specific area are somewhat related, essentially because the adsorption of molecules of known size is used to assess both characteristics. The well-known BET (Brunauer, Emmet, Teller) method is used to measure the adsorption isotherm of nitrogen (N2) absorbed by powdery fillers, whilst the aggregate complexity is assessed by evaluating the maximum quantity  of larger molecules (for instance di-butylphthalate DBP, or cetyltriethylammonium bromide CTAB) than can be adsorbed on the external surface. As might be expected, there is a (loose) correlation between the socalled BET surface and the activity (or reinforcing capability) of a filler:

BET  60 m2/g: active filler BET > 100 m2/g: very active filler

In fact, relationships between the reinforcing abilities and the characteristics of the filler are very complicated and, in general, one has to consider more than one criterion to make valid comparisons, useful for a given filler in a given polymer, for a given application. It is worth underlining that the concept of reinforcement has been more debated in the field of rubber science and technology than in the field of thermoplastics. The fact that, without suitable reinforcement, most elastomers exhibit so low mechanical properties that no interesting applications are possible is surely a reason. Another one is that most general purpose thermoplastics have known their tremendous development in the second

18

Filled Polymers

half of the twentieth century, in parallel with the expansion of petrochemistry, and have found immediately interesting applications “as such,” nearly without additives except a few protective chemicals. Polyethylene and polypropylene for instance are used to fabricate sheets and films by essentially exploiting their capabilities as semicrystalline polymers. No filler is needed to obtain the high mechanical properties that develop when crystalline structures are properly established and oriented. Polystyrene, ABS and other styrenics exhibit properties directly used in a number of applications, without the need of reinforcing fillers. Of course, in their usages, most thermoplastics must also meet a balance of properties but, except maybe polyvinyl chloride (PVC), the right material for a given application is obtained by controlling the macromolecular size and structure, essentially through a suitable adaptation of the polymerization process. The key role played by polymerization catalysts in the developments of polyolefins clearly supports this point. PVC is an exception because when suitably compounded with stabilisers, plasticizers, and other ingredients, a whole range of products can be obtained, essentially by changing the glass transition temperature of the material. It is quite symptomatic that the socalled “plastograph,” a small laboratory mixer, was specifically developed in the 1950s as a convenient tool to document the “plasticization” of PVC. The addition of fillers to thermoplastics polymers is thus quite a recent practice, around three decades old, whilst filled rubber compounds are used for more than a century. There is nevertheless another important, more technical reason for the different meaning of reinforcement in the rubber and plastics fields. In most of their applications, thermoplastics are used within the limits of their elastic behavior, generally below 10% strain. Indeed, once the yield strength limit is exceeded, permanent deformation occurs. It follows that most applications of thermoplastics are first concerned by the elastic behavior of the material; the viscoelastic character plays a secondary role, namely in what the long term variation of modulus is concerned through the creep phenomenon for instance. The situation is totally different with rubber materials, whose performance are controlled by their viscoelastic character, in a strain range that is substantially larger than for thermoplastics. For instance, with rubber materials, the tensile (Young) modulus is far less significant than the 100 or 200% modulus in most applications. It follows that the role played by fillers in “reinforcing” rubbers and thermoplastics is substantially different, as well as the balance of properties, as will be largely underlined throughout the book. A direct consequence is that the modeling of the filler’s effects in thermoplastics and in elastomers, whilst sometimes based on a similar theoretical background, is generally substantially differing in the supporting reasoning and therefore in the applicability. It is one of the objectives of this book to identify both the similitudes and the differences in those theoretical approaches, with respect to the class of polymer matrix considered.

Concept of Reinforcement

19

Reference

1. G. Kraus. Reinforcement of elastomers by carbon black. Adv. Polym. Sci., 8, 155–231, 1971.

4 Typical Fillers for Polymers

4.1  Carbon Black 4.1.1 Usages of Carbon Blacks Essentially, carbon black is the soot that results from the incomplete combustion of hydrocarbon materials, i.e., gas and oils. This definition does not pay tribute however to the high degree of development and control in use today in most industrial processes. The uses and the basic production principles of carbon black are lost in antiquity, but the development of controlled fabrication processes dates back to the previous century, resulting nowadays in highly sophisticated technologies with the capability to produce very fine and structurally complex materials, in accordance with the most recent standards of quality. As we will briefly see below, the term “carbon blacks” covers a very broad range of filler materials, with numerous applications, as outlined in Table 4.1. Except elastomer reinforcement, printing inks and several uses in the electrical industry, most application concern relatively low fraction of carbon black, typically below 5% volume. 4.1.2  Carbon Black Fabrication Processes Fabrication processes of carbon blacks all share the same principle: controlled heat decomposition of hydrocarbon products. Such processes are essentially chemical, either thermo-oxidative or mere thermal decomposition, as described in Table 4.2. Amongst the thermo-oxidative processes, the furnace black one is the most recent and nowadays the most important. As illustrated in Figure 4.1, the liquid combustible (either oil or gas) is sprayed in a flame of natural gas and hot air. Black smoke is produced that is a mixture of gas and carbon particles, initially nearly spherical elementary particles that partially fuse together to produce complex tri-dimensional objects called aggregates. Carbon black aggregates are quenched through water spraying that stops the pyrolysis and aggregation processes and cools down smoke, which is then filtered to recover solid particles. Unburned gas is treated and recycled in the process. 21

22

Filled Polymers

Table 4.1 Important Uses of Carbon Blacks Domain

Application

Elastomers Printing inks Enduction Thermoplastics

Fibers Paper Building Electrical industry

Reinforcing filler in tires and mechanical rubber goods Tinting, rheology modifier Black and gray tinting, color enhancement Black and gray tinting, color enhancement, anti-UV protection of polyolefins, high voltage cable shielding, application in semiconductors, static electricity dissipation Tinting Black and gray tinting, photograph protective paper Cement and concrete tinting Electrodes, dry batteries and cells

Table 4.2 Fabrication Methods of Carbon Blacks Chemical Process Thermo-oxidative decomposition

Method

Raw Material (Feedstock)

Furnace black Gas black (Degussa process) Lamp black

Thermal decomposition

Thermal black Acetylene black

Aromatic oils from coal tar or petrol distillates, natural gas Coal tar distillates, natural gas Aromatic oils from coal tar or petrol distillates Natural gas (or oils) Acetylene

Thermo-oxidative process : furnace black Air

Liquid feedstock atomized and sprayed into the flame

Smoke treatment for carbon black recovery

Oil

Gas

Flame from combustion of gas combined with preheated air

Smoke gas Water quench (stops pyrolysis)

Figure 4.1 Carbon black manufacturing process for furnace black.

23

Typical Fillers for Polymers

Thermo-oxidative process : lamp black Refractory bricks

Smoke treatment for carbon black recovery

Cooling water Flame under regulated air admission (=>partial combustion of feedstock) Air

Air

Oil (feedstock)

Figure 4.2 Carbon black manufacturing process for lamp black.

After filtration, carbon black aggregates are first packed into agglomerates then into pellets (of millimeter dimensions) in order to produce roughly spherical grains that are easy to handle. The process has several advantages: first it is a totally sealed, so that full respect of environment is obtained second a precise control of elementary particle size (from 10 to 100 nm) and of aggregate structures is achievable.1 The lamp black process is likely the oldest industrial process and has consequently been the object of numerous engineering variants. Figure 4.2 describes the principle of a typical modern plant. The partial combustion of a feedstock (oil generally) in an atmosphere purposely poor in oxygen produces smoke, which is cooled down and filtered to recover carbon black particles that are subsequently flocculated. The control of the pyrolytic process is loose and results in a large distribution of elementary particle sizes (from 60 to 200 nm). This fabrication process tends to be abandoned today in favor of the much cleaner and more versatile furnace one. Degussa (now EVONIK), in Germany, developed the so-called gas black process in the 1930s. Initially coal tar was used, quite a common feedstock at that time, when carbochemistry was very important in a country that had limited access to petrol. Today, any kind of hydrocarbon feedstock may be used in the process. As shown in Figure 4.3, a carrying gas is flown over preheated oil, then the oil–rich gas feeds a burner. Smoke is in part captured on the wall of water-cooled rotating cylinders and removed with scrapers, and in part recovered through filtration. Very fine elementary

24

Filled Polymers

Thermo-oxidative process : gas black Off gas

Cooling water

Carrier gas Oil (feedstock) Heating gas

Rotating drum

Knife Air

Burner Carbon black

Figure 4.3 Carbon black manufacturing process for gas black.

particles are obtained, in the 10–30 nm range, which aggregate in a controllable manner. The thermal black process is discontinuous and consists essentially of “cooking” a mixture of natural (i.e., hydrocarbons) and inert (N2) gas in two reactors in tandem, where cycles of heating then decomposition are achieved (Figure 4.4). One of the reactors is heated for five to eight minutes by burning natural gas in presence of air, whilst the other, previously heated, is loaded with pure natural gas that thermally decomposes. When pyrolysis is complete, flushing the reactor and conveying the smoke to filtration equipment allows the recovery of carbon black particles. Depending on the ratio natural/inert gas, various ranges of large and gross particles are obtained, either from 120 to 200 nm or from 300 to 500 nm. Acetylene black is produced by pyrolysing acetylene at high temperature; essentially hydrogen and carbon are obtained. Very pure carbon black particles are obtained in the 30–40 nm range. All the processes described above yield a very wide range of carbon blacks, differing in a number of properties, as described in Table 4.3. 4.1.3  Structural Aspects and Characterization of Carbon Blacks In terms of consumption, the most significant usage of carbon blacks is rubber reinforcement. This effect was discovered in the early years of the twentieth century and played an essential role in the development of tire technology and consequently in the automotive industry. As we shall see later, there are still some unknown aspects of carbon black reinforcement

25

Typical Fillers for Polymers

Thermal process H2 Gas

Air

Chimney

Carbon black

Ovens

Natural gas Heating cycle

Decomposition cycle

Figure 4.4 Carbon black manufacturing process for thermal black.

Table 4.3 Carbon Black Production: Properties vs. Process Thermo-Oxidative Decomposition Property Specific area, N2 Adsorption, I2 Particle size DBP absorption Oil absorption Volatiles pH

Unit m2/g mg/g nm ml/100g g/100g %

Thermal Decomposition

Lamp Black

Gas Black

Furnace Black

Thermal Black

Acetylene Black

16–24 23–33 110–120 100–120 250–400 1–2.5 6–9

90–500 n.a. 10–30 n.a. 220–1100 4–24 4–6

15–450 14–50 10–80 40–200 200–500 0.6–6 6–10

6–15 6–15 120–500 37–43 65–90 0.5–10 7–9

Around 65 Ar. 100 32–42 150–200 400–500 0.5–2 5–8

but a basic consideration is surely the capability of carbon black to exhibit various levels of spatial organization, which are schematically outlined in Figure 4.5. Elementary particles of approximately spherical shape appear in the early stages of the pyrolysis process, when soot is being formed and assembled together through partial fusion to give complex tri-dimensional objects, called aggregates. During quenching, aggregates entangle into agglomerates, which are eventually pelletized into granules of millimeter dimensions. Aggregates are very difficult, if not impossible (in rubber mixing conditions) to break and consequently are likely to be the ultimate particle size when

26

Filled Polymers

Elementary particle (colloidal black)

10–90 nm

Partial fusion

Occuring in soot formation and quenching Entanglement

Aggregate

100–300 nm

Agglomerate

Carbon blacks Occuring during wet filtering and powder drying Compaction

Pellet

Specific area

104 –106 nm

2–4 mm

“Structure” Reinforcing character 10–8m

10–7m

Scaling

10–5m

10–3m

Figure 4.5 Spatial organization and reinforcing character of carbon blacks.

dispersion is optimal. They play an essential role in rubber reinforcement whilst residual agglomerates are considered as failure initiation sites in filled compounds. There is a consensus nowadays to consider aggregates as the ultimate carbon black form, the only relevant one when rubber (polymer) reinforcement is concerned. Carbon blacks exhibit various characteristics whose importance depends on the application considered. The specific area (m2/g) is obviously the most basic information for a given filler: the smaller the elementary particles, the higher the specific area of aggregates with equivalent spherical volume. The specific gravity of carbon black is in the 1.82–1.89 g/cm3 range. Note that the common value of 1.86 g/cm3 will be used in all the illustrative calculations made in this book. The elementary analysis of carbon blacks is roughly as follows (in wt%):

Carbon: 95.0–99.5 Hydrogen: 0.2–1.3 Oxygen: 0.2–0.5 Nitrogen: 0.0–0.7 Sulfur: 0.1–1.0 Ashes: below 1.0

27

Typical Fillers for Polymers

In addition, toluene extraction reveals traces of organic materials, essentially poly-aromatic hydrocarbons (below 0.5 wt%). A number of oxygenated chemical groups have been found on carbon black surface, such as carbonyls, carboxyls, pyrones, phenols, quinone, lactol, etc., but in minute quantities and all are removed by heating at 950°C in an oxygen free atmosphere. A number of standard characterization methods for carbon blacks (and other fillers) are listed in Table 4.4; most of them are described as International Organization for Standardization (ISO), American Society for Testing and Materials (ASTM), or Deutsches Institute für Normung (German Institute for Standards) (DIN) methods. One can distinguish three groups of methods with respect to the information sought for reinforcement purposes: specific area, structure and chemical analysis. In addition, there are methods for characterizing the final product, i.e., the carbon black in pellet form, the only one readily handled in polymer technology (essentially for health and safety reasons). The specific surface area is assessed either through iodine I2 adsorption (result is given in mg of I2 per g of carbon black), or through nitrogen N2 adsorption (result in m2/g of carbon black), or through cetyltrimethylammonium bromide CTAB adsorption (result in m2/g of carbon black) or through the tint strength (an indirect measure of the specific area). As expected, all Table 4.4 Standard Characterization Methods for Fillers Method

ISO

ASTM

DIN

Specific area Iodine I2 adsorption Nitrogen N2 adsorption CTAB adsorption Tint strength

1304 4652 6810 5435

D-1510 D-3037/4820 D-3765 D-3265

53582 66132

Structure DBP absorption Compressed DBP absorption Oil absorption*

4656 6894 787/5

D-2414 D-3493

53601 787/5

1125 787/2 787/18

D-1506 D-1509 D-1514

787/9

D-1512

1306

D-1513 D-3313 D-1511

Chemical analysis Volatiles Ashes Moisture* Sieving residue* Toluene extraction pH* Final product properties Bulk specific gravity Pellet hardness Pellet sizes distribution * DIN-ISO methods.

