Electrokinetic Chromatography: Theory, Instrumentation and Applications

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Electrokinetic Chromatography

Electrokinetic Chromatography: Theory, Instrumentation and Applications Edited by U. Pyell # 2006 John Wiley & Sons, Ltd. ISBN: 0-470-87102-4

Electrokinetic Chromatography Theory, Instrumentation and Applications Edited by UTE PYELL University of Marburg, Germany

Copyright # 2006

John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ, England Telephone (+44) 1243 779777

Email (for orders and customer service enquiries): [email protected] Visit our Home Page on www.wileyeurope.com or www.wiley.com All Rights Reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning or otherwise, except under the terms of the Copyright, Designs and Patents Act 1988 or under the terms of a licence issued by the Copyright Licensing Agency Ltd, 90 Tottenham Court Road, London W1T 4LP, UK, without the permission in writing of the Publisher. Requests to the Publisher should be addressed to the Permissions Department, John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex PO19 8SQ, England, or emailed to [email protected], or faxed to (+44) 1243 770620. Designations used by companies to distinguish their products are often claimed as trademarks. All brand names and product names used in this book are trade names, service marks, trademarks or registered trademarks of their respective owners. The Publisher is not associated with any product or vendor mentioned in this book. This publication is designed to provide accurate and authoritative information in regard to the subject matter covered. It is sold on the understanding that the Publisher is not engaged in rendering professional services. If professional advice or other expert assistance is required, the services of a competent professional should be sought. Other Wiley Editorial Offices John Wiley & Sons Inc., 111 River Street, Hoboken, NJ 07030, USA Jossey-Bass, 989 Market Street, San Francisco, CA 94103-1741, USA Wiley-VCH Verlag GmbH, Boschstr. 12, D-69469 Weinheim, Germany John Wiley & Sons Australia Ltd, 42 McDougall Street, Milton, Queensland 4064, Australia John Wiley & Sons (Asia) Pte Ltd, 2 Clementi Loop # 02-01, Jin Xing Distripark, Singapore 129809 John Wiley & Sons Canada Ltd, 22 Worcester Road, Etobicoke, Ontario, Canada M9W 1L1 Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic books. Library of Congress Cataloging-in-Publication Data Electrokinetic chromatography: theory, instrumentation, and applications/[edited by] Ute Pyell. p. cm. Includes bibliographical references and index. ISBN-13: 978-0-470-87102-7 (cloth : acid-free paper) ISBN-10: 0-470-87102-4 (cloth : acid-free paper) 1. Electrokinetics. 2. Chromatographic analysis. I. Pyell, Ute. QC625.E425 2006 5430 .8–dc22 2005031939 British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN-13 978-0-470-87102-7 (HB) ISBN-10 0-470-87102-4 (HB) Typeset in 10/12 pt Times by Thomson Press (India) Limited, New Delhi, India Printed and bound in Great Britain by Antony Rowe Ltd, Chippenham, Wiltshire This book is printed on acid-free paper responsibly manufactured from sustainable forestry in which at least two trees are planted for each one used for paper production.

Contents

List of Contributors

vii

Preface

xi

PART I: SEPARATION PRINCIPLES

1

1

Theory of Electrokinetic Chromatography Ute Pyell

3

2

Determination of Critical Micelle Concentrations by Capillary Electrokinetic Techniques Thomas Le Saux, Anne Varenne and Pierre Gareil

33

Selectivity Characterization of Pseudostationary Phases Using the Solvation Parameter Model Colin F. Poole

55

General Aspects of Resolution Optimization with Micellar Pseudostationary Phases Li Jia and Shigeru Terabe

79

3

4

5

Optimization of the Separation Conditions in Electrokinetic Chromatography: Experimental Designs, Modelling and Validation Olga Jimeńez and Maria Luisa Marina

95

6

Microemulsion Electrokinetic Chromatography Alex Marsh, Kevin Altria and Brian Clark

115

7

Polymeric Pseudostationary Phases and Dendrimers Christopher P. Palmer

137

8

Pseudostationary Ion-exchange Phases Philip J. Zakaria and Paul R. Haddad

153

9

Principles of Enantiomer Separations in Electrokinetic Chromatography Bezhan Chankvetadze

179

vi

CONTENTS

10 On-line Sample Enrichment in Electrokinetic Chromatography Joselito P. Quirino

207

PART II: INSTRUMENTATION

233

11 General Aspects of Instrumentation Jan Fischer and Pavel Jandera

235

12 Laser-induced Fluorescence Detection: A Summary Christophe Bayle, Ve´ re´ na Poinsot, Clara Fournier-Noe¨ l and Franç ois Couderc

263

13 Amperometric Detection Frank-Michael Matysik

281

14 Photothermal Detection Werner Faubel, Stefan Heissler and Ute Pyell

289

15 Coupling of Electrokinetic Chromatography to Mass Spectrometry Roelof Mol, Gerhardus J. de Jong and Govert W. Somsen

307

16 Electrokinetic Chromatography on Microfluidic Devices ´ mar Gu´ stafsson and Jo¨ rg P. Kutter O

337

PART III: APPLICATIONS

351

17 Electromigration Separation Techniques in Pharmaceutical Analysis Jean-Luc Veuthey, Laurent Geiser and Serge Rudaz

353

18 Analysis of Body Fluids by Electrokinetic Chromatographic Techniques Ll. Puignou, R. Busquets and M.T. Galceran

373

19 Application of Electrokinetic Chromatography to Food and Beverages Mary Boyce

423

20 Application of Enantioselective Electrokinetic Chromatography Bezhan Chankvetadze

459

21 Environmental Analysis Ana Carolina O. Costa, Gustavo A. Micke, Elisabete A. Pereira, Clo´ vis L. Silva and Marina F.M. Tavares

475

Index

529

List of Contributors

Kevin Altria, GlaxoSmithKline R&D, Building H89, New Frontiers Science Park South, Harlow, Essex, CM19 5AW, UK Christophe Bayle, ERT 1046, Laboratoire des IMRCP, Universite´ Paul Sabatier, 118 Route de Narbonne, 31062 Toulouse cedex, France Mary Boyce, School of Natural Sciences, Edith Cowan University, Joondalup 6027, Western Australia R. Busquets, Department of Analytical Chemistry, Faculty of Chemistry, University of Barcelona, Martı´ i Franque`s 1 – 11, 08028 Barcelona, Spain Bezhan Chankvetadze, Molecular Recognition and Separation Science Laboratory, School of Chemistry, Tbilisi State University, Chavchavadze Ave 1, 380028 Tbilisi, Georgia Brian Clark, School of Pharmacy, Bradford University, Bradford, UK Ana Carolina O. Costa, Institute of Chemistry, University of Sao Paulo, Av. Prof. Lineu Prestes 748, 05508-900 Sao Paulo, Brazil François Couderc, ERT 1046, Laboratoire des IMRCP, Universite´ Paul Sabatier, 118 Route de Narbonne, 31062 Toulouse cedex, France Werner Faubel, Research Centre Karlsruhe, Institute of Technical Chemistry, Water Technology and Geotechnology Division, Postfach 3640, 76021 Karlsruhe, Germany Jan Fischer, University of Pardubice, Faculty of Chemical Technology, Department of Analytical Chemistry, Nam. Cs. Legii 565, 532 10 Pardubice, Czech Republic Clara Fournier-Noe¨l, ERT 1046, Laboratoire des IMRCP, Universite´ Paul Sabatier, 118 Route de Narbonne, 31062 Toulouse cedex, France M.T. Galceran, Department of Analytical Chemistry, Faculty of Chemistry, University of Barcelona, Martı´ i Franque`s l1 – 11, 08028 Barcelona, Spain

viii

LIST OF CONTRIBUTORS

Pierre Gareil, Laboratory of Electrochemistry and Analytical Chemistry, Ecole Supe´ rieure de Chemie de Paris, UMR CNRS 7575, 11 rue Pierre et Marie Curie, 75231 Paris cedex 05, France Laurent Geiser, Laboratory of Pharmaceutical Analytical Chemistry, School of Pharmacy, University of Geneva, 20 Bd d’Yvoy, 1211 Geneva 4, Switzerland ´ mar Gu´ stafsson, MIC, Department of Micro and Nanotechnology, Technical UniO versity of Denmark, 2800 Lyngby, Denmark Paul R. Haddad, Australian Centre for Research on Separation Science, School of Chemistry, University of Tasmania, Private Bag 75, Hobart 7001, Australia Stefan Heissler, Research Centre Karlsruhe, Institute of Technical Chemistry, Water Technology and Geotechnology Division, Postfach 3640, 76021 Karlsruhe, Germany Pavel Jandera, University of Pardubice, Faculty of Chemical Technology, Department of Analytical Chemistry, Nam. Cs. Legii 565, 532 10 Pardubice, Czech Republic Li Jia, Graduate School of Material Science, University of Hyogo, Kamigori, Hyogo, 678-1297 Japan Olga Jime´ nez, Department of Analytical Chemistry, Faculty of Chemistry, University of Alcala´ , 28871 Alcala´ de Henares, Madrid, Spain Gerhardus J. de Jong, Department of Biomedical Analysis, Utrecht University, P O Box 80082, 3508 TB Utrecht, The Netherlands Jo¨ rg P. Kutter, MIC, Department of Micro and Nanotechnology, Technical University of Denmark, 2800 Lyngby, Denmark Maria Luisa Marina, Department of Analytical Chemistry, Faculty of Chemistry, University of Alcala´ , 28871 Alcala´ de Henares, Madrid, Spain Alex Marsh, GlaxoSmithKline R&D, Building H89, New Frontiers Science Park South, Harlow, Essex, CM19 5AW, UK Frank-Michael Matysik, University of Leipzig, Institute for Analytical Chemistry, Linne´ strasse 3, 04103 Leipzig, Germany Gustavo A. Micke, Institute of Chemistry, University of Sao Paulo, Av. Prof. Lineu Prestes 748, 05508-900 Sao Paulo, Brazil Roelof Mol, Department of Biomedical Analysis, Utrecht University, P O Box 80082, 3508 TB Utrecht, The Netherlands Christopher P. Palmer, Department of Chemistry, University of Montana, Missoula, MT 59812, USA

LIST OF CONTRIBUTORS

ix

Elisabete A. Pereira, Institute of Chemistry, University of Sao Paulo, Av. Prof. Lineu Prestes 748, 05508-900 Sao Paulo, Brazil Ve´ re´ na Poinsot, ERT 1046, Laboratoire des IMRCP, Universite´ Paul Sabatier, 118 Route de Narbonne, 31062 Toulose cedex, France Colin F. Poole, Department of Chemistry, Wayne State University, Detroit, MI 48202, USA Ll. Puignou, Department of Analytical Chemistry, Faculty of Chemistry, University of Barcelona, Martı´ i Franque`s 1 – 11, 08028 Barcelona, Spain Ute Pyell, University of Marburg, Department of Chemistry, Hans-Meerwein-Strasse, D35032 Marburg, Germany Joselito P. Quirino, Biologies Analytical Chemistry Department, Scios Inc., 6500 Paseo Padre Parkway, Fremont, CA 94555, USA Serge Rudaz, Laboratory of Pharmaceutical Analytical Chemistry, School of Pharmacy, University of Geneva, 20 Bd d’Yvoy, 1211 Geneva 4, Switzerland Thomas Le Saux, Laboratory of Electrochemistry and Analytical Chemistry, Ecole Supe´ rieure de Chemie de Paris, UMR CNRS 7575, 11 rue Pierre et Marie Curie, 75231 Paris cedex 05, France Clo´ vis L. Silva, Institute of Chemistry, University of Sao Paulo, Av. Prof. Lineu Prestes 748, 05508-900 Sao Paulo, Brazil Govert W. Somsen, Department of Biomedical Analysis, Utrecht University, P O Box 80082, 3508 TB Utrecht, The Netherlands Marina F.M. Tavares, Institute of Chemistry, University of Sao Paulo, Av. Prof. Lineu Prestes 748, 05508-900 Sao Paulo, Brazil Shigeru Terabe, Graduate School of Material Science, University of Hyogo, Kamigori, Hyogo, 678-1297 Japan Anne Varenne, Laboratory of Electrochemistry and Analytical Chemistry, Ecole Supe´ rieure de Chemie de Paris, UMR CNRS 7575, 11 rue Pierre et Marie Curie, 75231 Paris cedex 05, France Jean-Luc Veuthey, Laboratory of Pharmaceutical Analytical Chemistry, School of Pharmacy, University of Geneva, 20 Bd d’Yvoy, 1211 Geneva 4, Switzerland Philip J. Zakaria, Australian Centre for Research on Separation Science, School of Chemistry, University of Tasmania, Private Bag 75, Hobart 7001, Australia

Preface

In their pioneering papers in 1984 and 1985 Terabe et al. [1,2] discovered that separations based on electrokinetic phenomena (electrophoresis and electroosmosis) can be described as chromatographic processes provided that an additive (also called separation carrier or pseudostationary phase) having a velocity different from that of the analytes is present in the separation electrolyte, and this is able to interact with the analytes to be separated. In the first papers on this topic this additive was a micelle-forming ionic surfactant at a concentration above the critical micelle concentration. However, it was also realized very early by Terabe [3] that the presence of micelles is not a prerequisite of electrokinetic chromatography (EKC). Since the presentation of the general separation carrier concept many variants of EKC have been developed that employ ‘polymeric micelles’, microdroplets, other types of colloidal phases, dissolved linear polymers and dendrimers or oligomeric units as separation carriers. In the last two decades EKC has been mainly regarded as a special form of capillary electrophoresis (CE), which has matured into a powerful analytical separation technique that brings speed, reproducibility and automation to the labour intensive methods of classical electrophoresis. However, the IUPAC recommendations concerning the terminology for analytical capillary electromigration techniques published in 2004 [4] clearly regard EKC and CE (also known as capillary zone electrophoresis, CZE) as two equal members of the large family of capillary electromigration techniques. Of course, regarding the unique position of EKC as an interface between electrophoresis and chromatography there inherently remain fuzzy borders between EKC and CE. This book is designed to be a guide to the large, rapidly growing and diverse field of EKC for a broad audience: those new to EKC, those more experienced, those interested in method development including instrumental developments, and those involved with applications research in various fields. The book aims to bring together a thorough theoretical description of methodological aspects, an overview of the current status of the various forms of EKC, and current and emerging applications, as well as looking forward to future developments. This book should be of interest for all those who need a highefficiency separation technique with easily adaptable selectivity and having the additional features of low sample volume requirements, short run times and high versatility. The task of compiling this book required the cooperation of internationally recognized experts with special competence in their respective fields. The volume is composed of 21 chapters organized into three major parts: I Separation Principles, II Instrumentation, and III Applications. Part I includes an introduction to the terminology used to describe the separation process in EKC (Chapter 1), a review of electrokinetic methods to investigate

xii

PREFACE

the micelle-formation process (Chapter 2), an introduction to the fundamentals of the solvation parameter model for the (selectivity) characterization of separation carriers (Chapter 3), a general guide to method development and resolution optimization with micellar pseudostationary phases (Chapter 4), an introduction to concepts for computerbased rapid method optimization (Chapter 5), and reviews of various forms of EKC including microemulsion electrokinetic chromatography (MEEKC), EKC with polymeric pseudostationary phases and dendrimers, EKC with pseudostationary ion-exchange phases and enantioselective EKC (Chapters 6–9). The part is completed by a detailed discussion on techniques employed for on-line sample enrichment in combination with EKC (Chapter 10). In the Part II general aspects of instrumentation are treated including the use of coated capillaries (Chapter 11). This part also presents reviews of different detection methods (laser-induced fluorescence detection, amperometric detection, photothermal detection and mass spectrometric detection) having high potential as sensitive and/or selective detection techniques for EKC (Chapters 12–15). The part is completed by a review of the implementation of EKC on microfluidic devices (Chapter 16). The final part is concerned with applications of EKC in the fields of pharmaceutical analysis, the analysis of body fluids, food analysis, chiral analysis and environmental analysis (Chapters 17–21). With this structure the book intends to illuminate many facets of this relatively young member in the family of separation methods, bringing together expert knowledge from various directions that will not only help the novice to estimate how EKC might help in solving analytical tasks, but will also assist the more experienced user in broadening and deepening their knowledge of this technique, which has already found its way into routine laboratories. I would like to thank all of the contributors and further scientists for their support and cooperation. My personal hope is that bringing together a comprehensive review of the state of the art of this fascinating technique will become a factor in its further dissemination in various fields of application. Ute Pyell

References [1] S. Terabe, K. Otsuka, K. Ichikawa and A. Tsuchiya. Electrokinetic separations with micellar solutions and open-tubular capillaries, Anal. Chem., 56, 111–113 (1984). [2] S. Terabe, K. Otsuka and T. Ando. Electrokinetic chromatography with micellar solution and open-tubular capillary, Anal. Chem., 57, 834–841 (1985). [3] S. Terabe. Electrokinetic chromatography: an interface between electrophoresis and chromatography, Trends Anal. Chem., 8, 129–134 (1989). ˚ . Jo¨ nsson and R.M. Smith. Terminology for analytical capillary electro[4] M.L. Riekkola, J.A migration techniques, Pure Appl. Chem., 76, 443–451 (2004).

Part I Separation Principles


1 Theory of Electrokinetic Chromatography Ute Pyell

1.1 Introduction Electrokinetic chromatography (EKC) is a term that was coined by Terabe and coworkers in 1985 [1,2]. EKC belongs to a family of electromigration separation techniques that employ electrokinetic phenomena (electrophoresis and electroosmosis) for the separation of constituents in a sample. EKC invariably also involves chemical equilibria, e.g. distribution, ion exchange and/or complex formation. According to Terabe and coworkers [1,2] EKC is defined as a capillary electromigration separation technique employing a separation carrier. The separation carrier, also called pseudostationary phase, is a unity (e.g. a microdroplet, a micelle, a dendrimer, or a dissolved polymer) that interacts with the solutes to be separated while its migration velocity is, in general, virtually unaffected by this interaction. The property of the migration velocity of the separation carrier being virtually unaffected by the interaction with dissolved solutes will be taken here to define the difference between a pseudostationary phase and a simple complex-forming agent, which is used in capillary electrophoresis to modify the effective electrophoretic mobility of the solutes to be separated. If the solutes to be separated do not posess an effective electrophoretic mobility without the presence of the separation carrier, the separation carrier must have an electrophoretic mobility. According to the IUPAC recommendations [3], EKC is a separation technique ‘based on a combination of electrophoresis and interactions of the analytes with additives (e.g. surfactants), which form a dispersed phase moving at a different velocity [...than the analytes (editorial note)]. In order to achieve separation either the analytes or this


4

ELECTROKINETIC CHROMATOGRAPHY

secondary phase should be charged’. Micellar EKC (MEKC) is ‘a special case of EKC, in which the secondary phase is a micellar dispersed phase in the capillary’ and microemulsion EKC (MEEKC) ‘is a special case of EKC, where a microemulsion is employed as the dispersed phase.’ In chromatography the observed velocity of a solute zone is the weighted mean of two velocities (velocity of the mobile phase and ‘velocity’ of the stationary phase) resulting from the partitioning of the solute between these two phases. In EKC, as defined above, a noncharged solute will migrate either with the velocity of the electroosmotic flow or with the velocity of the separation carrier. Consequently, the separation of neutral solutes differing in their partitioning coefficients (between the separation carrier and the surrounding phase) is possible and the separation process in EKC can be described in chromatographic terms. In fact, conventional chromatography can be regarded as a special case of EKC, where the observed velocity of the separation carrier is zero. In their first papers on EKC, Terabe and coworkers [1,4] had already emphasized the chromatographic nature of the underlying separation process (re-)defining parameters known from chromatographic theory. Their treatment is the basis of further considerations on rational resolution optimization [5], method development [6] or experimental determination of physicochemical parameters from EKC data [7,8]. One of the peculiarities of EKC is the nonexistence of a stationary phase, hence the solute zone is also transported (in the direction of the detector or in the opposite direction) when incorporated into the pseudostationary phase. Another peculiarity is the possibility of combining electrophoretic and chromatographic phenomena. The instrumentation used in EKC is identical to that employed in capillary electrophoresis (CE) (see Part II ‘Instrumentation’). Separation takes place in a (fused silica) capillary with an inner diameter less than 100 mm and a length mostly varying between 20 and 100 cm. The capillary is filled with the separation electrolyte containing the separation carrier and is immersed at both ends in vessels filled with the same electrolyte. The sample is injected directly into the first segment of the capillary. A high voltage (up to 35 kV) is applied between two electrodes (incorporated into the vessels) producing a very high field strength within the capillary. The migration of analyte zones during the separation process is then caused by electrokinetic effects. In order to avoid instrumental band broadening, detection is mainly done over a short segment of the capillary (e.g. photometric or fluorimetric detection). The resulting trace, detector signal versus time, can be called an electropherogram or chromatogram, which reflects the position of EKC as being between electrophoresis and chromatography. In this chapter chromatographic and electrophoretic terms that are needed to describe and to optimize the separation process will be introduced.

1.2 Electrokinetic Phenomena Two electrokinetic phenomena are of interest in EKC: electrophoresis and electroosmosis. Electrophoresis is the migration of a charged unity (e.g. an ion), surrounded by a medium, due to the presence of an electric field. The charged unity will experience acceleration due to electrostatic forces and friction due to the surrounding medium.

THEORY OF ELECTROKINETIC CHROMATOGRAPHY

5

Under steady-state conditions the two opposite forces balance each other. A final electrophoretic velocity vep is reached which remains constant at constant electric field strength E. vep ¼

eE ¼ mep E 6pZ

ð1:1Þ

where e is the electric permittivity of the surrounding medium, is the electrokinetic potential (zeta potential) at the surface of the charged unity, Z is the viscosity of the surrounding medium, and mep is the electrophoretic mobility of the charged unit in the specific medium. (In a capillary filled with a homogeneous buffer, E is given by voltage U divided by the total length LT of the capillary.) In capillary electrophoresis (CE) solutes can be separated into zones if they differ sufficiently in their effective electrophoretic mobilities meff. In the case of fast equilibria (e.g. protonation equilibria, complexation equilibria) being involved, the efficient electrophoretic mobility is the weighted mean (respecting the degree of dissociation/ protonation or complexation) of the electrophoretic mobilities of all solute species being present in equilibrium. Hence fast equilibria are exploited in CE for resolution optimization, e.g. via the adjustment of the pH (separation of solutes differing in their degree of dissociation/protonation) or the addition of a complex forming agent to the separation buffer (separation of solutes differing in their degree of complexation). The second electrokinetic phenomenon that is important in EKC is electroosmosis. Regarding the typical instrumentation used for EKC, electroosmosis is the bulk flow of liquid inside the capillary at constant velocity due to the effect of the electric field on the counterion layer adjacent to the charged capillary wall. In bare fused silica capillaries the surface is negatively charged under most pH conditions. There will be an excess of positive counterions in the zone forming the boundary layer. This zone of surplus charge adjacent to the capillary wall will be accelerated in the electric field and will also experience friction by the medium next to this layer. In consequence, a steady-state constant velocity, the electroosmotic velocity veo, is reached in the liquid outside the electrical double layer (Helmholtz Smoluchowski equation) [9]. veo ¼

eE ¼ meo E 4pZ

ð1:2Þ

where is the electrokinetic potential (zeta potential) at the surface of the charged wall and meo is the electroosmotic mobility. Equation (1.2) is only valid if the capillary inner diameter is large compared with the thickness of the electric double layer. However, this restriction is fulfilled in practice. It is important to note that veo is independent of the capillary inner diameter and (outside the electric double layer) the velocity of a liquid segment is not a function of the radial position (in contrast to pressure-induced laminar flow). Consequently, neither electrophoresis nor electroosmosis contribute to zone broadening in EKC. The observed (apparent) velocity vs of a solute zone corresponds to the sum of the effective electrophoretic velocity vep of a solute and the electroosmotic velocity veo (vs ¼ vep þ veo ).

6


1.3 The Separation Carrier It is the application of a separation carrier that transforms capillary electrophoresis (electrokinetic separation in a homogeneous electric field [10]) into EKC. The term ‘separation carrier’ was coined by Terabe [2,11] generalizing the concept of micellar electrokinetic chromatography (MEKC) [1,3], in which a micellar pseudophase is employed. The term pseudostationary phase, which is more often used in the literature [12], has an identical meaning. The separation carrier is a unit that is added to (or dissolved/dispersed in) the separation electrolyte. In general (see Section 1.1) the separation carrier has an effective electrophoretic mobility and is able to interact with the solutes of interest. In Figure 1.1 the separation mechanism in EKC for a neutral solute and a micelle forming anionic surfactant as separation carrier is depicted. In chromatography, solutes are separated in a system consisting of a stationary and a mobile phase. The velocity vs of a solute zone in the chromatographic bed corresponds to: tmob 1 vmob vmob ¼ tmob þ tstat kþ1

vs ¼

ð1:3Þ

where tmob is the residence time in the mobile phase, tstat is the residence time in the stationary phase, and k is the retention factor (tstat/tmob). In EKC the separation carrier replaces the stationary phase. However, the separation carrier is not immobilized, and hence can have an observed velocity different from zero. Consequently, the observed velocity of a solute zone (neutral solute) is the weighted mean of the velocity of the mobile phase and of the observed velocity of the separation carrier: vs ¼

tmob trsc 1 k vmob þ vsc vmob þ vsc ¼ tmob þ trsc tmob þ trsc kþ1 kþ1

ð1:4Þ

where trsc is the residence time associated with the separation carrier, vsc is the observed velocity of the separation carrier (vsc ¼ vepsc veo), and vepsc is the electrophoretic velocity of the separation carrier.

– – – – – – – – – – – – – – + + + + + + + + + + + + + + -

-

S

-

+

-

-

-

-

-

-

-

S

–

-

-

-

-

+ + + + + + + + + + + + + + – – – – – – – – – – – – – – Figure 1.1 Scheme illustrating the separation mechanism in micellar EKC (anionic surfactant, normal elution mode)


7

Table 1.1 Modes in EKC Mode

Separation carrier

Micellar EKC (MEKC)

Micellar pseudophase: anionic, cationic, or nonionic surfactant (or mixture of nonionic surfactant with ionic surfactant) in a concentration above the CMC Microdroplets present in oil-in-water or water-in-oil microemulsions Polymerized micelles or amphiphilic (charged) linear copolymers or cocondensates Charged dendrimers Soluble linear polymers with ion-exchange sites or other moieties with ion-exchange sites (interaction analyte/separation carrier via electrostatic forces) Micellar pseudophase plus dissolved complex ligand or metal complex

Microemulsion EKC (MEEKC) Polymeric EKC Dendrimeric EKC Ion-exchange EKC (IE-EKC)

Secondary-equilibrium modified MEKC, e.g. cyclodextrin-modified MEKC (CD-MEKC) or ligandexchange MEKC (LE-MEKC)

Here the retention factor k is redefined to be the ratio trsc/tmob. Equation (1.4) shows why EKC is considered to be a chromatographic process if the observed velocity vsc of the separation carrier is vitually unaffected by the interaction with the solute. When associated with the separation carrier the solute is transported with the velocity of the free separation carrier. EKC was introduced first in 1984 by Terabe and coworkers [1,2,4], who employed charged micelles formed by anionic or cationic surfactants as separation carriers. In 1991 Watarai [13] introduced microemulsion EKC (MEEKC) employing charged microdroplets as the separation carrier. Later, polymeric micelles, charged dissolved (amphiphilic) polymers and charged dendrimers were used as separation carriers in EKC [14,15]. Table 1.1 gives an overview of developed modes in EKC. Generally, all modes of interaction of the solute with the (pseudo)stationary phase known in chromatography should also be applicable in EKC: hydrophobic interaction, Van-der-Waals interaction, electrostatic interaction, coordinative interaction, etc. In contrast to EKC, a capillary electromigration separation technique employing a true stationary phase is called capillary electrochromatography (CEC) [16]. According to the IUPAC recommendations [3] CEC is ‘a special case of capillary liquid chromatography, where the movement of the mobile phase through a capillary, filled, packed or coated with a stationary phase, is achieved by electroosmotic flow’. EKC was first developed to make it possible to separate noncharged compounds by using an electromigration separation technique without the participation of a stationary phase. Figure 1.2 shows the separation of positional isomers of neutral nitrotoluenes by employing micelles of the anionic surfactant sodium dodecylsulfate (SDS) as the separation carrier. However, EKC also proved to be a versatile tool for mixtures of charged and uncharged compounds as well as for charged compounds with similar effective electrophoretic mobilities. As EKC is invariably performed in a chamber of high electric field strength, electrophoresis will contribute to the separation if the solutes are permanently or partially charged (weak electrolytes). Consequently, measures taken

8

ELECTROKINETIC CHROMATOGRAPHY E

2

7

0.006

5

0.004 4

6

1 0.002 3

8 9

t0

0.000 3

4

5

6

7

8

t/min

Figure 1.2 Separation of neutral nitrotoluenes by micellar EKC. Electrolyte: c(SDS) ¼ 55 mmol L1, c(urea) ¼ 1.8 mol L1; c(Na2B4O7) ¼ 10 mmol L1. Solutes: 1 ¼ 2,4,6,trinitrotoluene; 2 ¼ 2,4-dinitrotoluene; 3 ¼ 2,5-dinitrotoluene; 4 ¼ 2,6-dinitrotoluene; 5 ¼ 3,4-dinitrotoluene; 6 ¼ 2-nitrotoluene; 7 ¼ 2,3-dinitrotoluene; 8 ¼ 4-nitrotoluene; 9 ¼ 3-nitrotoluene; capillary: 75 mm i.d., 50 cm effective length, 56.5 cm total length; voltage: 25 kV; 25 C; pressure injection: 1.5 s; detection: photometric, l ¼ 254 nm. (Reprinted from U. Pyell, U. Bu¨tehorn, J. Chromatogr. A., 716, 81–95 (1995), copyright 1995, with permission from Elsevier)

to modify the effective electrophoretic mobility in CE (e.g. addition of a complex forming agent, variation of pH) can be also applied in EKC to optimize the selectivity of the separation system.

1.4 Separation of Neutral Solutes 1.4.1

Retention Factor

Corresponding to theory in chromatography the retention factor k (older term: capacity factor k0 or ~k0, sometimes referred to as migration factor k0 [17]) in EKC is defined as residence time in the separation carrier devided by residence time in the surrounding liquid phase. If we assume the separation carrier to be a homogeneous (pseudo)phase, the separation process can be understood to be due to distribution between two distinct phases having two different observed mobilities: k ¼ jP ¼

Vsc P Vmob

ð1:5Þ


9

(j ¼ phase ratio, Vsc ¼ volume of separation carrier, Vmob ¼ volume of surrounding (mobile) phase, P ¼ partition coefficient). If the molar (or mass) concentration and the partial molar (or specific) volume of the separation carrier are known, the distribution coefficient can be calculated from the retention factor [1]. This makes EKC a valuable tool for the determination of liquid–liquid partition coefficients [18]. Replacing the velocities in Equation (1.4) with the respective distance-over-time and rearranging results in Equation (1.6) [1,4]: ts t0 ð1:6Þ k ¼ t0 ð1 ts =tsc Þ (t0 ¼ migration time of the front of the surrounding (mobile) phase, ts ¼ migration time of the solute zone, tsc ¼ migration time of the front of the separation carrier). It should be noted that micelles (molecular aggregates of surfactants), which are mainly used as the separation carrier, have too small an aggregation number to be regarded as a phase in the usual sense and, on the other hand, also contain too many surfactant molecules to be considered as a chemical species [19]. In contrast to bulk phases, whose properties are invariant with position, the properties of small aggregates are expected to vary with distance from the interface (spatial heterogeneity). However, those solutes that enter the micelle, can diffuse rapidly within the micelle and experience a wide range of microenvironments, so that an averaging effect would prevail. Consequently, micelles are complex solvents and can only be treated in an approximate sense as bulk solvents. In spite of these restrictions, the retention data for a large number of solutes are homogeneous with respect to the construction of solvation parameter models, suggesting a uniform average solvation environment for all solutes [19]. In addition to these considerations, the interaction of the solute with the dispersed separation carrier can also be described by the binding model, where solute–separation carrier ‘binding’ is defined as occurring whenever the solute interacts with the separation carrier unity (e.g. a micelle) [20]. An equilibrium binding constant Kb can be defined for the equilibrium S þ SC Ð [SSC]. On one hand, the binding model is more universal, as it is also possible to describe equilibria where the observed velocity of [SSC] is not identical to the observed velocity of the separation carrier. On the other hand, only oneto-one associates are taken into consideration. In general, the phase model is preferred to the binding model. Equation (1.6) is valid in the case of so-called normal elution mode according to Vindevogel and Sandra [12]. In this elution mode, veo and vsc have identical direction and jveo j > jvsc j. It is important to state that in other elution modes veo and vsc can have opposite directions. Gareil [21] has shown that in the case that the observed velocity of the solute zone being opposite to veo (reversed direction mode according to Vindevogel and Sandra [12]), k has to be determined using Equation (1.7): ts þ t0 k ¼ ð1:7Þ t0 ðts =tsc 1Þ In that case ts and tsc can be determined simultaneously in one run whereas the determination of teo is only possible after the reversal of polarity or the injection of a marker solution at the opposite end of the capillary. Equation (1.4) has to be rewritten,

10


provided that only absolute velocities (v ¼ j~ vj) are given: vs ¼

1 k veo þ vsc kþ1 kþ1

ð1:8Þ

In case of observed velocity of the solute zone being opposite to vsc (restricted elution mode according to Vindevogel and Sandra [12] ) Equation (1.9) and (1.10) are valid [21]. 1 k veo vsc kþ1 kþ1 ts t0 k ¼ t0 ðts =tsc þ 1Þ

vs ¼

ð1:9Þ ð1:10Þ

A scheme of the three elution modes compared here is given in Figure 1.3. Figure 1.4 shows the development of solute zones during the separation process for EKC in the normal elution mode. Generally, the effective electrophoretic mobility of the separation carrier is opposite to the electroosmotic mobility of the mobile phase, because a veo vsc vs (a) Normal elution mode

v eo v sc vs (b) Restricted elution mode

v eo vsc vs (c) Reversed direction mode

Figure 1.3 Elution modes in electrokinetic chromatography


11

t=0

Injected zone

t >0

SC marker

Solute 3

Solute 2

Solute 1

EOF marker

Figure 1.4 Development of solute zones during the chromatographic run, normal elution mode, neutral solutes, P(Solute 1) < P(Solute 2) < P(Solute 3) [see Equation (1.5)]

separation carrier of opposite charge to the surface of the capillary wall (e.g. a cationic surfactant or a cationic polymer in a negatively charged fused-silica capillary) will be adsorbed onto the surface of the capillary wall reversing the direction of the electroosmotic flow. There are two special cases: (i) vsc equals zero, (ii) veo equals zero. The first case corresponds to conventional chromatography, the second also corresponds to conventional chromatography if we rename the phases. With EKC it is possible easily to vary the volume ratio j (volume of separation carrier/ volume of surrounding (mobile) phase) by increasing the concentration of the separation carrier in the separation buffer. Assuming that the volume of the mobile phase is not significantly reduced by addition of the separation carrier, we would expect a linear increase in the retention factor with concentration of separation carrier [refer to Equation (1.5)]. This expectation has been confirmed by many authors [22]. We would also expect a retention factor of zero at a separation carrier concentration of zero. In the case of a micellar separation carrier it has to be taken into account that the concentration of the separation carier is zero at or below the critical micelle concentration (CMC). Consequently, in micellar EKC (if there is no interaction of the solute with the capillary wall and with surfactant monomers) by plotting the retention factor versus the surfactant concentration, straight lines are obtained that pass through the identical x-axis intercept, which corresponds to the CMC (see Figure 1.5). 1.4.2

Secondary Complex Equilibria

If a compound that forms complexes with the solutes to be separated is added to the separation electrolyte containing a separation carrier, then the apparent retention factor will be decreased due to the coupled equilibria. This effect is used in cyclodextrin-modified

12


Figure 1.5 Dependence of the retention factor k for several neutral solutes on the molar concentration of the anionic surfactant SDS in the separation buffer; solutes: & 2-naphthol, toluene, nitrobenzene, ~ phenol, & resorcinol. (Reprinted with permission from M.G. Khaledi, S.C. Smith, J.K. Strasters, Anal. Chem., 63, 1820–1830 (1991), copyright 1991 American Chemical Society)

micellar electrokinetic chromatography for chiral separations and for the separation of hydrophobic compounds [23]. The partitioning coefficient P [see Equation (1.5)] corresponds to the ratio of the concentration of solute in the separation carrier to the concentration of uncomplexed solute in the surrounding phase. The concentration of the uncomplexed solute in the surrounding phase is dependent on the concentration of the complex forming additive and the complex formation equilibrium constant KC. When assuming a 1:1 complex, the degree of complexation b of the solute in the surrounding phase is given by: b ¼

KC cðAÞ 1 þ ½KC cðAÞ

ð1:11Þ

where c(A) is the molar concentration of the free complex forming additive. b remains constant if c(A) remains constant. In general, c(A) can be approximated by the total concentration of the complex forming additive. b can only take values between 0 and 1. It is evident that the situation will become more complicated if several separation carriers or several complex forming additives are used for selectivity optimization. 1.4.3

Resolution

The resolution of two adjacent zones in the normal elution mode is given by [1]: pffiffiffiffi k N a 1 1 t0 =tsc ð1:12Þ Rs ¼ k þ 1 4 a 1 þ ðt0 =tsc Þ k ðRs ¼ resolution, N ¼ plate number, a ¼ selectivity factor, k ¼ mean retention factor ¼ arithmetic mean of the two retention factors for the two solutes investigatedÞ. Comparing Equation (1.12) with the equation for the resolution of two solute zones in conventional chromatography reveals that the dependence of Rs on the mean retention


13

1.0 0.9

t0/tsc = 0

0.8 0.7

f (k)

0.6

0.1

0.5 0.2

0.4 0.3

0.4

0.2

0.6

0.1

0.8

0.0 0

10

20 30 Retention factor

40

50

Figure 1.6 Dependence of f(k) on the retention factor in EKC in the normal elution mode [see Equation (1.13)] for several ratios t0/tsc. The ratio t0/tsc ¼ 0 corresponds to conventional chromatography with an immobilized stationary phase (according to [12])

factor is more complex in EKC and that the time ratio t0/tsc has a major impact on the achievable resolution. In normal elution mode, the time span (window) in which a neutral compound can be eluted is restricted to values between t0 and tsc. Consequently, t0/tsc or its reciprocal value tsc/t0 have mainly been used in the literature to characterize the ratio of the observed velocities of the two ‘phases’ in EKC. One widely accepted term for this time ratio is migration (time) window. Plotting the last two factors of Equation (1.12) [ f ðk), see Equation (1.13)] against k reveals that f ðk) reaches a maximum and that this maximum is smaller than 1 in all instances, with 1 as the limiting value if tsc approaches infinity (see Figure 1.6). f ðkÞ ¼

k 1 t0 =tsc k þ 1 1 þ ðt0 =tsc Þ k

ð1:13Þ

In their pioneering paper on micellar EKC Terabe et al. [1] recognized that the lower resolution obtained in the normal elution mode with identical N, a, and k is a disadvantage of EKC as compared with conventional chromatography that can be, however, compensated for by the large plate numbers achievable under routine conditions in EKC (200 000–300 000). It has to be emphasized that the equation to determine the resolution of two solute zones is dependent on the elution mode [see Equations (1.7) to (1.10)] [21]. In the reversed direction mode, Equation (1.14) is valid. pffiffiffiffi N a 1 1 þ t0 =tsc k ð1:14Þ Rs ¼ k þ 1 4 a ðt0 =tsc Þ k 1

14

ELECTROKINETIC CHROMATOGRAPHY 10

t0/tsc = 0.3

0.5

1

8

f (k)

6

4

2

f (k) = 1 0 0

1

2

3

4

5

6

7

8

9

10

Retention factor

Figure 1.7 Dependence of f(k) on the retention factor in EKC in the restricted elution mode [left side of the graph, see Equation (1.15)] and the reversed migration mode [right side of the graph, see Equation (1.14)] for several ratios t0=tsc. The dashed line indicates f(k) ¼ 1 (according to [21])

In the restricted elution mode, Equation (1.15) is valid. pffiffiffiffi N a1 1 þ t0 =tsc k Rs ¼ k þ 1 4 a 1 ðt0 =tsc Þ k

ð1:15Þ

In these modes there is no restricted time span (window) during which a neutral compound can be eluted and f ðk) can exceed unity. Foley p [5]ffiffiffiffiffiffiffiffiffiffi andffi Gareil [21] have shown that in normal elution mode f ðk) is maximum for k ¼ tsc =t0. However, for the reversed direction mode and for the restricted elution mode f ðk) increases dramatically, when k approaches tsc=t0 (see Figure 1.7) [12,21]. Here, if k ¼ tsc =t0 , then the velocity of the solute zone is zero. Consequently, in these modes very high resolution can be obtained even for very low selectivity, but at the expense of migration time of the solutes to be separated. For example, Bushey and Jorgenson [24] succeeded in separating isotopically substituted compounds (dansylated methylamine and dansylated methyl-d3amine) by micellar EKC with migration times of more than 90 minutes. In 1993 Zhang et al. [25] published a paper describing phenomena in EKC based on conventional chromatography theory. They defined three new parameters. One is the phase velocity ratio Pr , which is identical to tsc=t0. They define a negative time as that where the direction of migration is towards the positive electrode (the anode), and a positive time if the direction of migration is towards the negative electrode (the cathode). The second new parameter is the column availability Aco, which corresponds to the last term in Equation (1.13): Aco ¼

Pr 1 Pr þ k

ð1:16Þ


15

The third parameter is the virtual column length L0 , which corresponds to the actual length of the capillary to the detector multiplied by the column availability Aco. In the case of conventional chromatography, Aco ¼ 1 and the solute zone is only transported by the mobile phase to the detector. Zhang et al. [25] showed that in normal elution mode, Aco < 1, whereas in restricted elution mode and in reversed direction mode Aco can exceed unity. 1.4.4

Peak Capacity

According to Giddings [26], the peak capacity n corresponds to the maximum number of components resolvable in one chromatographic run. It is obvious that for the analysis of a complex sample with a high number of constituents a high peak capacity is mandatory in order to avoid comigration of solutes. In deriving an equation approximating the number of components resolvable in one chromatographic run, Giddings assumed a constant plate number independent of the solute and the retention factor: pffiffiffiffi N t2 ln ð1:17Þ n ¼ 1þ t1 4 t1 is the migration (or elution) time of the first solute zone, while t2 is the migration time of the last solute zone. In normal elution mode in EKC, t1 is identical to t0 and t2 is identical to tsc, because all neutral solutes have to be eluted within this time span. Consequently, the migration window has a direct impact on the peak capacity in normal elution mode. In other elution modes of EKC there is no fundamental restriction of migration time. It is, however, important to note that the requirement for Equation (1.17), constant plate numbers independent of the retention factor, is not fulfilled in practice. Some authors have therefore preferred to use the separation number SN instead of the peak capacity [27,28]. The separation number is defined as the number of component peaks that can be placed between the peaks of two consecutive homologous standards (e.g. the homologous series of n-alkyl phenyl ketones) with z and z þ 1 carbon chain atoms, separated by a resolution of 1.177. Also the separation number is dependent on the migration window. The separation number takes into account the varying band broadening with increasing migration time. Kolb et al. [28] have therefore suggested calculating the overall peak capacity from the sum of separation numbers within a given z range. 1.4.5 Determination of the Velocities of the Mobile Phase and the Separation Carrier Generally, for the determination of the electroosmotic velocity, which is identical to the velocity of the mobile phase, a sample that contains a neutral compound is injected (the marker of the velocity of the mobile phase), which is not retained by the separation carrier or the capillary wall and which has an effective electrophoretic mobility of zero. Several polar substances have been used to this end: acetone, formamide, and thiourea [29]. The marker must be detected by the detector in use. In the case of a UV detector the baseline disturbance caused by a zone of different refractive index to the separation buffer can be used as a signal [30].

16


If a substance (the marker of the velocity of the separation carrier) is available that is exclusively transported by the separation carrier and not transported by the mobile phase (k ! 1) and this substance can be detected by the detector in use, then the velocity of the separation carrier can also be determined with a sample containing a marker. It is important to note that the marker of the velocity of the separation carrier does not have to be a neutral substance, and mainly nonpolar azo dyes (Sudan III, Sudan IV) [1,31], dodecanophenone [32] or polycyclic aromatic hydrocarbons [33] have been employed as marker substances. When using negatively charged micellar phases as separation carriers, Terabe et al. suggested using positively charged compounds with a nonpolar structure unit [34]. One of these substances is timepidium bromide [35]. Another compound employed to this end is quinine hydrochloride [8,36]. However, determinations of the velocity of the separation carrier with a simple marker should be treated with caution. Careful investigations have shown that these data can be misleading, especially if mobile phases are used that contain a considerable volume fraction of an organic solvent [37]. Bushey and Jorgenson [24,38] therefore suggested an iteration procedure to determine the separation carrier migration time. This iteration procedure is now used by many scientists working in the field. For chromatographic separations based on solvophobic interaction the Martin equation holds true: there is a linear relationship between the logarithm of the retention factor and the carbon number of the members of a homologous series. Muijseaar et al. [39] verified that this linear relationship is also valid in EKC with a micellar separation carrier (for the homologous series of n-alkyl benzenes and n-alkyl phenyl ketones as solutes and buffers containing sodium dodecylsulfate, decyltrimethylammonium bromide, or hexadecyltrimethylammonium bromide). According to the iteration procedure suggested by Bushey and Jorgenson, the migration time of the longest chain homologue is taken as approximation of the separation carrier migration time. Then the retention factors of the shorter chain homologues are calculated using this approximated separation carrier migration time. With the retention factors of the shorter chain homologues (plotting logarithm of k versus carbon number) a regression line is calculated. A new value for the retention factor of the longest chain member of the series is obtained by extrapolation of the regression line to the corresponding carbon number. Then a new value for the separation carrier migration time is calculated from the extrapolated value of the retention factor for the longest chain member of the series, and this procedure is continued until the difference between a new value for tsc and the value calculated in the last iteration step is below a threshold value. This general procedure has been used by many groups in estimating the migration time of the separation carrier with different mobile phases and different pseudostationary phases: micelles [40–43], microdroplets [44], dendrimers [45] and polymeric pseudostationary phases [46]. Certainly, the marker method is more convenient than the iterative procedure. Several researchers have shown that in the case of purely aqueous mobile phases, the results for tsc obtained from the migration time of a suitable marker can be equivalent to that obtained by the iterative procedure [30,39]. However, Bailey and Dorsey [47] emphasize that small errors in determining the migration time of the marker can lead to drastic errors in the calculated retention factor. From several potential markers of the velocity of the separation carrier, dodecanophenone has been selected by several authors as the most suitable due to its solubility properties and its high absorbance coefficient [30,47].


17

Methods to regulate the migration window have been reviewed recently [37]. The migration window reflects the velocity ratio of the two ‘phases’ involved. While it is difficult to modify the effective electrophoretic mobility of the pseudostationary phase, the electroosmotic mobility generated using a native fused-silica capillary can easily be modified by changing the pH of the separation electrolyte. For neutral solutes, the pH has no impact on the retention factor. Rasmussen and McNair [48] showed for micellar EKC with SDS that the elution order for n-alkyl parabenes can easily be reversed by decreasing the separation buffer pH from 7.0 to 3.37. This corresponds to a change in the elution mode (normal elution to reversed direction mode). Also Otsuka and Terabe [49] investigated the effect of the pH of the separation buffer on the velocities of the mobile and the micellar phase (SDS as surfactant). The pH range investigated was from 7.0 to 3.0. The electroosmotic velocity decreased dramatically with a decrease in pH below 5.5, while the electrophoretic velocity of the micellar phase was almost constant throughout the pH-range investigated. At a pH of 5.0 the absolute velocity of the micellar phase was identical to the absolute electroosmotic velocity. Another approach to modifying the velocity of the mobile phase is to use coated capillaries. Janini et al. [50,51] showed that in micellar EKC with SDS and polyacrylamide-coated capillaries, hydrophobic solutes can be separated with high efficiency in a short run time. With these capillaries the electroosmotic flow is almost completely suppressed [52], so that in this case the separation carrier takes over the role of the mobile phase and the surrounding medium can be regarded as equivalent to the stationary phase of conventional chromatography. Consequently, here the column availability Aco is 1 and there is no restricted migration window. 1.4.6

Retention Indices

In 1994 Muijselaar et al. [39] presented the application of the retention index concept in EKC. In chromatography, retention indices have been used for the identification of solutes because they are considered to express the retention with the best reproducibility and precision. They can also be used for structure–activity relationships and the characterization of stationary (and mobile) phases. Generally, the retention index I of a solute is calculated by the logarithmic interpolation between two neighbouring members of a homologous series according to: I ¼ 100z þ 100

lg kS lg kz lg kzþ1 lg kz

ð1:18Þ

where kz and kzþ1 are the retention factors of the homologues with z and z þ 1 carbon atoms, respectively, and kS ¼ retention factor of the solute. Regarding the determination of k in EKC (normal elution mode) it follows: ts t0 tz t0 lg lg t ts t tz sc sc I ¼ 100 z þ 100 ð1:19Þ tzþ1 t0 tz t0 lg lg tsc tzþ1 tsc tz where ts is the migration time of solute, tz and tzþ1 are migration times of the homologues with z and z þ 1 carbon atoms respectively, t0 is the migration time of the front of mobile

18


phase, and tsc is the migration time of the front of the separation carrier. Consequently, for the determination of I the migration velocities of the separation carrier and of the surrounding phase also have to be determined exactly. In contrast to the retention factor, the retention index I (a relative quantity) is independent of the phase ratio and consequently, is also independent of the separation carrier concentration, which follows from theory and has been verified experimentally [39]. The dependence of retention indices on temperature was shown to be very small. A significant decrease in relative standard deviations was obtained by comparing retention indices to retention factors [53]. These features make the retention index the ideal parameter for the identification of peaks [54]. Muijselaar et al. [39] and Ahuja and Foley [55] demonstrated for micellar EKC that the series of alkylbenzenes, of n-alkyl phenyl ketone, and of 1-nitroalkanes show a linear relationship between the logarithm of the retention factor and the carbon number of the homologues. Hence, these series can be applied as retention index standards in MEKC. The determination of I for different solutes and different micellar separation carriers indicated that polar and nonpolar compounds are solubilized in different ways. Hence, the shift in I(I) for the same compound and a different separation carrier can serve as a valuable parameter for characterizing the selelectivity in EKC. I values can be applied to the classification of separation carriers in EKC analogously to using the Rorschneider– McReynolds scale in gas chromatography [56]. Ishihama et al. [57] reported, for microemulsion EKC, a high correlation between I and the logarithmic octanol–water distribution coefficient (log POW) for 53 aromatic sample compounds possessing different functionalities. They preferred I to k, because the reproducibility and the repeatability (batch-to-batch and run-to-run) were drastically improved, when using I as a parameter for correlation studies. 1.4.7

Efficiency

Efficiency is a measure of the band broadening occurring during separation. Terminology developed for chromatography has been transferred to capillary electromigration separation methods. The height equivalent to one theoretical plate, (or plate height) H corresponds to the peak variance (in length units) divided by the migrated distance. The plate number N is the migrated distance divided by the plate height. In EKC with standard experimental parameters plate numbers of 200 000 to 300 000 can be obtained under routine conditions. Yu et al. [58] have shown that plate numbers obtained in micellar EKC with neutral analytes having low to medium retention factors can be estimated by a simple model based on longitudinal diffusion and length of the injected sample plug. The efficiency for these neutral analytes was independent of the sufactant (SDS) concentration (15–100 mmol L1). This model has been refined by attributing the instrumental variance not only to the length of the analyte plug but by estimating it from the peaks of the micellar marker (regression method) [59]. In these investigations it was taken into consideration that the overall diffusion coefficient in a medium containing a separation carrier is the weighted average of the analyte diffusion coefficient in the mobile phase and the diffusion coefficient of the analyte-separation carrier adduct [60]. In the past it has been a subject of debate as to whether the efficiency in EKC is also influenced by nonequilibrium effects (separation carrier mass transfer, transchannel mass transfer) or separation carrier (micellar) polydispersity [61–63]. Recent investigations,


19

however, show that lower plate numbers than those that would be expected if only instrumental band broadening and diffusion are responsible mechanisms, can be explained by the radial variation of the effective separation carrier mobility resulting from Joule heat [59,64]. It was experimentally verified that peak asymmetries and efficiency loss found with samples of high analyte concentration (concentration overload) can be explained in terms of nonlinear chromatography [65]. The technique of ‘vacancy injection’ makes it possible to determine the distribution isotherms, which can be described by a Langmuir isotherm [66]. Generally, in capillary electromigration separation techniques, laminar flow due to pressure differences between the two ends of the capillary has to be avoided, as it can dramatically reduce efficiency. In the case of differences in the electroosmotic velocity in different segments of the capillary (e.g. partial filling technique) band broadening can result from intersegmental pressure [67]. A further source of band broadening can be analyte adsorption at the inner capillary wall, which should be suppressed by a suitable composition of the separation electrolyte or dynamic or static coating of the inner capillary wall.

1.5 Separation of Weak Electrolytes 1.5.1

Migration of Acids

The separation mechanism of charged compounds in EKC is based on both chromatographic and electrophoretic principles. In 1985, Otsuka et al. [68] studied the migration behaviour and separation of chlorinated phenols by micellar EKC with SDS as separation carrier. They describe the overall effective electrophoretic velocity of a (partially) ionized solute veps in a micellar medium as the weighted sum of the effective electrophoretic velocity vep of the solute and the electrophoretic velocity of the separation carrier vepsc. veps ¼

1 k vep þ vepsc kþ1 k þ1

ð1:20Þ

The true retention factor k [in contrast to the appararent retention factor kapp calculated according to Equation (1.6)] can only be calculated if the effective electrophoretic velocity vep of the solute zone in the separation electrolyte without separation carrier is known. This quantity is mainly determined by CE experiments. However, it should be noted that several assumptions are made in this case: the influence of the separation carrier on ionic strength, dielectric constant and viscosity are assumed to be negligible and, in the case of micellar or microemulsion EKC interactions of the solute with surfactant monomers, are assumed not to occur [69]. In that case, k can be calculated from: meps mep veps vep ¼ ð1:21Þ k ¼ vepsc veps mepsc meps With this equation, k can be calculated even for a fully ionized solute. Otsuka et al. determined vep for phenolic compounds with a buffer containing 5 mmol L1 SDS, assuming that this concentration is below the CMC. Generally when using this approach, it has to be considered that the CMC of a surfactant in an aqueous separation electrolyte

20


can be substantially lower than that in pure water [70]. The phenomenological approach of Otsuka et al. [68] satisfactorily explains the dependence of the retention factor k on the pH of the separation buffer for the chlorinated phenols investigated. It is important to note that the retention factor for the negatively charged species was measurable and different from zero. If the migration time t0sc of a solute in absence of the separation carrier is known, then the true retention factor k can also be calculated from t0sc, from the migration time ts of the solute in presence of the separation carrier, and from the migration time of the separation carrier tsc [71]: ts t0sc ð1:22Þ k ¼ t0sc ð1 ts =tsc Þ Equation (1.22) is analogous to Equation (1.6). The problem here is the determination of t0sc. If the electroosmotic velocity is not independent of the separation carrier concentration, then t0sc cannot be directly determined and has to be calculated from the effective electrophoretic velocity of the solute vep and the electroosmotic velocity in the presence of the separation carrier [47]. In 1991 Khaledi et al. [72] investigated in detail the migration behaviour of acidic solutes in micellar EKC dependent on the pH and the concentration of an anionic surfactant. Their phenomenological approach confirms the observations made by Otsuka et al. [68]. The retention factor k of an acid is the weighted average of the retention factors of its undissociated (HA) and its dissociated (A) forms: aq kHA þ FAaq kA k ¼ FHA

ð1:23Þ

aq where FHA is the mole fraction of the undissociated acid in the aqueous phase, FAaq is the mole fraction of the dissociated acid in the aqueous phase, kAH is the retention factor of the undissociated acid, and kA is the retention factor of the dissociated acid, aq þ FAaq ¼ 1. FHA It is assumed that secondary equilibria with buffer constituents do not occur. The mole fractions of the undissociated and the dissociated acid in the aqueous phase are dependent on the pH and the acid constant Ka:

cðHþ Þ cðHþ Þ þ Ka Ka FAaq ¼ cðHþ Þ þ Ka kHA þ kA ðKa =cðHþ ÞÞ k ¼ 1 þ ðKa =cðHþ ÞÞ

aq ¼ FHA

ð1:24Þ ð1:25Þ ð1:26Þ

According to Equation (1.26), the dependence of the retention factor for acidic solutes on the pH is a sigmoidal relationship with maximum slope for pH ¼ pKa. This also holds true for the partition coefficient P. In EKC not only the retention factor k but also the observed (apparent) effective mobility m can be taken as parameter to describe the migration behaviour of acidic solutes quantitatively: SC mSC þ FASC mSC þ FAaq maq m ¼ FHA A

ð1:27Þ


21

where F is the molar fraction of the dissociated or undissociated species associated with the separation carrier or in the aqueous phase, mSC is the observed mobility of the separation carrier, and maq A is the observed mobility of the dissociated acid in the aqueous phase, aq sc þ FAsc þ FHA þ FAaq ¼ 1 FHA

If we define the apparent acid constant Ka,app in a medium containing a separation carrier as: Ka;app ¼

ðcSC ðA Þ þ caq ðA ÞÞ caq ðHþ Þ ðcSC ðHAÞ þ caq ðHAÞÞ

ð1:28Þ

it can be shown that the observed overall effective mobility m of a solute in a medium containing a separation carrier can be described as a function of mHA and mA (the apparent mobilities of the two species in the medium containing a separation carrier), the apparent acid constant Ka,app and the molar proton concentration c(H+): m ¼

mHA þ mA ðKa;app =cðHþ ÞÞ 1 þ ðKa;app =cðHþ ÞÞ

ð1:29Þ

with mHA ¼

mA ¼

SC KHA cðSCÞ mSC SC cðSCÞ 1 þ KHA

ð1:30Þ

SC maq A þ KA cðSCÞ mSC 1 þ KASC cðSCÞ

ð1:31Þ

On the basis of these equations, Smith and Khaledi [73] developed a model to predict the migration behaviour of organic acids in micellar EKC employing an anionic surfactant (SDS) in terms of the acid constant Ka, the separation carrier binding constants KASC and SC , the pH and the molar separation carrier concentration. In the case of micelles as KAH separation carriers, KSC is identical to the partition coefficient P multiplied by the molar volume of the micelles. Quang et al. [74] generalized this phenomenological approach, also taking ion pair interactions into consideration. For an acidic solute this type of interaction would be expected for cationic surfactant micelles as separation carriers. In this case ion pair formation of the anionic species with the cationic surfactant monomers (reducing the effective electrophoretic mobility of the solute in the aqueous phase) can take place. In Figure 1.8 the possible interactions of an acidic or a basic solute in an anionic or in a cationic micellar phase are schematically depicted. We then have to take into consideration the ion pair formation equilibrium A þ Smono ! [ASmono] (Smono ¼ surfactant monomer) with the ion pair equilibrium constant KIP. The concentration of Smono corresponds to the critical micelle concentration. The electrophoretic mobility of the ion pair [ASmono] is zero and following molar fractions have to be considered: aq aq SC FHA þ FASC þ FHA þ FAaq þ FASmono ¼ 1

ð1:32Þ

22

ELECTROKINETIC CHROMATOGRAPHY (a)

µeo

HA KHA,sc -

-

+

Ka

-

-

–

KA,sc

-

A– µep

µepsc

(b)

KHA,sc +

+

A– +

+

KA,sc

–

+ A–

µepsc

(c)

+

Ka

+

+

µeo

HA

µeo

KIP µep

B

KB,sc

BH+

-

-

-

-

Kb -

+

-

BH

+

µepsc

(d)

KBH,sc + +

µepsc

µep

µeo

B

+

+

+

–

KIP

KBH,sc

Kb

+ +

–

KBH,sc BH+

µep

Figure 1.8 Interaction of ionizable solutes with micellar separation carriers: (a) acidic solute (AH) with anionic SC; (b) acidic solute (AH) with cationic SC; (c) basic solute (B) with anionic SC; (d) basic solute (B) with cationic SC (according to [74])


23

Table 1.2 Influence of cationic surfactant monomers on electrophoretic mobilities of acidic solutes (electrolyte composition: (a) c(H3BO3) ¼ 10 mmol L1, c(Na2B4O7) ¼ 10 mmol L1, pH ¼ 9.0; (b) c(H3BO3) ¼ 10 mmol L1, c(Na2B4O7) ¼ 10 mmol L1, c(DoTAB) ¼ 5 mmol L1, pH ¼ 9.0. capillary 75 mm i.d., 50 cm effective length, 57 cm total length; voltage 25 kV; temperature 25 C; sample pressure injection: 2 s) Solute 4-Hydroxy-3-methoxybenzyl alcohol 4-Hydroxybenzyl alcohol Ethylvanilline Vanilline 4-Methoxybenzoic acid 4-Hydroxybenzaldehyde Vanillic acid 4-Hydroxybenzoic acid 3,4-Dihydroxybenzoic acid

mep /(103 cm2 V1 s1) CE buffer

mep /(103 cm2 V1 s1) CE buffer þ DoTAB

0.034

0.034

0.036 0.228 0.253 0.265 0.271 0.293 0.311 0.394

0.039 0.223 0.246 0.256 0.269 0.297 0.317 0.393

Where FAaq is the molar fraction of the free dissociated species in the surrounding phase, aq is the molar fraction of the ion-paired dissociated species in the surrounding and FASmono phase. One possibility of studying the presence or absence of ion pair formation of charged solutes with oppositely charged surfactant monomers in the aqueous phase is afforded by capillary electrophoresis experiments with surfactants showing a high CMC. In Table 1.2 effective electrophoretic mobilities of several phenol and benzoic acid derivatives determined by CE in the presence and absence of 5 mmol L1 dodecyltrimethylammonium bromide (DoTAB) are given. The CMC of DoTAB (21–23 C) in these two buffers is 13–14 mmol L1 (determined by conductometric titration [75]). Consequently, in these buffers DoTAB is only present as monomer. The comparison of effective electrophoretic mobilities shows that ion pair formation can be neglected in this case. There is no significant decrease in mep due to the presence of surfactant monomers. It has to be emphasized that with 5 mmol L1 DoTAB there is a reversal of the direction of the electroosmotic flow and consequently a reversal of the migration order. Consequently, DoTAB is also present in form of positively charged hemimicelles formed at the interface liquid–capillary. However, there is no band broadening due to solute–capillary wall (hemimicelle) interactions. It has to be emphasized that the solutes studied here are relatively hydrophilic. Muijselaar et al. [69] verified experimentally that both the mobility model and the retention model describe the migration of monovalent acids in micellar EKC well. However, they observed (hydrophobic) interaction of the (hydrophobic) undissociated form of the acid with surfactant monomers. This interaction is a phenomenon that may have a marked influence on the determination of true retention factors for hydrophobic species. 1.5.2

Migration of Bases

The same concept outlined in the previous section was used by Strasters and Khaledi [76] in 1991 to describe the migration behaviour of cationic solutes in EKC with anionic

24


micellar separation carrier. They took into consideration the acid–base equilibrium, ion pair formation between the conjugated acid of the base and the surfactant monomer, and the distribution equilibria of both the base and its conjugated acid between the aqueous phase and the separation carrier (see Figure 1.8c). In the case of an ion pair formation constant KIP approaching infinity the solute will be present in the aqueous phase either as neutral species or as neutral ion pair. Consequently the effective electrophoretic mobility of this solute vep [refer to Equation (1.20)] in the aqueous medium is zero, and the true retention factor can be calculated from [refer to Equation (1.21)]: k ¼

meps mepsc meps

ð1:33Þ

In the absence of ion pair formation k can be calculated from Equation (1.21). Employing these two equations, Strasters and Khaledi calculated the retention factors for several basic solutes dependent on the concentration of SDS in the separation electrolyte. They obtained linear relationships differing in the x-axis intersection. As the x-axis intersection should correspond to the CMC of SDS, negative values clearly indicate the invalidity of the approach. Their results suggest that ion pair formation must not be neglected, especially for the hydrophobic solutes. On the basis of only five experiments, Quang et al. [74] succeeded in correctly modeling the migration behaviour of 17 aromatic amines separated by micellar EKC with an anionic surfactant (SDS) within a parameter range of c(SDS) ¼ 20–85 mmol L1 and pH ¼ 7.0–12.0. In their approach it was assumed that the protonated base is present in the surrounding aqueous phase only as an ion pair formed with the surfactant monomer. It would be interesting to model the migration behaviour of partly protonated bases or partly dissociated acids employing separation carriers that are not present as surfactant monomers (e.g. polymeric separation carriers) in order to verify the phenomenological approach outlined in the previous sections. Those equations concerning the resolution of charged solutes derived by Corstjens et al. [77] assume that the electrophoretic mobility of a charged solute in the surrounding medium is constant and not influenced by the separation carrier.

1.6 Separation of Ions In 1992 Kaneta et al. [78] studied the migration behaviour of inorganic anions in micellar EKC using a cationic surfactant (cetyltrimethylammonium chloride). They employed the overall effective electrophoretic mobility meps [which is not identical to the observed overall effective mobility m of a solute in a medium containing a separation carrier in Equation (1.29)] as the parameter to describe the migration (m ¼ meps þ meo ). In the presence of a cationic surfactant the electrophoretic mobility of an anion is influenced by interaction with the surfactant monomers (ion pair formation) and by interaction with the positively charged micellar pseudophase (‘distribution’). In fact, in this case the micellar pseudophase might be regarded as an ion-exchange separation carrier.


25

Below the CMC, the effective electrophoretic mobility mep is given by: mep ¼ FAaq mep;ion

ð1:34Þ

where FAaq is the molar fraction of free ion and mep,ion is the electrophoretic mobility of free ion. Regarding that: KIP ¼

cð½ASmono Þ cðAÞ cðSmono Þ

ð1:35Þ

cðAÞ cðAÞ þ cð½ASmono Þ

ð1:36Þ

and FAaq ¼ it follows: 1 cðSmono Þ KIP 1 ¼ þ mep;ion mep mep;ion

ð1:37Þ

Indeed, assuming that c(Smono) is given by the total surfactant concentration and that plotting 1/mep versus c(Smono) results in a straight line, this verifies the theoretical considerations. At the CMC there is a change in the slope, making it possible to determine the CMC and to determine the electrophoretic mobility of a solute at the CMC using a regression method. Above the CMC c(Smono) remains constant, consequently also the electrophoretic mobility mep,CMC of the anion in the surrounding aqueous phase remains constant independent of the total surfactant concentration. If the electrophoretic mobility of the separation carrier mepsc is known, the retention factor is then given by: meps mep;CMC ð1:38Þ k ¼ mepsc meps Therefore, the method of Kaneta et al. [78] makes it possible to determine true retention factors in a micellar medium for charged and partially charged compounds without neglecting the effects of solute surfactant monomer association.

1.7 Application of Neutral Separation Carriers In 1997 Collet and Gareil [79] reported the MEKC separation of long chain saturated and unsaturated free fatty acids in an alkaline medium with neutral micelles formed by polyoxyethylene-23-dodecyl ether (Brij 35). In this case, the two phases (the separation carrier and the surrounding phase) itself have the same velocity; however, this is not the case for the solutes in the two phases. Neutral separation carriers can only be used in EKC, if the solutes to be separated have an effective electrophoretic mobility in the surrounding phase. If the two solutes to be separated have identical effective electrophoretic mobilities in the surrounding phase, then all considerations made in Section 1.4 can be also applied, provided that the parameter t0 (migration time of the front of the surrounding phase) is replaced by the parameter t0sc, which is the migration time of a solute zone in the absence of the separation carrier.

26


1.8 Conclusions As pointed out by Terabe [2] EKC can be regarded as an intermediate between electrophoresis and chromatography. Consequently, the separation process can be described either as a chromatographic or as an electrophoretic process. Both descriptions are valid and fully describe the migration behaviour for neutral solutes or for solutes being present in the mobile phase either in the uncharged form or in the form of an uncharged ion pair. In the case that the solute is also present in a charged form in the mobile phase, both the electrophoretic properties of the solutes and their interaction with the separation carrier have to be taken into consideration.

List of Symbols and Abbreviations Aco c(A) c(H+) CMC E FAaq aq FHA aq FASmono I k k kA kAH ks kz kzþ1 Ka Kc KIP L0 n N P POW Pr Rs t0 t0sc tmob ts tsc trsc

column availability molar concentration of the free complex forming additive molar concentration of protons critical micellar concentration electric field strength mole fraction of the dissociated acid in the aqueous phase mole fraction of the undissociated acid in the aqueous phase molar fraction of the ion-paired dissociated species in the aqueous phase retention index retention factor mean retention factor retention factor of the dissociated acid retention factor of the undissociated acid retention factor of the solute retention factor of the homologue with z carbon atoms retention factor of the homologue with z þ 1 carbon atoms acid constant complex equilibrium constant ion pair equilibrium constant virtual column length peak capacity plate number partition coefficient octanol/water partitioning coefficient phase velocity ratio resolution migration time of the front of the surrounding (mobile) phase migration time of a solute in absence of the separation carrier residence time in the mobile phase migration time of the solute zone migration time of the front of the separation carrier residence time associated with the separation carrier


tstat tz tzþ1 veo vep veps vepsc vmob vs vsc Vmob Vsc z a b e Z j m mAaq meo mep mep,CMC mep,ion meps mepsc

27

residence time in the stationary phase migration time of the homologue with z carbon atoms migration time of the homologue with z+1 carbon atoms electroosmotic velocity (effective) electrophoretic velocity overall effective electrophoretic velocity of a (partially) ionized solute electrophoretic velocity of the separation carrier velocity of the mobile phase observed velocity of a solute zone observed velocity of the separation carrier volume of surrounding (mobile) phase volume of separation carrier number of carbon atoms selectivity factor degree of complexation electric permittivity of the surrounding medium viscosity of the surrounding medium phase ratio observed overall effective mobility of a solute in a medium containing a separation carrier observed mobility of the dissociated acid in the aqueous phase electroosmotic mobility (effective) electrophoretic mobility (effective) electrophoretic mobility of a solute at the CMC of the added surfactant electrophoretic mobility of free ion overall effective electrophoretic mobility of a (partially) ionized solute electrophoretic mobility of the separation carrier electrokinetic potential (zeta potential)

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2 Determination of Critical Micelle Concentrations by Capillary Electrokinetic Techniques Thomas Le Saux, Anne Varenne and Pierre Gareil

2.1 Introduction Surfactants are amphiphilic molecules composed of a hydrophobic hydrocarbonaceous tail comprising at least six–eight carbon atoms, attached to a hydrophilic, more or less bulky, neutral or ionic head group. At low concentration in aqueous solution, surfactant molecules are almost entirely dispersed, although dimers, trimers, etc. can be found [1]. When concentration in solution is over a threshold value, surfactants form aggregates, with the part of solvent-like polarity turned outside, towards the solvent. The first type of aggregate appearing beyond this threshold concentration can often be considered as spherical in shape and is called a micelle [2]. The corresponding threshold is called the critical micelle concentration (CMC). Micellization of surfactants in aqueous media occurs due to the fact that the reduction of the hydrocarbon–water interface is energetically favored. The CMC at which aggregation takes place reflects the fact that the hydrophobic interaction between the hydrocarbonaceous moieties of the surfactant molecules is balanced by hydration and electrostatic repulsive effects of hydrophilic head groups [3]. Thus hydrophobic forces control the formation of micelles, while electrostatic ones limit their maximum size (aggregation number) under determined conditions. CMC is commonly recognized not to be a sharp transition point but a concentration range below which the solution contains negligible amounts of micelles and above which most of the surfactants are found in the


34


form of micelles [4,5]. In practice, CMC is the lowest concentration at which a given experimental method detects associates. CMC depends on the surfactant nature (hydrophobicity of the hydrocarbon chain, net charge on the surfactant, nature of the polar head and counterion) [6], medium composition (pH [7], ionic strength [8], counterion in case of ionic surfactants [9], additives [10,11], hydroorganic solvent composition [12]) and temperature [7]. Surfactants have found widespread application for their solubilizing, homogenizing, cleaning or degreasing properties in many industrial processes (e.g. liquid–liquid and cloud point extractions, membrane separations, biotechnologies, formulations) and areas (petroleum, lubricants, painting, phamaceuticals, health care, etc) [13]. Moreover, they play a key role in the principles of several analytical methods, such as polyacrylamide gel electrophoresis, ion-pair chromatography, micellar normal or reversed phase liquid chromatography, and more recently micellar electrokinetic chromatography. For optimizing all of these applications, the knowledge of CMC values is of prime importance. Several tens of methods have been used for the determination of the CMC of aqueous surfactants systems, among them being electric conductivity [14–17], dielectric constant [16] and surface tension measurements [18–20], electrochemical methods such as potentiometry [21] and cyclic voltametry [22], dye solubilization associated with various modes of spectroscopic monitoring (absorbance [5,14,15,23,24], fluorescence [25,26]), static [27,28] and dynamic light scattering [28–30] and even NMR [31] or speed of sound [10]). Insofar as the value attributed to CMC corresponds to a major variation of the physicochemical property measured, reported CMC values often depend somewhat on the technique employed. The choice of a technique may be governed by its availability, easiness of use, and also by the surfactant type (ionic, nonionic) and its spectroscopic properties. In the last decade, several additional methods based on capillary electrophoretic (CE) techniques have been also proposed for determining CMC values of surfactants. These methods can be sorted into three groups according to their overall approach: the current intensity method [32,33], which is no more than a CE instrumental setup of the aforementioned classical conductivity method; the zonal methods [17,34–36], which are based on the migration speed monitoring of a micelle-interacting marker injected as an analyte in a capillary filled with a surfactant solution, and the frontal methods [37,38], relying on partial electrophoretic separations of monomeric and aggregated surfactant forms to produce minimum perturbation of the monomer–aggregate equilibrium, as in a dialysis process, and subsequent quantitation of the monomeric form. Some of these methods have been recently reviewed by C.-E. Lin [39]. The aim of this chapter is to provide the reader with a brief comprehensive presentation of each methodological approach, with special attention being paid to the most critical experimental conditions and to procedures for data treatment. Afterwards, these methods will be compared to the more conventional ones on the basis of CMC values obtained and on method performance and suitability.

DETERMINATION OF CRITICAL MICELLE CONCENTRATIONS

35

2.2 Current Intensity Method This approach, which was first applied by Tickle et al. [32] and later described in greater detail by Cifuentes et al. [33], simply uses CE instrumentation to set up conductivity measurements. According to Ohm’s law, the current intensity inside a capillary, filled with an ionic surfactant solution at a concentration cS lower than the CMC, is related to applied voltage V by: I¼

p dc2 FðmS þ mX ÞcS V 4L

ð2:1Þ

where F is Faraday’s constant, dc and L, the inner diameter and total length of the capillary, respectively, and mS and mX, the mobilities of the surfactant and counterion. For cS higher than the CMC, Ohm’s law becomes: I¼

p dc2 FðmS þ mX Þ CMC þ ðmX þ mmic Þð1 yÞðcS CMCÞ V 4L

ð2:2Þ

where mmic is the mobility of the micelle and y the rate of counterions condensed to the micelle. Plotting current intensity against surfactant concentrations for a given capillary, voltage and temperature, will result in two straight lines corresponding to the monomeric and micellar states of the surfactant. Equations (2.1) and (2.2) explain why the slope of the second straight line (cS > CMC) is normally lower than that of the first one (cS < CMC) and the difference in slopes of these two parts appears to be related directly to counterion condensation and micelle size (with typical y values in the 0.6–0.8 range). Figure 2.1 shows an example of current–concentration plot obtained experimentally. Similar curves are given in the literature [26,37,40,41]. The abscissa of the break displayed is therefore recognized as the CMC. This value can be obtained from classical least-squares linear regression of the data points or from more sophisticated mathematical treatment using second derivatives [16]. For better precision, experimental points too close to the intersection point should be ignored.