53552 53586 787/2 787/18 53553 787/9 53600

28

Filled Polymers

of these methods give similar but not equivalent information and there is no consensus regarding their respective advantages/disadvantages. Iodine adsorption for instance is sensitive to surface chemistry and the presence of polyaromatic hydrocarbons, but the method is considered correct for furnace and lamp blacks. The N2 adsorption is the BET method whose principle is based on the shape of adsorption isotherms.2 When a monolayer of material is adsorbed on a very uniform surface, a knee occurs in the isotherm before reaching another plateau that corresponds to the adsorption of a second layer. Ordinary surfaces are energetically quite heterogeneous as far as the adsorption energy in the first layer is concerned: however it is possible to work with carbon blacks because particles exhibit (at least locally) graphitelike facets that are quite homogeneous. Nevertheless the nitrogen molecule is small enough to reach pores and other small cavities within aggregates, and therefore results are sometimes obtained in excess with the area readily in contact with the polymer matrix. CTAB is a larger molecule than nitrogen and consequently only the “external” specific area is probed, leading to results better correlated with aggregates’ size. All methods for structure assessment are indirect and essentially consist of measuring the absorbed amount of a suitable chemical, for instance dibutylphthalate DBP. Results are expressed in ml or cm3 (of DBP) absorbed per 100 g of filler. The method consists of adding dropwise DBP to a known quantity of carbon black, which is malaxed in a calibrated laboratory mixer. Mixing torque is recorded and as long as the liquid just fills the “voids” between aggregates, the torque trace remains essentially flat. As soon as the whole external surface of aggregates is “wetted,” a coherent mass is obtained and a significant torque rise is observed. The more complex the structure, the higher the amount of absorbed DBP. As such, the method does not distinguish between aggregates and agglomerates, and this limitation is somehow overcome with the so-called compressed (or crushed) DPA absorption method. Before loading the mixer cavity the carbon black is compressed four times under a pressure of 24 MPa. Only the permanent structure, i.e., the aggregates, is expected to survive the crushing step. The size of the elementary particles and the structure of aggregates are the most important parameters in the ability of a given carbon black to reinforce a polymer. And both parameters essentially depend on the fabrication process. In time, a number of manufacturers went on the market with products, essentially described with respect to their manufacturing process and (expected) reinforcing character, essentially with respect to tire applications. For years, carbon blacks were described through acronyms, such as HAF, i.e., high abrasion furnace: a furnace black imparting a high resistance to abrasion to rubber (tread band) compounds, or ISAF-LS, i.e., intermediate superabrasion furnace-low structure: a furnace black of low structure offering an excellent resistance to abrasion, to name a few. Only carbon black experts familiar with rubber reinforcement aspects—and aware of the (sometimes) subtle differences between carbon blacks, described by similar

29

Typical Fillers for Polymers

acronyms but produced by different companies—were at ease with such a description. The essential role played by carbon blacks in rubber reinforcement prompted the American Society for Testing Materials (ASTM) to propose a standard classification and nomenclature, described in ASTM D1765 that became widely accepted, thanks to its simplicity. Figure 4.6 illustrates the principle of this nomenclature that invites all carbon black manufacturers to class their materials using a four character system: one letter (either N or S) and three numbers. The letter N means normal curing, meaning that the carbon black does not interfere (too much) with vulcanization chemistry; S means slow curing and concerns carbon blacks prepared with feedstock leaving chemical residues that affect the vulcanization process. S grade carbon blacks tend to disappear nowadays. The first number refers to the size of the elementary particles, at least in the 1986 version of the standard, because a recent proposal (in 1996) was made to assign the first digit a value (between 0 and 9) with respect to the specific area, as measured through N2 adsorption. The two last digits refer to the aggregate structure and are assigned to the carbon black by the manufacturer, with respect to various evaluation techniques, presently not standardized however. As a matter of fact, a very large diversity of carbon black grades has been and is still produced, essentially because there is an excessively large number of process variables, not all perfectly monitored despite encouraging progresses, as well as a great variety in the feedstock used. Despite modern Refers to aggregate structure N x

yz Refers to the size of elementary particles

Change in defining x

D1765–86

x

D1765–96

Typical average size of particles, nm

Average nitrogen N2 specific area, m2/g

1–10 11–19 20–25 26–30 31–39 40–48 49–60 61–100 101–200 201–500

> 150 121–150 100–120 70–99 50–69 40–49 33–39 21–32 11–20 0–10

0 1 2 3 4 5 6 7 8 9 Figure 4.6 ASTM classification of carbon blacks.

30

Filled Polymers

trends in standardization, this inevitably results in a large diversity of products. The present ASTM classification schema obviously offers a number of advantages but only the first digit (X in Figure 4.6) can be considered as solid information; in other words, for a given carbon black grade, its ASTM classification guarantees only the size range of the elementary particles. The structure that, in the opinion of the author, is likely the most significant aspect is “described” by the two last digits (yz). This description is however depending on the set of methods used by the manufacturer. To document this aspect, Table 4.5 was filled by compiling and averaging out typical test data for carbon black, as found in the trade or scientific literature, with respect to their ASTM designation. Sources of data, as well as a few interesting relationships between the quoted quantities are given in Appendix 4.1. Practical experience, essentially with respect to applications in tire technology, allows to somewhat distribute available carbon blacks in three main categories: • Highly reinforcing, so called “tread” blacks: series N100–N300 • Semireinforcing, so called “carcass” blacks: series N300–N600 • Weakly reinforcing: series N600, N700 The words “tread” and “carcass” refer to tire applications and with respect to wearing resistance, it is clear that tread band compounds need highly reinforcing blacks. As a rule of thumb, the higher the reinforcing capabilities of a carbon black, the more difficult its dispersion in the rubber, and consequently the more complex the mixing procedure. Conversely, low reinforcing blacks can be added to rubber formulations in very large quantities. An attractive manner to consider carbon black grades consists of plotting a parameter related to elementary particle size, for instance CTAB adsorption, vs. a parameter related to aggregate structure, for instance DBP absorption (Figure 4.7). Roughly speaking the reinforcing character increases as one moves along the increasing left to right diagonal. As can be seen in Figure 4.7, not all combinations of both parameters are available, and the largest variety of grades is found in the N300 series. 4.1.4  Carbon Black Aggregates as Mass Fractal Objects The central role plaid by aggregates in the reinforcing capabilities of carbon black is nowadays well established but recent progress in particles observation techniques, as well as fundamental studies on the physics of elementary particle aggregation through ballistic processes occurring during soot formation and quenching, shed new light on the particular nature of such complex objects. New concepts such as “fractal objects,” obviously inspired by the breakthrough work of B. Mandelbrot,3 were considered in describing carbon black aggregates.

1.02

1.20

1.30

1.25

N330

N343

N347

0.76

N326

N339

1.37

1.23

N242

N299

0.92

1.15

N220

1.24

0.73

N219

N231

0.85

N210

N234

1.09

1.27

1.33

N121

N125

1.13

N115

N134

1.14

N110

0.05

–

0.04

0.03

0.12

0.01

0.07

0.02

0.00

0.02

0.00

–

–

0.07

0.01

0.00

0.02

Std. dev.

ASTM D2414

Method:

Mean value

(dm³/kg)

Unit:

ASTM Nr

DBP Absorption

Data:

 

 

0.97

1.04

0.99

0.87

0.68

1.05

 

1.01

0.85

0.98

 

1.02

0.95

1.10

0.97

0.98

Mean value

ASTM D3493

(dm³/kg)

0.03

–

0.04

0.02

0.02

0.00

–

0.03

0.02

0.02

–

–

0.08

0.03

0.01

0.04

Std. dev.

Comp. DBP ab. 24M4

 

 

87.14

–

92.10

79.45

82.57

106.50

128.75

123.26

117.00

116.75

112.67

152.00

 

126.00

143.00

137.97

Mean value

3.50

–

4.32

4.28

8.22

1.80

9.91

1.97

0.00

4.19

6.35

–

5.29

–

4.82

Std. dev.

ASTM D3037

(m²/g)

N2 Adsorption

 

 

89.29

92.00

90.15

81.50

83.59

108.93

119.00

121.28

121.00

119.93

117.00

142.00

121.00

121.00

156.50

145.60

Mean value

2.75

–

1.22

1.36

2.69

1.62

–

1.86

–

2.24

–

–

–

0.00

4.95

2.00

Std. dev.

ASTM D1510

(mg/g)

I2 Adsorption

 

 

  125.45

85.40

91.31

80.54

82.82

105.90

–

118.63

108.50

111.56

134.00

126.00

118.50

128.00

(continued)

3.10

5.91

2.62

4.52

2.69

–

1.86

0.71

3.50

–

–

3.54

–

3.77

Std. dev.

ASTM D3765

(m²/g)

CTAB Adsorption

Mean value

Carbon Blacks—ASTM Designation vs. Characterization Data, as Compiled from Trade and Scientific Literature

Table 4.5

Typical Fillers for Polymers 31

0.35

0.38

N880

N990

0.04

0.08

0.02

0.00

0.04

0.04

0.02

0.17

0.12

0.04

0.14

0.11

0.08

0.01

0.03

–

0.02

 

0.37

 

0.63

0.59

 

0.81

0.58

0.86

0.73

0.83

0.84

0.83

1.18

0.90

1.13

1.14

0.96

Mean value

ASTM D3493

(dm³/kg)

0.02

0.02

0.01

0.05

0.03

0.02

0.03

0.02

0.04

0.01

0.06

0.10

0.01

–

0.02

Std. dev.

Comp. DBP ab. 24M4

 

9.09

12.25

29.64

 

25.00

33.88

28.47

38.12

34.85

35.75

41.12

42.70

248.67

93.48

84.30

88.05

71.43

Mean value

0.93

2.87

2.48

2.00

3.06

3.49

2.04

3.09

3.18

2.82

1.57

18.48

11.01

2.05

5.59

2.17

Std. dev.

ASTM D3037

(m²/g)

N2 Adsorption

Note: In the column for standard deviation – means that only one source of data was available.

0.65

0.74

N772

N774

1.17

0.73

N765

N770

1.29

0.66

N683

N762

1.24

0.94

N650

N660

1.03

1.17

N539

N550

1.15

1.86

1.55

N358

N375

1.57

N356

N472

1.21

N351

Std. dev.

ASTM D2414

Method:

Mean value

(dm³/kg)

Unit:

ASTM Nr

DBP Absorption

Data:

Table 4.5  (Continued)

 

9.40

 

29.05

30.00

28.00

32.70

28.20

34.54

35.73

35.00

42.58

42.75

250.00

88.72

84.00

82.90

68.22

Mean value

1.22

–

0.10

0.00

–

2.40

1.85

2.75

2.02

1.41

1.11

0.50

–

3.45

–

–

1.09

Std. dev.

ASTM D1510

(mg/g)

I2 Adsorption

 

9.70

 

30.37

33.00

 

36.17

29.75

40.24

37.52

36.00

41.32

41.33

147.50

91.72

88.00

87.50

73.23

Mean value

0.99

2.28

–

3.96

5.03

2.12

3.04

–

1.21

0.65

3.54

10.29

–

–

0.52

Std. dev.

ASTM D3765

(m²/g)

CTAB Adsorption

32 Filled Polymers

33

Typical Fillers for Polymers

140.0 N110

CTAB adsorption (m2/g)

120.0 100.0

60.0

r cte

ra N330

ha

N326 ng c ci for n i Re

80.0

N299 N339 N347

20.0

N990 0.20

0.40

N774 N762

N660

0.60 0.80 1.00 DBP absorption (dm3/kg)

N356

N351

N550

40.0

0.0 0.00

N234

N220

1.20

N683

1.40

1.60

Figure 4.7 Carbon blacks reinforcing capabilities with respect to parameters related to elementary particle size and aggregate structure.