Figure 2.1 Plot of the current intensity inside the capillary as a function of the ionic surfactant concentration present in the filling solution. Fused silica capillary: 75 mm i.d. 47 cm length. Filling solution: SDS at varying concentrations in water. Applied voltage: 25 kV. Temperature: 25 C. (Reprinted with permission from [33], copyright 1997 American Chemical Society)

36


Capillary diameter and length, and voltage to be applied should be chosen in order to obtain adequate current values, preferably, in the 1–100 mA range [33, 41]. Especially, for low conductivity-surfactant solutions, capillary diameter and voltage should be increased and capillary length decreased. Proper control of Joule heating also requires power to be kept dissipated below 2 W/m inside the capillary [33]. As for the classical conductivity method, the current intensity method applies only to anionic [33] and cationic [40] surfactants and its precision depends on the extent of the difference between the slopes in the premicellar and micellar states, which is related in turn to the system studied. In this connection, it allows CMC determinations in pure water but measurements in high ionic strength background electrolytes (BGE) can become problematic. It also has the great advantage of not needing any marker likely to perturb the aggregation equilibrium. Finally, as compared with classical conductimetry, the CE procedure benefits from having easier temperature control and can be operated unattended. It also requires about one hundred times less surfactant solution volume and amount [33]. CMC values for SDS obtained by the current method in various electrolyte and temperature conditions are given in Lin’s review [39], Table 2.1.

2.3 Zonal Methods Zonal electrophoretic methods for CMC determination all rely on the principles of micellar electrokinetic chromatography (MEKC), as formulated by Terabe et al. [34]. This method was devised to extend the scope of CE to the simultaneous separation of neutral and ionic analytes. Briefly, MEKC consists in implementing CE by using a charged micelle-containing BGE, so that neutral analytes are allowed to partition between the hydrophobic core of the micelles and the electrolyte bulk, just like in a reversed-phase chromatographic system. When an electric field is applied, neutral analytes will gain a nonzero electrophoretic mobility proportional to the micelle mobility, and separate from each other according to their affinity for the micelles. Figure 2.2 schematically depicts a typical chromatogram obtained when MEKC is achieved in a (a) Micelle inj. (b)

Solute column

Water

Solute

Water det. Micelle

Time 0

t0

tR

tmc

Figure 2.2 Schematic representation of (a) the zones separated in a capillary and (b) a typical micellar electrokinetic chromatogram. t0 ¼ teo: retention time of a hydrophilic electroosmotic flow marker. tR: retention times of a neutral analyte. tmic: retention time of a micelle-mobility marker. (Reprinted with permission from [34], copyright 1985 American Chemical Society)


37

bare silica capillary with an anionic surfactant such as SDS, and when micelles are dragged to the cathode by electroosmotic flow (normal elution mode). The neutral analytes are detected within a range delimited by the elution time of an electroosmotic flow marker, teo and that of a micelle-mobility marker, tmic. For CMC determination applying MEKC principles, the surfactant to be studied is introduced into the BGE of interest at various successive concentrations encompassing the CMC, and the retention time of an appropriate marker interacting with the surfactant micelles is measured. The marker is most often detected from a spectroscopic property that does not belong to the surfactant. UV-transparent surfactants are therefore the best candidates. Four methodological variants are distinguished, mainly according to the mode of data treatment, namely the retention factor, retention time, mobility and zeta-potential methods. 2.3.1

Retention Factor Method

In MEKC, retention factor k is defined as [34]: k ¼ Kmic

Vmic v ðct CMCÞ ¼ Kmic Vaq 1 v ðct CMCÞ

ð2:3Þ

where Kmic is the analyte partition coefficient between micellar pseudophase and aqueous BGE bulk, Vmic and Vaq the volume fractions of both phases, ct the total surfactant concentration, and v the partial molar volume of the surfactant. For ct values of practical utility, v (ct -CMC) is much smaller than 1 and the retention factor can be approximated to: k ¼ Kmic v ðct CMCÞ

ð2:4Þ

For a neutral analyte, k can be experimentally accessed from measurements of its retention time tR and those of electroosmotic flow and micelle markers, teo and tmic respectively, using [34]: k¼

tR teo teo ð1 tR =tmic Þ

ð2:5Þ

According to Equation (2.4), the plot of experimental k values as a function of the total surfactant concentration will give a straight line with the x-axis intercept corresponding to CMC (see Figure 2.3, from the work by Terabe et al. [34]. Similar results were given elsewhere [42, 43]). For CMC determination, this approach requires simultaneous injection of a properly selected micelle-interacting analyte, of an electroosmotic flow marker that does not interact at all with the micelles, and of a micelle-mobility marker. To be valid, Equations (2.4) and (2.5) assume that the surfactant monomers and micelles do not adsorb to the capillary wall and that the micelle-mobility marker does not change the structure of the micelles. In addition, the micelle-interacting analyte should not interact appreciably with the surfactant monomer and should not perturb the micellization equilibrium. As anticipated by Terabe et al. [34], the retention factor method may not be accurate and reliable due to uncertainties in the measurements of teo and tmic. Nevertheless, this method has been used, in particular, for the determination of the CMC values of SDS in various electrolyte solutions (see [39], Table 2.1).

38


Figure 2.3 Experimental dependence of retention factor k on total SDS concentration for various neutral analytes: resorcinol (2), phenol (3), p-nitroaniline (4), nitrobenzene (5), toluene (6) and 2-naphthol (7). BGE: 0.1 M borate–0.05 M phosphate buffer, pH 7. Temperature: 35 C. The straight lines represent the linear regression performed. (Reprinted with permission from [34], copyright 1985 American Chemical Society)

2.3.2

Retention Time Method

To obviate some of the aforementioned difficulties, Nakamura et al. [36] proposed direct plotting of the retention time of a micelle-interacting analyte in terms of total surfactant concentration. Retention time is related to retention factor by: tR ¼

teo ð1 þ kÞ 1 þ ðteo =tmic Þk

ð2:6Þ

Below the CMC, retention time should be constant and equal to teo. Above the CMC and taking account of Equation (2.4), retention time should increase nonlinearly upon increasing total surfactant concentration ct. Nevertheless, the experimental data were fitted to straight lines near to the CMC value (Figure 2.4) and CMC was determined at the intersection point. This method does not need calculation of electroosmotic flow or micelle mobility, but they normally should remain constant. Its suitability was demonstrated for several anionic, UV-transparent surfactants in the 1–35 mM CMC range, with RSD value less than 4 % (n ¼ 5) for SDS [36]. It is to note that, similarly, Nagamine et al. [44] plotted (tR teo)/teo (improperly called relative mobility) instead of tR, as a function of ct in case of cationic surfactants and determined CMCs from linear regression.


39

Migration time (min)

20

15

10

5 00

10

20

Concentration (mM)

Figure 2.4 Experimental dependence of migration time on total SDS concentration for various analytes: toluene (*), naphthalenemethanol (*), naphthol (~). BGE: 20 mM phosphate buffer, pH 7. Temperature: 40 C. (Reprinted from [36] by permission of The Japan Society for Analytical Chemistry)

2.3.3

Mobility Method

This method was initially devised by Jacquier and Desbe`ne [35] to take into account the solvophobic interactions between an anionic surfactant monomer and a neutral micelle-interacting analyte. More generally, the effective mobility meff of the analyte is given by: meff ¼

Ksolv ct m 1 þ Ksolv ct solv

for ct < CMC

½35; 39; 45; 46

ð2:7Þ

and meff ¼

Ksolv CMC m 1 þ Ksolv CMC þ Kmic ðct CMCÞ=n solv

þ

Kmic ðct CMCÞ=n m 1 þ Ksolv CMC þ Kmic ðct CMCÞ=n mic

for ct > CMC

½45; 46

ð2:8Þ

where n is the aggregation number, Ksolv and Kmic are the 1:1 association constants between the analyte and the surfactant monomer, and between the analyte and the micelle, respectively. msolv and mmic are the mobilities of the analyte–monomer complex and of the micelles, respectively. Figure 2.5 shows the experimental variation of the mobility of some neutral analytes as a function of total surfactant concentration. The flat part on the left of the curve indicates that for these analytes, solvophobic analyte–monomer interactions are negligible. Besides, the first break on the mobility curve is representative of the onset of surfactant aggregation, known as critical aggregation concentration (CAC). Accurate CMC determination can be achieved at the intersection point of the nonlinear fittings of the experimental points apart from the micellization regions using Equations (2.7) and (2.8) [46]. Simplified linear fittings were used as well [35], approximating

40


Figure 2.5 Experimental variation of the effective mobility of pyridine derivatives as a function of total SDS concentration. BGE: 20 mM phosphate buffer, pH 7. Temperature: 25 C. Reprinted from Lin et al., Capillary electrophoresis study on the micellization and critical micelle concentration of sodium dodecyl sulfate. (Influence of solubilized solutes. J. Chromatogr. A., 924, 83–91, copyright 2001, with permission from Elsevier)

Equations (2.7) and (2.8) to: meff ¼ Ksolv ct msolv þ Kmic

ðct CMCÞ mmic n

ð2:9Þ

The larger the difference between Ksolv and Kmic is, the more precise the CMC determination will be [39]. In the special case where Ksolv Kmic, CMC is derived as the surfactant concentration leading to extrapolated zero electrophoretic mobility [6]. The mobility method does not need the measurement of micelle mobility. It does, however, require electroosmotic mobilities for the calculation of effective mobilities. CMC values obtained by this method for SDS in various BGE conditions and for some cationic surfactants are reported in [39], Table 2.1. This method has also proved useful for the CMC determination of some anionic surfactants in formamide [6]. 2.3.4

Zeta Potential Method

For the sake of completeness, it should be mentioned that zeta potential measurements have also been used to study surfactant aggregation [17]. This parameter, which has been mainly considered in the field of colloidal particles [47], can be related to electrophoretic mobility through the modified Smoluchowski equation: ¼

3 Z meff 2 ef ðkaÞ

ð2:10Þ

where Z is the electrolyte viscosity, e the dielectric constant, k the reverse Debye length, a the radius of the particle and f (ka) the corrective Henry function. In spite of their close


41

Figure 2.6 Experimental variation of zeta potential in terms of total dodecyltrimethylammonium bromide concentration for various KBr concentrations: (*) 0 mM; (&) 2 mM; (~) 4 mM; () 6 mM. Temperature: 25 C. (Reprinted from [17], by permission of Wiley-VCH Verlag)

connection to electrophoretic mobility, zeta potentials are usually derived from a distinct experimental electrokinetic implementation, referred to as laser-Doppler microelectrophoresis. Briefly, such a commercially available setup involves the migration of the particles to be studied in a short closed capillary channel of cylindrical or rectangular crosssection under alternating high electric field strength (>100 V/cm) of relatively low frequency (typically 1 Hz), to suppress electrode polarization. Light scattering detection from a laser source optical arrangement is also usually provided. A more detailed description of the experimental setup can be found in Reference [47]. Particle mobility meff and size a can be simultaneously extracted by analysing the light scattered with a digital correlator. In effect, the Lorentzian-shaped power spectrum of scattered light undergoes a shift in frequency that is proportional to the particle migration velocity (Doppler effect), while its width at half height is proportional to the particle diffusion coefficient. As illustrated in Figure 2.6, depicts a bell-shaped variation in the concentration range of surfactant aggregation, but the maximum of the curve was reported to be significantly lower (10–20 %) than the CMC values obtained by classical conductimetry [17]. It might rather indicate the onset of counterion condensation. Nevertheless, this method allows clear detection of premicellar association of ionic surfactants in low conductivity media. 2.3.5

Discussion on Operating Conditions

The impact of solubilized solutes on micellization has been emphasized by several groups [39,43,46]. For the best accuracy, the micelle-interacting marker should not therefore be ionizable, for a proper control of ionic strength [39,40] and to avoid anomalous pH effects [48]. It should not interact with the micelles too strongly, otherwise micellization will be favored. It should also have a high molar UV absorptivity (to be used at low concentration), be soluble in water to a certain extent (not to introduce too high a content of organic solvent ( 10 % v/v) with the markers). A lack of solubility in water will probably result in a shift in the micellization equilibrium and

42


therefore in systematic errors in CMC values [35,43,46]. Likewise, too high a content of organic solvent in the marker solution will induce disruption of micelles [12,39,49]. Nevertheless, the baseline perturbation generated by the presence of a slight organic solvent content in the injected marker mixture can be used in practice for the measurement of teo. Although questioned by Mrestani et al. [41], the influence of the marker concentration was studied by Lin and Lin [40]. Based on these criteria, 2naphthalenemethanol was the best choice according to Nakamura et al. [36], whereas naphthalene was selected by Jacquier and Desbe`ne in spite of its low water solubility for the case of SDS [35], and anionic markers (cephalosporins) were used successfully for cationic surfactants [40]. Other recommended markers can be found in Lin’s review [39]. For the micelle mobility marker, hydrophobic dyes such as Sudan III [34,42,43], polyaromatic hydrocarbons [50], alkyl phenyl ketones [44,51] or hydrophobic compounds bearing a charge of sign opposite to that of the micelles [52] have been advocated. The nature of the capillary to be used may depend on the type (anionic, cationic) of surfactant. Bare silica capillaries are perfectly adapted to anionic surfactants as electroosmotic flow remains virtually independent of surfactant concentration. As cationic surfactants interact with the inner capillary surface and induce reversal of the electroosmotic flow inside these capillaries [53,54], the choice of the more appropriate capillary has been more controversial in the latter case [39]. Nagamine and Nakamura [44] recommended the use of (3-aminopropyl)triethoxysilane-treated capillaries to produce stable anodic electroosmotic flows, whereas use of bare silica capillaries was not reported to be problematic, once electroosmotic flow reversal has been established [40,45]. Finally, as for the current intensity method, proper temperature control is essential.

2.4 Frontal Methods As recently introduced by Gao et al. for the determination of interaction parameters [55], frontal analysis continuous capillary electrophoresis (FACCE) consists in first equilibrating a capillary with the BGE of interest and then continuously introducing a multicomponent sample dissolved in this electrolyte into the capillary under the influence of an electric field. This electrokinetic process achieves partial separation of the sample components simultaneously with their injection. Resulting electropherograms present successive migration fronts in order of decreasing apparent mobilities, with heights of the corresponding plateaus related to the concentrations of the components. Applied to an interacting system, this process avoids disturbance of the equilibria involved (similarly to dialysis or ultrafiltration), is free from kinetic constraints and allows direct measurement of the concentration of the faster migrating partner from a simple calibration step. As far as CMC determination is concerned, FACCE was first applied to UV-absorbing, anionic surfactants by Le Saux et al. [37]. Figure 2.7(a) shows that, depending on the total surfactant concentration, one or several migration fronts pertaining to surfactant monomer and aggregates can be detected. CMC is thus determined in this case without any marker being needed, as the total surfactant concentration for which the height of the monomer plateau remains almost constant [Figure 2.7(b)]. Importantly, the experimental

DETERMINATION OF CRITICAL MICELLE CONCENTRATIONS (a) mAU

F2

P2

43

F3 P3

P1 F1

600

400 EOF 200 0 1

3

5

min

(b)

Height of plateau P1 (mAU)

450

300

150

0

0

6

12

18

Concentration (mM)

Figure 2.7 Frontal analysis continuous capillary electrophoresis (FACCE) of sodium octylbenzenesulfonate. (a) Electropherograms obtained at various concentrations: from bottom to top: 7, 9, 11 and 13 mM. Bare silica capillary: 50 mm i.d. 35 cm (detection, 26.5 cm). BGE: 20 mM sodium borate buffer, pH 9.2 (ionic strength: 10 mM). Temperature: 30 C. UV absorbance detection at 200 nm. Injection: benzyl alcohol (30 mbar, 2 s), BGE (30 mbar, 2 s), followed by continuous electrokinetic introduction of surfactant sample under þ10 kV. EOF: electroosmotic flow. F1, F2, F3: migration fronts of monomeric, micellar and oligomeric forms, respectively. P1, P2, P3: corresponding concentration plateaus. (b) Height of the concentration plateau P1 of the free surfactant (at 230 nm) as a function of total surfactant concentration. Solid line: least-squares regression straight lines, yielding CMC = 9.5 0.8 mM (95 % confidence level) at intersection point. (Reprinted from Le Saux et al., Determination of aggregation thresholds of UV-absorbing anionic surfactants by frontal analysis continuous capillary electrophoresis, J. Chromatogr. A., 1038, 275–282, copyright 2004, with permission from Elsevier)

setup should be devised so that the discrete plateau of surfactant monomer will be detected first, thus allowing its easy quantitation. For the case of UV-transparent surfactants, a preferably UV-absorbing, micelleinteracting marker M is required [38], as for zonal methods, and FACCE allows direct determination of free marker concentration [M] from the measurement of corresponding

44

ELECTROKINETIC CHROMATOGRAPHY 1.1 A

B

0.8 [M] / [M]t

1 0.96 0.92 0.88 3

5

7

9

0.5

0.2 0

2

4

6 8 10 12 14 Total surfactant concentration (mM)

16

Figure 2.8 Theoretical variation of the free to total marker concentration ratio [M]/[Mt] as a function of the total surfactant concentration, according to Equations (2.11) and (2.12), with (A) Ksolv ¼ 0.5 M1 and Kmic ¼ 150 M1; (B) Ksolv ¼ 5 M1 and Kmic ¼ 1500 M1 and (C) Ksolv ¼ 50 M1 and Kmic ¼ 15 000 M1; CMC ¼ 6 mM; n ¼ 60. (Reprinted from Le Saux et al., Determination of aggregation thresholds of non-UV-absorbing neutral or charged surfactants by frontal- and vacancy-frontal analysis continuous capillary electrophoresis, J. Chromatogr. A., 1041, 219–226, copyright 2004, with permission form Elsevier)

plateau height. When the total surfactant concentration ct is below CMC, the marker can interact only with monomeric surfactant and [M] is given by [38]: ½M ¼

½M t 1 þ Ksolv ct

ð2:11Þ

When ct is greater than CMC, the expression for [M] becomes: ½M ¼

1 þ Ksolv

½M t CMC þ Kmic ðct CMCÞ=n

ð2:12Þ

Figure 2.8 represents the theoretical variations of the fraction of free marker [M]/[M]t for various Ksolv and Kmic values, according to Equations (2.11) and (2.12). The CMC can therefore be determined from the curve discontinuity. It can also be noticed from Figure 2.8 that the most appropriate marker should be of intermediate hydrophobicity, to allow simple linear fitting of the data points. The suitability of this approach was established for SDS in a pH 6.9 phosphate buffer, using a bare silica capillary and a neutral compound, ethylparaben, as a micelle-interacting marker. Under these conditions, the migration front of the free marker, monitored by UV-absorbance, appears before those of the marker–surfactant complexes, as it is solely moved in the capillary by the cathodic electroosmotic flow. The height of the subsequent plateau could hence be easily quantified, yielding a CMC value in very close agreement with literature data [38]. The FACCE method also applies to the CMC determination of UV-transparent cationic


45

surfactants, as exemplified in Figure 2.9 [38]. In this latter case, an amine-coated capillary and again a neutral marker should be used, to minimize electrostatic interactions with the capillary wall, and electroosmotic flow is reversed. Then, introducing the surfactant/marker mixture by the short end of the capillary (with respect to the position of the detection window) to further suppress wall adsorption effects, and still applying a positive voltage at the conventional capillary inlet, again results in the migration front of the free marker being detected first, the marker-surfactant complexes migrating counterelectroosmotically. This experimental setup is quite symmetrical to that used for anionic surfactants with bare silica capillaries. Finally, the interest in FACCE has also been demonstrated for CMC determination of neutral, UV-transparent surfactants [38]. In this case, an anionic, UV-absorbing amphiphilic marker with a bare silica capillary can be selected. In low ionic strength media, however, electroosmotic flow then drags all the species of interest to the cathodic side of the capillary, and classical implementation of FACCE protocol results in the front of the free anionic marker being detected last. As this situation is not especially favorable for precise quantitation of the corresponding plateau height, due to occurrence of wall adsorption and of noisy, high absorbance levels, a vacancy FACCE protocol should preferably be used. This protocol consists in first filling the capillary with surfactant/ marker mixtures dissolved in the electrolyte of interest, and then continuously injecting this electrolyte alone under an electric field. This implementation results in easier detection of the decreasing migration front of the free anionic marker from a lowabsorbance baseline. Figure 2.10(a) shows the vacancy frontal electropherograms obtained for different concentrations of Brij 35 (polyoxyethylene-23-dodecanol) and a constant concentration of octylbenzenesulfonate, used as a marker. When plotted against the total Brij 35 concentration, the height of the last descending migration front, pertaining to the free form of this anionic marker, exhibits two linear variation ranges [Figure 2.10(b)]. The CMC value determined from the break between these two parts (0.089 mM) was in excellent agreement with the literature value [56].

2.5 Discussion of the Suitability of Electrophoretic and Conventional Methods As compared with the armory of conventional methods, electrokinetic methods based on the use of CE instrumentation appear to be very suitable for the quantitative characterization of surfactant aggregation, both from theoretical and practical viewpoints. Electrokinetic methods are likely more universal than classical ones (especially conductimetry and dye solubilization), with respect to the types of surfactants that can be dealt with, in that they apply to UV- or non-UV-absorbing anionic, cationic and neutral surfactants [36,38,39,45]. The case of mixed surfactants has also been addressed successfully [37]. Although not yet reported [39], they should apply to zwitterionic surfactants as well. For most methods, premicellar aggregation phenomena can be vizualized. Electrokinetic methods offer a large compatibility in medium composition (pH, ionic strength, solvents, additives) [12] and temperature range [57]. The remarkable agreement between CMC values obtained from different CE and conventional methods and their consistency with respect to ionic strength (Table 2.1) lend support to the high

46

ELECTROKINETIC CHROMATOGRAPHY (a) mAU 25 20

F2 EOF / F1

15

F3

10 5 0 EOF / F1

–5 –10 2

4

6

8

10

12

14

min

(b) 18 y = 15.7 n=8

Height of migration front (mAU)

17 16 15

y = – 4.24x + 25.14 R 2 = 0.9989 n=5

14 13 12 11 10 9 8 0

0.5

1 1.5 2 2.5 3 Total TTABr concentration (mM)

3.5

4

Figure 2.9 Frontal analysis continuous capillary electrophoresis (FACCE) of tetradecyltrimethylammonium bromide/ethylparaben mixtures. (a) Electropherograms obtained for constant (0.33 mM) ethylparaben concentration and varying surfactant concentrations in water: from left to right: 0, 0.75, 1.25, 1.50, 2, 3, and 3.50 mM. Amine-coated silica capillary: 50 mm i.d. 62.5 cm (detection, 8.5 cm). BGE: 7.3 mM sodium phosphate buffer, pH 6.4 (ionic strength: 10 mM). Temperature: 25 C. UV absorbance detection at 256 nm. Shortend, continuous, electrokinetic injection of the surfactant/marker mixtures under þ15 kV. EOF: electroosmotic flow. F1, F2, F3: migration fronts of free marker, marker-monomeric surfactant and marker-micelle complexes, respectively. (b) Height of migration front F1 of the free marker as a function of total surfactant concentration. Solid line: least-squares regression straight lines, yielding CMC ¼ 2.25 mM at intersection point. (Reprinted from Le Saux et al., Determination of aggregation thresholds of non-UV-absorbing neutral or charged surfactants by frontal- and vacancy-frontal analysis continuous capillary electrophoresis, J. Chromatogr. A., 1041, 219–226, copyright 2004, with permission from Elsevier)


47

(a) EOF F2

mAU

F1

15 EOF 10

5

0 0

1

2

3

4

min

(b) 13.6 Height of migration front (mAU)

13.5 y = –9.25x + 14.17 R 2 = 0.996 n=4

13.4 13.3 y = –2.50x + 13.58 R2 = 1 n=4

13.2 13.1 13 12.9 12.8 12.7 0

0.02

0.04

0.06 0.08 0.1 0.12 Total Brij 35 concentration (mM)

0.14

0.16

Figure 2.10 Vacancy frontal analysis continuous capillary electrophoresis (VFACCE) of Brij 35/sodium octylbenzenesulfonate (SOBS) mixtures. (a) Electropherograms obtained for constant (0.064 mM) SOBS concentration and varying Brij 35 concentrations in the BGE: from bottom to top: 0.05, 0.07, 0.09, 0.13, 0.15 mM. Bare silica capillary: 50 mm i.d. 35 cm (detection, 26.5 cm). BGE: 20 mM sodium borate buffer, pH 9.2 (ionic strength: 10 mM). Temperature: 25 C. UV absorbance detection at 193 nm. Initial capillary filling with the Brij 35/SOBS mixtures followed by continuous, electrokinetic injection of BGE under þ10 kV. EOF: electroosmotic flow. F1, F2: migration fronts of free marker (SOBS), and mixed Brij 35/ SOBS micelles, respectively. (b) Height of migration front F1 of the free marker (SOBS) as a function of total Brij 35 concentration. Solid line: least-squares regression straight lines, yielding CMC = 0.089 mM at intersection point. (Reprinted from Le Saux et al., Determination of aggregation thresholds of non-UV-absorbing neutral or charged surfactants by frontal- and vacancy-frontal analysis continuous capillary electrophoresis, J. Chromatogr. A., 1041, 219–226, copyright 2004, with permission from Elsevier)

Current intensity Mobility

Water, 25 C

Extrapolated to zero ionic strength, 25 C Borax trisodium phosphate sodium chloride 2.8 mM sodium phosphate buffer, pH 6.9 (5 mM IS), 25 C 20 mM sodium borate buffer, pH 9.2 (10 mM IS), 25 C 10 mM sodium phosphate buffer, pH 7.0 (20 mM IS), 25 C

Sodium dodecyl sulfate

35 C 30 mM NaCl, 25 C

Retention time (2-naphthalenemethanol)

20 mM phosphate buffer, pH 7, 40 C

Sodium decyl sulfonate

7.8 7.9 6.1 5.3

3.5 6.1 4.8 3.0 3.6

Frontal (ethylparaben) Mobility (naphthalene)

Current intensity Mobility (pyridine) (2,3,5-trichloropyridine) Current intensity Current intensity

8.3

34

30

(naphthalene) (naphthalene)

Retention time (2-naphthalenemethanol)

20 mM phosphate buffer, pH 7, 40 C

CMC (mM)

Sodium decyl sulfate

Method

Conditions

Surfactant

CE techniques

56 46 46 56 33

35

38

12 12

33

36

36

Ref.

Mobility

Surface tension

Mobility (naphthalene)

Absorbance (Sudan III) conductometry Absorbance (Sudan III) conductometry

Method

5

34.3 8.1–8.4

2.9–3.7

5.3

6.9

5, 12

58

12

58

36

26.9 32.9

8.1

36

Ref. 25.0

CMC (mM)

Reference techniques

Table 2.1 Comparison of CMC values obtained form CE techniques and from conventional techniques. Abbreviations used: DoTMAB: dodecyltrimethylammonium bromide; DoTMAC: dodecyltrimethylammonium chloride; TTMAB: tetradecyltrimethylammonium bromide; CTMAB: cetyltrimethylammonium bromide; CTMAC: cetyltrimethylammonium chloride. IS: ionic strength

20 mM sodium phosphate buffer, pH 7.0, 25 C

DoTMAB

Sodium cholate

20 mM phosphate buffer, pH 7, 40 C Water, 25 C KBr 6 mM, 25 C 20 mM phosphate buffer, pH 7.5 (52 mM IS), 25 C 70 mM phosphate buffer, pH 6 (86 mM IS), 25 C

Sodium alkylbenzene-sulfonates: Octyl20 mM sodium borate buffer, pH 9.2, 30 C Dodecyl-

Sodium tetradecyl sulfate Sodium alkenyl sulfates: OctenylNonenylDecenylUndecenyl-

Retention time (2-naphthalenemethanol) Zeta potential Zeta potential Mobility (cephalosporins) Mobility (propazine)

Frontal

Current intensity

20 mM sodium Mobility phosphate buffer, pH 7.0 (pyridine) (41 mM IS) 25 C (2,3,5-trichloropyridine) Retention time 40 C (2-naphthalenemethanol) Current intensity 80 mM sodium borate buffer, pH 9.2 (40 mM IS), 25 C Retention factor 24 mM phosphate buffer, pH 7.0 (50 mM IS), 25 C (catechol) (methylcatechol) 20 mM phosphate buffer, Retention time pH 7, 40 C (2-naphthalenemethanol) 33

3.1

13.4 10.4 12.5 12.4 11 0.1

12.8

2.30 0.09

9.5 0.8

255 119 61 33

17 17 40 40 45

36

37

26

36

43

36

4.4 3.9

4.3 4.0 0.87

46

4.8

Conductivity Conductivity Conductivity

Conductivity Surface tension Conductivity Surface tension Absorbance (Sudan III)

Fluorescence (pyrene)

Absorbance (Sudan III) conductometry

Absorbance (sudan III) conductometry Retention factor, Mobility

15.5 13.9 13.0

17 17 40

36

37

26

36

36 36 59 12

(Continued)

9.8 0.3 7.5–10 unsuitable unsuitable 12.6

252 133 63 31

0.86 0.89

3.5 4.0 2.6–3.2

Water, 25 C 20 mM Britton–Robinson buffer, pH 3, 25 C Water, 25 C 7.3 mM sodium phosphate buffer, pH 6.4 (10 mM IS), 25 C 70 mM sodium phosphate buffer, pH 6 (86 mM IS), 25 C Water, 25 C 20 mM Britton-Robinson buffer, pH 3, 25 C 20 mM Britton-Robinson buffer, pH 3, 25 C 20 mM sodium borate, pH 9.2, 25 C

DoTMAC

Brij 35

Cetylpyridinium

CTMAB CTMAC

TTMAB

Conditions

Surfactant

Table 2.1 (Continued)

0.93 0.75 0.57

Current intensity Mobility (acetophenone) Mobility (acetophenone) 0.0089

1.6 0.1

Mobility (propazine)

Vacancy frontal

2.25

18.8

CMC (mM)

Frontal analysis (ethylparaben)

Method

CE techniques

38

44

33 44

45

38

44

Ref.

Absorbance (Sudan III)


Conductivity


Method

0.09

0.54

0.90–0.98 0.67

56

44

5 44

45

56

3.5

1.5

54 44

Ref. 20 17.4

CMC (mM)

Reference techniques


51

level of accuracy provided by electrokinetic methods. Although performances of CE and conventional methods have been rarely discussed in terms of precision, these are quite similar and mainly depend on the number and the quality of the data points and the surfactant nature [37]. From a practical point of view, CE techniques take advantage of their miniaturized implementation and small volume requirement (a few hundreds of microliters of each varying concentration of surfactant solution) [36], good temperature control [33], and have proven superior to other techniques as regards time needed (especially, as compared to dye solubilization [24]) and ease of implementation, due to instrument automation. Among the CE methods, those involving a marker may lead to inaccurate determinations (lower CMC values insofar as micellization can be favored [33, 35]) if marker nature and concentration are not properly chosen, as emphasized before. This makes the current intensity method particularly attractive for ionic surfactants, especially in low conductivity media. Indeed, detection of the intersection point between the two straight lines becomes imprecise when background conductivity is high [33]. Another drawback of this method is that the slopes of the straight lines may not vary abruptly in the case of premicellar aggregation [39]. When BGE conductivity is markedly higher than that brought by the surfactant in the range of its CMC, the mobility method becomes preferable [39]. Finally, newly developed frontal methods appear to be very effective for fast, precise and accurate determinations of aggregation thresholds of any kind of surfactant, including, for the first time, neutral ones. One fundamental advantage of frontal methods over zonal ones comes from the fact that the surfactant monomer–micelle and surfactant–marker equilibria are perturbed to a minor extent. The choice for the markers can also be enlarged towards compounds of lower hydrophobicity, a favorable situation with respect to marker solubility, detection sensitivity and hence accuracy. On the other hand, frontal methods suffer from the fact that plateau heights can only be measured manually. More specifically, the frontal approach is best suited for UV-absorbing ionic surfactants, for which no marker is needed and zonal methods may present detection difficulties, and for aggregation studies of amphiphilic polymers, which may present slow equilibrium kinetics. Lastly, it is worthy of note that differences between results afforded by the various methods can be increased for polydisperse surfactants, so that complementary insights can be obtained in this latter case.

References [1] L.J. Cline Love, J.G. Harbata and J.G. Dorsey. The micelle–analytical chemistry interface, Anal. Chem., 56, 1132A–1146A (1984). [2] E. Pramauro and E. Pelizzetti. Surfactants in Analytical Chemistry, Elsevier, Amsterdam, 1996. [3] C. Tanford. The Hydrophobic Effect: Formation of Micelles and Biological Membranes, John Wiley & Sons, Inc. New York, 1980. [4] H. Hoffman and W. Ulbricht, in Thermodynamic Data for Biochemistry and Biotechnology, H.J. Hinz (Ed), pp. 297–348, Springer Verlag, New York, 1986.

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[5] P. Mukerjee and K.J. Mysels. Critical Micelle Concentrations of Aqueous Surfactants Systems, National Standards Reference Data Service, National Bureau of Standards (US) Washington, DC, 1971. [6] J.-M. Lin, M. Nakagawa, K. Uchiyama and T. Hobo. Determination of critical micelle concentration of SDS in formamide by capillary electrophoresis, Chromatographia, 50, 739–744 (1999). [7] D. Myers. Surfactant Science and Technology, VCH, New York, 1998. [8] B.C. Paul, S.S. Islam and K. Ismail. Effect of acetate and propionate co-ions on the micellization of sodium dodecyl sulfate in water, J. Phys. Chem., B, 102 (40), 7807–7812 (1998). [9] E.S. Ahuja and J.P. Foley. Influence of dodecyl sulfate counterion on efficiency, selectivity, retention, elution range, and resolution in micellar electrokinetic chromatography, Anal. Chem., 67, 2315–2324 (1995). [10] E. Junquera, G. Tardajos and E. Aicart. Effect of the presence of beta-cyclodextrin on the micellization process of sodium dodecyl sulfate or sodium perfluorooctanoate in water, Langmuir, 9, 1213–1219 (1993). [11] S. Terabe, T. Katsura, Y. Okada, Y. Ishihama and T. Otsuka. Measurement of thermodynamic quantities of micellar solubilization by micellar electrokinetic capillary chromatography with SDS, J. Microcol. Sep., 5, 23–33 (1993). [12] J.C. Jacquier and P.L. Desbe`ne. Determination of critical micelle concentration by CE. Application to organo-saline electrolytes, J. Chromatogr. A, 743, 307–314 (1996). [13] D.O. Shah. Micelles, Microemulsions and Monolayers, Sciences and Technology, Marcel Dekker, New York, 1998. [14] J. Garcia-Anto and J.L. Guinon. Determination of Hyamine 2389 critical micelle concentration by means of conductometric, spectrophotometric and polarographic methods, Colloids Surf., 61, 137–145 (1991). [15] M. Dominguez, A. Fernandez, N. Gonzalez, E. Iglesias and L. Montenegro. Determination of critical micelle concentration of some surfactants by three techniques, J. Chem. Educ., 74, 1227–1230 (1997). [16] M. Perez-Rodriguez, G. Prieto, C. Rega, L.M. Varela, F. Sarmiento and V. Mosquera. A comparative study of the determination of the critical micelle concentration by conductivity and dielectric constant measurements, Langmuir, 14, 4422–4426 (1998). [17] R. Sabate´ , M. Gallardo and J. Estelrich. Electrophoretic properties of dodecyltrimethylammonium bromide micelles in KBr solutions, Electrophoresis, 21, 481–485 (2000). [18] M. Zulauf, U. Furstenberger, M. Grabo, P. Jaggi, M. Regeass and J.P. Rosenbusch, in Methods in Enzymology, S. Fleischer and B. Fleischer (Eds.), Vol. 172, p. 528, Academic Press, San Diego, 1989. [19] Y.D. Smet, L. Deriemaeker, E. Parloo and R. Finsy. On the determination of Ostwald ripening rates from dynamic light scattering measurements, Langmuir, 15, 2327–2332 (1999). [20] S.A.A. Rizvi and S.A. Shamsi. Polymeric alkenoxy amino acid surfactants: I. Highly selective class of molecular micelles for chiral separation of beta-blockers, Electrophoresis, 24, 2514– 2526 (2003). [21] T. Nakashima, T. Anno, H. Kanda, Y. Sato, T. Kuroi, H. Fujii, S. Nagadome and G. Sugihara. Potentiometric study on critical micellization concentrations (CMC) of sodium salts of bile acids and their amino acid derivatives, Colloids Surf. B: Biointerfaces, 24, 103–110 (2003). [22] A.B. Mandal and B.U. Nair. Cyclic voltammetry technique for the determination of the critical micellar concentration of surfactants, self-diffusion coefficient of micelles, and partition coefficient of an electrochemical probe, J. Phys. Chem., 65, 9008–9013 (1991). [23] H. Schott. Solubilization of a water-insoluble dye as a method for determining micellar molecular weights, J. Phys. Chem., 70, 2966–2973 (1996).


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[24] C. Maeder, G.M.J. Beaudoin III, E.K. Hsu, V.A. Escobar, S.M. Chambers, W.E. Kurtin and M.M. Bushey. Measurement of bilirubin partition coefficients in bile salt micelle/aqueous buffer solutions by micellar electrokinetic chromatography, Electrophoresis, 21, 706–714 (2000). [25] N.J. Turro and A. Yekto. Luminescent probes for detergent solutions. A simple procedure for determination of the mean aggregation number of micelles, J. Am. Chem. Soc., 100, 5951–5952 (1978). [26] C. Akbay and S.A. Shamsi. Polymeric sulfated surfactants with varied hydrocarbon tail: I. Synthesis, characterization and application in micellar electrokinetic chromatography, Electrophoresis, 25, 622–634 (2004). [27] K.J. Mysels and L.H. Princen. Light scattering by some lauryl sulfate solutions, J. Phys. Chem., 63, 1696–1700 (1959). [28] N.C. Santos, A.C. Silva, M.A. R.B. Castanho, J. Martins-Silva and C. Saldanha. Evaluation of lipopolysaccharide aggregation by light scattering spectroscopy, Chembiochem, 4, 96–100 (2003). [29] H.G. Elias. The study of association and aggregation via light scattering, in Light Scattering from Polymer Solutions, M.B. Huglin (Ed.), pp. 397–457, Academic Press, London, 1972. [30] E.D. Goddard. Polymer–surfactant interaction. Part I: uncharged water-soluble polymers and charged surfactants, Colloids Surf., 19, 255–300 (1986). [31] Y.S. Lee and K.W. Woo. Micellization of aqueous cationic surfactant solutions at the micellar structure transition concentration – based upon the concept of the pseudophase separation, J. Colloid Interface Sci., 169, 34–38 (1995). [32] D.C. Tickle, G.N. Okafo, P. Camilleri, R.F.D. Jones and A.J. Kirby. Glucopyranoside based surfactants as pseudostationary phases for chiral separations in capillary electrophoresis, Anal. Chem., 66, 4121–4126 (1994). [33] A. Cifuentes, J.L. Bernal and J.C. Diez-Masa. Determination of critical micelle concentration values using capillary electrophoresis instrumentation, Anal. Chem., 69, 4271–4274 (1997). [34] S. Terabe, K. Otsuka and T. Ando. Electrokinetic chromatography with micellar solution and open-tubular capillary, Anal. Chem., 57, 834–841 (1985). [35] J.C. Jacquier and P.L. Desbe`ne. Determination of critical micelle concentration by capillary electrophoresis. Theoretical approach and validation, J. Chromatogr. A, 718, 167–175 (1995). [36] H. Nakamura, A. Sano and K. Matsuura. Determination of critical micelle concentration of anionic surfactants by capillary electrophoresis using 2-naphthalenemethanol as a marker for micelle formation, Anal. Sci., 14, 379–382 (1998). [37] Th. Le Saux, A. Varenne and P. Gareil. Determination of aggregation thresholds of UV-absorbing anionic surfactants by frontal analysis continuous capillary electrophoresis, J. Chromatogr. A., 1038, 275–282 (2004). [38] Th. Le Saux, A. Varenne and P. Gareil. Determination of aggregation thresholds of non-UVabsorbing, neutral or charged surfactants by frontal- and vacancy-frontal analysis continuous capillary electrophoresis, J. Chromatogr. A., 1041, 219–226 (2004). [39] C.-E. Lin. Determination of critical micelle concentration of surfactants by capillary electrophoresis, J. Chromatogr. A., 1037, 467–478 (2004). [40] C.E. Lin and K.S. Lin. Determination of critical micelle concentration and interactions between cephalosporins and charged surfactants, J. Chromatogr. A, 868, 313–316 (2000). [41] Y. Mrestani, R. Neubert and H.H. Ru¨ ttinger. Reply to ‘Determination of critical micelle concentration and interactions between cephalosporins and charged surfactants’, J. Chromatogr. A, 868, 317–319 (2000). [42] M.G. Khaledi, S.C. Smith and J.K. Strasters. Micellar electrokinetic capillary chromatography of acidic solutes: migration behavior and optimization strategies, Anal. Chem., 63, 1820–1830 (1991).

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[43] J.K. Strasters and M.G. Khaledi. Migration behavior of cationic solutes in micellar electrokinetic capillary chromatography, Anal. Chem., 63, 2503–2508 (1991). [44] N. Nagamine and H. Nakamura. Measurements of critical micelle concentrations of cationic surfactants by capillary electrophoresis, Anal. Sci., 14, 405–406 (1998). [45] C.E. Lin, T.Z. Wang, T.C. Chiu and C.C. Hsueh. Determination of the critical micelle concentration of cationic surfactants by capillary electrophoresis, J. High Resolut. Chromatogr., 22, 265–270 (1999). [46] C.E. Lin, M.J. Chen, H.C. Huang and H.W. Chen. Capillary electrophoresis study on the micellization and critical micelle concentration of sodium dodecyl sulfate. Influence of solubilized solutes, J. Chromatogr. A, 924, 83–91 (2001). [47] R.J. Hunter. Foundations of Colloid Science, second edition, Oxford University Press, Oxford, 2002. [48] C.E. Lin, W.C. Lin and W.C. Chiou. Migration behaviour and selectivity of dichlorophenols in micellar electrokinetic capillary chromatography. Influence of micelle concentration and buffer pH, J. Chromatogr. A., 722, 333–343 (1996). [49] C.-E. Lin, H.-C. Huang and H.-W. Chen. A capillary electrophoresis study of the influence of cyclodextrin on the CMC of SDS, J. Chromatogr. A, 917, 297–310 (2001). [50] P. Morin and M. Dreux. Factors influencing the separation of ionic and non-ionic chemical natural compounds in plant extracts by capillary electrophoresis, J. Liquid Chromatogr., 16, 3735–3755 (1993). [51] E.S. Ahuja, E.L. Little, K.R. Nielsen and J.P. Foley. Infinite elution range in micellar electrokinetic capillary chromatography using a nonionic anionic mixed micellar system, Anal. Chem., 67, 26–33 (1995). [52] J.R. Mazzeo, E.R. Grover, M.E. Swartz and J.S. Petersen. Novel chiral surfactant for the separation of enantiomers by micellar electrokinetic capillary chromatography, J. Chromatogr., 680, 125–135 (1994). [53] T. Kaneta, S. Tanaka and M. Taga. Effect of cetyltrimethylammonium chloride on electroosmotic and electrophoretic mobilities in capillary zone electrophoresis, J. Chromatogr., 653, 313–319 (1993). [54] D. Crosby and Z.E. Rassi. Micellar electrokinetic capillary chromatography with cationic surfactants, J. Liquid Chromatogr., 16, 2161–2187 (1993). [55] J.Y. Gao, P.L. Dubin and B.B. Muhoberac. Measurement of the binding of proteins to polyelectrolytes by frontal analysis continuous capillary electrophoresis, Anal. Chem., 69, 2945–2951 (1997). [56] H. Nishi and S. Terabe. Micellar electrokinetic chromatography. Perspectives in drug analysis, J. Chromatogr. A, 735, 3–27 (1996). [57] Y. Mrestani, Z. Marestani and R.H.H. Neubert. Characterization of micellar solubilization of antibiotics using micellar electrokinetic chromatography, J. Pharm. Biomed. Anal., 26, 883– 889 (2001). [58] D. Stigter. Physical Chemistry, Enriching Topics for Colloids and Surface Science, H. Van Olphen. and K.J. Mysels, (Eds), Chapter 12, IUPAC Commission I.6, Theorex, La Jolla, CA, 1975. [59] K. Saitoh, C. Kiyohara and N. Suzuki. Mobilities of metal-diketonato complexes in micellar electrokinectic capillary chromatography, J. High Resolut. Chromatogr., 14, 245–248 (1991).

3 Selectivity Characterization of Pseudostationary Phases Using the Solvation Parameter Model Colin F. Poole

3.1 Introduction Separations in electrokinetic chromatography result from differences in the electrophoretic mobility of analytes as well as differences in their distribution between the electrolyte solution and a pseudostationary phase. Since all neutral molecules have the same electrophoretic velocity, it is the presence of the pseudostationary phase that is important in explaining differences in the retention of these compounds. To understand this process it is necessary to have a quantitative model that accounts for the ability of different pseudostationary phases to interact selectively with neutral compounds. In contemporary practice this is achieved by fitting retention data for compounds with varied properties to the solvation parameter model and extracting the contribution of defined intermolecular interactions to the separation process. The solvation parameter model has been widely applied to the characterization of distribution systems in chromatography, and References [1–6] can be consulted for a broader view of these applications. In early studies of the characterization of pseudostationary phases in electrokinetic chromatography the Kamlet–Taft solvatochromic model was often employed [7–10]. This model is similar, but not identical to Abraham’s solvation parameter model. The solute descriptors in the solvation parameter model are all free energy related properties, which is not the case for the solvatochromic model, and for this reason as well as others [1,2,6] the solvation parameter model has largely superseded the solvatochromic model in


56


contemporary studies of chromatographic distribution properties. To take full advantage of these early studies, all data using the solvatochromic model has been recalculated by the solvation parameter model and is presented in this article in a common form [11–13].

3.2 Solvation Parameter Model The solvation parameter model is based on a cavity model of solution. Firstly, a cavity of a suitable size to accommodate the solute is formed in the solvent, with the solvent molecules in the same configuration as the bulk solvent. The energy required for this process depends on the forces holding the solvent molecules together and the solute’s size. In the second step, the solvent molecules are reorganized into their equilibrium position around the solute. The free energy for this process is small and can be neglected without much consequence. Finally, the solute is inserted into the cavity and various solute–solvent interactions are set up. For neutral compounds these are identified as dispersion, induction, orientation, and hydrogen bonding. For electrokinetic chromatography, transfer occurs between two condensed phases, and the free energy of transfer is equivalent to the difference in cavity formation and solute–solvent interactions in the electrolyte solution and pseudostationary phase. The contribution of each intermolecular interaction to transfer in the solvation parameter model is represented by the sum of product terms made up of solute factors (descriptors) and complementary solvent factors (system constants). A solute, therefore, has a certain ability to participate in each intermolecular interaction and the contribution of each interaction to the free energy of transfer is the product of solute and solvent properties. The solvation parameter model in a form suitable for characterizing the transfer of neutral compounds from an electrolyte solution to a pseudostationary phase in electrokinetic chromatography is set out in Equation (3.1): log SP ¼ c þ vV þ eE þ sS þ aA þ bB

ð3:1Þ

SP is some free energy related solute property such as a distribution constant or retention factor in electrokinetic chromatography. The remainder of the equations is made up of several product terms consisting of system constants (e, s, a, b, and v) and solute descriptors (earlier symbols for the descriptors are given in parenthesis) E(R2 ), S(pH 2 ), H A (aH 2 ), B (b2 ) and V(VX). Each product term represents a contribution to the solute property from a defined intermolecular interaction. The contribution from cavity formation and dispersion interactions are strongly correlated with solute size and cannot be separated if a volume term, such as the characteristic volume [V in Equation (3.1)], is used as a solute descriptor. Solute transfer between two condensed phases occurs with little change in the contribution from dispersion interactions, and thus, the absence of a specific term in Equation (3.1) to represent dispersion interactions is not a serious problem. For the solvation parameter model to have practical utility it is important that the solute descriptors are accessible for a wide range of compounds by either calculation or experiment. McGowan’s characteristic volume, V, in units of cm3mol1/100, can be calculated by simple summation rules for any compound whose structure is known [14,15]. The characteristic molecular volume is the sum of all atomic volumes less

SELECTIVITY CHARACTERIZATION OF PSEUDOSTATIONARY PHASES

57

Table 3.1 Examples of the calculation of V and E solute descriptors Calculation of McGowan’s characteristic volume, V, for toluene Atomic volumes: C ¼ 16.35, H ¼ 8.71, N ¼ 14.39, O ¼ 12.43, F ¼ 10.48, Si ¼ 26.83, P ¼ 24.87, S ¼ 22.91, Cl ¼ 20.95, B ¼ 18.23, Br ¼ 26.21, I ¼ 34.53. Subtract 6.56 for each bond of any type. Toluene ¼ 7 carbon atoms þ 8 hydrogen atoms – 15 bonds ¼ 114.45 þ 69.68 – 98.40 ¼ 85.73 in cm3mol1. After scaling V ¼ 0.857 in cm3mol1/100. Calculation of the excess molar refraction, E, for toluene using Equation (3.2). The refractive index for toluene (Z) at 20 C (sodium D-line) ¼ 1.496 E ¼ 8.57 (0.292) þ 0.5255 – 2.832 (0.857) ¼ 0.601 in cm3mol1/10.

6.56 cm3mol1 for each bond, no matter whether single, double or triple (see Table 3.1). For complex molecules the number of bonds, NB, is easily calculated from the algorithm NB ¼ N – 1 þ R where N is the total number of atoms, and R is the number of rings. The excess molar refraction, E, characterizes the contribution from the polarizability of solute n- and p-electrons. It is defined as the solute molar refraction less the molar refraction of an imaginary n-alkane with the same characteristic volume and is simply calculated in units of cm3mol1/ 10 from the refractive index of the solute at 20 C for the sodium Dline, Z, as indicated by Equation (3.2) [16]: E ¼ 10V½ðZ2 1Þ=ðZ2 þ 2Þ 2:832V þ 0:526

ð3:2Þ

The use of Equation (3.2) to calculate the excess molar refraction is straightforward for liquids, see Table 3.1, but even for solids refractive index values are easily estimated using available software for molecular property estimations. In addition, excess molar refraction is almost an additive property, and values for solids can be estimated through addition of fragments with known E values [1,6,17]. Initially the solute descriptors for hydrogen-bond acidity and basicity were determined from 1:1 complexation constants measured in an inert solvent [18,19]. These studies also led to scales with a zero origin. A problem remained, however, when these descriptors were used to characterize distribution processes. The effect of solute structure on the distribution process is a consequence of hydrogen bonding of the solute to any surrounding solvent molecules, not just to one. New scales of effective or overall hydrogen bond acidity and basicity, A and B, were determined in conjunction with other solute descriptors using liquid–liquid distribution and chromatographic measurements [15,20]. A minor complication is that some solutes (sulfoxides, anilines, pyridines) show variable hydrogen-bond basicity in distribution systems where the stationary phase absorbs appreciable amounts of water [20]. A new solute descriptor B was defined for these solutes and is generally used in electrokinetic chromatography. Except for the solute types indicated above, the two hydrogen-bond basicity scales are identical. It should also be noted that the scales of hydrogen-bond acidity and basicity are unrelated to proton transfer acidity and basicity expressed by the pKa scale. It would be useful to have descriptors that were related to the propensity of a solute to engage in dipole–dipole and induced dipole–dipole interactions. In the event, it proved impossible to separate out descriptors for the two types of interactions, and it was necessary to construct a solute descriptor for dipolarity/polarizability, S, combining the two interactions [16]. The dipolarity/polarizability solute descriptor is now more

58


commonly determined in combination with the hydrogen-bonding descriptors from liquid–liquid distribution constants and chromatographic measurements [1,6,15]. Solute descriptors are available for over 4000 compounds, with the most complete repository being the University College London database incorporated into Absolv (Sirius, UK) [17]. For additional compounds estimation methods are available using fragment constants [1,6,17]. In all other cases it is possible to calculate V and E and determine the other descriptors from experimental distribution constants and chromatographic measurements. This is of little concern for the characterization of pseudostationary phases since the number and variety of solutes with established solute descriptors is more than adequate for the determination of system constants. The system constants in Equation (3.1) are obtained by multiple linear regression analysis for a number of solute property determinations for solutes with known descriptors. The system constants are more than mere regression constants and contain important chemical information about the system. The system constants reflect the difference in solute interactions in the background electrolyte solution and pseudostationary phase in electrokinetic chromatography. The e system constant indicates the difference in the tendency for the electrolyte solution and pseudostationary phases to interact with solute p- and n-electron pairs; the s system constant to the difference in the tendency of the electrolyte solution and pseudostationary phases to interact with solutes through dipole-type interactions; the a system constant indicates the difference in hydrogen-bond basicity between the two phases (because acidic solutes will interact with a basic phase); and the b system constant is a measure of the difference in hydrogenbond acidity between the two phases (because basic solutes will interact with an acidic phase). The v system constant is a measure of the difference in cavity formation in the electrolyte solution and pseudostationary phases together with any residual dispersion interactions that do not cancel when the solute is transferred between phases. 3.2.1

Model Requirements

A reliable model is one that makes chemical sense and is statistically valid. To obtain such a model certain conditions must be met. The dependent variable for electrokinetic chromatography is usually the retention factor (log k) or equilibrium constant (log K) for the distribution of the solute between the electrolyte solution and pseudostationary phase. The retention factor is easily accessible in electrokinetic chromatography and is used predominantly. There are two features of the retention factor that are important with respect to its use in the solvation parameter model. For modeling it is desirable that the log k values cover a reasonable numerical range with a uniform distribution throughout the range. In addition, the general error in the determination of the retention factor increases exponentially as k ) 0 and k ) 1 [21]. To achieve a minimal error and a stable error distribution, most of the k values should fall between 0.15 and 0.75 of the migration window for the separation system. Clustering of a large number of k values into either portion of the undesirable region will result in models with a large prediction error and erroneous or imprecise system constants. The solutes selected to establish reliable system constants should be sufficient in number and variety to properly define all interactions and to establish the statistical validity of the model [12,13,22]. A minimum of seven solutes is sufficient to solve


59

Equation (3.1) by multiple linear regression techniques. For statistical evaluation three varied values for each solute descriptor and the intercept is a reasonable minimum, but since individual solutes express several interactions simultaneously, the number of solutes required can be safely reduced from about 18 to 9. This condition presupposes that the error in the solute retention factors is roughly constant and that the descriptor values for each solute are known to the same accuracy. Neither condition is likely to prevail for most cases, and to select the minimum number of solutes for system characterization seems unwise. It is common practice to overdetermine the statistical requirements of Equation (3.1) to obtain an exhaustive fit. With such a fit it should be possible to remove a small set of randomly selected solutes from the model without significant variation in the system constant values. This can usually be achieved using 20–40 varied solutes. The solutes employed for system characterization are not selected at random. They are chosen so as to cover as evenly as possible the descriptor space to be explored. Clustering of descriptor values into narrow ranges should be avoided. This is easily checked by constructing a histogram plot for each descriptor. The presence of a central tendency in the plot is an indication of poor solute selection. The A solute descriptor is a partial exception, reflecting that among any group of varied compounds a significant number are going to be nonhydrogen-bond acids with A ¼ 0. When a varied group of solutes has been selected that adequately populates the descriptor space, it is necessary to check that the descriptor values are not highly cross correlated. Cross correlation results from the unintentional correlation between descriptor values. It results in a loss in capability of the multiple linear regression algorithm to distinguish between the correlated descriptors. There is almost always some correlation between any two sets of independent descriptor values and this is only considered a serious problem for r 0:8. When a high level of correlation exists between two sets of descriptors, it is likely that the model obtained will incorrectly assign values to the complementary system constants or may arbitrarily eliminate one of the system constants from the model entirely. In either case, the models are unlikely to be robust and will have poor predictive properties for new solutes. A useful compilation of solutes for characterizing pseudostationary phases in electrokinetic chromatography is given in Table 3.2. Selection of additional solutes may be appropriate to break cross correlation among subsets of the solutes and to obtain a reasonable range of retention factor values for the chosen separation system. The solute descriptors are defined for compounds in their neutral form. Compounds that will be significantly ionized at the pH selected for measurements should be removed from consideration. The solutes in Table 3.2 have a reasonable absorbance between 210–250 nm to facilitate absorption detection, since this is the common mode of detection in electrokinetic chromatography. Table 3.3 illustrates part of a typical output for the calculation of system constants by multiple linear regression analysis. The overall correlation coefficient, standard error in the estimate, Fischer F-statistic, and the standard deviation in the individual system constants are used to judge the statistical properties of the model. Acceptable models in electrokinetic chromatography will typically have values for the overall correlation coefficient of R > 0:97, a standard error in the estimate SE of 0.05–0.1, and a Fischer F-statistic of 150–1000. The standard error for the system constant should be smaller

60


Table 3.2 Solute descriptors for typical compounds used for the characterization of pseudostationary phases in electrokinetic chromatography (UV absorbance detection between 210–250 nm) Descriptor values Compound

E

S

A

B

V

Acetanilide Acetophenone 4-Aminobenzamide Aniline Anisole Anthracene Antipyrine Benzaldehyde Benzamide Benzene Benzenesulfonamide Benzonitrile 2,3-Benzofuran Benzophenone Benzyl alcohol Benzyl benzoate Biphenyl Bromobenzene n-Butylbenzene n-Butyl benzoate n-Butyrophenone Caffeine Catechol 4-Chloroacetanilide 3-Chloroaniline 4-Chloroaniline Chlorobenzene 4-Chlorophenol Corticosterone Cortisone 1,4-Dichlorobenzene 2,3-Dimethylphenol 2,4-Dimethylphenol Estradiol Estriol Ethylbenzene Fluorobenzene Fluorene Geraniol n-Heptanophenone Hydrocortisone Indole Iodobenzene N-Methylbenzamide Methyl benzoate Methyl 3-hydroxybenzoate 1-Methylnaphthalene

0.870 0.818 1.340 0.955 0.708 2.290 1.320 0.820 0.990 0.610 1.130 0.742 0.888 1.447 0.832 1.264 1.360 0.882 0.600 0.668 0.797 1.500 0.970 0.980 1.050 1.060 0.718 0.915 1.860 1.960 0.825 0.850 0.840 1.800 2.000 0.613 0.477 1.588 0.513 0.720 2.030 1.200 1.188 0.950 0.733 0.905 1.344

1.36 1.01 1.94 0.96 0.75 1.34 1.50 1.00 1.50 0.52 1.55 1.11 0.83 1.50 0.95 1.42 0.99 0.73 0.51 0.80 0.95 1.60 1.10 1.50 1.10 1.10 0.65 1.08 3.43 3.50 0.75 0.90 0.80 3.30 3.36 0.51 0.57 1.03 0.63 0.95 3.49 1.12 0.82 1.44 0.85 1.40 0.90

0.46 0 0.80 0.26 0 0 0 0 0.49 0 0.55 0 0 0 0.37 0 0 0 0 0 0 0 0.88 0.64 0.30 0.30 0 0.67 0.40 0.36 0 0.52 0.53 0.88 1.40 0 0 0 0.39 0 0.71 0.44 0 0.35 0 0.66 0

0.69 0.48 0.94 0.50 0.29 0.26 1.48 0.39 0.67 0.14 0.80 0.33 0.15 0.50 0.56 0.51 0.22 0.09 0.15 0.46 0.51 1.33 0.47 0.51 0.36 0.35 0.07 0.20 1.63 1.87 0.02 0.36 0.39 0.95 1.22 0.15 0.10 0.20 0.66 0.50 1.90 0.31 0.12 0.73 0.46 0.45 0.20

1.1137 1.0139 1.0726 0.8162 0.9160 1.4540 1.5502 0.8750 0.9728 0.7164 1.0971 0.8711 0.9055 1.4808 0.9230 1.6804 1.3242 0.8914 1.2800 1.4953 1.2957 1.3632 0.8338 1.2237 0.9390 0.9390 0.8388 0.8975 2.7389 2.7546 0.9612 1.0569 1.0569 2.1988 2.2575 0.9982 0.7341 1.3565 1.4903 1.7184 2.7975 0.9460 0.9746 1.1132 1.0726 1.1313 1.2263


61

Table 3.2 (Continued) Descriptor values Compound

E

S

A

B

V

3-Methylphenol Naphthalene 2-Naphthol 2-Nitroaniline 3-Nitroaniline 4-Nitroaniline 2-Nitroanisole Nitrobenzene 4-Nitrobenzyl alcohol 1-Nitrobutane 1-Nitrohexane 1-Nitronaphthalene 4-Nitrotoluene Phenol 4-Phenylbutanol 2-Phenylethanol 4-Phenylphenol a-Pinene n-Propiophenone n-Propylbenzene n-Propyl benzoate Pyrimidine Pyrrole Quinoline Thiourea Thymol Toluene 2-Toluidine 1,2,3-Trihydroxybenzene Valerophenone p-Xylene

0.822 1.340 1.520 1.180 1.200 1.220 0.965 0.871 1.064 0.227 0.203 1.600 0.870 0.805 0.811 0.811 1.560 0.446 0.804 0.604 0.675 0.606 0.613 1.268 0.840 0.822 0.601 0.970 1.165 0.795 0.613

0.88 0.92 1.08 1.37 1.71 1.91 1.34 1.11 1.39 0.95 0.95 1.51 1.11 0.89 0.90 0.91 1.41 0.14 0.95 0.50 0.80 1.00 0.73 0.97 0.82 0.79 0.52 0.90 1.35 0.95 0.52

0.57 0 0.61 0.30 0.40 0.42 0 0 0.44 0 0 0 0 0.60 0.33 0.30 0.59 0 0 0 0 0 0.41 0 0.77 0.52 0 0.23 1.35 0 0

0.34 0.20 0.40 0.36 0.35 0.38 0.38 0.28 0.62 0.29 0.29 0.29 0.28 0.30 0.70 0.64 0.45 0.12 0.51 0.15 0.46 0.65 0.29 0.51 0.87 0.44 0.14 0.59 0.62 0.50 0.16

0.9160 1.0854 1.1441 0.9904 0.9904 0.9904 1.0902 0.8906 1.0902 0.8464 1.1282 1.2596 1.0320 0.7751 1.3387 10.596 1.3829 1.2574 1.1548 1.1391 1.3544 0.6342 0.5774 1.0443 0.5696 1.3387 0.8573 0.9751 0.8925 1.4366 0.9982

than the value of the system constant itself and a t-test used to indicate whether the system constant is statistically different from zero at the probability level selected for the test. In the final evaluation of any model, not only must the system constants be statistically valid but they must make chemical sense as well.

3.3 Micelles as Pseudostationary Phases Surfactants can be conveniently categorized by the charge on the head group as nonionic, anionic, cationic or zwitterionic, or by the type of organic moiety as hydrocarbon, bile salt and fluorocarbon surfactants. A general property of all surfactants is the formation of micelles (molecular aggregates) when their solution concentration exceeds a threshold value, called the critical micelle concentration (CMC). The driving force for micelle

62


Table 3.3 An example of part of the output for fitting the solvation parameter model to a micellar electrokinetic chromatographic system by multiple linear regression analysis Descriptors

log k

Solute

V

E

S

A

B

Experimental

Predicted

Phenol Benzyl alcohol Aniline Toluene Ethylbenzene Naphthalene Benzaldehyde Nitrobenzene Chlorobenzene Acetophenone

0.775 0.916 0.816 0.857 0.998 1.085 0.873 0.890 0.838 1.014

0.805 0.803 0.955 0.601 0.613 1.340 0.820 0.871 0.718 0.818

0.89 0.87 0.96 0.52 0.51 0.92 1.00 1.11 0.65 1.00

0.60 0.33 0.26 0 0 0 0 0 0 0

0.31 0.56 0.50 0.14 0.15 0.20 0.39 0.28 0.07 0.49

0.306 0.268 0.386 0.553 0.997 1.185 0.017 0.143 0.618 0.275

0.273 0.252 0.380 0.524 0.937 1.256 0.011 0.225 0.597 0.236

Cross-correlation matrix (r2) V E S A B

1.00 0.19 0.00 0.29 0.00

1.00 0.33 0.22 0.03

1.00 0.03 0.42

Model statistics

1.00 0.17

1.00

R ¼ 0.994 SE ¼ 0.07 F ¼ 570 n ¼ 40

System constants v ¼ 2.99 (0.07) e ¼ 0.46 (0.05) s ¼ 0.44 (0.05) a ¼ 0.30 (0.05) b ¼ 1.88 (0.08) c ¼ 1.82 (0.07)

formation in aqueous solution is the favorable free energy change accompanying segregation of the hydrocarbon-like portion of the surfactant from water by packing hydrocarbon groups into a central core surrounded by the polar head groups. Electrostatic repulsion between head groups in ionic micelles, and the steric repulsion of hydrated head groups in the case of nonionic micelles, oppose this favorable free energy change. 3.3.1

Affect of System Properties on Selectivity

Micelles are dynamic structures whose shape, size and aggregation number fluctuate with changes in the surrounding electrolyte solution [2,23]. The concentration of surfactant, the type and concentration of buffer, pH of the electrolyte solution and temperature are expected to influence retention and selectivity in micellar electrokinetic chromatography through their affect on micelle properties. A systematic study of these variables using the surfactant sodium cholate indicated significant changes in retention but only modest changes in selectivity, Table 3.4 [11]. Numerical differences in the system constants should be established as significant by application of a Student t-test on a case-by-case basis (standard error in the system constants is indicated by the values in parentheses). For the present, only significant general features in the data are discussed. Changes in surfactant concentration effects retention mainly through changes in the phase ratio (incorporated in the c term when the retention factor is the dependent variable) and to a lesser extent through changes in the difference in cohesion between the micelles and electrolyte solution (v system constant). The phase ratio is weakly affected by the choice of buffer and pH but not by the concentration of the buffer over the range studied.


63

Table 3.4 Affect of experimental variables on the system constants of the solvation parameter model for sodium cholate micelles in electrokinetic chromatography (a ¼ 0 for all conditions) Experimental variables

System constants

Electrolyte solution v Surfactant concentration Concentration (mM) (mM) Compositiona pH

e

s

b

c

50

20

SP þ SB

75

20

SP þ SB

125

20

SP þ SB

75

20

SP þ SB

75

20

SP þ SB

75

20

SP

75

20

SB

75

10

SP þ SB

75

30

SP þ SB

0.65 (0.09) 0.63 (0.08) 0.48 (0.07) 0.61 (0.07) 0.57 (0.08) 0.59 (0.06) 0.63 (0.07) 0.60 (0.07) 0.60 (0.07)

0.47 (0.10) 0.47 (0.09) 0.46 (0.08) 0.47 (0.08) 0.41 (0.09) 0.48 (0.07) 0.46 (0.08) 0.50 (0.08) 0.50 (0.08)

2.27 (0.13) 2.29 (0.13) 2.14 (0.12) 2.31 (0.12) 2.26 (0.13) 2.26 (0.11) 2.30 (0.13) 2.23 (0.13) 2.29 (0.12)

2.11 (0.13) 1.71 (0.12) 1.34 (0.10) 1.90 (0.11) 1.77 (0.12) 1.79 (0.10) 1.93 (0.11) 1.63 (0.11) 1.65 (0.11)

8

2.59 (0.13) 8 2.45 (0.12) 8 2.39 (0.10) 8.5 2.59 (0.11) 9.0 2.45 (0.12) 8 2.52 (0.10) 8 2.58 (0.11) 8 2.43 (0.11) 8 2.49 (0.11)

a

SP ¼ sodium phosphate and SB ¼ sodium tetraborate

Changes in selectivity are small compared with general retention for the range of experimental conditions explored. In fact selectivity can be considered a reasonably robust parameter that depends on the identity of the surfactant and to only a limited extent on the choice of operating conditions. For those conditions indicated in Table 3.4, the average and standard deviation for the system constants are vAV ¼ 2.50 ( 0.08), eAV ¼ 0.60 ( 0.05), sAV ¼ 0.47 ( 0.03), bAV ¼ 2.26 ( 0.05). The change in system constants with temperature is approximately 0.013 for v, 0.002 for e, 0.004 for s and 0.022 for b for each 1 C change over the temperature range 15 to 35 C. The a system constant is not statistically different from zero for all conditions. Larger effects might be observed at surfactant concentrations closer to the critical micelle concentration where fluctuations in micelle properties are expected to be larger, but these conditions are less likely to be used for method development than those indicated in Table 3.4. The system constants reported by several research groups for the same surfactant are expected to show greater variation than the reproducibility of results from a single group using a robust experimental design. To illustrate this point the system constants for sodium dodecyl sulfate micelles reported by different groups are collated in Table 3.5 [7,9,11,22,24–31]. The data shows no particular trends related to differences in experimental conditions, although in a number of cases the difference in individual system constants are significant at the 95 % confidence level. The central tendency is indicated

64


by the average value for each system constant and the dispersion by the standard deviation for all entries in Table 3.5. These values are: vAV ¼ 2.87 ( 0.14), eAV ¼ 0.39 ( 0.11), sAV ¼ 0.40 ( 0.13), aAV ¼ 0.21 ( 0.11) and bAV ¼ 1.80 ( 0.16). A significant amount of the observed variation probably results from a failure to select solutes that homogeneously fill the descriptor space, provide sufficient range for the dependent variable as well as failure to ensure that an exhaustive fit was obtained. Variation in experimental conditions is probably less important than variations in the statistical design of the studies. In the absence of other information the reported dispersion for the system constants in Table 3.4 (single group) and Table 3.5 (different groups) can be taken as an estimate of anticipated variation in compilations of system constants. 3.3.2

Anionic Surfactants

The system constants for a number of common anionic surfactants are summarized in Table 3.6 [11–13,22,27–29,32,33]. In general, the relative ease of cavity formation and dispersion interactions (v system constant) and electron lone pair interactions (e system constant) favor transfer to micelles from the electrolyte solution. Solute interactions of a dipole-type and hydrogen bonding are more favorable in the electrolyte solution, and oppose transfer to the micelles. An exception is the surfactant lithium perfluorooctanesulfonate, which has a positive s system constant, although literature values are in conflict (see Table 3.6). A single feature that stands out in Table 3.6 is the narrow range of v system constant values for all anionic surfactants. This is probably a reflection of the need for a minimum cohesive energy difference for aggregation of surfactant monomers. The solvation properties of the alkane sulfate and sulfonate micelles are not particularly sensitive to changes in the identity of the counterion or alkyl chain length [29,32]. For selectivity optimization there are only minor benefits in replacing sodium dodecyl sulfate with any of the other alkane sulfates and sulfonates in Table 3.6. The perfluorooctanesulfonate and N-alkyl-N-methyltaurine surfactants, however, afford a useful change in selectivity compared with sodium dodecyl sulfate [13,22]. Lithium perfluorooctanesulfonate has different selectivity for electron lone pair interactions (the only negative e system constant) and is the strongest hydrogen-bond acid and weakest hydrogen-bond base of all surfactants in Table 3.6. The N-alkyl-N-methyltaurine surfactants are about as dipolar and stronger hydrogen-bond bases and weaker hydrogen-bond acids than the other alkane sulfate micelles. The bile acids have similar solvation properties as a group with different selectivity to the alkane sulfates. They are more cohesive, stronger hydrogen-bond bases and weaker hydrogen-bond acids [11,12]. The N-alkylsarcosinates have similar solvation properties to the N-alkyl-N-methyltaurine surfactants. The dodecylcarboxylate and dodecylphosphate surfactants are slightly more hydrogen-bond basic than sodium dodecyl sulfate, and could be useful for optimizing the peak position of solutes with different hydrogenbond acidity [27,28,33]. It is clear from the results in Table 3.6 that both the identity of the surfactant head group and relatively small changes in structure in the region of the head group can affect selectivity for dipole-type and hydrogen-bond interactions. These changes in selectivity


65

Table 3.5 System constants for sodium dodecyl sulfate micelles determined for different experimental conditions (temperature ¼ 25 C) System constants c

Statistics

Conditions

(i) 50 mM sodium dodecyl sulphate 2.62 0.56 0.67 0.31 1.57 (0.07) (0.09) (0.07) (0.07) (0.08)

1.48 (0.07)

R ¼ 0.996 SE ¼ 0.07 F ¼ 517

2.99 (0.07)

0.46 (0.05)

0.44 (0.05)

0.30 (0.05)

1.88 (0.08)

1.82 (0.07)

R ¼ 0.994 SE ¼ 0.07

2.40 (0.09)

0.51 (0.05)

0.41 (0.07)

0.34 (0.08)

1.76 (0.08)

1.41 (0.06)

F ¼ 569 R ¼ 0.994 SE ¼ 0.10 F ¼ 507

2.98

0.35

0.43

0.02

2.02

1.76

R ¼ 0.993 SE ¼ 0.08 F ¼ 291

2.84 (0.09)

0.38 (0.11)

0.29 (0.13)

0.13 (0.08)

1.69 (0.14)

1.99 (0.12)

R ¼ 0.996 SE ¼ 0.08 F ¼ 445

Buffer ¼ 20 mM sodium phosphate pH ¼ 7 [9] n ¼ 26 Buffer ¼ 20 mM sodium phosphate -sodium tetraborate, pH ¼ 8 [11] n ¼ 40 Buffer ¼ 100 mM sodium tetraborate þ60 mM sodium phosphate, pH ¼ 7 n ¼ 38 [24] Buffer ¼ 20 mM sodium phosphate -sodium tetraborate, pH ¼ 8 [25] n ¼ 27 Buffer ¼ 20 mM Tris, pH ¼ 8, T ¼ 30 C [26] n ¼ 25

(ii) 40 mM sodium dodecyl sulfate 2.81 0.46 0.48 0.16 (0.09) (0.06) (0.07) (0.04)

1.71 (0.08)

1.78 (0.08)

2.72 (0.06)

0.56 (0.08)

0.60 (0.06)

0.27 (0.05)

1.67 (0.07)

1.68 (0.05)

2.95 (0.11)

0.19 (0.07)

0.30 (0.08)

0.17 (0.04)

1.84 (0.09)

1.80

2.86 (0.09)

0.25 (0.06)

0.31 (0.06)

0.15 (0.04)

1.70 (0.07)

1.85

Buffer ¼ 50 mM sodium phosphate pH ¼ 7 [7] n ¼ 59 R ¼ 0.991 Buffer ¼ 20 mM SE ¼ 0.12 sodium phosphate F ¼ 618 pH ¼ 7 [22] n ¼ 63 R ¼ 0.993 Buffer ¼ 10 mM SE ¼ 0.06 sodium phosphate pH ¼ 7 [27] n ¼ 36 R ¼ 0.995 Buffer ¼ 10 mM sodium phosphate pH ¼ 7 [28]

1.72 (0.08)

2.16 (0.06)

v

e

s

a

(iii) 30 mM sodium dodecyl sulfate 2.90 0.42 0.34 0.11 (0.07) (0.06) (0.04) (0.05)

b

R ¼ 0.991 SE ¼ 0.07 F ¼ 565

R ¼ 0.994 SE ¼ 0.06

Buffer ¼ 13 mM sodium phosphate pH ¼ 6.92 [29] n ¼ 36 (Continued)

66


Table 3.5 (Continued) System constants v

e

s

a

(iv) 20 mM sodium dodecyl sulfate 2.83 0.47 0.44 0.15 (0.09) (0.06) (0.07) (0.04)

b

c

Statistics

Conditions

1.71 (0.08)

2.17 (0.08)

R ¼ 0.991 SE ¼ 0.07 F ¼ 574

Buffer ¼ 50 mM sodium phosphate pH ¼ 7 [7] n ¼ 59

R ¼ 0.998 SE ¼ 0.06

Buffer ¼ 12.5 mM sodium phosphate –sodium tetraborate, pH ¼ 9.2 [30] n ¼ 18 Buffer 20 mM Tris pH ¼ 7 [31] n ¼ 20

(v)1.0–1.2 % (w/v) sodium dodecyl phosphate 2.74 0.27 0.37 0.23 1.82 1.65 (0.11) (0.08) (0.07) (0.13) (0.16) (0.11)

F ¼ 479 3.17 (0.11)

0.37 (0.06)

0.32 (0.09)

0.31 (0.05)

2.19 (0.13)

2.16 (0.68)

R ¼ 0.998 SE ¼ 0.05 F ¼ 520

are probably determined by the amount of water attracted into the interphase region as a result of the modification of the surfactant structure [22,23,28]. 3.3.3

Cationic Surfactants

System constants for tetradecyltrimethylammonium and hexadecyltrimethylammonium bromide micelles are summarized in Table 3.7 [11–13,22]. They afford complementary selectivity to the anionic surfactants described in Table 3.6. They are about as cohesive and dipolar as the anionic surfactants but are stronger hydrogen-bond bases and among the weakest hydrogen-bond acids of all surfactants studied. 3.3.4

Mixed Surfactant Micelles

The separation characteristics of single surfactant micelles can be modified by forming mixed micelles using surfactants with different solvation properties. Surfactants with a zero net charge, such as nonionic and zwitterionic surfactants, unsuitable for use on their own, when added to an ionic surfactant, form mixed surfactant micelles with an overall net charge and adjustable selectivity. Variation of the mole fraction ratio of nonionic surfactant Brij 35 (polyoxyethylene(23)dodecyl ether) on the selectivity of the mixed surfactant micelles formed with sodium dodecyl sulfate [25,34] or sodium N-dodeconyl-N-methyltaurine [35] produced similar trends, Figure 3.1. The addition of Brij 35 resulted in little change in cohesion of the micelles or the relative importance of dipole-type and electron lone pair interactions. Changes in selectivity resulted mainly from variation in hydrogen bonding interactions, particularly hydrogen-bond basicity at low mole fractions of Brij 35. These trends in selectivity conformed to predictions by the interfacial retention model [24,34,35]. Lithium dodecyl sulfate and lithium perfluorooctanesulfonate mixed micelles have also been studied in some detail, Table 3.8 [36,37]. Changes in the hydrogen-bonding system constants were virtually linear with an increase in the mole fraction of lithium perfluorooctanesulfonate while the other system constants show a quadratic dependence.