Carbon black aggregates can indeed be viewed as mass fractal objects whose description results from the so-called “fractal scaling law”: two parts of a fractal object, a larger one of size DL and a smaller one of size DS, are ­statistically equivalent if the latter is enlarged by a factor DL/DS. Applied to the case of an (carbon black) aggregate of overall size D made of Np aggregated ­elementary particles of size d, such a law leads to the following equality (see Figure 4.8a): F



 D Np = α    d

(4.1)

where α is a prefactor, also called front factor and F is the so-called massfractal dimension of the aggregate, which depends on the conditions for the aggregation process. The mass fractal F describes how the mass of an object varies with its size. This concept was first applied by Kaye4 and Flook5 to the determination of the perimeter type fractal of carbon black aggregates, then was used by Bourrat et al.6 Ehrburger-Dolle and Tence7 for the structural characterization of a few carbon blacks, and by Herd et al.8 who reported an extensive study comparing the utility of fractal and Euclidean geometries in characterizing quite a large series of 19 carbon black grades, with DBP adsorption ranging from 35 to 174 cm3/100 g. By measuring the perimeter and the mass fractal values for various carbon blacks in the dry state, these authors found that

Size d

Size D

Np particles

(b)

Size d

Geometrical distance R

Fractal path L

(c)

Size d

Length L

Figure 4.8 Fractal geometry description of aggregates (a) basic dimensions of an aggregate, (b) concept of fractal path, (c) Chain-like aggregate.

(a)

34 Filled Polymers

35

Typical Fillers for Polymers

the mass fractal dimension F was in the 2.19–2.85 range, i.e., a mean value of 2.44±0.15. This indicates that carbon blacks have a moderately rough surface, since a smooth surface has a value of F = 2. Indeed, Göritz et al.9 used scanning tunneling microscopy (STM), atomic force microscopy (AFM) and small-angle x-ray scattering (SAXS) to study the surface structure of quite a broad range of carbon blacks, from N115 to N990. They well documented the surface topography of carbon blacks and demonstrated that graphitized (2700°C treatment) high structure blacks, e.g., N115 and N234, lost all surface roughness and exhibit typical flat huge local terraces. Moreover x-ray scattering experiments gave access to the surface fractal dimension which was found to vary systematically from 2.27 (N115) down to about 2.0 (N990). The smaller the primary particle diameter the higher the measured fractal dimension. Consequently surface roughness decreases with increasing primary particle diameter and is related to the reinforcing character of carbon black grades. One would therefore expect fractal dimensions of carbon blacks to be correlated with DBP absorption numbers in the dry state. Figure 4.9 is for instance drawn using mass fractal dimensions reported by Herd et al. and average DBP absorption data from Table 4.5. Mean DBPA data and their standard deviation were used in drawing the graph. If, indeed, there is a loose linear correlation between both characteristics of carbon black, one can hardly expect the measurement of mass fractal dimensions to become a valid replacement candidate for the well spread and much easier ASTM methods, particularly with respect to the complexity of the former. 2.0

DBPA, dm3/kg

1.5

1.0

0.5

0.0

2

2.2

2.4 2.6 Mass fractal dimension F

2.8

3

Figure 4.9 Mass fractal dimension vs. (mean) DPA absorption number of carbon black. (Mass fractal data from C.R. Herd, G.C. McDonald, R.E. Smith, W.M. Hess., Rubb. Chem. Technol., 66, 491–509, 1993. DBPA data from Table 4.5.)

36

Filled Polymers

Table 4.6 Surface Energy Components for Carbon Black Carbon Black Grade N110 N220 N234 N326 N330 N347 N550 N660 N762 N774 N880 N990

Specific Surface Area N2 (BET) [m²/g] 140.0 118.0 123.3* 83.2 76.5; 80.0 85.8 39.7; 43.2 39.4 32.5 ; 24,0 29.0 12.3 7.9; 10.3

Dispersive Component γ ds (at 150°C) [mJ/m²] 270.4 235.2 382.0* 186.5 196.9; 150.4 192.9 134.4; 173.4 124.7 126.4  ; 132.8 118.1 113.1 71.8; 78.7

Polar Component p sp I benzene ( γs ) (at 150°C) [mJ/m²] 120.0 103.9 93.0* 90.2 85.9; 80.2 87.9 75.0; 75.0 71.1 77.7 ; 74.0 63.8 63.9 56.6; 58.8

Source 29 29 55 29 29,30 29 29,31 29 29,31 30 31 29,31

sp measured at 180°C. * BET value from Table 4.5; γ ds and I benzene

Nevertheless, the fractal description of carbon black aggregates on one hand brings quite a convincing theoretical support for the former interpretation of DBP absorption results by Medalia and, on the other hand, provides the starting argument for several recent theoretical descriptions of certain nonlinear effects associated with the reinforcement of rubbers by carbon black. As largely illustrated by published transmission electron micrographs (see Herd et al.8,10 for instance), most carbon black aggregates exhibit a branching structure that can be considered in terms of fractal geometry. If L is the shortest connecting (fractal) path between any two arbitrarily chosen elementary particle of an aggregate (see Figure 4.8b), then this quantity is related to their geometrical distance R in the three dimensional (Euclidean) space through the following relationship: C



L  D = β   d d

(4.2)

where β is a prefactor of the order or unity and C, the so-called ­connectivity exponent, readily related to the branching structure of the aggregate. Indeed for a chain-like aggregate (i.e., without any branches; see Figure 4.8c), the fractal path is the length of the chain and consequently the connectivity exponent C equals the mass fractal dimension F and has the value of 2. It follows that, because they have many branches, most carbon black aggregates have connectivity exponent C significantly

37

Typical Fillers for Polymers

smaller than two. In fact, when performing their TEM/AIA (transmissionelectron-­m icroscopy/automated-image-analysis) study on a representative sampling of 19 different carbon black grades, Herd et al. 8,10 classified aggregates in four specific shapes: spheroidal, ellipsoidal, linear, and branched. Different aggregate shapes exist within a given grade of carbon black but it seems that the highest percentages of branched aggregates are found in the highly reinforcing carbon black grades. In weight percent, the branched aggregates quantity decreases as both the DBP absorption number and the surface area decrease. With respect to reinforcement, branched aggregates have the greatest influence on properties such as modulus, tear, and wear resistance, which are known to be connected with the effectiveness of the aggregate in “occluding” the polymer from deformation. The (mass) fractal description of carbon black suits obviously the effects of aggregate branching and, as we will see, is the background of advanced modeling approaches. The size D of an aggregate can be viewed as the diameter of its spherical envelope with respect the well-known void volume concept of aggregates introduced by Medalia.11,12 Whilst apparently not aware of the concept of “fractals,” it is quite clear that Medalia somewhat foresaw the fractal nature of carbon black aggregates when he wrote: “the effective volume of a carbon black aggregate composed of Np particles is proportional to Np raised to a power greater than unity, so that with increasing number of particles per aggregate, the aggregate becomes more open and more voluminous.” The effective volume of an aggregate cannot however be directly assessed with any precision and, therefore with respect to the at-the-time capabilities of electronic microphotography techniques, Medalia suggested to consider that the effective volume of an aggregate is that of a sphere of the same (mean) projected area as the aggregate (see Figure 4.10). If Des is the diam-

Equivalent sphere of diameter Des

Size D

seen by TEM

Size d

Np particles

Figure 4.10 Concept of equivalent sphere for a single aggregate.

Project area A of the aggregate

38

Filled Polymers

eter of the equivalent sphere and A is the measured projected area of the aggregate, it follows that:



Ves =

π Des3 π  4 A  =  6 6  π 

3/2

=

4 A 3/2 3 π

(4.3)

Obviously the volume of solid carbon within an aggregate is the product of the number of particles Np times the volume of an elementary particle (assumed to be spherical). It follows that the measured projected area (a two dimensional quantity) of an aggregate can be related to the project area of its calculated equivalent sphere (a three dimensional quantity) through a scaling law. Medalia et al. performed a so-called “floc simulation” to establish the following equality:13,14

 A Np =   Ap 

1/ε

or A = Ap N pε

(4.4)

where Np is the number of elementary particle of projected area Ap and ε a scaling exponent. From his floc simulation, Medalia reported a value of 0.87 for ε , which however seems to be an unfortunate printing mistake since, using his published data, it can be shown that the correct value is 0.847 (see Appendix 4.2). If d is the (average) diameter of the elementary particles of the aggregate, it follows from Equation 4.4:



A=

 4A π d2 ε N p or N p =  4  π d 2 

1/ε



(4.5)

Using ε = 0.847 , Equation 4.5 is rewritten as N p = ( 4 A/πd 2 )1.18 , with an exponent slightly different from the one reported by Medalia (i.e., 1.15), not only in his original publication but also in all his subsequent ones, and moreover blindly used by a number of other authors. It is worth noting that the exponent 1.18 is still far, but closer to the surface fractal exponent of ≈ 1.8 as derived later from colloid agglomeration modeling,15,16 and also confirmed by experimental results on carbon black filled EthylenePropylene-Diene Monomer rubber (EPDM) compounds.17 From Equations 4.3 through 4.5 it follows that the diameter of the equivalent sphere is given by:

Des = d N pε/2 or Des = d N p0.4235

(4.6)

39

Typical Fillers for Polymers

The exponent in Equation 4.6 is sufficiently different from the one reported by Medalia (i.e., 0.435) to bring large differences in calculated Des when either the diameter d of the elementary particle increases and/or when the number Np of elementary particles is large. However, the misprint in Medalia publications must not shade his merit in having foreseen the fractal nature of carbon black aggregates. In addition, Medalia has thoroughly elaborated practical formulas to convert an easily measured quantity (i.e., the DBP absorption number, in cm3/100 g filler) into the number of particles in an aggregate (see Appendix 4.3 for details and numerical illustrations). The solid volume Vs of an aggregate is nothing else that the volume of an elementary particle (of diameter d) times the number of particles, and by combining Equations 4.3 and 4.5, it follows: Vs = N p



π d3  4 A  = 6  π d 2 

1/ε

π d3 6

(4.7)

Using his floc simulation approach, Medalia has established the following practical relationship between the so-called “void ratio,” i.e., the ratio of the equivalent sphere Ves to the solid volume Vs, and the DBP absorption number, i.e.

CF

Ves (1 + vf ) g − 1 = DBPA ρ 0.0115 Vs C

(4.8)

where CF = 0.765: correction factor accounting for difference between the projected area of the equivalent sphere and the projected area of the aggregate (around 8.5% reduction in diameter) vf = 0.46: void fraction for randomly packed spheres C = 1.4: correction for partial fusion of primary particles in aggregate g = 0.94: anisometry correction factor for non-perfect alignment of aggregate’s main axis with projection plan ρ = filler specific gravity [carbon black: ρ = 1.86 g/cm3] DPBA = di-butylphtalate absorption (cm3/100 g filler) 0.0115: correction for DBPA end point (i.e., 1.15/100 , to take into account that at the end of the DBP absorption test, the sample contains around 15% air) By combining the equations for the volume of the equivalent sphere (Equation 4.3), for the projected area (Equation 4.5) and for the volume of solid carbon in the aggregate (Equation 4.7) with Equation 4.8, one gets immediately:

ε    ε + 2 − 1

N p

= ( 1 + DBPA ⋅ ρ ⋅ 0.0115 ) ⋅

C CF ⋅ g ⋅ ( 1 + vf )

40

Filled Polymers

or ε    ε + 2 − 1

N p



= ( 1 + DBPA ⋅ ρ ⋅ 0.0115 ) ⋅ 1.333

(4.9)

if one replaces the various correction factors by their values given above. The number of elementary particle in an aggregate can consequently be assessed from the DBPA number, the specific gravity ρ of carbon black (1.8 g/cm3) and the value assigned to ε , using: N p = [ 1.333 ⋅ ( 1 + DBPA ⋅ ρ ⋅ 0.0115 )] 2/( 3 ε − 2 )



(4.10)

Depending on the value used for ε , the result yielded by Equation 4.10 can be very different, as shown in Figure 4.11, in fact largely underestimated using ε = 0.87 , as published by Medalia. For instance, for a typical High Abrasion Furnance (HAF) grade, e.g., N330 (DBPA = 102 cm3/100 g), the correct value ε = 0.847 gives 211 particles/aggregate, whilst ε = 0.87 gives 114. The more reinforcing the carbon black, the larger the difference. It is interesting to compare the number of particles per aggregate as calculated with Equation 4.10 (Medalia’s; based on TEM analysis and “floc” 800 700

ε = 0.847

Number of particles

600 500 400 300 ε = 0.87 (Medalia)

200 100 0

0

0.5

1 DBPA, dm3/kg

1.5

2

Figure 4.11 Assessing the number of elementary particles in a carbon black aggregate; curves were calculated with Equation 4.10, ρ = 1.86 g/cm3, DBPA values in the range 38 (N990) to 157 (N356) cm3/100 g and the ε values given in the figure. (Data (◽) are from A.I. Medalia, F.A. Heckman, Carbon, 7, 567–582, 1969.)