67

Table 3.6 System constant ratios from the solvation parameter model for anionic surfactants (temperature ¼ 20–25 C except were noted) System constant ratios Surfactant (i) Alkane sulfates and sulfonates Sodium octyl sulfate Sodium decyl sulfate Sodium dodecyl sulfate (36 C) Lithium dodecyl sulfate (35 C) Magnesium dododecyl sulfate (35 C)Mg(DS)2 Copper dododecyl sulfate (35 C) Tris(hydroxymethyl)aminomethane dodecyl sulfate Sodium dodecyl sulfonate (36 C) Sodium tetradecyl sulfate (35 C) Lithium perfluorooctanesulfonate

Abbreviation v SOS SDecS SDS

3.3.5

b/v Reference [29] [29] [11] [28] [22] [32] [32]

Cu(DS)2

3.05 0.11 0.17 0.09 0.63 2.56 0.22 0.26 0.13 0.62

[32] [12]

SDSu STS LPFOSu

2.84 0.12 3.01 0.09 2.36 0.29 2.30 0.23 1.97 0.06 2.88 0.18 3.07 0.23

0.15 0.01 0.63 0.11 0.06 0.60 0.19 0.34 0.26 0.15 0.36 0.23 0.12 0.45 0.23 0.12 0.14 0.82 0.16 0.07 0.84

[28] [33] [13] [12] [22] [27] [11]

2.45 2.67 2.43 2.62

0.26 0.25 0.25 0.26

0.19 0.18 0.14 0.17

0 0 0 0

0.93 0.93 0.85 0.83

[11] [11] [11] [11]

3.02 2.99 3.10 2.92

0.13 0.16 0.14 0.15

0.11 0.14 0.15 0.13

0.16 0.77 0.15 0.82 0.15 0.83 0.17 0.83

[33] [33] [33] [27]

2.99 2.96 3.01 2.96

0.14 0.05 0.08 0.16

0.19 0.13 0.18 0.13

0.05 0.81 0.08 0.60 0.05 0.66 0.04 0.82

[28] [28] [28] [28]

Sodium N-lauroyl-N-methyltaurine SLMT Sodium N-dodecanoyl-NSDMT methyltaurine (ii) Bile acids Sodium cholate SC Sodium deoxycholate SDC Sodium taurocholate STC Sodium taurodeoxycholate STDC (iii) Miscellaneous anionic surfactants Sodium N-lauroylsarcosinate SLN Sodium N-myristoylsarcosinate SMN Sodium N-parmitoylsarcosinate SPN Sodium N-lauroyl-N-methylALE b-alaninate Sodium dodecoxycarbonylvaline SDCV Sodium dodecylcarboxylate (36 C) SDCA Sodium dodecylphosphate (36 C) SDP Sodium lauryl sulfoacetate (36 C) SLSA

0.16 0.12 0.12 0.09 0.22 0.10 0.09

s/v a/v

0.11 0.04 0.66 0.09 0 0.59 0.14 0.08 0.64 0.11 0.05 0.59 0.23 0.12 0.60 0.12 0.07 0.59 0.14 0.09 0.62

LDS

2.85 2.69 2.98 2.86 2.61 3.01 3.02

e/v

Addition of Organic Solvents

Typical water miscible organic solvents (e.g. short chain alcohols, acetonitrile) are known to increase the critical micelle concentration of surfactants and at sufficiently high concentrations inhibit micelle formation [2,23,35,38,39]. Instability of the micelles restricts the range of normal composition variation to 25 % (v/v) organic solvent. Changes in selectivity are consistent with the view that organic solvents moderate the characteristic solvophobic properties of the electrolyte solution and barely interact with the micelles. Some typical results are illustrated in Figure 3.2 [35]. Increasing the volume fraction of

68


Table 3.7 System constant ratios from the solvation parameter model for cationic surfactants (temperature ¼ 20–25 C) System constant ratios Surfactant

Abbreviation v

Tetradecyltrimethyl-ammonium TTAB bromide

2.90 2.82 2.63 3.40 2.71

Hexadecyltrimethyl-ammonium CTAB bromide

e/v

s/v

a/v

b/v

0.10 0.13 0.34 0.18 0.41

0.07 0.10 0.23 0.16 0.28

0.29 0.32 0.29 0.17 0.30

0.91 0.95 0.92 0.91 0.90

Reference [13] [12] [22] [11] [22]

4

System constants

v 2 e a s c

0 –2

b –4 0

10

20

30

40

50

Brij 35 (mM)

Figure 3.1 Variation of the system constants for mixed surfactant micelles formed by adding 0–50 mM nonionic surfactant Brij 35 to 50 mM sodium dodecyl sulfate in a 20 mM sodium phosphate and sodium tetraborate pH ¼ 8 buffer (Brij 35: 0–20 mM) or 20 mM sodium phosphate pH ¼ 7 buffer (Brij 35: 25–50 mM). (Plotted from data given in Ref. [34])

Table 3.8 System constants for mixed micelles formed by adding lithium perfluorooctanesulfonate to lithium dodecyl sulfate (40 mM total surfactant, 20 mM lithium phosphate buffer, pH ¼ 7, T ¼ 25 C). (Data from [36]) Mole fraction LPFOSu a

0

0.25 0.50 0.75 1.00a a

System constants v 2.81 (0.09) 2.74 (0.07) 2.64 (0.07) 2.45 (0.08) 2.20 (0.08)

e 0.36 (0.10) 0.27 (0.08) 0.16 (0.08) 0.02 (0.09) 0.25 (0.09)

s 0.43 (0.07) 0.41 (0.06) 0.31 (0.06) 0.16 (0.06) 0 (0.07)

a 0.20 (0.06) 0.37 (0.05) 0.58 (0.05) 0.76 (0.05) 0.92 (0.06)

Different values for the system constants for the single surfactants are reported in [37].

b 1.54 (0.11) 1.20 (0.10) 0.85 (0.09) 0.45 (0.10) 0 (0.11)

c 1.78 (0.08) 1.79 (0.07) 1.85 (0.06) 1.90 (0.07) 1.90 (0.08)


69

System constants

4 v

2

e a s c

0

–2

b

–4 0

5

10

15

20

Acetonitrile (%v/v)

Figure 3.2 Variation of the system constants for the mixed surfactant micelles formed by adding 20 mM Brij 35 to 50 mM sodium N-dodeconyl-N-methyltaurine in an electrolyte solution containing 0–20 % (v/v) acetonitrile. (Plotted from data given in Ref. [35])

acetonitrile reduces retention by lowering the difference in cohesion between the micelles and electrolyte solution and by increasing the hydrogen-bond acidity of the micelles relative to the electrolyte solution. Higher mass alcohols, alkyl polyols and neutral polar compounds, in contrast to typical water soluble solvents, are solubilized by the micelles forming mixed micelles with properties similar to mixed surfactant micelles [26,40,41].

3.4 Microemulsions A microemulsion consists of a homogeneous dispersion of charged oil droplets in an aqueous electrolyte [2,42,43]. They are formed from an organic solvent of low water solubility (e.g. octane, heptane, diethyl ether, octanol, etc.), a charged surfactant (e.g. sodium dodecyl sulfate) and a cosurfactant (e.g. butanol, 2-ethoxyethanol, tetrahydrofuran) in an aqueous buffer. The organic solvent and cosurfactant form the core of the droplet solvating a part of the hydrophobic portion of the surfactant with its charged head group located in the electrolyte solution. Stable microemulsions are formed over a narrow composition range for the main components, although a variety of cosurfactants and anionic and cationic surfactants alone or mixed with zwitterionc and nonionic surfactants can be used. The concentration and type of organic solvent chosen to form the oil drop, plays only a minor role in controlling selectivity compared with the concentration and identity of the surfactant and cosurfactant [44,45]. The microemulsion formed by 0.8 % (w/w) n-octane, 6.6 % (w/w) n-butanol, 3.3 % (w/w) sodium dodecyl sulfate and 89.3 % (w/w) of 10–20 mM pH 8.5–9.5 borate or phosphate buffer accounts for most of the practical applications of microemulsions in electrokinetic chromatography. System constants for this microemulsion at several pH values are summarized in Table 3.9 [3,46,47]. An important application of this microemulsion is the estimation of the octanol–water partition coefficient for neutral compounds owing to the strong correlation of the partition properties of the microemulsion with those of wet octanol [3,47].

0.34 (0.10) 0.56 (0.13)

2.24 (0.07) 3.09 (0.18) 2.85 (0.16)

pH ¼ 10

40 mM bis(2-ethylhexyl) sodium sulfosuccinate þ10 % (v/v) methanol 1.8 % (w/w) sodium octylsulphate and hexadecyltrimethylammonium bromide (7:3)

0.37 (0.04)

0.31 (0.06)

2.39 (0.09)

pH ¼ 8

0.41 (0.06)

0.28

e

2.16 (0.10)

3.05

v

pH ¼ 3

1.4 % (w/v) sodium dodecyl sulfate þ 8 % (v/v) n-butanol þ 1.2 % (v/v) n-heptane pH ¼ 7

System

0.57 (0.12)

0.43 (0.13)

0.51 (0.05)

0.52 (0.06)

0.50 (0.06)

0.69

s

0.23 (0.09)

0.02 (0.10)

0

0

0

0.06

a

System constants

3.25 (0.18)

3.02 (0.19)

1.97 (0.07)

2.26 (0.08)

2.01 (0.09)

2.81

b

Table 3.9 System constants for microemulsion and vesicle electrokinetic chromatography

1.52

1.82

0.85 (0.05)

0.87 (0.06)

0.91 (0.07)

1.13

c

R ¼ 0.989 n ¼ 39

R ¼ 0.994 SE ¼ 0.09 F ¼ 792 n ¼ 53 R ¼ 0.984 SE ¼ 0.14 F ¼ 283 n ¼ 42 R ¼ 0.985 SE ¼ 0.16 F ¼ 363 n ¼ 51 R ¼ 0.990 SE ¼ 0.12 F ¼ 471 n ¼ 45 R ¼ 0.987 n ¼ 43

Statistics

[48]

[48]

[47]

[47]

[47]

[46]

Reference


71

3.5 Vesicles Vesicles, self-assembling structures that contain a continuous bilayer of monomers enclosing an aqueous core, can be synthesized using surfactants with structures containing two alkyl chains and a polar head group, or by using a mixtures of single chain cationic and anionic surfactants under appropriate conditions. System constants for the vesicles formed by 40 mM bis(2-ethylhexyl)sodium sulfosuccinate and methanol (10 % v/v) in 10 mM phosphate pH 7 buffer and hexadecyltrimethylammonium bromide and sodium octyl sulfate (30:70 mole ratio, total mass 1.8 % w/w) in 50 mM phosphate pH 7 buffer are summarized in Table 3.9. These vesicles were shown to have partition properties suitable for use as correlation models for the estimation of octanol–water partition coefficients [48]. In this respect their selectivity is similar to the sodium dodecyl sulfate, n-butanol and n-heptane microemulsion in Table 3.9, which is a better model for the estimation of octanol–water partition coefficients [3].

3.6 Polymeric Pseudostationary Phases Typical polymeric pseudostationary phases include micelle polymers, polymeric surfactants, and water-soluble anionic siloxanes and dendrimers [49,50]. Micelle polymers [e.g. poly(sodium 10-undecylenate), poly(sodium 10-undecenylsulfate), etc.] are synthesized from polymerizable surfactant monomers at a concentration above their critical micelle concentration [30,51]. These polymers have similar structures to surfactant micelles without the dynamic nature. Polymeric surfactants are polymers with surfactant properties [e.g. acrylate copolymers, polybrene, etc.] [31,52]. Water-soluble anionic siloxane polymers are copolymers of alkylmethylsiloxane and methylsiloxane monomers containing ionic groups [53,54]. Polymeric micelles form stable pseudostationary phases with a critical micelle concentration of virtually zero (aggregation number of 1), and are tolerant of high organic solvent concentrations in the electrolyte solution. The system constants for 34 polymeric pseudostationary phases are summarized in Table 3.10 [30,31,51–55]. The models for polybrene and PDADMA seem unlikely in chemical terms and present poor statistics [51]. They are not discussed further. The polymeric pseudostationary phases have similar cohesion to surfactant micelles, except for the anionic siloxane polymers, which are more cohesive as a group than either the surfactant micelles or acrylate copolymers. Electron lone pair interactions favor transfer to the polymeric pseudostationary phases similar to surfactant micelles. The polymeric pseudostationary phases, except for poly(Na 11-AAU), have weak dipole-type interactions that favor solvation in the electrolyte solution. Some polymer pseudostationary phases have much weaker dipole-type interactions than do typical surfactant micelles, representing a significant difference in selectivity. The polymeric pseudostationary phases exhibit a wide range of hydrogen bonding properties. Some are significantly stronger hydrogen-bond bases than the electrolyte solution, not unlike typical alkylcarboxylate and tetraalkylammonium surfactant micelles. All of the polymeric pseudostationary phases are weaker hydrogen-bond acids than the electrolyte solution, with some of the anionic siloxane polymers among the weakest hydrogen-bond acids observed for pseudostationary phases in electrokinetic chromatography.

72


Table 3.10 System constants for polymeric pseudostationary phases used in electrokinetic chromatography System constants System

v

e

s

a

b

c

References

1.18 (0.17) 1.05 (0.13) 0

2.28 (0.11) 1.86 (0.09) 0.09

0

0.81

[51]

3.86 (0.91) 2.91 (0.22) 3.40 (0.20) 3.15 (0.17) 2.84 (0.23) 3.58 (0.26) 3.36 (0.16) 3.39 (0.13) 3.17 (0.16) 3.65 (0.18) 3.76 (0.15) 3.78 (0.21) 2.88 (0.13) 3.39 (0.13) 2.07 (0.2) 1.71 (0.2) 1.76 (0.1) 2.21 (0.3) 2.06 (0.3) 1.34 (0.3)

0.19 (0.05) 0.11 (0.07) 0.04 (0.10) 0.24 (0.09) 0.23 (0.08) 0

0

Poly( sodium undecenylsulfate) pDHCHAt-2-Nae

0.45 (0.08) 0.18 (0.06) 0.35 (0.02) 0.35 (0.07) 0.44 (0.66) 0.60 (0.19) 0.46 (0.17) 0.40 (0.15) 0.32 (0.20) 0.40 (0.22) 0.44 (0.14) 0.53 (0.11) 0.32 (0.09) 0.67 (0.16) 0.69 (0.13) 0.85 (0.18) 0.32 (0.11) 0.53 (0.11) 0.07 (0.1) 0.22 (0.1) 0.38 (0.08) 0.90 (0.2) 1.08 (0.2) 1.05 (0.2)

0.15 (0.13) 0.27 (0.11) 0

PDADMAd

0.18 (0.08) 0.26 (0.06) 0.75 (0.06) 0.75 (0.06) 0

[30]

Polybrenec

1.64 (0.11) 2.11 (0.09) 0

1.39 (0.75) 2.58 (0.28) 3.21 (0.25) 3.19 (0.21) 2.75 (0.28) 3.52 (0.32) 3.22 (0.20) 3.05 (0.16) 2.19 (0.13) 3.70 (0.22) 3.87 (0.19) 3.83 (0.26) 2.45 (0.16) 3.05 (0.16) 1.93 (0.2) 2.36 (0.2) 1.90 (0.1) 2.53 (0.2) 2.29 (0.2) 1.96 (0.2)

2.79

[51]

3.11 (0.20) 2.68 (0.18) 3.15 (0.15) 3.25 (0.20) 2.96 (0.23) 2.86 (0.14) 2.57 (0.12) 2.16 (0.68) 2.84 (0.16) 2.73 (0.14) 2.73 (0.19) 2.69 (0.11) 2.57 (0.12) 2.81 (0.2) 2.37 (0.2) 1.96 (0.1) 1.51 (0.2) 1.65 (0.22) 1.29 (0.3)

[52]

Poly(Na 11-AAU)

a

Poly(Na 10-U)b

pDHCHAt-33-TEAf pLAt-9.2-TEAg pLAt-9-Nah pLAt-13-Nah ptOAm-49-Nai pSAm-28-Naj pOMAt-21k pLMAt-15l pSMAt-13m pSMAt-16m pLMAm-19n pSAm-28o AGENTp OAGENT (10 % C8)q OAGENT (15 % C8)q OAGENT (20 % C8)q OAGENT (25 % C8)q DAGENT (10 % C12)r

0.61 (0.13) 0.65 (0.12) 0.50 (0.10) 0.34 (0.14) 0.39 (0.15) 0.33 (0.10) 0.42 (0.08) 0.37 (0.06) 0.44 (0.11) 0.42 (0.09) 0.65 (0.13) 0.37 (0.13) 0.42 (0.12) 0.76 (0.1) 0.54 (0.1) 0.46 (0.07) 0.49 (0.2) 0.71 (0.1) 0.58 (0.2)

0.02 (0.12) 0.43 (0.08) 0.19 (0.06) 0.31 (0.05) 0.27 (0.08) 0.22 (0.07) 0.50 (0.10) 0.25 (0.06) 0.19 (0.06) 0.45 (0.09) 0.25 (0.08) 0.20 (0.05) 0.11 (0.1) 0.11 (0.1) 0.51 (0.1)

[30] [51]

[52] [52] [31] [52] [52] [52] [31] [31] [31] [31] [31] [31] [53] [53] [53] [53] [53] [53]


73

Table 3.10 (Continued) System constants System

v

e

s

a

b

c

References

DAGENT (15 % C12)r

2.46 (0.3) 2.39 (0.2) 1.49 (0.2) 1.22 (0.2) 2.51 (0.3) 1.33 (0.3) 2.49 (0.4) 2.04 (0.2) 2.72 (0.1) 2.25 (0.23)

0.32 (0.2) 0.59 (0.1) 0.16 (0.1) 0.20 (0.2) 0.63 (0.2) 0.57 (0.2) 0.31 (0.2) 0.40 (0.1) 0.46 (0.06) 0.30 (0.16)

0.86 (0.2) 0.78 (0.1) 0.57 (0.2) 0.65 (0.2) 1.14 (0.2) 1.06 (0.2) 0.88 (0.3) 0.17 (0.1) 0.43 (0.08) 0.08 (0.18)

0.21 (0.1) 0.23 (0.07) 0.01 (0.09) 0.05 (0.09) 0.33 (0.1) 0.51 (0.1) 0.21 (0.1) 0.24 (0.08) 0.27 (0.04) —

2.38 (0.3) 2.42 (0.2) 2.00 (0.2) 1.65 (0.2) 2.64 (0.3) 1.95 (0.3) 2.40 (0.3) 2.09 (0.09) 2.46 (0.09) 2.18 (0.29)

1.84 (0.3) 1.98 (0.2) 1.51 (0.2) 1.23 (0.2) 1.75 (0.3) 1.26 (0.3) 1.83 (0.3) 2.50 (0.2) 2.40 (0.1) 1.86

[53]

DAGENT (20 % C12)r SAGENT (10 % C18)s SAGENT (15 % C18)s SAGENT (20 % C18)s C12AGENT-10t C12AGENT-15t C12AGESS-8u C12AGESS-13u Elvacite 2669v a

[53] [53] [53] [53] [54] [54] [54] [54] [55]

Poly(sodium 11-acrylamidoundecanoate) Poly(sodium 11-undecylenate) Poly(N,N,N0 ,N0 -tetramethyl-N-trimethylenehexamethylenediammonium) dibromide d Poly(diallyldimethylammonium) bromide e Poly(sodium dihydrocholesteryl acrylate-co-2-acrylamido-2-methyl-1-propane sulfate) containing 2 % dihydrocholesteryl acrylate monomer f Poly(triethylammonium dihydrocholesteryl acrylate-co-2-acrylamido-2-methyl-1-propane sulfate) containing 33 % dihydrocholesteryl acrylate monomer g Poly(triethylammonium lauryl acrylate-co-2-acrylamido-2-methyl-1-propane sulfate) containing 9.2 % lauryl acrylate monomer h Poly(sodium lauryl acrylate-co-2-acrylamido-2-methyl-1-propane sulfate) containing 9 or 13 % lauryl acrylate monomer i Poly(sodium t-octyl acrylamide-co-2-acrylamido-2-methyl-1-propane sulfate) containing 49 % t-octyl acrylamide monomer j Poly(sodium stearylacrylamide-co-2-acrylamido-2-methyl-1-propane sulfate) containing 28 % stearylacrylamide monomer k Poly(sodium octyl methacrylate-co-2-acrylamido-2-methyl-1-propane sulfate) containing 21 % octyl methacrylate monomer l Poly(sodium lauryl methacrylate-co-2-acrylamido-2-methyl-1-propane sulfate) containing 15 % lauryl methacrylate monomer m Poly(sodium stearyl methacrylate-co-2-acrylamido-2-methyl-1-propane sulfate) containing 13 % or 16 % stearyl methacrylate monomer n Poly(sodium lauryl methacrylamide-co-2-acrylamido-2-methyl-1-propane sulfate) containing 19 % lauryl methacrylamide monomer o Poly(sodium steryl methacrylamide-co-2-acrylamido-2-methyl-1-propane sulfate) containing 28 % steryl methacrylamide monomer p Poly(allyl gycidyl ether N-methyltaurine siloxane) q Poly(octane allyl glycidyl ether N-methyltaurine siloxane) r Poly(dodecane allyl glycidyl ether N-methyltaurine siloxane) s Poly(steryl allyl glycidyl ether N-methyltaurine siloxane) t Poly(allyl gycidyl ether N-methyltaurine siloxane-co-dodecylmethylsiloxane) containing 10 or 15 % of dodecylmethylsiloxane monomer u Poly(allyl gycidyl ether sulfonate siloxane-co-dodecylmethylsiloxane) containing 8 or 13 % of dodecylmethylsiloxane monomer v Poly(methyl methacrylate–ethyl acrylate–methylacrylic acid). None of the solutes used to evaluate this polymer were hydrogen-bond acids. b c

74


Often large changes in the selectivity for polymeric pseudostationary phases have been observed for incremental changes in chain length or monomer composition that are not easy to explain. A possible contributing factor is steric hindrance of polar functional groups and changes in hydration of the polymers as a result of alterations in composition of the polymer backbone and substituent chain lengths. Consequently, the best approach for the design of polymeric pseudostationary phases with specific selectivity is unclear at this time. The phase ratios for several polymeric pseudostationary phases (c term in Table 3.10) are unfavorable for optimum retention of typical small molecules separated by electrokinetic chromatography. On the other hand, the range of selectivity observed for polymeric pseudostationary phases is greater than for surfactant micelles, suggesting that further exploration could result in the identification of useful materials if other kinetic and sample loading problems were overcome.

3.7 Selectivity Equivalence of Surfactant Micelles and Other Chromatographic and Biopartitioning Systems The solvation parameter model provides a suitable framework to identify separation techniques with similar properties and surrogate chromatographic models for biopartitioning (and similar difficult-to-study) processes [3,4,15,56–58]. For two processes to emulate each other they would need to have identical system constants. This requirement is quite restrictive and there are no reported successes for systems of interest. Two models will be correlated, however, when the ratio of their system constants (e/v, s/v, a/v and b/v) are (nearly) identical. An outstanding example of this approach for property estimates was the identification of the microemulsion system in Table 3.9 as a suitable model for the high-throughput determination of octanol–water partition coefficients, a widely used measure of lipophilicity in quantitative structure–activity relationships [3,47]. Data base searches of system constant ratios affords the tools for identification of suitable chromatographic models to study biopartitioning processes in a straightforward manner, eliminating the need for inspired guesswork. Data base searches can be made across techniques adding to the flexibility of this approach. For example, data base searches indicated that several microemulsion and micellar electrokinetic chromatography systems would provide suitable models for determining octanol–water partition coefficients but few reversed-phase liquid chromatographic systems would be suitable for this measurement, accounting for the difficulty of identifying reversed-phase liquid chromatographic techniques for this purpose [3,59]. Searching across available data bases also indicates that in general, the selectivity of micellar electrokinetic chromatography and reversed-phase liquid chromatography are largely complementary with limited overlap. Strong similarities exist between the separation properties of immobilized artificial membrane columns and micellar electrokinetic chromatography [60] but not between conventional octadecylsiloxane-bonded silica columns and micellar electrokinetic chromatography.

3.8 Conclusions The solvation parameter model is a useful tool for characterizing selectivity of pseudostationary phases for EKC. A comparison of system constants allows redundant


75

pseudostationary phases with similar separation properties to be identified for elimination and a manageable number of pseudostationary phases with suitable selectivity differences identified for selectivity optimization in method development [4,12,22,23]. Selectivity optimization is facilitated by simulation for solutes with known or estimated descriptors for all pseudostationary phases with established system constants. The retention factors are estimated by simple calculations and the predicted selectivity factors ranked in order of usefulness or displayed as a window diagram. For mixed micelles or micelle buffers containing additives retention factors, and therefore selectivity factors, can be simulated as a continuous function of the second component to optimize the composition of the pseudostationary phase for target compound separations [4,25,34–37]. A powerful feature of the solvation parameter model for method development is that it allows simulation of selectivity by gas, liquid and electrokinetic chromatography for target compounds with equal facility, thus allowing the unbiased selection of the preferred separation mode. Beyond method development, the solvation parameter model provides insight into the physical processes responsible for retention and is able to contribute to the development of new pseudostationary phases with desirable properties to extend the selectivity range of available materials.

References [1] M.H. Abraham, A. Ibrahim and A.M. Zissimos. Determination of sets of solute descriptors from chromatographic measurements, J. Chromatogr. A., 1037, 29–47 (2004). [2] C.F. Poole, The Essence of Chromatography, Elsevier, Amsterdam, 2003. [3] S.K. Poole and C.F. Poole. Separation methods for estimating octanol–water partition coefficients, J. Chromatogr. B, 797, 3–19 (2003). [4] C.F. Poole and S.K. Poole. Column selectivity from the perspective of the solvation parameter model, J. Chromatogr. A., 965, 263–299 (2002). [5] C.F. Poole, A.D. Gunatilleka and R. Sethuraman. Contributions of theory to method development in solid-phase extraction, J. Chromatogr. A., 885, 17–39 (2000). [6] M.H. Abraham, C.F. Poole and S.K. Poole. Classification of stationary phases and other materials by gas chromatography. J. Chromatogr. A., 842, 79–114 (1999). [7] S. Yang and M.G. Khaledi. Chemical selectivity in micellar electrokinetic chromatography: characterization of solute–micelle interactions for classification of surfactants, Anal. Chem., 67, 499–510 (1995). [8] S. Yang, J.G. Bumgarner and M.G. Khaledi. Chemical selectivity in micellar electrokinetic chromatography II. Rationalization of elution patterns in different surfactant systems, J. Chromatogr. A., 738, 265–274 (1996). [9] P.G. Muijselaar, H.A. Claessens and C.A. Cramers. Characterization of pseudostationary phases in micellar electrokinetic chromatography by applying linear solvation energy relationships and retention indexes, Anal. Chem., 69, 1184–1191 (1997). [10] Z. Liu, H. Zou, M. Ye, J. Ni and Y. Zhang. Effect of organic modifiers on retention mechanism and selectivity in micellar electrokinetic capillary chromatography studied by linear solvation energy relationships, J. Chromatogr. A., 863, 69–79 (1999). [11] S.K. Poole and C.F. Poole. Characterization of surfactant selectivity in micellar electrokinetic chromatography, Analyst, 122, 267–274 (1997). [12] C.F. Poole, S.K. Poole and M.H. Abraham. Recommendations for the determination of selectivity in micellar electrokinetic chromatography, J. Chromatogr. A., 798, 207–222 (1998).

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[13] M.D. Trone and M.G. Khaledi. Statistical evaluation of linear solvation energy relationship models used to characterize chemical selectivity in micellar electrokinetic chromatography, J. Chromatogr. A., 886, 245–257 (2000). [14] M.H. Abraham and J.C. McGowan. The use of characteristic volumes to measure cavity terms in reversed-phase liquid chromatography, Chromatographia, 23, 243–246 (1987). [15] M.H. Abraham. Scales of solute hydrogen-bonding: Their construction and application to physicochemical and biochemical processes, Chem. Soc. Revs., 22, 73–83 (1993). [16] M.H. Abraham, G.S. Whitting, R.M. Doherty and W.J. Shuely. Hydrogen bonding. Part 13. A new method for the characterization of GLC stationary phases – the Laffort data set, J. Chem. Soc. Perkin Trans 2, 1451–1460 (1990). [17] J.A. Platts, D. Butina, M.H. Abraham and A. Hersey. Estimation of molecular free energy relation descriptors using a group contribution approach, J. Chem. Inf. Comput. Sci., 39, 835– 845 (1999). [18] M.H. Abraham, P.L. Grellier, D.V. Prior, P.P. Duce, J.J. Morris and P.J. Taylor. Hydrogen bonding, Part 7. A scale of solute hydrogen-bond acidity based on log K values for complexation in tetrachloromethane, J. Chem. Soc. Perkin Trans. 2, 699–711 (1989). [19] M.H. Abraham, P.L. Grellier, D.V. Prior, J.J. Morris and P.J. Taylor. Hydrogen bonding, Part 10. A scale of solute hydrogen-bond basicity using log K values for complexation in tetrachloromethane, J. Chem. Soc. Perkin Trans. 2, 521–529 (1990). [20] A.M. Zissimos, M.H. Abraham, M.C. Barker, K.J. Box and K.Y. Tam. Calculation of Abraham descriptors from solvent–water partition coefficients in four different systems; evaluation of different methods of calculation, J. Chem. Soc. Perkin Trans. 2, 470–477 (2002). [21] M.A. Garcia, M.L. Marina and J.C. Diez-Masa. Determination of solute–micelle association constants for a group of benzene derivatives and polycyclic aromatic hydrocarbons with sodium dodecyl sulfate by micellar electrokinetic chromatography, J. Chromatogr. A., 732, 345–359 (1996). [22] E. Fuguet, C. Rafols, E. Bosch, M.H. Abraham and M. Roses. Solute–solvent interactions in micellar electrokinetic chromatography III. Characterization of the selectivity of micellar electrokinetic chromatography systems, J. Chromatogr. A., 942, 237–248 (2002). [23] C.F. Poole and S.K. Poole. Interphase model for retention and selectivity in micellar electrokinetic chromatography, J. Chromatogr. A., 792, 89–104 (1997). [24] B.J. Herbert and J.G. Dorsey. n-Octanol–water partition coefficient estimation by micellar electrokinetic chromatography, Anal. Chem., 67, 744–749 (1995). [25] M. Roses, C. Rafols, E. Bosch, A.M. Martinez and M.H. Abraham. Solute–solvent interactions in micellar electrokinetic chromatography. Characterization of sodium dodecyl sulfate-Brij 35 micellar systems for quantitative structure–activity relationship modelling, J. Chromatogr. A., 845, 217–226 (1999). [26] W.E. Wall, D.J. Allen, K.D. Denson, G.I. Love and J.T. Smith. Exploration of alkyl polyols as ‘class I’ organic modifiers to adjust selectivity in micellar electrokinetic capillary chromatography, Electrophoresis, 20, 2390–2399 (1999). [27] M.D. Trone and M.G. Khaledi. Influence of ester and amide-containing surfactant headgroups on selectivity in micellar electrokinetic chromatography, Electrophoresis, 21, 2390–2396 (2000). [28] M.D. Trone and M G. Khaledi. Characterization of chemical selectivity in micellar electrokinetic chromatography, 4. Effect of surfactant headgroup, Anal. Chem. 71, 1270–1277 (1999). [29] M.F. Vitha and P.W. Carr. A linear solvation energy relationship study of the effects of surfactant chain length on the chemical interactions governing retention and selectivity in micellar electrokinetic capillary chromatography using sodium alkyl sulfate elution buffers, Sep. Sci. Technol., 33, 2075–2100 (1998).


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[30] C. Fujimoto. Application of linear solvation energy relationships to polymeric pseudostationary phases in micellar electrokinetic chromatography, Electrophoresis, 22, 1322–1329 (2001). [31] W. Shi, D.S. Peterson and C.P. Palmer. Effect of pendent chains and backbone functionalities on the chemical selectivity of sulfonated amphiphilic copolymers as pseudo-stationary phases in electrokinetic chromatography, J. Chromatogr. A., 924, 123–135 (2001). [32] M.D. Trone, J.P. Mack, H.P. Goodell and M.G. Khaledi. Characterization of chemical selectivity in micellar electrokinetic chromatography VI. Effects of surfactant counter-ion, J. Chromatogr. A., 888, 229–240 (2000). [33] M.D. Trone and M.G. Khaledi. Characterization of chemical selectivity in micellar electrokinetic chromatography, V. The effect of the surfactant hydrophobic chain, J. Microcol. Sep., 12, 433–441 (2000). [34] S.K. Poole and C.F. Poole. Variation of selectivity with composition for a mixed-micellar buffer in micellar electrokinetic chromatography, J. High Res. Chromatogr. 20, 174–178 (1997). [35] S.K. Poole and C.F. Poole. Influence of composition on the selectivity of a mixed-micellar buffer in micellar electrokinetic chromatography, Anal. Commun., 34, 57–62 (1997). [36] E. Fuguet, C. Rafols, E. Bosch, M. Roses and M.H. Abraham. Solute–solvent interactions in micellar electrokinetic chromatography. Selectivity of lithium dodecyl sulfate–lithium perfluorooctanesulfonate mixed-micellar buffers, J. Chromatogr. A., 907, 257–265 (2001). [37] E. Fuguet, C. Rafols, J.R. Torres-Lapasio, M.C. Garcia-Alvarez-Coque, E. Bosch and M. Roses. Solute–solvent interactions in micellar electrokinetic chromatography, 6. Optimization of the selectivity of lithium dodecyl sulfate–lithium perfluorooctanesulfonate mixed micellar buffers, Anal. Chem., 74, 4447–4455 (2002). [38] K. Sarmini and E. Kendler. Influence of organic solvent on separation selectivity in capillary electrophoresis, J. Chromatogr. A., 792, 3–12 (1997). [39] R.M. Selfar, J.G. Kraak and W. Th. Kok. Mechanism of electrokinetic separations of hydrophobic compounds with sodium dodecyl sulfate in acetonitrile–water mixtures, Anal. Chem., 69, 2772–2778 (1997). [40] S. Katsuta and K. Saitoh. Control of separation selectivity in micellar electrokinetic chromatography by modification of the micellar phase with solubilized organic compounds, J. Chromatogr. A., 780, 165–178 (1997). [41] C.F. Poole. Relationship between liquid–liquid distribution and liquid–micelle distribution systems, J. Chromatogr. A., 807, 307–310 (1998). [42] S.H. Hansen, C. Gabel-Jensen and D.W.M. El-Sherbiny. Microemulsion electrokinetic chromatography – or solvent-modified micellar electrokinetic chromatography?, Trends Anal. Chem., 20, 614–619 (2001). [43] K.D. Altria. Application of microemulsion electrokinetic chromatography to the analysis of a wide range of pharmaceuticals and excipients, J. Chromatogr. A., 844, 371–386 (1999). [44] C. Gabel-Jensen, S.H. Hansen and S. Pedersen-Bjergaard. Separation of neutral compounds by microemulsion chromatography: Fundamental studies on selectivity, Electrophoresis, 22, 1330–1336 (2001). [45] S. Pedersen-Bjergaard, C. Gabel-Jensen and S.H. Hansen. Selectivity in microemulsion electrokinetic chromatography, J. Chromatogr. A., 897, 375–381 (2000). [46] M.H. Abraham, C. Treiner, M. Roses, C. Rafols and Y. Ishihama. Linear free energy relationship analysis of microemulsion electrokinetic chromatographic determination of lipophilicity, J. Chromatogr. A., 752, 243–249 (1996). [47] S.K. Poole, D. Durham and C. Kibbey. Rapid method for estimating the octanol–water partition coefficient (log Pow) by microemulsion electrokinetic chromatography, J. Chromatogr. B, 745, 117–126 (2000).

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[48] W.L. Klotz, M.R. Schure and J.P. Foley. Rapid estimation of octanol–water partition coefficients using synthesized vesicles in electrokinetic chromatography, J. Chromatogr. A, 962, 207–219 (2002). [49] C.P. Palmer. Recent progress in the development, characterization and application of polymeric pseudophases for electrokinetic chromatography, Electrophoresis, 23, 3993–4003 (2002). [50] I. Peric and E. Kenndler. Recent developments in capillary electrokinetic chromatography with replaceable charged pseudostationary phases or additives, Electrophoresis, 24, 2924–2934 (2003). [51] K. Gogova, B. Marchel, B. Gas and E. Kenndler. Electrokinetic chromatography with micelles, polymeric and monomeric additives with similar chemical functionality as pseudostationary phases, J. Chromatogr. A., 916, 79–87 (2001). [52] W. Shi and C.P. Palmer. Effect of pendent group structures on the chemical selectivity and performance of sulfonated copolymers as novel pseudophases in electrokinetic chromatography, Electrophoresis, 23, 1285–1295 (2002). [53] D.S. Peterson and C.P. Palmer. Novel alkyl-modified anionic siloxanes as pseudostationary phases for electrokinetic chromatography: II. Selectivity studied by linear solvation energy relationships, Electrophoresis, 22, 3562–3566 (2001). [54] S. Schutte and C.P. Palmer. Alkyl-modified siloxanes as pseudostationary phases for electrokinetic chromatography, Electrophoresis, 24, 978–983 (2003). [55] M.S. Leonard and M.G. Khaledi. A mixed ionic block copolymer–surfactant pseudostationary phase in micellar electrokinetic chromatography, J. Sep. Sci., 25, 1019–1026 (2002). [56] M.H. Abraham, J.M.R. Gola, R. Kumarsingh, J.E. Cometto-Muniz and W.S. Cain. Connection between chromatographic data and biological data, J. Chromatogr. B, 745, 103–115 (2000). [57] C.F. Poole, A.D. Gunatilleka and S.K. Poole. In search of a chromatographic model for biopartitioning, Adv. Chromatogr., 40, 159–230 (2000). [58] D.M. Cimpean and C.F. Poole. Systematic search for surrogate chromatographic models of biopartitioning processes, Analyst, 127, 724–729 (2002). [59] N.C. Dias, M.I. Nawas and C.F. Poole. Evaluation of a reversed-phase column (Supelcosil LCABZ) under isocratic and gradient elution conditions for estimating octanol–water partition coefficients, Analyst, 128, 427–432 (2003). [60] C. Lepont and C.F. Poole. Retention characteristics of an immobilized artificial membrane column in reversed-phase liquid chromatography, J. Chromatogr. A., 946, 107–124 (2002).

4 General Aspects of Resolution Optimization with Micellar Pseudostationary Phases Li Jia and Shigeru Terabe

4.1 Introduction Electrokinetic chromatography (EKC) is one branch of the capillary electromigration separation techniques. An EKC mode with a micellar solution as pseudostationary phase is called micellar electrokinetic chromatography (MEKC), developed by Terabe et al. in 1984 [1]. MEKC is effective for the separation of small molecules including neutral analytes. The separation mechanism is based on partitioning of the analyte between the micellar phase and the surrounding aqueous phase [2]. The most effective way to obtain high resolution in MEKC is to increase the selectivity factor, as in conventional chromatography. The selectivity factor in MEKC depends on the molecular structure of the micelle and hence on the surfactant used, the pH of solution, and the nature of any additives to the micellar solution. The hydrophilic moieties of surfactant molecules generally affect selectivity more than do the hydrophobic moieties. Mixed micelles consisting of ionic and nonionic surfactants display different selectivity from that of single ionic micelles. Additives such as cyclodextrins, ion-pair reagents, urea and organic solvents can also serve as useful modifiers of the micellar solution for enhancing resolution.

4.2 Resolution Equation MEKC can be performed by dissolving an ionic surfactant in the separation electrolyte solution at a concentration higher than the critical micelle concentration (CMC) with no Electrokinetic Chromatography: Theory, Instrumentation and Applications Edited by U. Pyell # 2006 John Wiley & Sons, Ltd. ISBN: 0-470-87102-4

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instrumental modifications compared to capillary electrophoresis (CE). Under the capillary electrophoretic conditions, the ionic micelle migrates at a different velocity from the bulk solution because the micelle is subjected to electrophoretic migration. Under neutral or alkaline conditions, the electroosmotic velocity is faster than the electrophoretic velocity of the micelle, and hence the micelle also migrates in the same direction as the electroosmotic flow (EOF). When an anionic micelle such as sodium dodecyl sulfate (SDS) is employed, all the neutral analytes migrate toward the cathode due to the strong EOF. The neutral analyte free from the micelle migrates only by the EOF, while the analyte totally incorporated by the micelle migrates at the observed velocity of the micelle (the sum of the electroosmotic velocity and the electrophoretic velocity of the micelle). Other neutral analytes are detected between t0 and tmc, which are the migration times of the EOF marker and the micelle, respectively. The interval between t0 and tmc is called the migration time window. The wider the window, the larger the peak capacity, which is the number of peaks that can be separated during a run. The parameters t0 and tmc can be experimentally determined by injecting acetone, formamide or methanol, which are assumed not to interact with the micelle, and lipophilic dyes Sudan III or Sudan IV, or hydrophobic cations such as timepidium or halofantrine, which are assumed to be totally solubilized into the micelle, respectively. In MEKC the retention factor, k, is defined as: k¼

nmc naq

ð4:1Þ

where nmc is the amount of substance of analyte incorporated into the micelles and naq represents the amount of substance of free molecules in the aqueous phase. For a neutral analyte migrating between t0 and tmc with a migration time (tR), the retention factor for the analyte can be calculated by the following equation derived by Terabe et al. [1]: tR t0 ð4:2Þ k¼ t0 ð1 tR =tmc Þ The fact that neutral analytes must migrate between t0 and tmc is the most significant difference between MEKC and conventional chromatography. If tmc becomes infinite (micellar phase becomes stationary), Equation (4.2) reduces to the analogous equation for conventional chromatography. The resolution Rs in MEKC is given by [3]: pffiffiffiffi N a1 k2 1 t0 =tmc ð4:3Þ Rs ¼ 4 1 þ k2 1 þ ðt0 =tmc Þk1 a where N is the theoretical plate number, k1 and k2 are retention factors of Analytes 1 and 2, respectively, and a is the selectivity factor given by k2/k1. Equation (4.3) differs from that for conventional chromatography by virtue of the last term on the right-hand side, which arises from the limited migration time window. The migration of the micelle inside the capillary causes reduction of the virtual column length [4]. If the micelle migration is completely suppressed or tmc is infinity, the last term equates to unity and the resolution equation is identical to that of conventional chromatography. Equation (4.3) shows that resolution is related to N, a, k and t0 =tmc . Resolution increases in proportion to the square root of N. In MEKC, as in capillary zone

GENERAL ASPECTS OF RESOLUTION OPTIMIZATION

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electrophoresis (CZE), the higher the applied voltage, the higher the N value and the higher the resolution, unless the temperature increase is too high. Usually a high voltage of 10–30 kV is applied to perform the MEKC separation and 100 000–300 000 theoretical plates are obtained with a 50 cm 0.05 mm i. d. capillary tube within a relatively short time. If N is significantly lower than that, the experimental conditions must be reconsidered. The most probable cause of low N is adsorption of the analyte onto the capillary wall. If this happens, the capillary must be rinsed thoroughly. The retention factor k is important in increasing the resolution in MEKC. The optimum k value to give the highest resolution is determined by the following equation [5]: pffiffiffiffiffiffiffiffiffiffiffiffi ð4:4Þ kopt ¼ tmc =t0 Under neutral or alkaline conditions, tmc/t0 is 3–4; hence, kopt is 1.7–2.0. Large retention factors mean that a high molar fraction of the analyte is incorporated into the micelle, and small values mean the reversed situation or that a high molar fraction of the analyte exists in the aqueous phase. The result given by Equation (4.4) suggests that the retention factors should not be close to either extreme for separation by MEKC. In general, retention factors between 1 and 5 are recommended for optimal resolution. The desired k value in MEKC can be obtained by adjusting the concentration of the surfactant because k can be expressed as: k ¼ KVmc =Vaq ffi KvðCsf CMCÞ

ð4:5Þ

where K is the distribution coefficient of the analyte between the micelle and the aqueous phase, Vmc/Vaq is the phase ratio and Vmc and Vaq are volumes of the micelle and the aqueous phase, respectively, v is the partial specific volume of the micelle, and Csf is the surfactant concentration [3]. Equation (4.5) suggests that k increases linearly with the surfactant concentration. This is a characteristic feature of MEKC since the Csf needed to obtain a given k can be calculated, provided the CMC and k at a certain Csf are known. In contrast to EKC, for reversed-phase liquid chromatography (RPLC), the alteration of the phase ratio is seriously limited. The migration time ratio, t0 =tmc , is directly related to the width of the migration time window. The smaller the value of t0 =tmc , the wider is the migration time window and hence the higher is the Rs value. The value of t0 =tmc is in the range 0.2–0.4 for most ionic micelles under neutral or alkaline conditions. It is necessary to reduce the velocity of the EOF to obtain a smaller value of t0 =tmc . Addition of an organic solvent such as methanol, acetonitrile or 2-propanol, or the use of a nonionic/anionic mixed micelle are useful methods, and changing the pH to acidic is also a possible approach. However, in practice, a longer run time is required. The addition of an organic solvent increases the viscosity of the separation electrolyte and reduces the velocity of EOF and also reduces the velocity of the micelles, resulting in the extension of the migration time window with the side effect of a reduction of the retention factor. The selectivity factor a is the most important and most effective term to increase resolution. The selectivity factor can be manipulated through selection of surfactants and modification of the buffer solution. In RPLC, usually the separation is not manipulated by changing the stationary phase since C18 is the most widely accepted phase and different

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products vary little. In MEKC, however, pseudostationary phases are micelles and the type of surfactant significantly affects the a value. The choice of surfactants and modification of the buffer solution are discussed in more detail below.

4.3 Resolution Optimization The choice of micelle and of modifier added to the aqueous phase is the most effective and important means of enhancing resolution. Another key parameter that affects resolution is temperature. Each experimental factor is discussed separately below. 4.3.1

Choice of the Micelle

4.3.1.1 Ionic Surfactants. For the separation of neutral analytes, the micelle used in MEKC must be ionic, that is, it must consist of an ionic surfactant or a mixture of ionic and nonionic surfactants. Some typical surfactants with their CMC and aggregation numbers are listed in Table 4.1. Surfactants have a hydrophobic and a hydrophilic group within each molecule, and both groups affect selectivity in MEKC. SDS is the most widely used surfactant in MEKC; it possesses a long alkyl chain as the hydrophobic group and an ionic group as the polar group. The micelle formed by SDS is believed to be spherical in shape, with the polar groups being located in the outer zone of the micelle and the alkyl groups constituting a hydrophobic core, as shown in Figure 4.1. When an Table 4.1 Aggregation number (AN) and CMC of some typical surfactants [2] Surfactant Anionic

SDS Sodium tetradecyl sulfate Sodium decanesulfonate Sodium N-lauroyl-N-methyltaurate Sodium polyoxyethylene dodecyl ether sulfate Sodium N-dodecanoyl-L-valinate Sodium cholate Sodium deoxycholate Sodium taurocholate Sodium taurodeoxycholate Potassium perfluoroheptanoate Cationic Tetradecyltrimethylammonium bromide Dodecyltrimethylammonium bromide Cetyltrimethylammonium bromide Cetyltrimethylammonium chloride Non-ionic Polyoxyethylene(23) dodecyl ether (Brij35) Polyoxyethylene(23) sorbitan monolaurate (Tween 20) Zwitterionic 3-[(3-cholamidopropyl)dimethylammonio]1-propanesulfonate N-Dodecyl-N,N-dimethylammonio3-propanesulfonate

CMC (at 25 C; 103 M)

AN

8.1 2.1 (50 C) 40 8.7 2.8 5.7 (40 C) 13–15 4–6 10–15 2–6 28 3.5 15 0.92 1.3 0.1

62 138 40 NA 66 NA 2–4 4–10 5 NA NA 75 56 61 NA NA

0.059

NA

4.2–6.3

10

3.3

NA

GENERAL ASPECTS OF RESOLUTION OPTIMIZATION A

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B

C

Figure 4.1 Schematic diagram of the structure of an ionic micelle and the interaction between three types of analyte and the ionic micelle. A, on the surface; B, as a cosurfactant; C, within the core. (Reprinted with permission from Ref. [2], copyright 2004 American Chemical Society)

analyte is incorporated into the micelle, three types of interaction are possible as shown in Figure 4.1: A, the analyte is adsorbed onto the surface of the micelle by electrostatic or dipole interaction; B, the analyte behaves as a cosurfactant by participating in the formation of the micelle; C, the analyte is incorporated into the core of the micelle. The effect of the surfactant’s molecular structure on the separation selectivity will differ according to the type of interaction involved. The hydrophilic, or ionic group, is generally more important in determining selectivity than is the hydrophobic group since most analytes interact with the micelle at the surface. Figure 4.2 gives an example of the comparison of selectivity between surfactants possessing different polar groups [6]. The result as shown in Figure 4.2 indicates that the different polar groups of various surfactants will show different selectivity for analytes, even if the surfactants have identical alkyl chain groups. The influence of surfactant type on the separation selectivity can be investigated through linear solvation energy relationships (LSER) [7]. Using the LSER methodology, useful information about the nature of solute interactions with different types of surfactant aggregates can be obtained (see Chapter 3). One result of these studies is that selectivity differences in MEKC between several anionic surfactants are primarily due to hydrogen-bonding interactions rather than the dipolar interactions [7]. Cationic micelles show substantially different selectivity for neutral and for ionic solutes, as compared with anionic micelles because of the different polar group on this surfactant [8]. Most cationic surfactants have an alkyltrimethylammonium group and their counter ions are halides. Cetyltrimethylammonium bromide (CTAB) is the most popular cationic surfactant used in CE, mainly to reverse the direction of EOF due to adsorption of the cationic surfactant on the capillary wall. However, it is not widely used

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Figure 4.2 Comparison of selectivity between surfactants possessing different polar groups: 1, caffeine; 2, acetaminophen; 3, sulpyrin; 4, trimetoquinol; 5, guaiphenesin; 6, naproxen; 7, ethenzamide; 8, phenacetin; 9, isopropylantipyrine; 10, noscapine; 11, chlorpheniramine; 12, tipepidine. Conditions for separation solution: (a) 0.1 M sodium trioxyethylenealkyl (C12–C14) ether acetate (ECT) in 20 mM phosphate–borate buffer (pH 9.0); (b) 0.1 M SDS in the same buffer as for (a). Capillary, 50 mm i.d. 65 cm (effective length 50 cm); applied voltage, 20 kV; detection, UV absorbance at 210 nm. (From Nishi et al., Effect of surfactant on the separation of cold medicine ingredients by micellar electrokinetic chromatography, J. Pharm. Sci., 79, 519–523, copyright 1990 John Wiley & Sons, Inc., reprinted with permission)

as a micelle-forming surfactant in MEKC, probably due to its UV absorption in the short wavelength region and the generation of bromine in the anodic vial during electrophoresis. However, CTAB or the corresponding chloride (CTAC) shows significantly different selectivities compared to anionic surfactants while the migration order of analytes still follows the order of increasing distribution constant, as in the case of anionic micelles. According to studies using the solvation parameter model, CTAB differs significantly from SDS concerning its hydrogen-bond acidity and basicity (see Chapter 3). Therefore, the use of a cationic surfactant instead of SDS is a promising alternative to change the selectivity. Figure 4.3 shows examples of the effect of the type of surfactant (anionic or cationic surfactant) on selectivity [9]. 4.3.1.2 Nonionic Surfactants. Nonionic surfactants themselves do not posses electrophoretic mobility and cannot be used as pseudostationary phases in conventional MEKC. However, nonionic surfactant micelles are useful for the separation of charged compounds, especially for peptides with closely related structures [10]. Since the separation principle is the same as with ionic surfactants, we can classify the technique with nonionic micelles as being an extension of MEKC. This technique was successfully applied to the mass spectrometric detection of peptides separated by MEKC with nonionic surfactants [11]. Nonionic surfactants can also be employed as pseudostationary phases in MEKC with a combination of ionic surfactants. Most nonionic surfactants have polyoxyethylene groups. Mixed micelles of nonionic and ionic surfactants with surfaces covered by polyoxyethylene groups, as shown in Figure 4.4, will have different surface characteristics and hence selectivity from that of the ionic surfactant micelle. Some natural chiral surfactants are uncharged and were used as mixed micelles with SDS.


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Figure 4.3 Effect of the type of surfactant (anionic or cationic surfactant) on selectivity: 1, water; 2, aniline; 3, nitrobenzene; 4, m-nitroaniline; 5, p-nitroaniline; 6, o-nitroaniline. Conditions: capillary, 50 mm i.d. 65 cm (effective length 50 cm); separation solution: (a) 100 mM SDS in 50 mM phosphate–100 mM borate buffer (pH 7.0); (b) 50 mM CTAB in 100 mM Tris-HCl (pH 7.0); applied voltage, 20 kV; detection, UV absorbance at 210 nm [9]. (Reprinted with permission from Terabe in Capillary Electrophoresis Technology, N. Guzman (Ed.), copyright CRC Press, Boca Raton, Florida)

Figure 4.4 Schematic diagram of the structure of mixed micelle of ionic and nonionic surfactants and the interaction between an analyte and the micelle on the surface. (Reprinted with permission from Ref. [2], copyright 2004 American Chemical Society)

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4.3.1.3 Biological Surfactants–Bile Salts. Bile salts which are a group of natural steroidal surfactants are common biological surfactants used in MEKC as alternative surfactants. Some of the bile salts, which have been employed in MEKC separations, include sodium cholate (SC), sodium taurocholate (STC), sodium deoxycholate (SDC), and sodium taurodeoxycholate (STDC). Nonconjugated bile salts, such as SC and SDC, can be used under neutral or alkaline conditions to keep the carboxyl group ionized, whereas taurine-conjugated forms, such as STC and STDC, can be used in more acidic conditions above pH 3. It should be noted that the deoxycholate solution tends to gelate, when a relatively high concentration buffer solution is employed to prepare the micellar solution. These surfactants are considered to form a helical micelle with a reversed micelle conformation [12]. Bile salts display two characteristic features that differentiate them from long alkyl-chain surfactants: they have a relatively low solubilizing power, and they are capable of chiral discrimination. Highly hydrophobic compounds are not usually well separated by MEKC with long alkyl-chain surfactants, because of excessively large retention factors. However, bile salt micelles have been successfully employed to solve the problem by taking advantage of their low solubilizing effect [12]. Bile salts are chiral and can be used for enantiomeric separations [13]. In this respect, deoxycholate and its taurine conjugate have shown successful results. 4.3.1.4 Micelle Polymers. Micelle polymers and high molecular mass surfactants have been investigated as pseudostationary phase in MEKC [14–16]. These additives form monomolecular micelles (aggregation number of 1), so that an enhanced stability and rigidity of the micelle can be obtained as well as easier control of the micellar size as compared with micelles formed by a conventional low molecular mass surfactant. Since the CMC of the micelle polymer is essentially zero, the net micellar concentration is constant or independent of the concentration and composition of a buffer, pH, additives and temperature, and hence better reproducibility in the migration time can be expected in micelle polymer-MEKC than in low molecular mass surfactant-MEKC. In addition, micelle polymer-MEKC is suitable to be adapted for on-line coupling of MEKC with mass spectrometry (MS) (see Chapter 15). 4.3.1.5 Mixed Micelles. It is known that mixed micelles are formed when more than two different surfactants are dissolved in a solution. Mixed micelle consisting of an ionic and a nonionic surfactant are particularly useful in MEKC. Because such mixed micelles have a larger size and lower surface-charge density than ionic micelles, they provide higher retention factors and a narrower migration time window and also show a different separation selectivity [17]. As described above, most nonionic surfactants have polyoxyethylene groups as hydrophilic moieties, therefore the surface structure of the mixed micelle and hence its separation selectivity will be significantly different from that of an ionic micelle. An example is given in Figure 4.5 [18]. Zwitterionic surfactants are not widely used in MEKC. However, zwitterionic surfactants will be interesting if they are used in mixed micelles, because they should show significantly different selectivities compared to other types of surfactants. 4.3.2

Choice of Buffer Solution

In general, the constituents of the buffer, in which the pseudostationary phase is dissolved do not significantly affect resolution, but the pH of the buffer is an important factor in


87

Figure 4.5 Effect of addition of nonionic surfactant: 7, acetaminophen; 8, caffeine; 9, guaiphenesin; 10, ethenzamide; 11, isopropylantipyrine; 12, trimetoquinol. Conditions: separation solution: (a) 100 mM SDS in 50 mM phosphate–100 mM borate buffer (pH 7.0); (b) 30 mM Tween 60 added to the same solution as in (a); capillary, 75 mm i.d. 57 cm (effective length 50 cm); applied voltage, 18 kV; detection, UV absorbance at 214 nm [18]. (Reprinted from J. Pharm. Biomed. Anal., 10, 705–715, S. Terabe, Selectivity manipulation in micellar electrokinetic chromatography, copyright 1992, with permission from Elsevier)

manipulating resolution of ionizable analytes. An ionized form of the analyte having the same charge as the micelle will be incorporated into the micelle to a lesser extent than its unionized form. The retention factor of an acid is the weighted average of the retention factors of its undissociated (HA) and its dissociated (A) forms. Thus, the distribution coefficient, migration time and resolution can be substantially altered by changing the pH for ionizable analytes [18,20]. The pH of the separation electrolyte is mainly optimized empirically. 4.3.3

Choice of Temperature

The distribution coefficient is dependent on temperature, and an increase in temperature causes reduction of the migration time because of the decrease in the distribution coefficient. The temperature rise also results in increases of the velocity of EOF and micelle by the same extent owing to the lowered viscosity of the separation electrolyte. The dependence of the distribution coefficient on temperature is different among analytes. Therefore, temperature will also affect resolution [21]. Although if the temperature does not have a significant impact on selectivity and resolution it will seriously affect the migration time. Therefore, it is essential for the reproducibility of results to keep temperature precisely constant. 4.3.4

Choice of Additives to the Aqueous Phase

The aqueous phase in MEKC corresponds to the mobile phase in RPLC and therefore the various mobile phase modifiers developed in RPLC are also applicable in MEKC. So far, the following additives, organic solvents, cyclodextrins (CDs), ion-pair reagents, and urea are particularly useful. 4.3.4.1 Organic Solvents. Water-miscible organic solvents such as methanol and acetonitrile can be used in MEKC, just as they are in RPLC. These organic solvents reduce

88


the retention factor and alter separation selectivity. A high concentration of organic solvent may break down the micellar structure and therefore it is recommended that the volume fraction of the solvent should not exceed 20 %. The addition of the organic solvent to a micellar solution usually reduces the electroosmotic velocity, thereby extending the migration time window and increasing resolution, probably resulting from the reduced charge on the micelle or the increased size of the micelle due to swelling caused by the organic solvent. A solvent programming operation, where the content of the organic solvent is changed with time, has been developed to improve resolution [22,23]. 4.3.4.2 Cyclodextrins. CDs are now popular in the field of chromatography. Most of the techniques using CD are based on its capability to recognize specific molecules that fit its hydrophobic cavity. From the viewpoint of MEKC, native CDs are electrically neutral and have no electrophoretic mobility, but CD derivatives with ionic group substituents can be used as a pseudostationary phase instead of a micellar separation carrier in EKC. This is especially effective for the separation of a number of neutral compounds, including aromatic isomers and racemic mixtures [24,25]. CD has also been used as an additive to micellar solutions for CD-modified MEKC (CD/MEKC) [26]. When CD is added to a micellar solution, the analyte is distributed among three phases: micelle, CD and water (aqueous phase). From the viewpoint of electrophoretic separation, CD and water migrate at identical velocities, equal to the EOF velocity. However, CD exerts a remarkable effect on the apparent retention factor between the micellar and nonmicellar (i.e. CD and water) phases. Highly hydrophobic compounds tend to be almost totally incorporated into the micelle because of their low solubilities in water. CD is water soluble and capable of including hydrophobic compounds into its hydrophobic cavity. The inclusion complex formation equilibrium constant for an analyte depends on steric parameters. Thus a fraction of the hydrophobic analyte will be included into the CD cavity, even in the presence of micelles. Therefore

Figure 4.6 CD/MEKC separation of eight corticosteroids: a, hydrocortisone; b, hydrocortisone acetate; c, betamethasone; d, cortisone acetate; e, triamcinolone acetonide; f, fluocinolone; g, dexamethasone acetate; h, fluocinonide. Conditions: separation solution. (a) 50 mM SDS in 20 mM phosphate–borate buffer (pH 9.0); (b) 15 mM g-CD and 4 M urea added to the same buffer solution as in (a); capillary, 50 mm i.d. 65 cm (effective length 50 cm); applied voltage, 20 kV; detection, absorbance at 210 nm [27]. (Reprinted with permission from Nishi and Matsuo, J. Liq. Chromatogr., 14, 973–986 (1991), copyright CRC Press, Boca Raton, Florida)


89

the migration time or the apparent retention factor of a hydrophobic analyte that forms an inclusion complex with a CD will decrease with an increase in CD concentration. Separation selectivity among highly hydrophobic analytes depends solely on the difference in their distribution ratio between CD and the micellar phase, because such hydrophobic analytes can be assumed to be insoluble in water. Figure 4.6 shows an example of the separation of highly hydrophobic corticosteroids by CD/MEKC [27]. CD/ MEKC is helpful not only for the separation of highly hydrophobic compounds but also for enantiomeric separations because of the chirality of CD. An example of enantiomeric separation by CD/MEKC is given in Figure 4.7 [28]. 4.3.4.3 Ion-pair Reagents. Ion-pair reagents are often employed in RPLC for the separation of ionic compounds. There is an essential difference in the separation of ionic compounds between MEKC and RPLC although both have close similarities for the

Figure 4.7 CD/MEKC separation of a mixture of five CBI (l-cyano-2-substituted-benz[f]isoindole)-DL-amino acids. Conditions: separation solution, 50 mM SDS, 10 mM g-CD in 100 mM borate buffer (pH 9.0); capillary, 50 mm i.d. 70 cm (effective length 50 cm); applied voltage, 15 kV; detection, laser-induced fluorescence (lex ; ¼ 442 nm, lem ; ¼ 490 nm) (Reprinted with permission from Ref. [28], copyright 1991 American Chemical Society)

90


separation of neutral compounds. The difference is due to the electrical charge on the micelle. As the micelle is ionic, ionic analytes having the same charge as the micelle will not be incorporated into the micelle, or if so, then only slightly. On the other hand, ionic analytes having a different charge will strongly interact with the micelle. An ion-pair reagent will strongly modify the interaction between ionic analytes and an ionic micelle mentioned above. For example, a cationic ion-pair reagent such as tetraalkylammonium salts will enhance the interaction between an anionic analyte and an anionic micelle by forming the ion-pair with the analyte or with the micelle. On the other hand, a cationic ion-pair reagent will reduce the interaction between a cationic analyte and an anionic micelle by competing with the analyte for combining with the micelle. The effect of the ion-pair reagent on the migration time or separation selectivity depends on the molecular structure of the ion-pair reagent itself [29]. 4.3.4.4 Urea. Although urea is not often used in RPLC, it is useful for the separation of hydrophobic compounds in MEKC. Urea is very soluble in water up to 7 M. The solution is UV-transparent and the viscosity is not very high. A high concentration of urea is known to increase the solubility of hydrophobic compounds in water as well as to hinder hydrogen bond formation in the aqueous phase. The addition of a high concentration of urea to the SDS solution enabled the MEKC separation of highly hydrophobic compounds, as shown in Figure 4.8 [30]. These steroidal compounds were not successfully resolved with the SDS solution alone because their retention factors were much larger than the optimal value. The high concentration of urea slightly reduced the

Figure 4.8 The effect of urea addition to the SDS solution: a, hydrocortisone; b, hydrocortisone acetate; c, betamethasone; d, cortisone acetate; e, triamcinolone acetonide; f, fluocinolone acetonide; g, dexamethasone acetate; h, fluocinonide. Conditions: separation solution: (a) 50 mM SDS in 20 mM borate–20 mM phosphate buffer (pH 9.0); (b) the same SDS solution as in (a), but containing 6 M urea; capillary, 50 mm i.d. 65 cm (effective length 50 cm); applied voltage, 20 kV; detection, absorbance at 210 nm [30]. (Reprinted from J. Chromatogr., 545, 359–368, Terabe et al., copyright 1991, with permission from Elsevier)


91

EOF velocity and considerably reduced the observed migration velocity of the micelle, resulting in the extension of the migration time window. These observed changes in velocities can not be attributed exclusively to the slight increase in viscosity due to the addition of urea.

Run with a standard MEKC conditions

Yes

Is the separation successful

End or optimize migration times

No Option 2

No

Cationic analyte?

k > 10

Caculate k

k < 0.5

Yes 0.5 < k < 10 Option 1 Use a different surfactant (including a mixed micelle)

Anionic analyte?

No

Increase [SDS]

Yes Option 1

Rs < 0.5

Estimate Rs Rs > 0.5

Optimize k to about 2 and/or use a longer capillary

No

Is the separation successful Yes End

Figure 4.9 Introductory guide to the development of an optimum separation. Standard MEKC conditions: Running solution: 50 mM SDS in 50 mM borate buffer (pH 8.5–9.0); capillary: 50–75 mm i.d. 30–50 cm (from the injection end to the detector); applied voltage: 10–20 kV (keep current below 50 mA); temperature: 25 C or ambient; sample solvent: water or methanol; sample concentration: 0.1–1 mg ml1; injection end: the positive end or anodic end; injection volume: below 2 nl (or less than 1 mm from the end of the capillary); detection: 200–210 nm (depending on the sample). Option 1: use an ion-pair reagent (an ammonium salt) or a cationic surfactant. Option 2: use bile salts instead of SDS, add CD to an SDS solution (CD/MEKC), or add an organic solvent or urea to an SDS solution [18]. (Reprinted from J. Pharm. Biomed. Anal., 10, 705–715, S. Terabe, Selectivity manipulation in micellar electrokinetic chromatography, copyright 1992, with permission from Elsevier)

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4.4 Strategies for Optimizing Resolution The simplest way to reach optimum separation is to follow a guide, as described by Terabe [18]. Such a guide is instructive and helpful for finding preliminary experimental conditions. Figure 4.9 shows a general guide to successful separation by MEKC. A set of standard operating conditions using a 50 mM SDS solution, as given in Figure 4.9, is proposed for the initial stage in developing an analytical method employing MEKC. If a sample consists of a few components, the standard conditions, as shown in Figure 4.9, may be successful. When the resolution is larger than that required, the migration time can be reduced by using a shorter capillary or reducing the concentration of SDS. If the separation is not satisfactory, it is necessary to know the approximate values of the retention factors, according to Equation (4.2). To evaluate the retention factor, t0 and tmc must be measured experimentally (see Chapter 1). The marker or tracer is usually added to the sample solution. The peak of the micelle corresponding to tmc is not always readily observed due to the low solubility of the tracer. In such cases, tmc can be assumed to be three to four times t0. For analytes having retention factors that are too large or too small, either Option 1 or Option 2 are recommended, according to the flow chart. In particular, for hydrophobic compounds, there is a wide range of choices as noted in Option 2. When peaks are partially resolved, further refinement of the conditions will often lead to a successful separation. However, when the separation is unsuccessful with SDS as micellar phase, other surfactants should be explored.

References [1] S. Terabe, K. Otsuka, K. Ichikawa, A. Tsuchiya and T. Ando. Electrokinetic separations with micellar solutions and open-tubular capillaries, Anal. Chem., 56, 111–113 (1984). [2] S. Terabe. Micellar electrokinetic chromatography, Anal. Chem., 76, 240A–246A (2004). [3] S. Terabe, K. Otsuka and T. Ando, Electrokinetic chromatography with micellar solution and open-tubular capillary, Anal. Chem., 57, 834–841 (1985). [4] C.X. Zhang, Z.P. Sun and D.K. Lin. Micellar electrokinetic capillary chromatography theory based on conventional chromatography, J. Chromatogr. A, 655, 309–316 (1993). [5] J.P. Foley. Optimization of micellar electrokinetic chromatography, Anal. Chem., 62, 1302– 1308 (1990). [6] H. Nishi, T. Fukuyama, M. Matsuo and S. Terabe. Effect of surfactant on the separation of cold medicine ingredients by micellar electrokinetic chromatography, J. Pharm. Sci., 79, 519–523 (1990). [7] S. Yang and M.G. Khaledi. Chemical selectivity in micellar electrokinetic chromatography: characterization of solute–micelle interactions for classification of surfactants, Anal. Chem., 67, 499–510 (1995). [8] K. Otsuka, S. Terabe and T. Ando. Electrokinetic chromatography with micellar solutions: Separation of phenylthiohydantoin-amino acids, J. Chromatogr., 332, 219–226 (1985). [9] S. Terabe. Micellar electrokinetic chromatography, in Capillary Electrophoresis Technology, N.A. Guzman (Ed), Marcel Dekker, New York, 1993. [10] N. Matsubara, K. Koezuka and S. Terabe. Separation of eleven angiotensin II analogs by capillary electrophoresis with a nonionic surfactant in acidic media, Electrophoresis, 16, 580– 583 (1995).


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[11] K. Koezuka, H. Ozaki, N. Matsubara and S. Terabe. Separation and detection of closely related peptides by micellar electrokinetic chromatography coupled with electrospray ionization mass spectrometry using the partial filling technique, J. Chromatogr. B., 689, 3–11 (1997). [12] R.O. Cole, M.J. Sepaniak, W.L. Hinze, J. Gorse and K. Oldiges. Bile salt surfactants in micellar electrokinetic capillary chromatography: application to hydrophobic molecule separations, J. Chromatogr., 557, 113–123 (1991). [13] S. Terabe, M. Shibata and Y. Miyashita. Chiral separation by electronkinetic chromatography with bile salt micelles, J. Chromatogr., 480, 403–411 (1989). [14] H. Ozaki, S. Terabe and A. Ichihara. Micellar electrokinetic chromatography using highmolecular surfactants: use of butyl acrylate–butyl methacrylate–methacrylic acid copolymers sodium salts as pseudo-stationary phases, J. Chromatogr. A., 680, 117–123 (1994). [15] C.P. Palmer and S. Terabe. A novel sulfate polymer as a pseudo-stationary phase for micellar electrokinetic chromatography, J. Microcol. Sep., 8, 115–121 (1996). [16] C.P. Palmer and S. Terabe. Micelle polymers as pseudostationary phases in MEKC: chromatographic performance and chemical selectivity, Anal. Chem., 69, 1852–1860 (1997). [17] H.T. Rasmussen, L.K. Goebel and H. McNair. Micellar electrokinetic chromatography employing sodium alkyl sulfates and Brij 35, J. Chromatogr., 517, 549–555 (1990). [18] S. Terabe. Selectivity manipulation in micellar electrokinetic chromatography, J. Pharm. Biomed. Anal., 10, 705–715 (1992). [19] K. Otsuka, S. Terabe and T. Ando. Electrokinetic chromatography with micellar solutions: separation of phenylthiohydantoin–amino acids, J. Chromatogr., 332, 219–226 (1985). [20] K. Otsuka, S. Terabe and T. Ando. Electrokinetic chromatography with micellar solutions: retention behaviour and separation of chlorinated phenols, J. Chromatogr., 348, 39–47 (1985). [21] S. Terabe, T. Katsura, Y. Okada, Y. Ishihama and K. Otsuka. Measurement of thermodynamic quantities of micellar solubilization by micellar electrokinetic chromatography with sodium dodecyl sulfate, J. Microcol. Sep., 5, 23–33 (1993). [22] M.J. Sepaniak, D.F. Swaile and A.C. Powell. Instrumental developments in micellar electrokinetic capillary chromatography, J. Chromatogr., 480, 185–196 (1989). [23] A.T. Balchunas and M.J. Sepaniak. Gradient elution for micellar electrokinetic capillary chromatography, Anal. Chem., 60, 617–621 (1988). [24] S. Terabe, H. Ozaki, K. Otsuka and T. Ando. Electrokinetic chromatography with 2-Ocarboxymethyl-b-cyclodextrin as a moving ‘stationary’ phase, J. Chromatogr., 332, 211–217 (1985). [25] S. Terabe. Electrokinetic chromatography: an interface between electrophoresis and chromatography, Trends Anal. Chem., 8, 129–134 (1989). [26] S. Terabe, Y. Miyashita, O. Shibata, E.R. Barhart, L.R. Alexander, D.J. Patterson, B.L. Karger, K. Hosoya and N. Tanaka. Separation of highly hydrophobic compounds by cyclodextrinmodified micellar electrokinetic chromatography, J. Chromatogr., 516, 23–31 (1990). [27] H. Nishi and M. Matsuo. Separation of corticosteroids and aromatic hydrocarbons by cyclodextrin-modified micellar electrokinetic chromatography, J. Liq. Chromatogr., 14, 973–986 (1991). [28] T. Ueda, F. Kitamura, R. Mitchel, T. Metcalf, T. Kuwana and A. Nakamoto. Chiral separation of naphthalene-2,3-dicarboxaldehyde-labeled amino acid enantiomers by cyclodextrin-modified micellar electrokinetic chromatography with laser-induced fluorescence detection, Anal. Chem., 63, 2979–2981 (1991). [29] H. Nishi, N. Tsumagari and S. Terabe. Effect of tetraalkylammonium salts on micellar electrokinetic chromatography of ionic substances, Anal. Chem., 61, 2434–2439 (1989). [30] S. Terabe, Y. Ishihama, H. Nishi, T. Fukuyama and K. Otsuka. Effect of urea addition in micellar electrokinetic chromatography, J. Chromatogr., 545, 359–368 (1991).