41

Typical Fillers for Polymers

Number of particles/aggregate (Medalia)

800

600

400

200

0

0

200 400 600 Number of particles/aggregate (Fractal approach)

Figure 4.12 Comparing carbon black aggregates as described either through the TEM data analysis by Medalia and or the fractal approach.

simulation) with the estimation obtained using the mass fractal approach, i.e., Equation 4.1, and reported particles and aggregates dimensions (from Herd et al. for instance; see Appendix 4.4 for details). As shown in Figure 4.12, with respect to the equality line, an agreement is obtained only if the front factor α in Equation 4.1 is taken equal to around 11, i.e., more than 10 times the value guessed by some authors.18 Within the spherical aggregate envelope, one can distinguish the solid Vs and the void Vv volumes, whose relative importance is expressed in terms of volume fraction, i.e.: −1



V   Φ = 1+ v   Vs 

(4.11)

With respect to fractal geometry, this solid volume fraction is expressed in terms of basic dimensions of the aggregate as follows :

Φ=

N d3  d =α   D D3

3− F



(4.12)

where α is the so-called “front factor.” This fraction is the volume occupied by the (fractal) solid aggregate with respect to the overall volume occupied in the three dimensional space, and is obviously related to the aggregate surface accessible to polymer chains in a compound. When carbon black volume

42

Filled Polymers

fraction is large enough in a compound—in practice when the loading is above the so-called percolation level (i.e., Φ ≈ 0.12 − 0.13 ), all aggregates are expected to entangle (or at least to connect) and to form a secondary aggregated structure in the polymer matrix. As we have seen before, during the production process (precisely during the quenching), carbon black aggregates flocculate into agglomerates, that are further compacted by the final pelletizing step (see Figure 4.5). Carbon black pellets is the easier handling form of the filler, readily used in polymer compounding. Such pellets are very friable and no much (mixing) energy is needed to split them into agglomerates which correspond in fact to a close packing state of aggregates. Agglomerates have also a fractal nature with a mass fractal dimension of the order of three and a connectivity exponent of around one. Aggregates are recognized for decades as the filler structural state that plays the key role in rubber reinforcement, but some authors have recently argued that, when above a critical concentration threshold they are well dispersed in a polymer matrix, they form a kind of tenuous secondary structure, which helps in understanding certain aspects of the reinforcement of elastomers through a filler aggregates networking effect (Klüppel and Heinrich18), as we will see later in detail. Whatever is the packing state of aggregates into agglomerates, and the compaction degree of agglomerates into pellets, there is a certain degree of “voids” such that the solid fraction of carbon black pellets is given by:

Φ pellet = 1 + ρ

DBPA 100

(4.13)

The fraction Φ pellet is found nearly equal to the volume fraction Φ for the aggregate (Equations 4.11 and 4.12), which means of course that the front factor α is also close to one for carbon black pellets. The mean number of aggregates within the total volume R3 of a single agglomerate is defined as N aa = n R 3 with n the number density of the aggregate, i.e.

n=

Φ N d3

(4.14)

The number N aa is obviously related to the degree of interpenetration of aggregates in each other and, with respect to Equation 4.1 it follows:

N aa = α − 3/F Φ N (( 3/F ) − 1)

(4.15)

In relation with the void volume in carbon black aggregates, Medalia19 introduced the (debated) concept of “occluded rubber,” defined as the fraction of

Typical Fillers for Polymers

43

polymer that has penetrated the internal void space of filler aggregates and is thus shielded from deformation, at least partially. Medalia classified voids in a compacted carbon black in two categories: within and between aggregates, and he developed two relationships that permit to assess their relative importance from easily measured quantities, i.e.

Ratio

 1 + 0.02139 DBPA  =  ( 1 − Φ ) ×  − 1   1.46





voids volume within aggregate overall agglomeratee volume

Ratio

(4.16)

voids volume between aggregate overall agglomeratte volume

1 + 0.02139 DBPA   =  Φ − ( 1 − Φ ) ×  − 1   1.46 where DPBA is expressed in cm3/100 g, the factor 0.02139 is the product ρ × 0.0115 with ρ = 1.86 g/cm3 and the factor 1.46 is related with the Medalia’s assumption11 that, at the endpoint of an oil absorption test, the remaining void space between aggregates is 31.5% so that 1 + ( 31.5/100 − 31.5 ) = 1.45985. Such considerations about the fractal nature of carbon black are the background for recent theoretical developments on the very origin of the reinforcing effect of the filler and of certain aspects of the mechanical properties of rubber parts. During efficient mixing operations, carbon black pellets are expected to completely disappear and agglomerates to fully separate into their constitutive aggregates, the latter being ultimately evenly distributed in the rubber matrix. A “well dispersed” state can of course be considered in terms of an even statistical distribution in a given rubber volume, but in the opinion of the author, it is more interesting to define the ideal well dispersed state as the situation where all the reinforcing entities of the filler, in the occurrence the aggregates, have developed their maximum interaction potential with the rubber matrix. In other words, in the optimum dispersion state, the maximum available specific area of the aggregate is in contact with elastomer chains. It is now easy to understand that there will be a tremendous difference in carbon black effects on mechanical (and rheological) properties of rubber compounds, depending one is in the low concentration regime or above a critical concentration level. Below this critical concentration level, well mixed aggregates are sufficiently separated from each other and it is essentially the surrounding rubber matrix that support and transmit the stress. Above a critical filler level, obviously not much depending on the grade of carbon black, there are enough aggregates for a secondary carbon

44

Filled Polymers

black network to be formed through direct aggregate—aggregate interactions, with the resulting capability to support and transmit stress in the compound. As local aggregate density in the rubber matrix increases, a kind of aggregates flocculation occurs which, amongst other effects, can be considered as the very origin of phenomena such as dynamic stress softening. 4.1.5  Surface Energy Aspects of Carbon Black In addition to specific surface area and the fractal nature of carbon black as discussed above, it may be expected that rubber–filler interactions, which are the roots of reinforcement, somewhat depend upon the surface activity of the particles. The so-called surface activity is not however a clearly defined concept as many phenomena might be involved, from Van der Waals proximity forces (around 4 kJ/mole) to specific chemical interactions (e.g., hydrogen bonding, ≈ 20 kJ/mole; ionic bonds, ≈ 30 kJ/mole). Despite the considerable literature on the subject, there is so far no standard method to measure surface activity. Rubber grade carbon blacks contain small quantities of chemically combined hydrogen (0.2–1.0%), oxygen (0.1–4.0 %) and even sulfur (up to 1.0%) depending on the quality of the feedstock and the process. Over the years, a large variety of oxygen containing functional groups, most in minute quantities, has been detected in carbon blacks, for instance carboxyl and hydroxyl groups, phenol, lactones, quinones, ketones, aldehydes, hydroperoxydes, etc., (Figure 4.13). It must be noted however that a number of reported data that support the picture offered in Figure 4.13 have been obtained on lamp or gas blacks, obviously very sensitive to contamination by oxygen and other heteroatoms. Advanced and sophisticated analytical techniques performed on (modern) furnace blacks give quite a different picture. Indeed, Bertrand and

Ketone

O

O

O

HO C

Carboxyl

Pyrone O

O

C

O Lactone HO Hydroxyl

O

O Quinone

Figure 4.13 Chemical functions detected on (lamp and gas) carbon black surface.

Typical Fillers for Polymers

45

Weng20 used time-of-flight secondary ion mass spectrometry (ToF-SIMS) and x-ray photoelectron spectroscopy (XPS) to characterize various furnace blacks, either commercial or experimental, quite representative of the reinforcing carbon blacks available today. They carefully interpreted the various spectra obtained before and after toluene extraction of carbon blacks and came to the conclusion that there are only C and H on carbon black surface, with nearly no oxygen. Even after heat temperature treatment (1000°C), hydrogen containing fragments were still detected in ToF-SIMS spectra. This strongly supports the view that carbon black surface is locally graphitic in nature, with broken graphitic plan edges supporting only C–H or maybe some pendant methyl groups. Carbon black surface chemistry therefore plays nearly no role in the exceptional reinforcing capabilities of this filler. It is moreover well established today that oxygen complexes at the surface of carbon black particles are not essential for reinforcement in most rubbers, with the notable exception of polar elastomers, e.g., butyl rubber. As indeed convincingly demonstrated by Gessler et al.21 some 30 years ago, oxygen functionality on carbon black is a requisite to high-order interactions only for butyl rubber. Indeed when the surface oxygen on channel black is removed by high temperature treatment under inert gas, these authors observed significant loss in reinforcement (damping properties) of butyl rubber. Conversely when furnace blacks (for butyl rubber) are activated by heating at 250–300°C in a stream of oxygen, a significant benefit is observed in terms of reinforcement. With nonpolar elastomers, i.e., most general purpose rubbers, including Natural Rubber (NR), Butadiene Rubber (BR), Styrene-Butadience Rubber (SBR), Ethylene-Propylene Rubber (EPR) and EPDM, the occurrence of chemical reactions with functional groups on carbon black surface is far less convincing. The heating of carbon black below 800°C does not result in graphitization of the filler, i.e., there are no significant changes in the crystallinity of the inner particles, but it does remove most of the chemisorbed surface oxygen. However, rubber–filler interactions remain essentially unaffected, as shown by Dannenberg’s experiments with SBR compounds.22,23 There is therefore a consensus today to consider that the strong rubber–carbon black interaction is not necessarily resulting at all from chemical reactions involving oxygen complexes at the surface of particles. However if the rubber is containing specific reactive groups, then quite logically it may be interesting to consider purposely surface oxidized carbon blacks to promote chemical interaction, as shown for instance by Manna et al.24 with epoxidized natural rubber (ENR). Indeed, with respect to a 60 phr (part per one hundred rubber) Intermediate Super Abrasion Furnace Carbon black (ISAF) (likely N220) filled ENR reference compound, a corresponding 60 phr oxidized ISAF/ENR compound with 4 phr silane coupling agent exhibits twice higher tensile and tear properties, largely below however with what can be readily obtained with conventional natural rubber and carbon blacks. It is thus well established today that carbon black surface chemistry plays a very minor role, is any, in the reinforcement of general purpose elastomers,

46

Filled Polymers

i.e., essentially diene rubbers (NR, BR, SBR) and EPDM, more than 90% of the overall rubber consumption. As we will see, the situation is completely different with other fillers, namely silica, for which the surface chemistry of particles plays the essential role. An attempt to quantify the role of filler surface chemistry is to consider the so-called “surface activity,” generally assessed through the surface energy γ s , which consists of two main components,25 i.e. γ s = γ ds + γ sp



(4.17)

where γ s and γ s are respectively the so-called dispersive and polar (or specific) components. Such properties are measured by inverse gas chromatography (IGC),26 a technique in which the filler to be characterized is used as the stationary phase and the injected solute is the so-called probe. In practice, the filler particles are carefully poured into a stainless steel column of appropriate diameter, typically a few mm. Suitable model chemicals, in dilute solution, are used as probes in order to quantify their interactions with the filler. When the probe is operated at infinite dilution, information is obtained concerning the adsorption of the solute on a solid surface, by use of the Henry’s law that considers the standard free energy of transferring one mole of vapor from a gas phase (at the standard pressure of 1 atmosphere, or 101 kPa) to a standard state on the surface.27 By injecting a series of homologous n-alkanes (e.g., pentane to decane) as probes, the dispersive component of the surface energy γ ds is obtained from the free energy of adsorption, by considering the slope of the measured standard free energy for adsorption vs. the number of carbon atoms for different n-alkanes. The specific (or polar) component is derived from the difference in the free energy of adsorption between a polar probe and a real or hypothetical n-alkane with the same surface area (see details elsewhere25,26,28–31). Table 4.6 gives typical data as reported in literature; as usual data for the same grade slightly differ between authors. Carbon blacks exhibit a high dispersive component, actually proportional to their specific surface area, and a relatively low polar component, not much differing whatever the grade. As we will see later, the reverse is seen with reinp forcing silica grades, which have a lower dispersive component, but a high γ s . With carbon blacks, the reinforcing effect is thus essentially achieved by means of strong filler–rubber interactions, and the polar component is reflected by a relatively weak carbon black network, at least providing that the filler volume fraction is below the so-called percolation level. Above that level, some authors have recently argued that branched aggregates readily entangle through complex topological interactions in such a manner that the carbon black network plays the key role in modulus enhancement, as we will see later in detail. New equilibrium gas adsorption techniques were recently used to analyze the surface energy distribution of carbon blacks.32–35 By deconvoluting the d

p

47

Typical Fillers for Polymers

energy distribution function of adsorbed ethylene into four Gaussian peaks, it can be concluded that there are four different energetic sites on the surface of the filler (Figure 4.14). The nature of these energetic sites is however a matter of interpretation that depends on the model considered for the surface of the filler. For instance, if one considers as with some authors36,37 that the surface of elementary carbon black particles consists of turbostatic graphitic crystallites beside areas of amorphous carbon, then one could assign such energetic sites to different features:

Site I: graphitic surface of a crystallite Site II: amorphous carbon zone. Site III: crystallites edges Site IV: slit shaped cavities (or boundaries between two crystallites) Amorphous carbon zones (II)

Distribution of surface energy f(Q), kJ/mol

Graphitic planes (I)

0.20

Crystallite edges (III)