5 Optimization of the Separation Conditions in Electrokinetic Chromatography: Experimental Designs, Modelling and Validation Olga Jimeńez and Maria Luisa Marina

5.1 Introduction Electrokinetic chromatography (EKC) is a very popular separation technique because of such advantages as high efficiency, short analysis times and small injection volumes required [1–3]. The migration of analytes under the electric field is governed by the electrokinetic properties of the solutes and the partition coefficient differences between a pseudostationary phase and the surrounding aqueous phase. The most popular pseudostationary phases have been micelles (anionic, cationic, and neutral) but other pseudostationary phases have included microemulsions, polymers, vesicles, proteins, resorcarenes, dendrimers and cyclodextrins [2]. The optimization of the conditions of a separation is a difficult task due to the large number of variables affecting the process [4–7]. Among these we can cite pH, nature and concentration of surfactant, nature and concentration of buffer, and nature and concentration of organic modifiers. Furthermore, some instrumental variables, such as the applied voltage and the injection time or volume can also have a great influence on the solute separation. So it is important to follow an adequate strategy to obtain the best conditions for a certain separation. Ideally, an appropriate optimization strategy should


96


be able to find good separation conditions in the shortest time with only a few experiments, to assure the baseline separation of all components [8]. To date, optimization strategies can be divided in two great groups: those that employ a univariate optimization, that is, the variables are studied one at a time while keeping the others constant, and those that use a multivariate optimization scheme. Altria et al. [9] and Sentellas and Saurina [5] have reviewed the application of chemometric techniques to the optimization of the separation conditions in CE methods. So, in Table 5.1 the information published has been updated. In this table, the variables (also usually known as factors) and their experimental ranges, the type of model (empirical, theoretical or artificial neural networks (ANNs)) and the response(s), the type of validation, the solutes and the followed strategy are shown. The univariate optimization strategy is only efficient if there is no interaction between the variables. In other situations there is no guarantee of obtaining a global optimum. It must be clear that perhaps the obtained conditions permit a good separation of analytes but these conditions, in most situations, are not the best. This fact has been clearly illustrated by Liu et al. [21]. In their work, a comparison between computer aided simulation optimization and step-by-step (univariate) optimization for variation of a single factor was performed. In both optimization types, solutes were baseline resolved but when computer-aided ANNs simulation optimization was used, the analysis time was approximately reduced fourfold (7.5 minutes vs 30 minutes). Moreover, univariate optimization tends to be time consuming and tedious [4]. Hence the multivariate strategy is highly recommended. This strategy comprises different steps, that is, the use of an experimental design, the modelization step and the model validation, as it is described in the following sections.

5.2 Experimental Designs The objective of an experimental design is to obtain the best conditions for a separation with the minimum number of experiments. As a rule, the factors determining whether an experimental design will be successful or not are [23]: (i) the choice of parameters to optimize; (ii) the interval within which parameters are varied, and (iii) the choice of response used in the optimization. In this section, first, we will try to get an insight into the factors to be taken into account in an optimization scheme. It would be desirable to consider as many factors as possible to find the true optimum [23] but this is difficult due to the large number of them influencing migration in EKC. The factors of interest can be divided into two groups: instrumental or operational parameters, and the separation buffer factors. Instrumental parameters are common to the mode of operation in EKC and are represented by the applied voltage, the temperature, the injection time or injection volume, the capillary length, and the internal diameter, etc. The temperature affects physicochemical parameters like viscosity, pKa, absolute mobilities and critical micellar concentration of various surfactants, and thus separation [4].

Designs

Applied voltage (kV): 24–30 Buffer (mM): 10–20 pH: 8.0–9.6 SDS (mM): 50–80 Temperature ( C): 24–30 SDS (%): 2–5 1-Butanol(%): 5–9 Borate buffer (mM): 10–50 Brij 35 (%): 0–2.5 2-Propanol (%): 0–20 Cassette temperature ( C): 25–40

CM-b-CD (w/v): 0.20–0.40 SDS (mM):10–20 ACN (%): 0–15 pH: 8.2–9.7

Empirical (MLR)/ Prediction error of separation window, five additional plate height, experiments: retention factor, Q 0.2–10.7 %

Fractional factorial (26–2 þ 6)

Nairtazapine and its main active metabolite

Only analytical method

Univariate

Multivariate

Optimization

Anionic, cationic and neutral drugs

Multivariate

Benzodiazepines and Univariate g-hydroxybutyric acid related compounds Ketorolac Multivariate tromethamine and its impurities

One tetrapeptide and nine related substances

Analytes

Only analytical method

Validation

Empirical (MR, ANOVA (model) second order)/ Validity of resolution, analysis prediction time Analytical method

Empirical (MLR)/ resolution, migration time

Model/response function

Doehlert design

Plackett–Burman Methanol (%): 0–15 Full factorial ACN (%): 0–15 Central composite TEA (mM): 0–15 (2,6-DM)-b-CD (mM): 0–20 Buffer (M): 0.05–0.10 Ionic strength: 0.03–0.07 Temperature ( C): 15–40 Applied voltage (kV): 15–30 pH: 2.5–6.0 Type of chiral selector: CM-b-CD, b-CD sulphate, sulfobutyl ether-b-CD, b-CD, g-CD Temperature ( C): 10–25

Factors and levels

Table 5.1 Summary of experimental work on the optimization of conditions in electrokinetic chromatography

(Continued)

[12]

[6]

[11]

[10]

[1]

Reference

b-CD (mM): 5–15 Temperature ( C): 11–30 Applied voltage (kV): 11–25 ACN (%): 0–15

SDS (M): 0.01–0.05 n-Propanol or n-butanol (volume fraction): 0–0.05

Factorial

Multivariate

Multivariate

Univariate

Multivariate

Optimization

()-MethamphetaUnivariate mine, ()-methcathinone, ()ephedrine and ()pseudoephedrine

N-Phenylpyrazoles

Substituted benzenes

Empirical (MLR first and second order polynomials)/Resolution Empirical (MLR)/t0,tm, (ANOVA) Model Prediction errors k, resolution (normalized product) Non-linear regression (theoretical model)/k, resolution (normalized product)

Triangular ORM Cubic ORM

Injection time (s): 3–10 SDS (mM): 0–150 Borate buffer (mM): 10–50 pH: 8–10 SDS (mM): 30–60 pH: 6–8 Cyclodextrin (mM): 10–20

Triazine compounds ANOVA (model) Empirical (MR (herbicides) ANN: prediction second order)/ error for five objective function: additional data chromatographic exponential function Analytical method (CEF) (describes the quality in terms of resolution and duration of the electrophoretic separation) ANN/objective function: CEF Creatinine

Analytes

Central composite

Validation

Borate (mM): 5–50 Phosphate (mM): 5–50 SDS (mM): 5–50 1-Propanol (%): 3–15 pH: 8.5–10


Designs

Factors and levels

Table 5.1 ðContinued)

[15]

[14]

[8]

[2]

[13]

Reference

pH: 8–10.5 SDS (mM): 30–80 Borate (mM): 50–150 CDs: b-, sulfated b-, HP b-, a-, and g-cyclodextrin Organic modifiers: methanol, acetonitrile, propan-2-ol, tetrahydrofuran, and n-butanol

SDS (mM): 25–150 Brij 30 (mM): 10–30 Organic solvent: methanol and ACN H3PO4 (mM): 25–100

Borate (mM):5–25 Orthogonal SDS (mM): 0–20 Uniform ACN (%): 0–20 Buffer pH: 8.0–10.0 Factorial 33 or 22 HP-b-CD (mM): 100–300; 300–500 pH: 4–6 Buffer (mM): 50–200; 200–500 Hexanesulfonate (mM): 0–110 Poly(diallydimethylammonium chloride) (%): 0–0.5 [18]

Prediction error Theoretical model Aromatic carboxylic Multivariate (with the model acids, sulfonates and (Non-linear regression)/observed data set and the opiates prediction data set) mobility Empirical/ normalized resolution product and minimum resolution product Only analytical Lysergic acid Univariate method diethylamide, iso-lysergic acid diethylamide and lysergic acid N,Nmethylpropylamide Xanthones Univariate

(Continued )

[20]

[19]

[17]

[16]

Optical isomers of lac- Multivariate tic acid

Prediction error for Imperatorin and isoim- Multivariate two additional data peratorin

Empirical (MLR)/reso- Only analytical lution method

ANN/resolution

Orthogonal array

Applied voltage (kV): 20–25 pH: 8.0–9.0 Type of surfactant: SDS, NaCh Urea (M): 0.5–1 Borate (mM): 10–20

ANOVA (model)

Validation Pesticides

Analytes

Multivariate

Optimization

ANNs/Two objective Prediction error for Plant hormones Multivariate functions depending five additional data on resolution and resolution and migration time of the last peak Empirical, (MLR Model error Benzene, toluene, Multivariate cubic polynomials)/ ethylbenzene, overall resolution propylbenzene, etc.

Empirical (MLR)/Response function


[22]

[21]

[4]

Reference

ACN: acetonitrile; TEA: triethanolamine; MLR: multiple linear regression; Q: quotient between the effective mobility in the microemulsion and the effective mobility in the corresponding buffer (only for anions); ORM: overlapping resolution mapping; CD: cyclodextrin

pH: 8.0–10.0 Orthogonal Carrier electrolyte (mM): 20–100 Applied voltage (kV): 10–30 Temperature ( C): 15–35 SDS (mM): 20–100 Lithium dodecyl sulfate/lithium perfluorooctanesulfonate ratio

Designs

Factors and levels

Table 5.1 ðContinued Þ

OPTIMIZATION OF SEPARATION CONDITIONS

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Mikaeli et al. [23] have pointed out that it may be not possible to optimize some parameters that are known to influence the response due to limitations in the experimental instrumentation. For example, in their study the possibility of varying the dimensions of the capillary was limited by the relatively poor sensitivity of UV absorbance detectors. Also, applied voltage is another variable that affects the separation process. High voltages produce a greater number of theoretical plates and at the same time, on reducing analysis times, diffusion is minimized. However, application of high voltages is limited to the generation of an elevated electrical current strength, which produces more heat per unit time through the Joule effect [24,25]. The separation buffer factors depend on the mode of operation. In Table 5.1 we can observe that in micellar electrokinetic chromatography (MEKC) the most frequently studied factors are the concentration of the surfactant, the buffer, and the organic modifiers. Also, in this column, experimental ranges for these factors are included. For weak acids or bases, also, pH can affect the separation process [23]. Other factors that should be taken into account in the optimization of the separation conditions are the surfactant, the buffer and the modifier nature. In cyclodextrin modified micellar electrokinetic chromatography (CD-MEKC) the type and concentration of cyclodextrin are factors that influence the response in an important way. The factors that have been more rarely studied in EKC are ionic strength, the concentration of a secondary organic modifier or the concentration of a secondary surfactant. From the point of view of the optimization scheme, the possibility that so many variables affect the separation process renders an important complexity to the problem. For example, in a typical MEKC separation with eight factors (surfactant, modifier, and buffer concentration, pH, voltage, temperature, capillary length, and injection time) a full factorial design at two levels needs 256 experiments. So, the tendency in recent years has been to apply screening designs, as a previous stage in the optimization scheme, in order to evaluate significant parameters. As screening designs the most frequently used are the Plackett–Burman designs, orthogonal array designs, D-optimal designs and fractional factorial designs. In these experiments the main effects of the variables are studied, so the problem can be simplified with a lesser number of experiments. For example, Zhang et al. [4] studied the separation of nine pesticides in MEKC by means of an orthogonal array design taking into account five relevant factors: type and concentration of surfactant, concentration of buffer, pH and concentration of urea as the modifier. In this case, three or more variables interactions were ignored, since they were much less likely to occur and if they did exist, then they would most likely be of much a smaller magnitude than a main effect. From the results they concluded that the most significant factors were type of surfactant, the urea concentration, and the pH, so the problem was simplified to only three variables. Mikaeli et al. [23] optimized the separation of phenols and the chiral separation of (þ)-1-(9-anthryl)-2-propyl chloroformate-derivatized amino acids by MEKC. They included in their study the following parameters: pH, the concentration of the primary surfactant (sodium dodecyl sulphate, SDS), the concentration of a secondary surfactant (sodium deoxycholate, SDC), the buffer concentration (sodium tetraborate; borax), the temperature in the capillary compartment, the amount of acetonitrile added as an organic modifier, and the separation voltage. In the initial screening designs they used a Plackett– Burman design. All the parameters showed significant effects on the resolution except for

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the concentration of the buffer and the temperature of the capillary compartment. The nonsignificant parameters were thus locked at the value of the respective centre points and the voltage was kept at the lowest value in all further experiments. The significant parameters were thus investigated using a full factorial design in order to elucidate if any interaction effects occurred, and the results showed that the pH of the separation electrolyte was not a significant parameter. The final optimization step was a central composite design, that is, a full factorial design, with axial and centre point experiments. So, with this strategy a total of 45 experiments had been performed, in contrast with a full factorial design for eight factors (28) that required 256 experiments. Similarly, Brunnkvist et al. [1] developed an EKC method for separating the tetrapeptide H-Tyr-(D)Arg-Phe-Phe-NH2 and nine related substances by using heptakis (2,6-di-O-methyl)-b-cyclodextrin (2,6-DM-b-CD) in the separation buffer. The method was developed using experimental design in a four-step procedure, in which eight variables were investigated in a total of 47 experiments. The initial set of experiments was performed to establish basic requirements. This was followed by a Plackett–Burman design for variable selection (eight variables under study), a full factorial design (four variables) to estimate the significance of the selected variables, and, finally, a circumscribed central composite design, including axial points, to investigate carefully the influence of the retained significant variables (two variables, CD concentration and acetonitrile percentage) on the selected responses, resolution and migration time of the last eluting peak. Also, the separation of anionic, cationic and neutral drugs in microemulsion electrokinetic chromatography (MEEKC) was studied with a statistical experimental design. The concentration of SDS, 1-butanol (cosurfactant) and borate buffer and the factors Brij 35 (surfactant), 2-propanol (organic solvent) and cassette temperature were varied simultaneously, while the parameters pH, the concentration of octane (oil), the voltage and the dimension of the fused-silica capillary, were kept constant. The aim was to screen a number of parameters for their contribution in the separation performance of some analytes by means of a fractional factorial design (26-2, resolution IV). From all the results presented in the previous discussion, it is highly recommended that a scheme such as that shown in Figure 5.1 be followed. As an example, in this figure a fractional factorial, a full factorial and a central composite design, for three codified factors, are shown. The objective in using the screening designs (fractional factorial and/or full factorial designs) is to reduce the number of variables to at least two or three, evaluating the main and/or the interaction terms. Then, the nonsignificant variables are usually set at their central points and the significant ones are used in a more sophisticated design, such as the central composite design (usually known as the response surface design) to investigate carefully their influence on the selected response(s). This design includes axial points, in this case, face centred (see Figure 5.1) and a central point (usually, several replicated experiments are performed, typically five). So, the response curvature as a function of the remained variables and the experimental error can be evaluated. However, experimental design techniques are not the panacea: their indiscriminate or inadequate use may lead to erroneous conclusions [5]. Omitting significant factors, selecting inappropriate experimental ranges for study, misinterpreting results, etc., may be the cause of deficient optimization. Chemometric techniques offer excellent possibilities


Fractional factorial design

1

Full factorial design

1

1 1

–1

Central composite design

1

1

–1 –1

103

–1 –1 1

–1

1 –1 –1 1

–1

Figure 5.1 Experimental designs for three codified factors: fractional factorial, full factorial, and central composite design

in the optimization of CE separations but the analyst has to be aware of the characteristics, possibilities, and limitations of experimental designs [5].

5.3 Modelling Once, through a screening design (or a combination of screening designs) the problem is simplified to a reduced number of variables, an adequate model of the response(s) as a function of these variables must be obtained. Some different strategies have been used in the modelling of the response(s) as a function of the variables of interest; basically, they can be classified into two categories: theoretical models and empirical equations. However, nowadays, soft models, such as artificial neural networks, are acquiring great importance. 5.3.1

Physicochemical Models

Physicochemical models can be divided into equations that describe the separation between solutes and equations that describe the migration behaviour of individual solutes [7]. Table 5.2 summarizes the most representative physicochemical models that have been applied in MEKC. These equations, as can be observed in the table, depend on the surfactant concentration and pH or the surfactant concentration and organic modifier concentration. Terabe et al. [26,27] first introduced in MEKC the equation that gives the resolution (Rs) as a function of the plate number (N), the selectivity factor (a), the mean retention factor (k), the migration time of the electroosmotic flow marker (t0) and the migration time of the micelles (tm). Although the peak plate number depends on the experimental conditions, in most situations it has been fixed to a constant value in order to predict the

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Table 5.2 Most representative physicochemical equations in MEKC Physico-chemical Equations pffiffiffiffi! a 1 1 t0 =tm N k Rs ¼ a 4 1 þ ðt0 =tm Þk 1 þ k KMW;HA þ ½HKþa KMW;A ½M mmc þ ½HKþa maq;A ma;a ¼ 1 þ ½HKþa þ KMW;HA þ ½HKþa KMW;A ½M

Reference

Neutral and ionizable solutes-cationic and anionic micelles

[26–27]

Acidic solute-anionic micelles

[29, 30]

ma;c

KMW;HA þ ½HKaþ KMW;A ½M mmc þ ½HKþa maq;A ¼ 1 þ KIP cmc þ ½HKþa þ KMW;HA þ ½HKþa KMW;A ½M

Area of use

mb;a

KMW;BHþ þ ½HKþa KMW;B ½M mmc þ maq;BHþ ¼ 1 þ KIP cmc þ ½HKþa þ KMW;BHþ þ ½HKþa KMW;B ½M

Acidic solute-cationic micelles

mb;c

KMW;BHþ þ ½HKþa KMW;B ½M mmc þ maq;BHþ ¼ 1 þ ½HKaþ þ KMW;BHþ þ ½HKþa KMW;B ½M

Basic solute-anionic micelles

q P ai km H

meff ¼ i¼0

ðq iÞA

k¼

aq ½ M mm þ mHðq iÞ Ai i

q P ai km H

i¼0

Basic solute-cationic micelles

ðq iÞA

½ M þ 1 i

fK1 1 þ K3 Aaq ½M

2 1 þ K2 Aaq þ K2 K4 Aaq

Basic solute-cationic micelles

[31]

Neutral solute-anionic micelles, alcoholic modifier

[14]

KMW,SH and KMW,S are micellar binding constants of solute in the conjugate acidic and basic forms; Ka is the acid dissociation constant; KIP is the ion-pair formation constant between ionic solute with surfactant monomer; cmc is the critical micelle concentration of the surfactant; mmc is the mobility of the micellar phase; maq,SH and maq,S are the mobilities in the aqueous phase of the solute in the acidic and basic form, respectively; HA is an acidic solute and A the aq dissociated solute; B is a basic solute and BHþ its conjugate acidic form; mHðq iÞ Ai is the electrophoretic mobility of the ith undissociated anion in the aqueous phase; km Hðq iÞ Ai is the association coefficient between the ith undissociated anion and the micelle;

ai is the ith degree of dissociation of the conjugated acid of an anion; k is the retention factor; f is the phase ratio, Aaq is the alcohol concentration; K1 is the equilibrium constant that takes into account the association of the solute with the micelle to form a complex in the micellar pseudophase; K2 takes into account the enhancement of solubility of solute in the separation buffer modified by alcohols; K3 is the formation constant of the complexes among the solute, the alcohol and the micelle in the micellar pseudophase; and K4 the formation constant of the complex between the solute–alcohol complex and the other molecules of alcohol.

resolution between adjacent peaks, or the overall normalized resolution as the way to obtain the quality of the separation under study. Foley [28] differentiated this equation with prespect ffiffiffiffiffiffiffiffiffiffi to k. The maximum resolution was obtained for a mean retention factor, k ¼ tm =t0 , when the other quantities are kept constant (an assumption that cannot be fulfilled in practice). This approach does not focus on the optimization of a given well-defined MEKC system, but it provides a general optimum for MEKC. Although, from this equation a separation buffer composition can be derived, the main disadvantage of this strategy is the possibility of missing the actual optimum of a certain MEKC system.


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Khaledi and coworkers [29,30] introduced physicochemical models that describe the migration behaviour of both, acidic and basic solutes, as a function of the separation buffer pH and the surfactant concentration. In Table 5.2 equations relating the mobility of ionizable solutes (mi), acidic solutes, and basic solutes as a function of pH and surfactant concentration (½M ) by using anionic and cationic micelles are shown. Jimidar et al. [31] modelled the effective mobility of anions in MEKC by theoretical and empirical models as a function of pH and the surfactant concentration, and obtained a theoretical model similar to that used by Khaledi and coworkers [29,30]. The results showed that the predictions of the mobilities obtained with linear regression (empirical equations) were slightly more accurate for all the anions, except for carbonate. For this anion the shape of the response surface were clearly sigmoid. More recently, our own research group [14] has modelled the retention factor as a function of the surfactant and the organic modifier (n-propanol or n-butanol) concentrations and the results have been used to classify the retention behaviour of the different test solutes. Also, these results have been compared to those obtained by means of empirical equations. From the comparison of the mean prediction errors obtained by both methods, the statistical test indicated that the physicochemical model was the best to explain the retention behaviour of the solutes under study. Nowadays, chiral separations are gaining much attention and capillary electrophoresis has been demonstrated to be a powerful technique for analytical enantioseparation within the last decade [32]. Also, several physicochemical models for the quantitative treatment of the effect of the experimental variables on the migration behaviour of the analytes in a chiral separation system have been published and have been reviewed by Scriba [32]. These models relate the effective mobility of the enantiomers or the difference in the effective mobility of both enantiomers to the concentration of the chiral selector or with pH and the concentration of the chiral selector. 5.3.2

Empirical Models

In Table 5.1, the most recent applications of these empirical models have been summarized. Generally, the empirical equations used are first or second order polynomials relating, independently, one or more parameters (resolution, retention factor, t0, tm, analysis time, or some type of objective function) with different experimental variables. The chemometric method for obtaining the equation parameters is generally, multivariate linear regression, and when a two-factor system is evaluated, the final results are commonly depicted as response surfaces. One of the main problems that we encountered when we faced an optimization problem was the choice of the appropriate response to model as a function of the variables of interest. For instance, Wan et al. [33] have applied a central composite design to optimize the separation of neurotransmitter amino acids in normal and reversed migration MEKC. The responses used were resolution, efficiency and migration times. In Figure 5.2, the results obtained in normal MEKC for the modelling of resolution between DL-glutamic acid and DL-aspartic acid [Figure 2(a)], the efficiency for DL-aspartic acid peak [Figure 2(b)] and the migration time for DL-aspartic acid [Figure 2(c)] are shown as Pareto charts. The Pareto chart is an option of Statgraphic Plus Software [34] for Windows. The length of each bar is proportional to the absolute value of its associated regression coefficient or

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Figure 5.2 Standardized Pareto charts for the resolution between DL-glutamic acid and DL-aspartic acid (a); the efficiency for DL-aspartic acid peak (b); and the migration time for DL-aspartic acid (c). The three factors considered were the buffer concentration (A), the SDS concentration (B), and the applied voltage (C)

estimated effect. The effects of all parameters, interactions as well as quadratic terms, are standardized. The order in which the bars are displayed corresponds to the order of the size of the effects. The chart includes a vertical line that corresponds to the 95 % limit indicating statistical significance. An effect is, therefore, significant if its corresponding bar crosses this vertical line. From Figure 5.2 we can observe that different results are obtained depending on the response type evaluated. Thus, when the resolution between DL-glutamic acid and DL-aspartic acid is evaluated the applied voltage has no a significant influence on the response. In contrast, when the efficiency for DL-aspartic acid is studied, only the first and second order term, depending on the buffer concentration, influence the response. Furthermore, when the migration time of DL-aspartic acid (the last eluted peak) is considered, the interaction terms between buffer and SDS concentrations and the second order terms of buffer and SDS concentrations have no significant influence on the response. Similarly, Brunnkvist et al. [1] used two response functions, resolution and the migration time of the last eluting peak, to optimize the separation of H-Tyr-(D)ArgPhe-Phe-NH2 and its nine related products by EKC. Their results indicate that the presence of acetonitrile in the BGE does not improve the analysis time, and only the CD (heptakis(2,6-di-O-methyl)-b-cyclodextrin) concentration significantly influences, both, the resolution and the migration time. Also, Bu¨ tehorn and Pyell [35] and Garcıá-Ruiz et al. [14] modelled t0, tm and k as a function of the concentrations of SDS and the organic modifiers in MEKC. With these predicted values and considering a fixed number for N, the resolution between adjacent


107

peaks was achieved. Furthermore, the quality of the separation could be evaluated by using the overall normalized resolution so the best conditions for the system considered could be selected [14]. Although one of the most frequently modelled parameters has been the resolution between adjacent peaks [7], it must be taken into account that both the resolution and the separation factor may display discontinuous functions in the case of cross-over and these discontinuities interfere with the use of polynomial equations in the model building process. To overcome this problem, Zomeren et al. [7] suggested allowing the resolutions and separation factors to become negative and calculated them not only for adjacent peaks but for all peak pairs. Apart from the resolution and the migration time of the last eluted peak other researchers have used, as the response, objective functions in order to evaluate the separation quality. Among these, the overall normalization resolution (r) is the most cited in the literature. However, Liu et al. [21] indicated that the electrophoretic window should also be considered as a parameter to evaluate the separation selectivity, together with the overall normalization resolution. Hence they used an objective function, Q, considering the resolution between the first peak and the last peak in the electropherogram, the migration time of the last peak and the resolution between adjacent peaks. From their results, both criteria (r and Q) predicted the same value of pH and concentration of SDS. Also, the simulated concentration of buffer electrolyte and temperature were similar for both criteria. However, the applied voltages were quite divergent. Criterion Q predicted high voltages while criterion r chose a relatively low voltage. Consequently we suggest that as many as possible different responses be used in the optimization scheme, because the results are influenced in different ways by the variables considered. Also, we consider that when empirical equations are used, second order polynomials, as a starting point, should be used because it has been demonstrated that curvature effects in these models are important in the EKC separations [36]. Afterwards, the best model can be chosen by comparing the performance of the models considered, and also, their prediction capability. 5.3.3

Artificial Neural Networks

Nowadays, ANNs are emerging as one of the most promising areas in soft modelling and have been successfully used in the optimization of the separation conditions in MEKC in combination with experimental designs such as central composite designs [13] and orthogonal designs [16,21] (see Table 5.1). Furthermore, the modelling results obtained with ANNs have been compared to those obtained by means of theoretical models [37] and empirical equations [13,38–41], with ANNs as the best choice. Although a detailed description of the theory behind a neural network is out of the scope of this chapter, it can be consulted in the literature [42,43]. It must be pointed out that these soft models do not require formulation of mathematical equations and one of their most attractive advantages is the possibility of modelling nonlinear responses. By contrast, some drawbacks must be cited. As the architecture of the net, that is, the number of the hidden layers, the number of neurones in the hidden layer(s), the transformation of the experimental data, the training algorithm, the momentum, the

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learning rate, the transfer functions for the neurones in the hidden layer(s) and the output layer, must be optimized by trial and error, the optimization scheme is very complex. Also, problems of overfitting must be avoided.

5.4 Validation The purpose of validation is to establish whether or not a method is acceptable for its intended purpose [1], so, in this case, we must distinguish between model validation and analytical method validation. With respect to the model validation, the strategy most usually employed involves the use of two types of data, that is, those necessary to obtain the parameters of the empirical or theoretical equation (for ANNs, the training data set), and those to evaluate the prediction capability of the model. It is important to note that although the goodness of fit of a model is the best as possible, if the prediction capability is poor, the model cannot be considered appropriate anyway. From the literature consulted (see Table 5.1), the analysis of variance (ANOVA) is the most frequently method used to evaluate the significance of the models, and the most widely used descriptive criterion is the correlation coefficient (R2). However, in many cases, neither the significance of the parameters obtained by multiple linear regression (as F ratios, P values or by means of Pareto charts), or the pattern of the residuals is commented on, so the validity of the models may be questionable. Also, it is strongly recommended that central composite designs be used with replicated measurements in the centre to apply the lack of fit test, because this test is designed to determine if the selected model is adequate to describe the observed data. A common error in some works is the reporting of prediction errors for the models taking into account only those data that are used to construct the model (model data set) or, in some instances, both this data set and the prediction data set. It must be urged that the prediction capability of a model should not be evaluated only by the use of the model data set. The prediction data set should be used being the relative mean squared error of prediction (MSEPrel) [7] and the root mean square error of prediction (RMSEP) the most useful predictive criteria. They are calculated as follows: sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi m P 1 ðyk ^yk Þ2 m MSEPrel ¼

RMSEP ¼

k¼1

y

x100 %

vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi uP um u ð^yk yk Þ2 tk¼1 m

with y being the average response, yk the measured and ^yk the predicted responses of all the test points (m).


109

Although there is no agreement about the size of the prediction data set, in our opinion when it is not possible to get at least five points the validation should be achieved by using the cross validation method (leave-one-out method). When the separation conditions have been chosen, the next and final step is the analytical method validation so we can asses the validity of the quantification results. In this case the parameters of interest are the selectivity, the precision, the dynamic range and linearity range, the accuracy, the sensitivity, the detection and quantification limits, and the robustness [45, 46]. In particular, in order to quantify pharmaceutical products, the optimized experimental conditions are usually validated according to the ICH guidelines [47].

5.5 Selection of Optimum Separation Parameters Summarizing the principles outlined in the previous sections, the selection of optimum separation parameters can be viewed as a sequential process, in which each step is influenced by the results obtained in the previous one. The process begins with the selection of the variables (and ranges) influencing the separation process. At this stage the researcher’s knowledge and the bibliographic information can be of great importance. So, in Table 5.1 the variables studied and their variation ranges in the most recent works in EKC have been summarized. Also, the reviews of Altria et al. [9] and Sentellas and Saurina [5] can be consulted. In this selection it would be desirable to include as many variables as possible to assure that global optimum cannot be missed. With respect to response(s) we must be clear what we are looking for. If we are interested only in the base-line separation of the test solutes, an adequate response could be the resolution between adjacent peaks or the overall normalization resolution. The advantage of this latter function is that it is able to indicate the quality of an experiment with only one value, instead of the n 1 values obtained if we consider resolution between adjacent peaks (n being the number of test solutes). By contrast, if we are interested, not only in the base-line separation of the test solutes, but also in the analysis time we could use an objective function such as the Q criterion reported by Liu et al. [21]. At this point, we should construct a screening experimental design in order to reduce the number of variables, not to evaluate the quality of the model. The simplest designs are the fractional factorial designs as that shown in Figure 5.1. By means of multivariate linear regression we can obtain the coefficients of a first order polynomial and evaluate their statistical significance by using the ANOVA analysis or the Pareto charts. With this information we are able to select those variables significantly affecting the response. Then, the other variables can be adjusted for subsequent experiments to a fixed value (usually the mean value for the range studied). Depending on the results obtained, two routes can be followed. If the remaining variables are still many, we can apply a full factorial design at two levels with a first order polynomial to reduce, if possible, to a lesser number. By contrast, if the remaining variables are two or three, we could apply a central composite design with a second order polynomial. At this point, data of the design should be divided into two categories, the model data set and the prediction data set. The experiments conducted with the model data set allow the

110


coefficients of the second order polynomial to be obtained, and those conducted with the prediction data set allow evaluation of the prediction capability of the model. In order to evaluate the model developed, the ANOVA analysis can indicate the goodness of fit, the significance of the parameters (hence the possibility of simplification of the model eliminating those statistical nonsignificant terms) and the pattern of the residual can indicate if the requirements of the model are fulfilled. If more than one model is obtained (e.g. because we use different models with different responses), the best model can be chosen comparing R2 values, the number of significant terms in the polynomial and the prediction errors. If the prediction errors are large, then we could repeat the modelling step by using theretical models (if possible) or ANNs, both capable of modelling nonlinear responses. In the last step, the best separation conditions can be chosen graphically or by a gridsearch algorithm (finding the maximum value for the response selected). Modelling also makes it possible to estimate the robustness of a method.

5.6 Concluding Remarks From the discussion in the different sections of this chapter some conclusions can be drawn. The use of experimental designs can help us to find the best conditions for a particular separation by EKC, although special care should be taken to choose the variables of interest and the range of variation. Also, in order to optimize the separation with the minimum number of experiments, it is necessary to introduce a screening step (one or more) to reduce the number of variables to as few as possible. Although the modelling step can be achieved by using theoretical models or by empirical models (empirical equations or ANNs), the best choice seems to be the empirical equations due to their simplicity. Only when we suspect that the response(s) are not linear is the use of ANNs justified. The theoretical models, although permitting an insight in the mechanism of migration, are not very adequate because the number of factors in the models is very restricted. In most cases, only one or two variables are considered. Moreover, they usually need the application of iterative methods to obtain the model constants, so the results depend significantly on the initial estimates. Furthermore, the iterative methods are time consuming and the global optimum can be missed during the optimization process. With respect to the response(s) choice, it must be pointed out that different optimization conditions can be found when different response criteria are used. We consider that objective functions taking into account both the resolution and the analysis time are the most appropriate in EKC with the exception of those chiral separations in which the most important criterion is usually the resolution between enantiomers. Finally, we strongly recommend special care in the validation step. Many reports do not contain enough information about the validation of the model used in the prediction of the best separation conditions or about the analytical method validation, so it is very difficult to establish the usefulness of these methods. The validation step should reflect the goodness of fit of the model, its prediction capability and the characteristics of the analytical method.


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Acknowledgements M.L. Marina thanks the Ministry of Science and Technology (Spain) for the research project BQU2003-03638.

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6 Microemulsion Electrokinetic Chromatography Alex Marsh, Kevin Altria and Brian Clark

6.1 Introduction Microemulsion electrokinetic chromatography (MEEKC) is an extension of the micellar electrokinetic chromatography (MEKC) principle and was first presented by Watarai in 1991 [1]. In MEEKC separations are typically achieved using microemulsions composed of nanometre-sized droplets of oil suspended in aqueous buffer. The oil droplets are coated by surfactant molecules and the system is stabilized by the addition of a shortchain alcohol cosurfactant. The novel use of water-in-oil microemulsions for MEEKC separations has also been investigated recently [2]. Several reviews have been written on the subject [3–7]. MEKC and MEEKC differ in the type of pseudostationary phase used. In MEKC, the separation electrolyte consists of a solution of surfactant molecules, which are present at a concentration above the critical micelle concentration (CMC) at which aggregates (micelles) start to form. Further addition of surfactant above the CMC increases the volume fraction of the micellar phase while the concentration of free surfactant molecules in solution remains constant. In MEEKC, the separation electrolyte additionally contains an immiscible oil which forms surfactant-coated droplets dispersed throughout the aqueous buffer to form a stable oil-in-water microemulsion. The surfactant molecules are able to facilitate droplet formation because they consist of a hydrophilic, often charged, head group and a long hydrophobic carbon tail. The tail end dissolves in the oil while the head group remains in the aqueous continuous phase, which lowers the water-oil surface tension. A low chain length alcohol


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Figure 6.1 Schematic of a microemulsion droplet [3]. (Reprinted from Chromatographia, 52, Altria, Clark and Mahuzier, copyright 2000, with permission from Elsevier)

cosurfactant is also added which lowers the surface tension further still by acting in a similar manner to the surfactant; its carbon tail resides in the oil while the hydroxyl alcohol group remains in the water, bridging the oil–water interface. The cosurfactant has the effect of reducing the intermolecular repulsion experienced by the surfactant molecule head groups by positioning itself in between them around the droplet, which lowers the system surface tension to almost zero. The droplets in the microemulsion are less than 10 nm in diameter, hence they don’t scatter white light and the solution is optically transparent. The water continuous phase of the microemulsion usually contains additives, for example buffers or acid to control the pH, ion-pair reagents, cyclodextrins or organic modifiers, so that the optimum separation conditions are provided. Figure 6.1 illustrates a schematic of a microemulsion droplet, showing the SDS surfactant, butanol cosurfactant, the octane droplet and the counter ions surrounding it. The separation principle of MEEKC is similar to that of MEKC, where solutes are separated by both electrophoresis and interaction with the micelles (partitioning into the micellar phase). Use of a microemulsion electrolyte containing ionic surfactants allows chromatographic separation as solutes can partition between the oil droplet and the aqueous buffer phase. Hydrophobic solutes favour inclusion into the oil droplet rather than the aqueous buffer phase while hydrophilic analytes reside mainly in the aqueous phase. In the case of neutral solutes, separation according to differences in the partitioning coefficient between these two phases is possible. Generally, high pH buffers such as phosphate or borate are used in MEEKC. When the voltage is applied across the capillary, these buffers generate a high electroosmotic flow (EOF) towards the cathode at the detector end. The SDS surfactant-coated oil droplets are negatively charged and attempt to migrate towards the anode, but are eventually swept through the detector to the cathode by the EOF. Free solution capillary electrophoresis (FSCE) performed at high pH results in cationic solutes migrating to the detector first, followed by neutral solutes (not separated) and finally anions, with migration time being dependent on analyte size and charge. In MEEKC, the effective electrophoretic mobility of the solutes is modified by interaction with the charged microdroplets. MEEKC also offers the capability of separating neutral solutes, with their migration time directly related to their hydrophobicity. Indeed, MEEKC has been used [8–15] to assess compound hydrophobicity (log POW) with good cross correlation to other hydrophobicity

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Figure 6.2 MEEKC separation principle within the capillary [7]. (Reprinted from J. Chromatogr. A., 892, Altria, pp. 171–186, copyright 2000, with permission from Elsevier)

measurement techniques. Figure 6.2 illustrates the MEEKC separation principle within the capillary.