Adsorption of C2H2 on at T = 233 K N220 carbon black

0.16

Overall energy distribution function

I

0.12

Fraction (%) of energetic sites III IV I II

0.08 II

0.04 0.00

Slit shaped cavities (IV)

0

III

N115 N220 N550 Graphite

69 84 93 94

13 7 6 0

15 7 1 4

3 2 Φ occ ( γ ) =

1 1 = K ⋅γ 1+ c⋅γ 1+ vads

[3]

228

Filled Polymers

The number of isolated sites Nisolated, available for unstable links, times the fraction of free sites is in fact the number of unstable rubber-filler knots, which depends on the strain amplitude, i.e.: N unstable ( γ ) = N isolated ⋅ Φ occ ( γ ) = N isolated ⋅



1 1+ c⋅γ

There are thus, two contribution in the dynamic modulus, one due to the vulcanization and the stable rubber-filler knots, the other owing to unstable rubber-filler knots, thus, dependending on strain: 1   Gestable =  N chem + N stable + N isolated ⋅ ⋅kB⋅T  1 + c ⋅ γ 

or:

Ge(γ ) = Gest + Geun ⋅

1 1+ c⋅γ

The viscous modulus is considered proportional to the fraction of occupied sites times the probability P that an attached segment is able to slide into a near (free) site, i.e. G″(γ)∼Φocc(g)P. This probability depends on the quantity of free sites at the surface of the particle, i.e., P∼Φfree(γ) There are therefore, two contributions to the viscous modulus, one from the stable links and one from the unstable links, the latter proportional to the product Φfree × Φocc. From Equations [1] and [2], one has K⋅γ =   Φ free ( γ ) = Φ occ ⋅ thus: vads

1 K ⋅γ ⋅ K ⋅ γ vads 1+ vads

Therefore: Gv(γ) = Gvstable + Gvunstable⋅Φocc(γ)⋅Φfree(γ)

Gv(γ ) = Gv stable + Gv unstable ⋅



or:  Gv(γ ) = Gv stable + Gv unstable ⋅

1 K ⋅γ 1+ vads

1 K ⋅γ   ⋅  K ⋅ γ vads  1+  vads  

c⋅γ (1 + c ⋅ γ )2

with

c=

K vads

229

Polymers and Carbon Black

A5.6.2 A Few Mathematical Aspects of the Model γ: = 0.0001, 0.0002, .. 2

: strain range for calculation

Gest: = 0.74 ⋅ 106 ⋅ Pa   c: = 40.15   Gvst: = 0.10 ⋅ 106 ⋅ Pa

Data for butyl/N330 cpd (f N330 = 0.233) used by Maier and Göritz when probing their model

Geun: = 9.52 ⋅ 106 ⋅ Pa   Geun: = 4.55 ⋅ 106 ⋅ Pa Ge(γ ): = Gest + Geun ⋅

Gv(γ ):= Gv st + Gv un ⋅

1 c

5.106

1



c 1.106

5.105

0 1.10–4 1.10–3 0.01 0.1 Strain

10

c is the reverse of the strain for which G′ = 0.5 × G′unstable + G′stable.  1 Ge   = 5.5 ⋅ 106 Pa  c

( 1 + c ⋅ γ )2

1

1.107

0 1.10–4 1.10–3 0.01 0.1 Strain

c⋅γ

1.5.106 Viscous modulus, MPa

Elastic modulus, MPa

1.5.107

1 1+ c⋅γ

1

10

c is the reverse of the strain for which G″ is maximum and equal to 0.25 × G″unstable + G″stable.

 1 Gv   = 1.238 ⋅ 106 Pa  c

Gest + 0.5 ⋅ Geun = 5.5 ⋅ 106 Pa

Gv st + 0.25 ⋅ Gv un = 1.2238 ⋅ 106 Pa

Rem: one notes also that the 1st derivative of

1 −c is 1+ c⋅γ ( 1 + c ⋅ γ )2

Due to its starting hypotheses, the Maier and Göritz model has a mathematical form that leads to symmetries in both the G′ vs. strain and the G″ vs. strain functions; the former exhibits an horizontal symmetry with respect to a mid- modulus value, the latter shows vertical symmetry with respect to a critical strain = 1/c. Both the elastic and the viscous moduli at the critical strain are simple combinations of the “stable” and “unstable” links contributions.

230

Filled Polymers

A5.6.3  Fitting the Model to Experimental Data Dynamic strain softening data on SBR/60 phr black cpds [M. Gerspacher, C.P. O’Farrell, C. Tricot, L. Nikiel, H.A. Yang. ACS Rubb. Div; Mtg. Louisiana, KY, 1996. Paper 74] Strain sweep experiments N660 Strain %

 0.091   0.19  0.28   0.38  0.48   0.55   0.66  0.74   0.84  0.93   1.07  Data: =  1.22  1.48   1.7  1.9   2.8   3.7  4.6   5.5  6.5   7.6   8.5  9.5

G′

G ′′

2.34 2.31 2.330 2.26 2.24 2.23 2.22 2.21 2.20 2.18 2.16 2.15 2.14 2.12 2.11 2.06 2.05 2.04 2.02 2.00 1.99 1.97 1.95

0.265 0.275 0.280 2.290 0.295 0.296 0.297 0.297 0.297 0.298 0.2298 0.299 0.299 0.298 0.298 0.294 0.290 0.294 0.285 0.280 0.275 0.271 0.269

MPa

MPa

Maier and Göritz model Elastic modulus

N330 G′

MPa

4.45 4.41 4.30 4.24 4.10 4.05 3.95 3.89 3.82 3.75 3.61 3.55 3.46 3.40 3..34 3.08 2.95 2.85 2.78 2.71 2.65 2..62 2.57

N110 G ′′

MPa

0.630 0.630 0.650 0.660 0.670 0.685 0.692 0.7700 0.710 0.716 0.720 0.720 0.719 0.718 0.717 0.690 0.660 0.631 0.608 0.581 0.560 0.542 0.530

G′

MPa

6.02 5.95 5.80 5.61 5.50 5.32 5.18 5.05 4.95 4.83 4.65 4.48 4.31 4.20 4.08 3.71 3.49 3.30 3.18 3.08 3.01 2.95 2.90

G ′′

Ge( γ ) = Gest + Geun ⋅

MPa

0.915   0.938  0.942   0.960  0.9980   0.993   1.000  1.010   1.026  1.030   1.032   1.033  1.031   1.030  1.020   0.968   0.914  0.870   0.828  0.782  0.752   0.722  0.700 

1 1+ c⋅γ

Gest = G′stable: elastic modulus due to chemical crosslinks + stable rubber-filler interactions Geun = G′unstable: elastic modulus due to unstable rubber–filler interactions [ = f(strain)] Viscous modulus Gv( γ ) = Gv st + Gv un ⋅

c⋅γ

( 1 + c ⋅ γ )2

Gvst = G″stable: viscous modulus due to chemical crosslinks + stable rubber-filler interactions Gvun = G″unstable: viscous modulus due to unstable rubber–filler interactions [ = f(strain)] c = constant related to the rate of adsorptiondesorption of rubber segments on appropriate sites on filler particles γ = strain amplitude

231

Polymers and Carbon Black

A5.6.3.1 Modeling G′ vs. Strain Extracting data Strain(%)

 

j: = 0..2

γ : = Data

N660G ′(MPa) Ge0 := Data





n: = length( γ )

N330G′(MPa) Ge1 := Data n = 23

N110 G′(MPa) Ge2 := Data



: number of data

Guess parameters for nonlinear fitting algorithm (GenFit function)  ( Ge j )0    C j : =  ( Ge j )n− 1    1   γ   n  round 2  

hydrogen bonding (rare, if any) between particles

O

237

Polymers and White Fillers

polydimethylsiloxanes naturally interact with silica, thank to their similar chemistry. It is for instance long known that, with silicone polymers, the silica surface chemistry can be varied nearly at will, by controlling the degree of adsorbed water, the hydroxyl population and the degree of organophilicity,2 all aspects largely exploited by the silicone rubber industry.3 6.1.1.3  Comparing Carbon Black and (Untreated) Silica in Diene Elastomers Silicone rubber and, in general polar polymers, are by nature materials of choice for preparing silica filled systems; however limited to niche applications, with respect to the range of properties that such specialty polymers may offer. In order to develop optimum reinforcing performance with more common diene elastomers, silica must be chemically treated as we will see below, because contrary to carbon blacks, silica particles do not develop spontaneous strong interactions with nonpolar polymers. It is nevertheless interesting to see that, even with comparable size and structure, pure silica does not affect the mechanical properties of vulcanized rubber compounds in the same manner as carbon black. This was clearly demonstrated in the excellent review paper by S. Wolff 4 who studied the effects of two comparable series of silica and carbon black in 50 phr filled natural rubber (RSS1) compounds, vulcanized with peroxide (Note that such a vulcanization system was chosen because there is no interference between silica and peroxide curing). Table 6.1 gives typical size and structure data for the two series of filler considered. It is worth underlining that there are no standard methods for characterizing silica. Either an existing method can be used as such because it does not depend on the filler Table 6.1 Comparable Series of Precipitated Silica and Carbon Black

Filler Grade Precipitated silica

Furnace blacks

a

1 2 3 4 5 6 N660 N550 N326 N330 N356 N220 N110

DBP or TEA Absorptiona (ml/100 g)

N2 Specific Area (m2/g)

Uncompressed

30 48 123 167 172 173 36 40 76 78 88 110 139

100 164 192 227 188 204 95 123 70 100 153 114 115

Crushed (24M4)

DBP, di-butylphthalate for carbon black; TEA, triethanolamine for silica.

64 74 90 90 96 93 70 86 64 85 113 94 94

238

Filled Polymers

considered, or the method must be modified to take into account the surface chemistry of silica. For instance the specific area of silica can be assessed through nitrogen adsorption (BET method) but for aggregate structure, dibutylphtalate adsorption is not convenient (because DPB does not “break” interparticles hydrogen bonding). Adsorption of triethanolamine gives correct results, comparable to data obtained on carbon black with DPB. Comparing mechanical properties imparted by either carbon black or silica in a purposely simple natural rubber formulation allows several interesting conclusions to be drawn. Figure 6.2 shows for instance the 100% and 200% modulus, both affected by the size and the structure of the filler. At low strain, i.e., 100%, most precipitated silica and several high structure blacks exhibit similar reinforcing capabilities; at higher strain however, all silica are clearly less reinforcing than carbon black. Wolff attributed this effect to a “silica network” which is destroyed when straining vulcanizates. Low strain amplitude dynamic properties reveal quite an interesting aspect of silica reinforcement. As shown in Figure 6.3, high structure silica (i.e., with crushed TEA adsorption values higher than 80 ml/100 g) give NR compounds with higher complex modulus G* and lower tan δ than carbon blacks of similar structure. This advantages of high structure silica over carbon blacks is also observed when performing technological dynamic tests, for instance rebound resilience test. However, in line with tensile modulus data, silica gives larger compression sets than carbon blacks. Despite the fact that the compounds investigated were (purposely) oversimplified with respect to industrial practices, the key information in the experiments reported by Wolff is that silica filled compounds exhibit definitely better dynamic properties that carbon black filled ones, namely higher rebounds and lower heat build-up. In addition the higher the specific area of fillers, the larger the differences between silica and carbon black loaded materials. Freund and Niedermeier made a similar

100% Modulus, MPa

4.0

Carbon black Silica

3.5 3.0 2.5 2.0 1.5 1.0 60 80 100 120 40 Crushed DBP or TEA absorption, ml/100g

20 200% Modulus, MPa

4.5

15

NR (RSS1) 100 Filler 50 Peroxide (DCP) 2.03

10 5 0 40 60 80 100 120 Crushed DBP or TEA absorption, ml/100g

Figure 6.2 Effect of carbon black and silica structure of tensile properties. (Drawn using data from S. Wolff, Rubb. Chem. Technol., 69, 325–346, 1996.)

239

Polymers and White Fillers

26 20

Carbon black Silica Frequency : 5 Hz Temperature : 23°C

14 8 2 60 80 100 120 40 Crushed DBP or TEA absorption, ml/100g

0.20 0.15

NR (RSS1) Filler Peroxide (DCP)

100 50 2.03

Tan delta

Complex modulus E*, MPa

32

0.10 0.05 0 60 80 100 120 40 Crushed DBP or TEA absorption, ml/100g

Figure 6.3 Effect of carbon black and silica structure of low strain dynamic properties. (Drawn using data from S. Wolff, Rubb. Chem. Technol., 69, 325–346, 1996.)

comparative study on carbon black and silica compounded in nonpolar and polar elastomers.5 From their investigation of the dynamic strain softening effects, they concluded that reinforcement by carbon black and silica essentially proceed from different micro-mechanisms. Polymer adsorption prevails in carbon black filled systems, while filler particle networking is the key aspect in silica filled systems. Performed some 20 years ago, such basic studies (and many others) clearly indicated that highly structured silica (i.e., very large specific area) were surely interesting alternative fillers for carbon black in highly demanding dynamic applications, for instance tire technology. However, when compared to carbon blacks, silica have serious drawbacks, essentially arising from their peculiar surface chemistry. Besides the strong inter-particles interactions which give dispersion difficulties in hydrophobic polymers (notably all diene rubbers, i.e., around 90% of the overall elastomers consumption), the chemically active surface of silica has a strong potential for interacting/interfering with curing systems, particularly when basic accelerators are used, giving lower cure rates and lower crosslink densities (i.e., modulus).4,6,7 6.1.1.4  Silanisation of Silica and Reinforcement of Diene Elastomers In order to fully exploit the promising capabilities of silica in the reinforcement of diene elastomers, it is essential to consider their surface chemistry and to accordingly proceed to a number of changes, at various levels of rubber technology, in terms of formulation, compounding, mixing, and processing. First the vulcanization chemistry must be modified in order to take into account the high chemical reactivity of silica particles surface and the likely modification of the structure of the networking bonds, with respect to the experience gained over the years with carbon blacks. Second particle– particle interactions are very strong with silica, due to hydrogen bonding

240

Filled Polymers

and the hydrophobic character of diene elastomers is surely not a favorable aspect in what silica dispersion is concerned. Third rubber–filler interactions of physical origin, as occurring with carbon blacks, cannot be expected with silica with respect to the shielding effect of silanol groups. It follows that a chemical approach has to be considered in order to create covalent bonding between rubber and silica particles. The benefit in using silanes as coagents in (diene) rubber compounding has been recognized for long1,8 and many organo-silanes were studied. A number of investigated organo-silanes were found either limited in their interest, difficult or inconvenient to use, or too expensive for industrial applications. Eventually, the reduction of silica interparticle interactions, in association with the development of suitable (chemical) bonds with diene elastomers were obtained through the use of so-called “reinforcement promoters,” essentially bifunctional silanes of general formula:

(RO)3–Si–(CH2)n–X

One end of such molecules is expected to specifically react with silanols on silica surface, whilst the other end is expected to eventually interact with the vulcanization system (essentially sulfur based) in order to provide chemical bonding with the rubber network. It worth underlining again the fundamental difference between carbon black and silica reinforcement: no chemistry is needed with the former but is essential with the latter. Many organo-silanes have been synthesized and tested over the years (mainly in the 1970s) and essentially two chemicals were found of interest in the rubber (tire) industry: • Bis(3-triethoxysilylpropyl)tetrasulfane (TESPT); note that TESPT is in fact a mixture of different polysulfane with an average S chains of four9)

(C2H5O)3–Si–(CH2)3–S4–(CH2)3–Si–(OH5C2)3 frequently referred under its commercial name Degussa (Evonik) Si69 • 3-thiocyanatopropyl-triethoxy silane (TCPTS)



(C2H5O)3–Si–(CH2)3–SCN also referred under the commercial name Degussa (Evonik) Si264.

In principle, one may either pretreat silica with such silanes (usually in solution/suspension, with subsequent elimination of solvents) and then use the modified silica in compounding, or consider silane as a compounding

Polymers and White Fillers

241

ingredient and proceed to the silanization during mixing operations. Obviously pretreated silica are expensive products since notwithstanding the cost of such fine chemicals as organo-silanes, solvent elimination, product drying and conditioning bring uncompressible costs. In situ silanization became therefore the preferred approach despite the challenging difficulties in controlling a chemical reaction in a highly viscous medium, i.e., during mixing. In other terms, quite a complex set of physico-rheological processes had to be mastered in equipment that at first were essentially developed for preparing carbon black compounds. Chemistry in highly viscous media is not an issue in carbon black reinforcement and therefore, controlling the variation of temperature during mixing is essentially considered in terms of limitation of the warming up associated with the process, mainly due to viscous heat dissipation effects as arising when shearing a viscoelastic material. With in situ silanization of silica (i.e., during mixing), the problem is completely different since elementary considerations allows the following requirements and difficulties to be a priori identified:





1. An even dispersion of all reactive ingredients has first to be achieved in a highly viscous medium, which means than reactive species displacement is an issue. 2. Reactions between silica and silane must be activated (usually by reaching the appropriate temperature) and completed (by maintaining the appropriate temperature conditions for a sufficient time. 3. Premature reactions between the rubber and the silane must be avoided during mixing operation.

Directly studying silanization chemistry during rubber mixing is very challenging and has never been made (or even tempted) to the author’s knowledge. But a number of very elegant studies of silanization in solution or in suspension have been performed9–13 that eventually confirmed earlier proposals for a likely reactional scheme,14 and allowed to understand certain aspects of the in situ process and the interference with vulcanization. Investigations using rubber compounds15 essentially confirmed the conclusions of such basic studies. The silica modification with a bi-functional organosilane (either TESPT of TCPTS for instance) and the subsequent development of rubber–filler bonding during vulcanization is essentially considered as follows:16

1. Silanisation (Figure 6.4): first one ethoxy group reacts quickly with an isolated silanol (around 85% on silica surface) or a silanediol (15%); then there is hydrolysis of the remaining ethoxy groups, which produce a reticulation of silane molecules through siloxane bonding.



2. Vulcanization (Figure 6.5): the tetrasulfane group (with TESPT silanated silica) is broken and forms rubber–filler covalent bonds with the

242

Filled Polymers

Si

OH

Si

OH

+

C2H5O C2H5O C2H5O

Si (CH2)3 S4 (CH2)3 Si

OC2H5 OC2H5 OC2H5

-CHOH

Si

O

Si

O

Si

O

Si Silica reaction with TESPT

O

Si

Si

OC2H5 (CH2)3 Sa (CH2)3 Sb OC2H5

Silanated silica (a+b = 4)

Figure 6.4 Silica modification with bi-functional organosilane.

Si

O

Si

O

Si

O

Si

O

Si

Si

OC2H5 (CH2)3 Sa (CH2)3 Sb

+ Rubber

Si

O

Sulphur S8

Si

O

Accelerator

Si

O

Si

O

OC2H5

Si

Si

OC2H5 (CH2)3 Sa (CH2)3 Sb OC2H5

Figure 6.5 Silica–rubber bonding during vulcanization.

polymer during the rubber networking. Note that bonds between silanated silica and rubber are either mono- or disulphidic. In fact, the silanization itself occurs in two steps: first there is a reaction between the silanol groups on silica surface with the alkoxy group of the silane, likely through hydrolysis of the alkoxy groups followed by a condensation reaction with the silanols, but direct condensation is also possible. Hydrolysis then condensation is supported by the beneficial influence of the moisture content of silica on the rate of silanization. The second step is a condensation reaction between adjacent molecules of the silane on the silica surface, and a hydrolysis step is also likely occurring. The result is a significant decrease of the hydrophilic degree of silica particles and hence an easier dispersing in hydrophobic elastomers (i.e., most diene rubbers used in tire technology). Detailed investigations on the kinetics of this complex set of reactions have demonstrated that the activation energy of the first step is nearly twice of what is needed for the second step (i.e., 47 kJ/mole vs. 28 kJ/mole) but the secondary step is around 10 times slower that the first one.13 Recently reported results, obtained by using a model silane and time resolved IR spectroscopy in a microreactor with infrared transparent windows brought a very elegant confirmation of such a two steps mechanism.17 It was indeed shown that the silane interacts first by hydrogen bonding with isolated silanol groups. This first step is very fast and the so-immobilized species react dissociatively with silanols to give covalent bonding with the silica surface, while alcohol is released. Hydrogen bonded silane is less stable

243

Polymers and White Fillers

than when covalent bonded. It was also found that vicinal silanol groups do not react with silane, likely owing to a lower reactivity or to steric hindrance. Such results explain why only 25% of the total hydroxyl groups on silica surface are involved in the silanization process. Both sequences of reactions are acid as well as alkaline catalyzed and the rate constant for the primary reaction decreases as the silane content increases. It is likely that the lower accessibility of silanol groups on the filler surface as the silane content increases, and the decrease of H2O available for the hydrolysis step are responsible for this effect. It follows that the optimal loading of the silane is around eight parts of TESPT for 100 parts of silica. Details on this complex chemistry can be found in the referenced papers. The reactional scheme described above prompts several remarks: first ethanol is produced during silanization reactions (around 2 moles of ethanol per mole of TESPT), and must be eliminated of captured by the appropriate formulation ingredient, otherwise there will be porosity in the vulcanized product; second with TESPT, highly reactive tetrasulfane groups are formed which may give thermo-activated reactions with the polymer if the temperature is too high. It follows that controlling the temperature during mixing is a crucial aspect of the operation: it must be high enough for the silanization reaction to be activated and low enough for tetrasulfane networking or premature vulcanization to be avoided. As may be expected the nature of the alkoxy group in the organo-silane is playing a role in the silanization process (Figure 6.6); whilst very fast, the methoxy group cannot be used for obvious toxicological reasons and the reaction rate is decreasing with the size of the group, leaving the ethoxy as the best choice. Ethanol formation during the in situ silanization is readily an issue in practical compounding since for each gram of silane used, around 0.5 g of alcohol would be produced if all ethoxy groups were reacting. Not all ethoxy groups are reacting however13 but, on the factory floor, considerable amount of ethanol are produced, which besides potential health and toxicity hazards, can readily decrease the efficiency of the mixing process, through recondensation in the mixer chamber and hence wall slippage of the compound. The nature of the rubber has been found to affect the silica silanization process, as demonstrated by Table 6.2. It was also established that, at constant mixing time, the reaction efficiency increases with the (dump) temperature, but in the mean time higher mixing temperature increases the risk of premature vulcanization. Lengthening the mixing cycle and/or using several (re)mixing steps offers several advantages, most likely because it favors the volatilization of ethanol. Dierkes has

Methoxy group not used for toxicological reasons

CH3O- >

C2H5O-

> C3H70- > C4H9O > ...

Decreasing rate

Figure 6.6 Effect of the alkoxy groups in the silanization efficiency of organo-silanes.

244

Filled Polymers

Table 6.2 Effect of Rubber Type on the Silica Silanisation Reaction Rubber or Rubbers Blend

Mole Ethanol/mole TESPT

S-SBR/BR NR NR/BR E-SBR NBR EPDM

1.50 1.75 1.80 2.25 0.90 2.30

Source: Data from U.Görl and A.Parkhouse Kautch. Gummi Kunstst., 52, 493–500, 1999. Note: Experimental conditions: TESPT content: 6.5% of silica; 5 min. mixing with dump at 160°C.

0.30

Frequency : 5 Hz Temperature : 23°C

Frequency : 5 Hz Temperature : 23°C

Natural rubber cpd

30

Silica

N110 carbon black 0.20 Tan δ

Elastic modulus E´, MPa

40

20

10

Silica + TESPT

0.10

N110 carbon black

Silica

Silica + TESPT 0

–3

–2 –1 Log double strain amplitude

0

0

–3

–2 –1 Log double strain amplitude

0

Figure 6.7 Effect of silanization on the reinforcing properties of NR compounds (Data from S. Wolff, Rubb. Chem. Technol., 69, 325–346, 1996.)

thoroughly investigated the industrial mixing of silica filled compounds and considered several approaches to overcome such practical problems.18 Silanisation has profound effects on the reinforcing character of silica and allows to obtain vulcanized rubber systems which exhibit certain benefits with respect to corresponding carbon black filled compounds. As expected silica interparticle interactions are considerably reduced through silanization, as reflected by the large reduction in the dynamic strain softening effect. Figure 6.7 shows for instance the dynamic properties of NR

Polymers and White Fillers

245

compounds filled with carbon black, silica, or silica + TESPT, through strain sweep experiments performed at 5 Hz frequency. As can be seen, the treatment of silica with TESPT reduces the elastic modulus drop upon increasing strain amplitude; this indeed corresponds to a strong reduction of interparticles interactions but the reinforcing effect is also reduced (lower modulus that the reference carbon black filled compound. However the interest in using treated silica appears on tan δ which is slightly increased through silanization but remains significantly lower than the homologous carbon black filled system. In other words, silanization reduces the dynamic strain softening effect but keeps the lower viscous dissipation of silica under dynamic strain. These characteristics of silane treated silica are at the origin of the development of silica filled tread bands in automotive tires (so called “green tires” because with the lower viscous dissipation imparted by silica reinforcement, the energy produced by the engine is more efficiently used in moving the vehicle). The complex chemistry associated with the in situ silanization of silica, as mastered today by tire manufacturers, is surely worth detailed considerations, particularly with respect to the processing behavior. The mixing procedure and conditions, the temperature control, the elimination of ethanol, etc. are key issues on the factory floor, so-far typical of each mixing plant and essentially monitored through pragmatic engineering practices, about which tire manufacturers remain relatively discreet. Silanols can react with several compounding ingredients such as stearic acid, polyalcohols, and amines and, obviously would compete with silane and reduce the silanization efficiency. The order of addition of compounding ingredients is consequently of prime importance; indeed the mixing procedure must be such that the whole amount of TESPT is consumed during the primary reaction.15 In situ silanization is a very important subject in contemporary rubber technology, actually well mastered through the appropriate (and complicated) engineering practices,7,19 but outside the very scope of this book. What must be kept in mind with respect to the scope of this book, is first that for silanes to be effective “promoters” of mineral fillers, active chemical groups on filler particles are needed in quite large quantities, second that specific conditions must be met and maintained for a sufficient time, for the silanization to be complete, third that the polymer must have a reactivity potential with some chemical functionalities of the silane. Silica is surely the right filler for the effective use of silanes, but using such chemicals with other minerals having no or a poorer surface chemistry (e.g., kaolin, mica, talc, …) is obviously not expected to bring the same benefits on reinforcement. Nevertheless, as coated mineral particles are generally easier to dispersed in diene rubbers than their uncoated equivalent, silane-treated talc, mica, and kaolin grades permit fine dispersion to be obtained, with obviously less clustered particles that are always potential failure initiation sites. Any silica-filled rubber formulation may benefit from in situ silanization during the compounding operations and, in the tire industry, it is now well established that partial or total substitution of carbon black by silanated

246

Filled Polymers

(precipitated) silica in tread formulation gives the best compromise in terms of rolling resistance and wet grip. It is interesting to note that most of the ­silica-filled tread compounds in use today are essentially developments of the original Michelin formulation patented by Rauline,20 in which a mediumor high-vinyl solution styrene butadiene copolymer (S-SBR) is the main elastomer. S-SBR is produced by anionic polymerization whose capabilities to control the molecular weight distribution and the level of branching are well known. All such characteristics are of course of importance as they provide the rubber matrix the required performances with respect to tire tread dynamic behavior. However, as recently pointed out by Heinrich and Vilgis,21 the reason why S-SBR (instead of less expensive emulsion E-SBR) is the polymer of choice for silica-filled tread compounds is not fully understood. When comparing the tan δ vs. dynamic strain amplitude functions (at 30°C) of two S-SBR and E-SBR compounds with equal silica content (80 phr) and the same hardness, these authors note that the S-SBR system has a significantly lower tan δ (around 20% drop). Such a difference can hardly be explained with respect to the microstructure (cis, trans and 1,2-vinyl) and MW distribution of both elastomers, and Heinrich and Vilgis develop an argument based on the confinement of polymer segments in pores that would exist in amorphous precipitated silica, seen as clusters of elementary spherical particles. Polymer segments could be immobilized (or confined) in such pores if, indeed, their size, in the nanometer range, is close to typical dimensions of the polymer chain, for instance the so-called Kuhn length (from the theoretical view of a polymer chain seen as made of N segments of Kuhn length b, so that each segments are freely jointed with each other; the so-called contour length of the polymer is then L = N b). Because E-SBR is somewhat more branched than S-SBR, it would saturate the external surface of silica clusters, without penetrating much into silica pores. On the reverse, S-SBR segments would have the capability to completely fill pore volume and remained confined, thus giving strong polymer–filler interaction, that would of course superimposed to the chemical interaction imparted by the silanization. Such polymer segment confinement would lead to a hindered polymer dynamics within nano-scale ranges, playing a key role in the frequency domains associated with either wet skid or rolling resistance. Further works are needed to fully support such proposals, but recently published data document indeed the very special dynamic–mechanical properties of silica-filled S-SBR compounds, with very small effects assigned to silanization (with TESPT) up to 70 phr silica. 6.1.1.5  Silica and Polydimethylsiloxane Polyorganosiloxanes, the so-called “silicones,” whose general formula is R′–(SiOR2)n–R′, are a family of polymer materials with unique and interesting properties.3 Silicone polymers have the alternating –Si–O– type structure as part of their backbone chain and although silicon is in the same group as carbon in the periodic table, it has quite a different chemistry. Various

Polymers and White Fillers

247

organic groups, e.g., methyl, benzyl, etc., may be bonded to the silicon to yield polymer materials that are by nature water repellent, heat stable, and very resistant to chemical attack. Poly(dimethylsiloxane) or PDMS is by far the most common silicone polymer, whose flexibility is due to the inorganic siloxane backbone, with a very low surface energy imparted by the methyl groups. This results in a glass-transition temperature of less than –120ºC, and consequently quite a large usage temperatures window, from below –40ºC to above 150ºC. Various PDMS materials are obtained through synthesis and hydrolysis of chlorosilanes, then polycondensation, according to the following schema:

Si + 2 ClCH3 → SiCl2(CH3)2



n SiCl2(CH3)2 + 2 n H2O → Si(OH)2(CH3)2 + 2 n HCl



n Si(OH)2(CH3)2 → [SiO(CH3)2]n + n H2O

The value of n fixes the molecular weight, and hence the viscoelastic nature of the material, from low viscosity oils up to high MW polymers. Vulcanizable elastomers are obtained by introducing reactive sites, for instance vinyl groups. Mechanical properties of silicone polymers are improved through the addition of fillers, with silica the most obvious choice. Globally the same reinforcing effects as in other elastomers are observed with silicone/silica compounds, with the level and the structure of the filler playing qualitatively the same roles. However there are a few singular aspects in polysiloxane/ silica systems worth discussing in details because certain well established scientific knowledge can be somewhat extrapolated to other systems. Interactions between organosiloxanes and silica particles, either fumed or precipitated is a long studied subject, either for purposely promoting grafting chemical reactions on the particles23 or as an approach for understanding the interactions between siloxane and silanol groups.24 One would a priori consider that, owing to their close chemistry, polysiloxanes and silica are naturally compatible and that it is relatively easy to disperse the latter in the former. This is globally true but it has been observed for long that, once a silica and a silicone polymer have been mechanically mixed, the very adsorption process of polymer chains on the surface of silica particles is relatively slow, even if it tends to accelerate at higher temperature. For instance, at 70°C, three months are necessary for a PDMS sample to fully saturate the silica surface. The adsorption properties and kinetics in silica/PDMS systems, the structure of the adsorbed layer and other singular aspects were investigated by a number of authors and their findings allow to somewhat understand certain engineering practices that were pragmatically developed by manufacturers of silicone products, e.g., mastics, sealants, and other self­vulcanizing liquid silicones. Early observations revealed that in useful silica/

248

Filled Polymers

silicone dispersions, the polymer on the silica substrate is approximately ten times more concentrated than what would correspond to a monolayer of water.25 Then, by combining chemical microanalysis, Nuclear Magnetic Resonance (NMR) relaxation and swelling measurements, it was shown that directly after mechanical mixing, PDMS chains are strongly adsorbed on only a quarter of the silica surface, in the form of adsorbed islets.26 It was first established that, during the slow saturation of silica surface, which lasts around three months at 70°C, the average number of contact points of a chain with the silica surface is proportional to N b (Nb is the number of skeletal bonds in one chain).27 Eventually using NMR relaxation and diffusion studies, the structure of silica/PDMS systems was rationalized by a three-state model: close to silica particle, there is a (strongly) bound polymer layer, then polymer chains are entangled or restricted by the adsorbed layer and eventually there is the free bulk polymer.28 Recent works with modern sophisticated analytical techniques essentially confirm previous observations.29,30 It is worth noting here the remarkable similarity between such a description of the structure of silica/silicone systems and the established morphology for carbon black filled rubber compounds (refer to Figure 5.16). Thanks to their similar chemistry, silica and silicone polymers develop thus instant interactions but the full capabilities of such systems are obtained only when the structure of the adsorbed polymer is completely developed. The adsorption kinetics is consequently an issue of industrial importance with silica/silicone systems and was consequently thoroughly investigated. Cohen-Addad et al.31 studied the time dependence of the adsorption of siloxane chains on silica aggregates and proposed the following empirical model:

[Qsat − Q(t)] = [Qsat − Q0 ] × exp  −

t  tad 

(6.1)

where Q(t) is the amount of bound polymer at time t (in g/g of silica), Q 0 and Qsat respectively, the initial (i.e., directly after mechanical mixing) and final (i.e., at saturation) amounts of adsorbed polymer (in g/g of silica), t the time and tad a characteristic time. Experiments at room temperature with either hydroxyl or methyl terminated polymers and 29%wt silica gave very high values for tad, i.e., 7.1 × 107 s (around 2.25 years) and 6.2 × 108 s (nearly 20 years), respectively. Whatever their chain end, polydimethylsiloxanes adsorb on silica particles according to simple equivalent laws of adsorption, proportionally to Mn .32 For a given silicone polymer, there is a specific silica concentration for a tri-dimensional silica-polymer morphology to be obtained, with the associated viscoelastic behavior (i.e., gel or no-gel).33 Equation 6.1 is essentially an empirical model, likely selected for its convenience in fitting experimental data, using a linear algorithm for instance the least square method. It is worth noting that considering the variation of

Polymers and White Fillers

249

the adsorbed amount of polymer with respect to the square root of time is an obvious reference to a Fickean process. Providing nonlinear fitting algorithms are available, an equivalent but more explicit model is:

Q ( t ) = Q0 + Qinf 1 − exp ( − λ t )

(6.2)

where Q 0 is the initial adsorbed polymer (i.e., directly after mechanical mixing) and Qinf the additionally adsorbed polymer after an infinite time (i.e., at saturation), both in g/g of silica), t the time and λ is a parameter related with the characteristic time tad for the adsorption process (i.e. λ = t-0.5 ad). The overall bound polymer for an infinite time is then given by (Q 0 + Qinf), which corresponds obviously to Qsat in Equation 6.1. As shown in Figure 6.8, experimental data on silica/PDMS systems34 were fitted with Equation 6.2, using a nonlinear fitting algorithm (see details in Appendix 6.1). As can be seen the model meets well experimental data and the initial and the final quantities of polymer are directly obtained as fit parameters. The initial quantity of adsorbed polymer is somewhat depending on the mechanical mixing conditions (unfortunately not precisely documented in the source of data) but it is quite clear that, at equal silica content, the higher the molar mass of the polymer, the larger the bound polymer content at the end of the mixing step. Increasing the silica loading gives expectedly a higher initial bound polymer but also a lower quantity of adsorbed polymer at saturation. The value of the characteristic time tad (or the parameter λ in Equation 6.2) gives an insight on the time scale of the adsorption process. Even if increasing the temperature somewhat speeds up the process, quite long maturation periods are necessary for the silica surface to be fully saturated. As clearly seen in Figure 6.8, higher Mn polymers tend to mature faster and silicone product manufacturers obviously take advantage of this effect in tailoring their products. But slow maturation processes mean also that some “ageing” either on storage, or during the life of the material can be expected, as a mere result of polymer chain dynamics in the vicinity of silica particles. For instance, DeGroot and Macosko investigated the aging behavior of silica/ PDMS systems, by measuring the rheological properties, the bound rubber, and the state of dispersion as a function of time.35 They observed softening rather than hardening as typically reported for silica filled systems. Polymer adsorption onto the surface plays obviously an important role in determining the overall stability of these systems and the addition of a surface treating agent (e.g., hexamethyldisiloxane and hexamethyldisilazane), either physically adsorbed or covalently bound to the silica surface, can inhibit the adsorption of polymer. A better stability of the silica dispersion is then observed and therefore variation in rheological properties are reduced. With respect to the silica surface chemistry (see Figure 6.1) and the chemical nature of polysiloxane, the interaction sites are clearly identified since they

0

0.5

1

1.5

2

0

r2

Qinf (g/g) λ tad (h)

Q0 (g/g)

Mn, g/mole :

1000

0.257 0.588 0.044 514.8 0.991

43000 0.320 1.321 0.053 350.7 0.987

73000

2000 Time (h) 0.733 1.483 0.061 273.1 0.992

300000

3000

Mn = 43,000 g/mol

Mn = 73,000 g/mol

Mn = 300,000 g/mol

4000

Adsorbed polymer Q (g/g of filler) 0

0.5

1

1.5

0

0.103 1.702 0.041 588.7 0.980 r2

Qinf (g/g) λ tad (h)

0.049

Q0 (g/g)

2000 Time (h)

Silica fraction :

1000

PDMS Mn = 43000 g/mol 2

0.266 1.042 0.022 2020 0.993

0.103

3000

0.255 0.614 0.039 648.2 0.985

0.204

Φ = 0.204

Φ = 0.103

Φ = 0.049

4000

Figure 6.8 Adsorption kinetics of polydimethylsiloxane on silica particles. (Experimental data from L. Dujourdy, PhD Thesis, University of Grenoble, France, 1996; nonlinear fitting of Equation 6.2.)

Adsorbed polymer Q (g/g of filler)

Filler weight fraction = 0.20 2.5

250 Filled Polymers

251

Polymers and White Fillers

essentially concern hydrogen bondings, either at the ends of the polymer chain (if they are hydroxylated) or through any of the –O– of the chain. It follows that the area of an interaction site is perfectly known, by calculating the “area” of one silanol group, around 0.55 nm2 (55.10–20 m2). In comparison with carbon black/elastomer systems, having a clear identification of the fillermatrix interaction sites is a tremendous advantage in developing a theoretical approach of the adsorption process. Indeed, starting from the percolation theory with only two assumptions, Cohen-Addad developed a model for the bound PDMS polymer on silica at saturation.36 The assumptions are (1) that PDMS chains obey Gaussian statistics, (2) that there is hydrogen bonding at each PDMS-silica contact point. The model is written as follows: Qsat =



M0 c Sp ⋅ ⋅ Mn A0 ε 0 N Av

(6.3)

where Qsat is the bound polymer at saturation (g/g of silica), M0 the mass of the monomer unit [75 g/mole for -Si(CH3)2-O-], A0 the area of one interaction site (i.e., 0.55 nm2), c the filler concentration (g of filler/g of polymer), Sp the specific surface of silica, NAv the Avogadro number, Mn the number average molar mass of the polymer and ε0 a factor for the stiffness of the chain ( ≈ 1 in first approximation). Figure 6.9 shows how experimental data34 on various 1 [1 – exp(– 0.065 √Mn × ΦSil)]

Qsat × ΦSil

0.8

0.6

0.4

Ssp (m2/g) 150 50

0.2

0

300

0

100

200 √Mn × ΦSil

300

Figure 6.9 Adsorption of polydimethylsiloxane on silica particles; Cohen–Addad percolation model for maximum adsorbed polymer at saturation (Equation 6.3) vs. experimental data from L. Dujourdy PhD Thesis, University of Grenoble, France, 1996.

252

Filled Polymers

silica/PDMS systems, largely varying in polymer molar masses and/or silica contents, fall on a single curve when calculating the maximum adsorbed polymer at saturation and suitably reducing the scales. Having the interaction site well identified in a filled polymer system, in terms of chemical activity and surface, and a clear picture of the nature of the polymer–filler interaction allow quite convincing theoretical models to be developed. Such a favorable situation is however restricted to a few cases, namely silica/polysiloxane systems. With other systems, either the nature of the polymer–filler interaction is badly known or the size of the interaction site cannot be clearly quantified, or both. In such case however, the successful silica/PDMS case provides some interesting guidelines when assuming that, whatever are the respective chemical natures of the filler and the polymer, at least the physics is the same. As we have seen the author has successfully adapted this model to the case of carbon black/rubber systems, with however the additional difficulty that the surface area of the interaction site A0 cannot be known a priori (see Chapter 5, Section 5.1.5). Owing to the interactions described above, gels are easily obtained when adding silica particles to liquid PDMS, and without further cross-linking, such gels find niche applications such as protective materials for fiber-optic cables and as encapsulants for semiconductor devices. As may be expected, the rheological and mechanical properties of silica-PDMS gels are quite complex, namely with respect to the viscoelastic behavior, but are well documented in the research literature, likely because it is relatively easy to prepared silica filled polysiloxane systems with standard laboratory equipment. Hysteretic effects upon increasing shear rate in both the viscosity and the first normal stress difference, as well as significant overshoot in the stress growth function, were reported by Caruthers and colleagues,37,38 and interpreted in terms of interparticles interactions via entanglements of the polymer adsorbed on the (fumed) silica surface. After an applied shear is step changed, the shear stress relaxes or grows in a complex manner that depends on the shear history. Consequently, PDMS molecular weight and silica volume fraction play an important role in such effects, as well as the surface chemistry when modified in the appropriate manner, but the preparation procedures (mixing technique and time) and the sample age further affects the rheological behavior of such systems.39–42 Precipitated silica develop also strong interactions with PDMS, and bring similar effects, but less than that of fumed silica.43 At high volume concentrations of precipitated silica (0.128 and 0.160), a yield behavior is evident from the storage modulus measurements. It is worth underlining that the key for understanding all those effects is the physical adsorption of PDMS on the silica surface, without chemical bonding, as clearly demonstrated by several authors.44,45 Suitably cross-linked, an unfilled, high molecular weight polydimethylsiloxane exhibits very modest mechanical properties, for instance a tensile strength (TS) in the 0.35 MPa range, largely insufficient for most applications. But the addition of a reinforcing filler, such as a high structure silica, increases

253

Polymers and White Fillers

the same property by a factor of around 40, yielding products with TS in the 13–14 MPa range, and around 600–700% elongation at break. Such reinforcing effects are by large more important than what is currently achieved with reinforcing fillers (e.g., carbon black and silica) in common hydrocarbon elastomers. This unusually high degree of reinforcement observed with silica/ polysiloxane systems has long been attributed to the particular polymer– filler interactions previously described, which persist after exposure to high temperature curing.46 No chemical bonding has been demonstrated between silica and (uncrosslinkable) polysiloxane but, in a cured PDMS-silica system, one cannot exclude a combination of chemical and physical bonds. The former are likely covalent bonding occurring upon vulcanization; the latter are hydrogen bonding and van der Waals forces, indeed favored by a high structure of filler particles. There are of course a variety of finely divided minerals that can be used as fillers for (curable) polysiloxanes, for instance finely grinded quartz, or zinc, titanium and iron oxides, or calcium carbonate, but amorphous silica in the 150–400 m2/g surface area range provides the best reinforcement. In order to have easy-to-process systems, it is however necessary to prevent certain detrimental polymer–filler interaction prior to vulcanization by using suitable plasticizers, for instance low molecular weight polysiloxane oligomers. Figure 6.10  shows typical dynamic properties of vulcanized PDMSsilica systems, as investigated through strain sweep experiments at constant frequency and temperature.47 As can be seen, dynamic strain softening is observed in a qualitatively similar manner to other filled polymers. It follows that models, which successfully fit conventional filled rubbers (e.g., carbon black filled compounds), are expected to well suit such data. This is indeed the case, as shown by the curves in Figure 6.10, drawn by fitting the Kraus–Ulmer equations, i.e.,

G′ ( γ 0 ) = G′inf +

G0′ − G′inf γ  1+  0  γc 

2m



(6.4a)

and



G′′ ( γ 0 ) = Ginf ′′ +

γ  2 (Gm′′ − Ginf ′′ )  0   γc  γ  1+  0  γc 

2m

m

 γ  + Gk′′ exp  − 0   γk 

(6.4b)

The fitting parameters are given in Table 6.3. In agreement with the physical reasoning that supports the model, the critical strain γc decreases with

Elastic modulus G´, MPa

10–3

10–2 10–1 Strain amplitude

100

10+1

0 10–4

2

4

6

8

10

10–3

10–2 10–1 Strain amplitude

100

10+1

Figure 6.10 Dynamic strain softening as observed on PDMS-silica systems; 0.078% vinyl-pendant PDMS (Mn=140,000 g/mol; Mw=390.000 g/mol); 300 m2/g silica; peroxide crosslinked. (Experimental data from L. Dujourdy, PhD Thesis, University of Grenoble, France, 1996.)

0 10–4

2

4

6

8

Filler fraction 0.04 0.08 0.12 0.15 0.18 0.21 Viscous modulus G´´, MPa

PDMS + Silica; 1Hz; 25°C 10

254 Filled Polymers

255

Polymers and White Fillers

Table 6.3

Modeling the Dynamic Strain Softening Effect on PDMS-Silica Systems with the Kraus–Ulmer Equations Φsilica

0.18

0.21

G′ vs. Strain Amplitude (Equation 6.4a) 0.038 0.403 0.327 0.236 0.457 0.698 1.459 3.008 0.3398 0.0740 0.0392 0.0346 0.144 0.671 0.284 0.229 0.9872 0.9969 0.9979 0.9985

0.616 4.423 0.0235 0.308 0.9986

1.010 8.252 0.0195 0.385 0.9990

Modeling G′′ vs. Strain Amplitude (Equation 6.4b) (–0.108) 0.200 (–0.023) 0.451 G″inf 0.106 0.301 1.046 2.523 G″m 0.0382 0.0063 0.0415 0.0302 γc m 0.201 0.100 0.295 0.417 G”k 0.071 0.295 0.624 0.762 0.0022 0.0001 0.0009 0.0010 γk r2 0.8642 0.7777 0.9504 0.9961

1.023 4.224 0.0288 0.476 1.000 0.0011 0.9966

2.780 8.010 0.0300 0.611 1.154 0.0021 0.9990

Modeling G′inf G′0 γc m r2

0.04

0.08

0.12

0.15

Note: Fit parameters; note that negative values for G″inf have no physical meaning, likely reflect experimental inaccuracy and could be replaced by very low positive numbers.

increasing filler fraction and is not much different for G′ and G′′. However the exponent m is typically depending on the silica content and is nearly twice as large for G′′. The additional Ulmer term in Equation 6.4b allows to meet the G′′ vs. γ behavior at low strain, with the main result that the critical viscous modulus G′′k significantly increases with the filler fraction. The above data allows however to demonstrate how really strong are the PDMS-silica interactions. Indeed, using the fit parameters in Table 6.3 and the Kraus-Ulmer equations, one easily calculates low strain (let’s say 0.001) values of G′ and G′′, in order to draw Figure 6.11. Since the dynamic properties of the pure polymer were not given in the source data, G′(Φ = 0) and G′′(Φ = 0) were obtained by second degree extrapolation. The left graph shows that 20% silica increase the elastic and viscous moduli by a factor of respectively, 42 and 95. But because the elastic modulus of the pure polymer is considerably larger than the viscous modulus, filled materials still exhibit a strong viscoelastic character. In the right graph, the normalized complex modulus is plotted vs. the filler fraction. The complex modulus is calculated as G * = G′ 2 + G′′ 2 and normalized with respect to G * of the pure, unfilled material. In other terms, one plots the functional for the silica effect, in order to compare it with the well known Guth and Gold term for filled systems, when only hydrodynamic effects occur, i.e., (1 + 2.5 Φ + 14.1 Φ2). Of course, when significant interactions exist between a

0

1

2

3

4

5

6

7

0

0.05

0.1 0.15 Filler fraction Φ

: G´ : G´´

0.2

Normalized complex modulus G*(Φ)/G*(0) 0

10

20

30

40

50

0

0.05

0.1 0.15 Filler fraction Φ

0.2

Guth & gold

Figure 6.11 PDMS-silica systems; variation of the low strain (γ = 0.001) dynamic properties with filler fraction; the dash curve in the right graph is the Guth and Gold term for mere hydrodynamic effects.

Dynamic moduli G´ and G´´ at 0.001 strain, Pa

PDMS + Silica; 1 Hz; γ = 0.001; 25°C 8

256 Filled Polymers

Polymers and White Fillers

257

polymer matrix and dispersed mineral particles, one does not expect the Guth and Gold model to meet experimental data, but the right graph in Figure 6.11 is an impressive (and simple) demonstration of the exceptional reinforcing effect of high structure silica in polysiloxanes. As we will see later, other (white) fillers are far to give effects of such a magnitude. 6.1.2 Elastomers and Clays (Kaolins) Kaolins have the finest particle-size range of all naturally occurring white fillers. Compared to (silanated) silica, kaolins or clays have relatively mild reinforcing properties but satisfactory however in a number of applications, for which specific effects are obtained owing to their platy structure. Clays in rubber allow very high hardness parts to be fabricated, essentially because of their plate-like particles, in contrast with spherical particles of equivalent dimensions. So-called “hard clay” grades have reinforcing capabilities, i.e., higher modulus, tensile strength and resistance to abrasion. “Soft clays” give lower physical properties and therefore are rather extenders.48 There are essentially four qualities of kaolin, depending on the recovery process and/or the after mining treatment: air-floated, water-washed, delaminated, or calcined. Airfloat hard clay is a general purpose white extender in rubber applications. Other grades are used for specific purposes, e.g., (clear) color enhancement, better mechanical properties and  abrasion resistance for waterwashed and delaminated clays. Calcined and surface-treated clays are used for improved electrical properties in low and medium voltage power cables, with the insulation properties maintained under wet operating conditions owing to the low moisture adsorption of the calcined and coated particles. Rubber extrusion and calendering generally benefit from the processing aid capabilities of calcined clays, so that hoses, profiles, and sheets can be manufactured with a very smooth finish and an excellent dimensional stability. With certain specialty rubbers, e.g., polychloroprene, butyl rubber and chlorinated polyethylene, calcined kaolins give very low levels of mill sticking. Light colored and chemically inert, calcined clays allow to prepare compounds for applications where only high quality materials are permitted, for instance pharmaceutical closure applications. There are many grades of kaolins available worldwide, certain only locally. As illustrated in Table 6.4, it is not easy to compare the various products on the market, essentially because there is no standard description of such materials. Most suppliers give (in their published technical data sheets) a limited number of common information that would allow some comparison. Specific gravity is the same whatever the origin, essentially because the mineral composition is fairly constant, approximately 45–55%wt SiO2, 35–41 Al2O3 and smaller quantities of various oxides, certain obviously affecting the degree of whiteness (e.g., Fe203). In what the mechanical and rheological properties are concerned, the exact mineral composition of kaolin is not a relevant information; it is clearly the particle size and the

VANDERBILT (USA)

SERINA (South Africa)

IMERYS (Worldwide)

Producer

14 n.a.

2.6 2.6 2.62

SpeswhiteTM Ultrafine powder

SupremeTM Powdered

GlomaxTM LL High temperature treated

n.a

2.62 2.62

Dixie Clay® (Hard clay)

Par® Clay (Hard clay)

n.a.

21.25

2.6

Ultrafine Water washed, Screened

18.73

2.6

Filler grade Water washed

9

n.a.

2.62

PoleStarTM 450 Calcined clay

8.5

Specific Surface Area, BET (m2/g)

2.6

Specific Gravity (g/cm3)

PoleStarTM 200R Calcined clay

Brand Name

Selected Commercial Kaolin Grades from Various Suppliers

Table 6.4

40

42

57–63

45–50

53

n.a.

42

60

n.a.

Oil Absorption (g/100 g)

99.3%