6.2 Comparison with Other Capillary Electromigration Modes Comparisons are often made between MEEKC and micellar electrokinetic chromatography (MEKC) [16–22] as their separation principle is similar. In MEKC, the separation of neutral solutes is due to the interaction of dissolved molecules with the hydrophobic core of ionic micelles [20]. Solutes penetrate the surface of the MEEKC microdroplet more easily than that of the more rigid MEKC micelle, which allows MEEKC to be applied to a wider range of solutes. MEEKC has often been found to provide superior separation efficiency to MEKC, probably due to improved mass transfer between the microemulsion droplet and aqueous phase, mediated by the cosurfactant [6]. MEEKC offers a larger separation window, and the size of this window can be controlled and therefore potentially [6,23–24] offers greater separation capability for hydrophobic compounds than MEKC [25]. Investigations have been performed [21] comparing MEEKC to solvent-modified MEKC, which used an electrolyte containing the same buffer, cosurfactant and amount of SDS as the microemulsion. The two electrolytes were found to be very similar with respect to separation selectivity and efficiency. Studies have also been performed that compare MEEKC to other capillary electromigration modes [24,26–28]. Free solution CE (FSCE) and nonaqueous CE (NACE), MEKC and MEEKC separations of a range of methylquinolines have been compared [26], while the separation of nicotine and related impurities [27] was compared using MEEKC, NACE and FSCE, with MEEKC offering the better selectivity. Figure 6.3 shows the separation of nicotine and a range of related substances by a MEEKC method. The separation of isomers of dienoic acids was compared by cyclodextrin-modified CE,

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Figure 6.3 Separation of nicotine and related impurities by MEEKC. Test mix dissolved in electrolyte; 50 mm i.d. 30 cm standard fused silica capillary; sample injection of 10 mbar for 5 s; 10 kV separation; 260 nm UV detection; 40 C; electrolyte: 89 % 10 mM tetraborate at pH 9.15 þ 0.8 % octane þ 3.3 % SDS þ 6.6 % butanol [27]. (Reprinted from Electrophoresis, 25, Marsh, Altria and Clark, pp. 1270–1278, copyright 2004, with permission)

MEEKC and CEC [28], and MEEKC was found to give a superior separation to the cyclodextrin method, but full resolution of all the isomers was only given by CEC.

6.3 Method Development Options and Approaches in MEEKC In MEEKC, any of the many microemulsion electrolyte components can be varied or further modifiers can be added. This can affect the separation selectivity and quality, which provides considerable method development options for MEEKC when optimizing complex or difficult separations. The common variables encountered in MEEKC and their reported effects on the separation are described here. To ensure a thorough approach to method development, an experimental design can be employed for a full assessment of the separation-influential factors, as demonstrated recently for MEEKC [29]. Using a test mixture containing anionic, cationic and neutral drugs, a series of experiments was performed where the effect of variation of surfactant, cosurfactant and borate buffer concentrations, Brij 35 and propan-2-ol addition and temperature were measured by the change to the separation window, analyte migration velocity and plate height. Multiple linear regression models were used to analyse the results and SDS concentration and propan-2-ol addition were found to have the largest effect on separation selectivity. It has been shown that it is possible to predict MEEKC migration times using an artificial neural network (ANN) [30], as was demonstrated on a set of 53 benzene derivatives and heterocyclic compounds. The ANN was used to generate a quantitative structure– property relationship model between the molecular structural parameters of the benzene derivatives and their observed MEEKC migration indices. Given the structural


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parameters of unknown molecules, the model was found to predict their migration indices with minimum and maximum error of 7.25 and 1.18 % respectively. 6.3.1

Cosurfactant

The cosurfactant is the most influential of the microemulsion constituents on separation selectivity [4,6,31,32]. Butan-1-ol is the most commonly used cosurfactant in MEEKC. Increasing cosurfactant concentration [3] alters migration times. The electrolyte viscosity is increased by the viscous alcohol, which reduces the EOF velocity. The microemulsion droplet increases in size as it incorporates more cosurfactant, reducing its charge density and thus reducing its electrophoretic mobility [33]. Increasing the cosurfactant concentration can alter selectivity if the sample contains a mixture of neutral and ionic solutes [3] but for mixtures of similar compounds, it has been found that migration times, but not selectivity, are altered [34]. The retention factors of hydrophobic compounds are decreased with the butanol-enriched buffer, whereas the retention factor increases for more hydrophilic compounds. With a reduced electroosmotic velocity, the observed velocity of anions (having constant electrophoretic mobility) will be decreased thus increasing the migration time. Increasing the cosurfactant concentration has been found to improve the separation [35], and increase peak resolution [21,24,36]. A variety of different alcohol molecules have been employed as the cosurfactant in MEEKC; each of a homologous series of alcohols from propan-1-ol to hexan-1-ol markedly changed the separation selectivity [37] and four different selectivities were given by nine different cosurfactants [32]. Branched chain alcohols such as butan-2-ol do not enable microemulsion formation because they cannot bridge the oil–water interface effectively [3]. It has been suggested [4] that the cosurfactant, because it can partition into the oil droplet, can modify the chromatographic properties of the microemulsion oil phase and may therefore have quite an influence upon the microemulsion electrolyte’s selectivity. 6.3.2

Surfactant Type and Concentration

MEEKC separations are significantly affected by the choice of microemulsion surfactant, which affects droplet charge and size, level and direction of EOF and the degree of ion pairing with solutes. SDS, an anionic surfactant, is usually used in MEEKC at concentrations of 3.3 % w/w (118 mM). Increasing the SDS concentration of the microemulsion electrolyte reduces the EOF velocity, which affects solute migration times depending on analyte charge [3,16,24,29,38]. Depending on solute specific interaction with the surfactant, increasing surfactant concentration can either decrease [35] or increase [24,36] analyte migration time and peak resolution [35]. The use of a high concentration of surfactant has also been shown to produce a more stable and reproducible separation system [39]. A higher concentration of SDS increases the charge density of the droplet and hence its electrophoretic mobility, which increases migration times for neutral and hydrophobic solutes, and also those that show electrostatic interactions with the droplet. The electrolyte ionic strength is also increased, which reduces the EOF velocity and lengthens the analysis time. Selectivity can be greatly altered by replacing SDS partly or fully with other surfactants [40]. The use of various anionic bile salts in place of SDS has been shown to offer a different selectivity [41], specifically the bile salt sodium cholate was reported to offer a better selectivity for

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lipophilic solutes [35]. For log POW determinations by MEEKC, it has been reported [9] that using biosurfactants, e.g. phosphatidylcholine, gave better log POW estimations than did SDS microemulsion for a series of synthetic steroids. Selecting a different salt of the surfactant, for example LiDS instead of SDS, has been shown [3] to increase the EOF velocity and reduce the electric current strength so that a higher voltage can be applied and a faster separation can be achieved without generation of excessive current. The use of cationic surfactants instead of an anionic surfactant [3,42] will eliminate the electrostatic interactions which occur between cations (such as protonated basic drugs) and SDS-coated droplets when using the standard SDS microemulsion. Use of a cationic surfactant reverses the EOF direction and requires the use of negative polarity voltage. Nonionic surfactants can be added to the microemulsion without increasing the operating current but microemulsions with nonionic surfactants can not be used for the separation of neutral solutes. MEEKC electrolytes prepared with nonionic surfactants have been used to separate hydrophobic sun-tan lotion additives [43], a range of methylquinolines [26], and to provide optimum conditions for a MEEKC-dual opposite injection separation [44].

Figure 6.4 MEEKC separation of seven neutral solutes using four different surfactants. Test mix of FA: formic acid; 1: benzamide; 2: nicotinic acid; 7: p-chlorobenzamide; 8: prednisone; 13: ethyl-3-nitrobenzoate; 14: betamethasone; 15: nicotinic acid butyl ester dissolved in 50/ 50 MeOH/H2O at 0.2 mg mL1. Separation conditions: sample injection 2 s at þ 50 mbar; 20 kV; 48.5 cm 50 mm i.d. fused silica capillary; electrolyte: 0.8 % w/w octane, 3.3 % w/w surfactant, 6.6 % w/w 1-butanol, 89.3 % w/w 10 mM borate in water pH 9.2; surfactant: (a) SDS; (b) SDS þSDOSS (50/50 w/w); (c) SDS þ Tween 21(50/50 w/w); (d) SDS þ MAPS (50/50 w/w) [31]. (Reprinted from Electrophoresis, 22, Gabel-Jensen, Hansen and PedersenBjergaard, pp. 1330–1336, copyright 2001, with permission)


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Mixed surfactant systems, where two different types of surfactant are used to provide the optimum separation selectivity, have been reported [13, 31, 45]. A mixed surfactant microemulsion system containing 0.75 % w/w Brij 35 and 2.25 % w/w SDS was used to separate UV filters in sunscreen lotions [45]. Mixed systems of SDS and SDOSS (sodium dioctylsulphosuccinate), SDS and MAPS (3-(N,N-dimethylmyristylammonium) propane sulfonate), SDS and Tween 21 or SDS and Brij 35 gave different separation selectivity for a mixture of neutrals [31], and the four separations are shown in Figure 6.4. 6.3.3

Addition of Organic Solvents

In MEKC with aqueous separation electrolyte, hydrophobic solutes partition strongly into the micelles and are highly retained and poorly resolved. This problem can be overcome by adding an organic solvent, typically acetonitrile, methanol or isopropanol, at a volume fraction of up to 30 %, to the buffer. This approach can also be taken with MEEKC, but the amount of solvent that can be added before the microemulsion is disrupted varies. For instance propan-2-ol has been used at a volume fraction greater than 50 % [3] but methanol caused disruption of the microemulsion above 8 % v/v. The addition of organic solvents can alter the degree of ionization of solutes, which affects their electrophoretic mobility [4]. The addition of MeOH (up to 8 %) and MeCN (up to 12 %) change the electrolyte viscosity and slow the EOF, thus increasing the migration time [3]. This effect is greater upon hydrophobic compounds, and benefits their separation [13]. Propan-2-ol acts as a second cosurfactant and can change separation selectivity and increase migration time [3,19,29,45]. The addition of 30 % propanol was used to achieve resolution for two closely migrating, priority endocrine disruptors by increasing the migration time window [39]. The addition of 5 % MeOH, MeCN, IPA (isopropyl alcohol) or THF was found to improve the separation of isoquinoline alkaloids from herbal medicine by increasing migration times and peak resolution [35]. 6.3.4

pH of Microemulsion

pH is a major factor for MEEKC separations because it affects both the EOF velocity and the degree of ionization of the solutes. A number of reports have investigated the effect of pH on the separation [3, 17, 37]. Typically a pH of 7–9 is used in MEEKC, giving a high EOF velocity. Migration times have been found to decrease with an increase in electrolyte pH [35, 40]. Extremes of pH have been used for ion suppression during solubility analysis where the solute needs to be in its uncharged state [10–11]. Very high pH (pH 12) buffers have been used [10] for basic compounds and very low pH (pH 1.2– 1.4) for acidic solutes. At low pH [10] the EOF velocity is very low and a negative voltage needs to be applied to induce migration of the droplets towards the detector. In contrast to a typical high pH MEEKC separation, this results in the most retained compounds eluting first [3,46] (reversed direction mode). The separation of priority endocrine disrupting compounds in wastewater was performed by MEEKC at pH 2 [39]. A low pH MEEKC buffer has also been employed to separate a range of parabens from parahydroxybenzoic acid [46], a range of hydrophobic vitamins [47], a range of pharmaceuticals [48] and green tea catechins [32]. The separation of the parabens testmixture at both low and high pH is shown in Figure 6.5.

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Figure 6.5 Separation of paraben test-mixture using low (pH 2.1) and high (pH 9.5) pH MEEKC. Test mix of Ac: 4-hydroxybenzoic acid; MP: methyl paraben; EP: ethyl paraben; PP: propyl paraben; BP: butyl paraben, and ISS: internal standard dissolved in electrolyte at 5 mg mL1. Separation conditions: sample injection 3 s at þ 20 mbar; 11 kV; 33 cm 50 mm i.d. fused silica capillary; 40 C, 200 nm UV; electrolyte: 3.3 % w/w SDS; 6.6 % w/w 1-butanol; 0.8 % w/w octane; 89.3 % w/w aqueous buffer; buffer: (a) 50 mM phosphate buffer pH 2.1; (b) 10 mM borate buffer pH 9.2 [46]. (Reprinted from J. Chromatogr. A., 924, Mahuzier, Altria and Clark, pp. 465–470, copyright 2001, with permission from Elsevier)

6.3.5

Buffer Type and Concentration

Typically, low ionic strength (5–10 mM) borate or phosphate buffers are used as the microemulsion aqueous phase, giving a fast EOF while generating low currents. Increasing the buffer concentration of the electrolyte has been shown to improve peak resolution [26,49]. Using a low concentration of borate buffer in the microemulsion gave a faster separation because of the faster EOF at low ionic strength, but the precision of subsequent injections was lower due to electrolysis effects [3]. The use of a zwitterionic buffer such as TRIS can reduce the amount of current produced during separation, enabling higher voltages to be applied to give faster separations without the concern of Joule heating within the capillary [50]. 6.3.6

Buffer Additives

Further additives can be added to the electrolyte to improve separations. Urea is added in MEKC [3] to aid the separation of hydrophobic compounds by altering the hydrogen bonding properties of the aqueous phase, reducing the retention factors for hydrophobic solutes. When added to MEEKC buffer, the migration time window was observed to expand, similarly to the addition of organic solvents, which allows the resolution of hydrophobic compounds [3]. Cyclodextrins can be added to the buffer, and they can aid the solubilization of hydrophobic compounds and also offer solute partitioning possibilities [3]. The addition of 25 mM b-cyclodextrin to the microemulsion was found to alter the separation selectivity, and reduce the migration times of hydrophobic compounds [3] by complex formation and consequently reduction of the apparent retention factors, while the addition of 5 mM sulphated b-cyclodextrin enabled the resolution of nine xanthones [22].


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Ion-pairing reagents have their own electrophoretic mobility and can interact with solutes, and they can also interact to affect the net charge and mobility of ionic analytes. They can also become incorporated, or interact, with the charged microdroplet, and they increase the ionic strength of the electrolyte, which lowers the EOF velocity. Incorporation of the ion-pairing reagent sodium octanesulphonate into the microemulsion electrolyte was found to increase the migration times of solutes [3]. 6.3.7

Sample Preparation

It is regarded [13,16,19,25,35,37,51] as best practice to dissolve the sample in the microemulsion electrolyte for a good MEEKC separation. The microemulsion has a good dissolving power for both hydrophilic and hydrophobic compounds and makes a good sample solvent. The use of alternative sample diluents can disrupt the microemulsion buffer inside the capillary, causing a poor quality separation. If the sample is not directly solubilized in the required microemulsion then it can be dissolved in an alternative solvent and then diluted with microemulsion prior to injection. The technique of ‘stacking’, where improved separation efficiencies and increased detector response are obtained using a sample solution of lesser ionic strength than the microemulsion has been shown to be effective when used in MEEKC [3,52]. 6.3.8

Temperature

The temperature of the separation capillary affects the distribution coefficients between the microdroplets and the surrounding aqueous phase. The electrophoretic mobility of an ion increases by 2 % for each C, and hence the selectivity of mixtures of different types of solute can alter because the temperature affects neutral and charged species disproportionately [4, 17]. Increasing the temperature has been found to reduce migration times [13,17,24,35,40] because the EOF velocity increases due to the lower buffer viscosity. 6.3.9

Oil Type and Concentration

Generally, octane at a concentration of 0.8 % w/w is used as the microemulsion oil. Although hexane, heptane and octane have been shown to give similar selectivity and migration times [26,53], octane has been reported to give more repeatable microemulsions and superior peak resolution, efficiency and precision [19, 39]. A range of other oils have been reported [3,19,40,42,53–55] including pentan-1-ol, hexan-1-ol, octan-1-ol, cyclohexane, chloroform, methylene chloride, amyl alcohol and butyl chloride. Additionally the use of chiral oils [56] and low interfacial tension oils such as ethyl acetate [57–58] has been shown to effect chiral separations. Variation of the oil concentration within the range that allows stable microemulsion formation has been reported not to change the separation significantly [21,24,36]. 6.3.10

Water-in-oil MEEKC

Water-in-oil microemulsions have interesting potential for the separation of hydrophobic compounds, and their use has been demonstrated successfully [59]. The separation of

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Figure 6.6 Separation of test-mixture using water-in-oil MEEKC. Test mix of thiourea, caffeine, naphthalene, 4-hydroxyacetophenone and sorbic acid dissolved in electrolyte at 1 mg mL1. Separation conditions: sample injection 1 s at þ 50 mbar; electrolyte: 20 % w/w SDS, 48 % w/ w butanol, 32 % w/w 0.07 M sodium acetate in water; 30 kV; 24.5 cm 50 mm i.d. fused silica capillary; 25 C; 200 nm UV detection [2]. (Reprinted from Electrophoresis, 25, Altria, Broderick, Donegan and Power, pp. 645–652, copyright 2004, with permission)

analytes is markedly different to that obtained in oil-in-water MEEKC, the most noticeable difference being that neutral solutes do not migrate in order of their hydrophobicity, which offers a unique selectivity compared to o/w MEEKC, especially for the analysis of highly hydrophobic neutral compounds. The factors affecting separation by water-in-oil MEEKC have been investigated [2] and a range of neutral and acidic analytes separated, as shown in Figure 6.6. The water-in-oil microemulsion reported by Broderick and coworkers [2] consisted of 10 % w/w SDS, 78 % butanol, 2 % octane and 10 % 0.07 mM sodium acetate aqueous buffer. The advantage of w/o MEEKC is its ability to solubilize highly hydrophobic analytes due to the oil continuous phase. With aqueous electrolytes, sample extraction and preparation steps are normally needed to remove the hydrophobic excipient materials to prevent interference and precipitation. For o/w MEEKC sample preparation, these steps are eliminated. Water-in-oil MEEKC generates a low separation current, so high buffer concentrations are needed in w/o MEEKC to generate sufficient operating current for stable and efficient resolutions to be achieved. 6.3.11

Pressure Assisted MEEKC

Throughout the duration of a MEEKC separation it is possible to apply air pressure as well as voltage to the capillary. This technique works by gently forcing the capillary contents towards the detector and is useful in speeding up separations that are slow due to the presence of late-migrating, very hydrophobic, solutes. The use of a pressure assistance of 5 mbar during a 20 kV MEEKC separation [60] reduced the migration time of dodecanoacetophenone from 40 min to 25 min. Pressure assistance of up to 10 mbar was found not to affect the separation, but further increases resulted in narrowing of the separation window [60]. Pressure assisted MEEKC has been applied to log POW determinations [8,60,61,63] to reduce analysis time.


6.3.12

125

Dual Opposite Injection CE

Dual opposite injection is a sampling technique [44] where cations and anions are injected and migrate from opposite ends of the capillary toward the detector. A MEEKC electrolyte containing 10 mM zinc cations was used to suppress the EOF. A neutral surfactant (Brij 35) was used to achieve chromatographic partitioning of solutes as they migrated along the capillary towards the detector. 6.3.13

High Speed MEEKC

MEEKC analysis times are typically in the order of 10 minutes, mainly because high ionic strength buffers are used, which limits the voltage that can be applied due to the concerns of Joule heating within the capillary. To form a stable microemulsion, high concentrations of surfactant are usually required, but it has been reported [50] that by using a low surface tension oil, the amount of surfactant needed can be reduced. By also using the zwitterionic TRIS buffer, high temperature, high voltage and ‘short end’ capillary injection (where the sample is introduced at the detector end of the capillary), analysis times were reduced to 1 minute.

6.4 Applications The number of publications involving MEEKC has grown considerably recently, due to method development and optimization of the technique and further development of new methodologies. Table 6.1 contains a range of applications reported in the literature recently (2000–2004) and the composition of the microemulsion used. A brief overview of each application area (chiral separations, log POW determinations, pharmaceuticals, natural products and environmental analysis) is given. 6.4.1

Chiral Separations

Capillary electrophoresis is an important technique for enantiomer separation, and successful analyses have been carried out by MEEKC. To achieve chiral resolution of a range of basic drugs, a chiral surfactant dodecoxycarbonylvaline (DDCV) at a concentration of 1 % w/v in combination with low interfacial tension oils (methyl acetate, ethyl acetate, methyl propionate, methyl formate) has been used [57,58]. Ethyl acetate as the oil was found to provide the greatest enantioselectivity with subtle changes in selectivity resulting from changing the oil. A chiral oil, (2R, 3R)-di-n-butyl tartrate at a concentration of 0.5 % w/w, has been successfully employed for enantioselective ephedrine separation [56]. Chiral resolution has been achieved for racemic levetiracetam by cyclodextrin-modified microemulsions [62]. 6.4.2

Log POW Determinations

The oil-water partitioning process by which solutes are separated in MEEKC has enabled its use [8–15,60,61] for compound solubility assessment with good cross correlation to other hydrophobicity measurement techniques. The MEEKC method of octanol–water

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Table 6.1 Range of recent (2000–2004) MEEKC buffer compositions and applications Application Pharmaceuticals Determination of nine preservatives in pharmaceutical and cosmetic products Analysis of betamethasone and derivatives

Analysis of 4-hydroxybenzoate preservatives in pharmaceuticals Analysis of formulated drug products Hydrophobic ingredients of pharmaceutical ointment Levetiracetam from other antiepileptic drugs Separation of immunosuppressive drugs

Analysis of ephedrine and pseudoephedrine Amino acid derivatives using laser-induced fluorescence detection

Microemulsion composition

Reference

3.3 % w/w SDSa, 0.81 % w/w octane, 6.6 % w/w butan1-ol, 89.3 % w/w 50 mM borate pH 9.5 1.44 % w/w SDS, 0.81 % w/w octane, 6.61 % w/w butan1-ol, 91.14 % 20 mM sodium phosphate pH 7.5 1.9 % w/w isopropylmyristate, 2.0 % w/w SCb/SDCc, 3.5 % w/w PCd, 0.81 % w/w octane, 7.5 % w/w butan1-ol, 85.1 % 20 mM sodium phosphate pH 7.5 3.31 % w/w SDS, 0.81 % w/w n-octane, 6.61 % w/w butan-1-ol, 89.27 % w/w 50 mM phosphate buffer pH 2.1 3.31 % w/w SDS, 0.81 % w/w n-octane, 6.61 % w/w butan-1-ol, 89.27 % w/w 10 mM borate buffer pH 9.2 3.97 % w/w SDS, 0.81 % w/w n-octane, 6.61 % w/w butan1-ol, 10 % w/w propan-2-ol, 78.61 % w/w 10 mM borate buffer pH 9.2 1.8 % w/w SDS, 0.48 % w/w n-octane, 3.96 % w/w butan1-ol, 93.76 % w/w 10 mM borate buffer pH 9.2 1.44 % w/w SDS, 0.81 % w/w octane, 6.61 % w/w butan1-ol, 91.14 % 20 mM sodium phosphate pH 7.5 2.0 % w/w SDC, 3.5 % w/w PC, 1.9 % w/w IPMe, 0.81 % w/w octane, 7.5 % w/w butan1-ol, 85.1 % 20 mM sodium phosphate pH 7.5 2.0 % w/w SC, 3.5 % w/w PC, 1.9 % w/w IPM, 0.81 % w/w octane, 7.5 % w/w butan1-ol, 85.1 % 20 mM sodium phosphate pH 7.5 23.3 mM SDS, 16.4 mM nheptane,180.85 mM butan-1-ol, 8 % acetonitrile, 20 mM borate 2.12 % w/w SDS, 0.52 % w/w heptane, 4.21 % w/w butanol, 84 mM borate pH 8.4

[17]

[9]

[46]

[64]

[67]

[37]

[12]

[65] [49]


127

Table 6.1 ðContinuedÞ Application


Reference

Nicotine-related alkaloids

3.3 % w/w SDS, 0.8 % w/w octane, 6.6 % w/w butan-1-ol, 89.29 % w/w 10 mM sodium tetraborate pH 9.15 6.0 % w/w SDS, 0.8 % octane, 6.6 % butanol, 20.0 % propan2-ol, 66.6 % 25 mM phosphate pH 2.75 80 mM SDS, 1 % w/w octane, 5 % v/v butanol, 40 mM borate pH 8.5 6.0 % w/w SDS, 0.8 % octane, 6.6 % butanol, 20.0 % propan2-ol, 66.6 % 25 mM phosphate pH 2.75 2.25 g SDS/0.75 g Brij35, 0.8 g n-alkane, 6.6 g 1-butanol, 17.5 g 2-propanol, 72.1 g 10 mM borate buffer pH 9.2

[27]

2.31–3.32 % w/v SDS, 1.36 % w/v n-heptane, 7.38–9.72 % w/v cosurfactant, 86.3 %–94.12 % w/v, 50 mM phosphate buffer pH 2.5. 2.31 % w/v SDS, 1.36 % w/v heptane, 9.72 % w/v butan1-ol, 86.61 % 50 mM sodium phosphate buffer pH 2.5 100 mM SDS, 70 mM octane, 800 mM butan-1-ol, 10 mM phosphate buffer pH 7 120 mM SDS, 80 mM heptane, 10 % v/v n-butanol, 50 mM borate buffer pH 9.5, 5 mM sulphated b-cyclodextrin

[32]

1.0 % w/v DDCVf, 0.5 % v/v ethyl acetate, 1.2 % v/v butan1-ol, ACESg 50 mM pH 7 1.0 % w/v DDCV, 0.5 % v/v ethyl acetate, 1.2 % v/v butan1-ol, ACES 50 mM pH 7 1.0 % w/v DDCV, 0.5 % v/v ethyl acetate, 1.2 % v/v butan-1-ol, ACES 50 mM pH 7 þ 1.0 % s-b-CDh, phosphate 50 mM pH 7.0 þ1.0 % HS-b-CD

[57]

Analysis of vitamins

Analysis of water and fat-soluble vitamins Separation of fat-soluble vitamins UV filters in suncreen lotions

Natural products Analysis of catechins in green tea products

Analysis of catechin and galocatechin in extracts of cistus species Withanolides in plant extracts Separation of pharmacologically active xanthones from securidaca inappendiculata Chiral analysis Analysis of 14 chiral compounds Chiral separation of ephedrine related drugs Analysis of chiral compounds by chiral cyclodextrinmodified MEEKC

[21]

[19] [47]

[45]

[66]

[38] [22]

[58] [62]

(Continued)

128




Reference

0.6 % w/v SDS, 0.5 % v/v ethyl acetate, 1.2 % v/v butan-1-ol, Tris 100 mM, pH 8.0 þ1.0 % s-b-CD, phosphate100 mM, pH 8 þ 1.0 % HS-b-CD Log Pow determinations Log POW screening of weakly basic, weakly acidic and neutral pharmaceuticals Multiplexed MEEKC determination of log POW values for neutral and basic compounds Log POW of carbonate esters and small organic molecules

Log POW estimation of neutral and weakly acidic by MEEKC dynamically coated capillary columns Other applications Separation of isomers of dienoic acids Six biphenyl nitrile compounds and three related substances MEEKC using artificial neural networks Separation of neutralcationic and anionic analytes; performance evaluated by multiple linear regression models

50 mM SDS, 82 mM n-heptane, 0.87 M butan1-ol, 50 mM borate-phosphate buffer pH 10 3.3% w/v SDS, 0.8 % w/v n-heptane, 6.6% w/v butan-1-ol, 92% 68 mM 3-(cyclohexylamino)-1propanesulfonic acid pH 10.3 1.80 % w/w SDS, 0.82 % w/w n-heptane, 6.49 % w/w butan-1-ol, 0.1 M borate-0.05 M phosphate buffer pH 7.4 1. 44–2.88 % w/w SDS, 0.82 % w/w n-heptane, 6.49 % w/w butan-1-ol, 0.05 M acetate buffer pH 4.75 2.16 % w/w SDS, 0.82 % w/w n-heptane, 6.49 % w/w butan1-ol, 0.05 M HCl pH 1.4 1.4 % w/v SDS, 1.2 % v/v n-heptane, 8 % v/v butan-1-ol, 85 % w/w 50 mM sodium phosphate pH 3

3.31 % w/w SDS, 0.81 % w/w octane, 6.61 % w/w butan1-ol, 89.27 % w/w 10 mM sodium tetraborate 100 mM SDS, 80 mM SC, 0.81 % v/v heptane, 7.5 % v/v butan-1-ol, 10 % v/v acetonitrile, 10 mM borate 1.44 % w/w SDS, 0.82 % w/w n-heptane, 6.49 % w/w butan-1-ol, 0.1 M borate-0.05 M phosphate buffer pH 7 2–3.5 % w/w SDS, 0–2.5 % w/w Brij35, 5–9 % w/w butan1-ol, 0–20 % w/w propan-2-ol, 0–50 mM borate buffer pH 9.2

[60]

[8]

[11]

[61]

[28]

[13]

[30]

[29]


129



Reference

Separation of cations and anions by nonionic microemulsion

0.6 % w/w Brij35, 0.5 % w/w ethyl acetate, 1.2 % w/w butan-1-ol, 50 mM ACES buffer pH 6.5 200 mM SDS, 80 mM octane, 900 mM butan-1-ol, 20 % v/v propanol, 25 mM phosphate buffer pH 2 10 % w/w SDS, 2 % w/w octane, 78 % w/w butan1-ol, 10 % w/w 70 mM ammonium acetate 3.3 % w/w SDS, 0.81 % w/w octane, 6.61 % w/w butan-1-ol, 89.27 % w/w 10 mM sodium tetraborate pH 9.3 1.66 % w/w SDS, 0.91 % w/w heptane, 6.61 % w/w butan1-ol, 90.92 % w/w 20 mM sodium tetraborate pH 9.2 0.18 M AOTi, 0.05 M TEAj, 20 % water in decane 3.31 % w/w SDS, 0.81 % w/w octane, 6.61 % w/w butan1-ol, 89.27 % w/w 10 mM sodium tetraborate 2.25 % w/w SDS, 0.75 % Brij 35, 0.8 % octane, 6.6 % butanol, 25 % propan2-ol, 64.6 % 10 mM borate buffer pH 9.2

[44]

Priority endocrine disrupting compounds in wastewater Separation of neutral and acidic compounds and a range of aromatic acids by W/O MEEKC Separation of sulphated disaccharides Separation of lignin degradation products Test-mixture of hydrophobic compounds Separation of neutral, acidic and basic substances Separation of hydrophobic polymer additives

[39]

[2]

[68]

[69]

[59] [3]

[70]

a

SDS: sodium dodecyl sulphate surfactant SC: sodium cholate surfactant c SDC: sodium deoxycholate surfactant d PC: phosphatidylcholine surfactant e IPM: isopropylmyristate surfactant f DDCV: dodecoxycarbonylvaline surfactant g ACES: N-(2-acetamido)-2-aminoethanesulphonic acid buffer h s-b-CD: sulphated b-cyclodextrin; HS-b-CD: highly sulphated b-cyclodextrin i AOT: sodium di(2-ethylhexyl) sulfosuccinate surfactant j TEA: tetraethylammonium salt b

partition coefficient determination has recently been demonstrated for a series of synthetic steroids [9], small organic molecules [11], immunosuppressive drugs [12], biphenyl nitrile compounds used in the synthesis of liquid crystals [13] and pesticides [14], and for weakly acidic and neutral compounds using a dynamic capillary coating [61]. The use of MEEKC for log POW determinations has also been demonstrated with a 96-capillary array instrument for the high-throughput screening of compound hydrophobicity [8], and by pressure-assisted MEEKC [60]. Based on the same partitioning

130


principle used to determine log POW of compounds, the interaction between drug molecules and vehicle systems has been characterized using MEEKC [15]. 6.4.3

Pharmaceutical Analysis

Oil-in-water MEEKC has been used for many pharmaceutical applications over the past two years. Huang et al. [17] employed this technique in the separation of nine preservatives in various pharmaceutical and cosmetic products and compared results obtained by both MEEKC and MEKC methods. Both provided a successful separation but the MEKC analysis took 9 min compared with the 16 min MEEKC separation, due to the higher concentration of SDS in the electrolyte. Lucangioli et al. [9] have also compared different pseudostationary phases for microemulsion and micellar electrokinetic chromatography of betamethasone and derivatives. They found that using biosurfactants to enhance biopartitioning of the drugs gave a better model to estimate the hydrophobicity of the betamethasone series. MEEKC was found to give superior selectivity when compared to the use of a 60 mM tetraborate buffer containing bcyclodextrin for the separation of four geometrical isomers of decadienoic acid [28]. MEEKC also gave a better separation selectivity over other capillary electromigration techniques in the separation of nicotine and nicotine related alkaloids [27]. Polar pharmaceutical compounds have been separated in basic microemulsion media [36] and the separation found to be sensitive to surfactant and cosurfactant concentration. The method was successful for a variety of pharmaceutical separations including a mixture of 13 diuretics and five benzodiazepams. Levetiracetam has been separated [37] from five other antiepileptic drugs with which it can be coadministered, and the separation selectivity was found to be dependent on electrolyte composition, pH and cosurfactant type. Laser-induced fluorescence detection has been employed in combination with MEEKC to improve detection limits and to quantify ephedrine and pseudoephedrine [65] and amino acids [49] which had been derivatized with 4-chloro-7-nitrobenzo-2-oxa-1,3-diazol. 6.4.4

Quantitative Analysis

The capability of performing quantitative determinations is a very important factor if an analytical method is to be used routinely. MEEKC methods have been used to perform quantitative determinations including UV filters in sunscreen lotions [45], preservatives in pharmaceutical and cosmetic products [17], catechins in green tea [32], pharmaceuticals [16,25,55,64] and biphenyl nitrile compounds [13]. Using MEEKC coupled with laser-induced fluorescence detection offers higher sensitivity in quantitative methods for certain analytes, and this has been demonstrated in the determination of amino acid derivatives [49], and ephedrine and pseudoephedrine [65]. 6.4.5

Analysis of Natural Products

MEEKC is an effective technique with a high separation power for complex natural products. This has been demonstrated in the determination of catechin and gallocatechin in lyophilized extracts obtained from Cistus species [66] and the separation of catechins,


131

caffeine and theophylline [32]. Manipulation of surfactant, cosurfactant and oil were found to offer selectivity changes in the analysis of complex natural samples [32]. 6.4.6

Environmental Analysis

Analysis was carried out for determination of six priority endocrine disrupting compounds in environmental samples in industrial and domestic wastewater treatment effluents and sludges. An optimized method separated the six compounds in 15 minutes using a microemulsion of 25 mM phosphate buffer pH 2, 80 mM octane, 900 mM butanol, 200 mM sodium dodecyl sulphate and 20 % propanol, which suppressed the EOF allowing rapid analysis of alkyl phenols [39].

6.5 Conclusions The number of publications relating to MEEKC continues to rise as the diversity of method development options expands with new possibilities of generating unique selectivities. Water-in-oil MEEKC has been reported, which is especially useful for analysis of highly hydrophobic solutes. Chiral separations have been achieved using MEEKC through a variety of different enantioselective mechanisms. The number of applications has continued to expand with a particular emphasis on log POW determinations and analysis of pharmaceuticals.

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[66] R. Pomponio, R. Gotti, A. Santagati and V. Cavrini. Analysis of catechins in extracts of cistus species by microemulsion electrokinetic chromatography, J. Chromatogr. A., 990, 215–223 (2003). [67] H. Okamoto, A. Uetake, R. Tamaya, T. Nakjima, K. Sagara and Y. Ito. Simultaneous determination of eleven ingredients in ophthalmic solutions by cyclodextrin-modified micellar electrokinetic chromatography with tetrabutylammonium salt, J. Chromatogr. A., 888, 299– 308 (2000). [68] O. Mastrogianni, F. Lamari, A. Syrokou, M. Militsopoulou, A. Hjerpe and N. Karamanos. Microemulsion electrokinetic capillary chromatography of sulfated disaccharides derived from glycosaminoglycans, Electrophoresis, 22, 2743–2745 (2001). [69] T. Javor, W. Buchberger and I. Tanzcos. Determination of low-molecular-mass phenolic and non-phenolic lignin degradation compounds in wood digestion solutions by capillary electrophoresis, Mikrochimica Acta, 135, 45–53 (2000). [70] E.F. Hilder, C.W. Klampfl, W. Buchberger and P. Haddad. Separation of hydrophobic polymer additives by microemulsion electrokinetic chromatography, J. Chromatogr. A., 922, 293–302 (2001).

7 Polymeric Pseudostationary Phases and Dendrimers Christopher P. Palmer

7.1 Introduction The theory and applications presented in this text establish electrokinetic chromatography (EKC) as a powerful and useful separation technique. Ultimately, the strength and utility of EKC are determined by the performance of the pseudostationary phase (PSP). The limitations and restrictions imposed by the limited migration range of EKC place relatively stringent requirements on PSP performance. Optimization of EKC separations within the limited migration range requires that PSPs provide high selectivity and permit the retention factor to be optimized within a relatively narrow optimum range. The use of PSPs with high electrophoretic mobility can extend the migration range, thus placing less stringent requirements on selectivity and retention. Finally, PSPs must provide highly efficient separations. The development, characterization and application of polymeric PSPs for use in place of micelles is motivated by the fact that conventional micelles do not always satisfy all of the requirements noted above. Polymeric PSPs are particularly suitable for the separation of hydrophobic compounds, often provide unique separation selectivity, and offer a potential solution to the difficulty of interfacing EKC and mass spectrometric (MS) detection. Polymeric PSPs allow separations to be carried out in buffers modified with high concentrations of organic solvent modifiers, such that the retention factors of hydrophobic compounds can be adjusted to within the optimal range. Polymeric media are free from the structural constraints imposed by the need to form micelles and can thus provide separation selectivity that cannot be achieved with micelles. Polymeric PSPs can


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be used at low concentration and in the absence of low molecular mass surfactant. Thus, current is often lower, secondary buffer additives such as cyclodextrins are more effective, and the coupling of EKC with mass spectrometric detection is less difficult. At the same time, polymeric PSPs provide highly efficient separations. The essential feature and differentiation of polymeric PSPs relative to micellar PSPs is that the polymers are held together by covalent bonds and act as individual molecules in solution rather than as equilibrium self-assemblies of multiple molecules. The performance and selectivity of polymeric PSPs are determined for the most part by the primary covalent structure, which does not change with solvation, temperature, pH or buffer concentration. No free surfactant is required to maintain the primary polymer structure. A variety of ionic polymeric materials is available or has been introduced that can solvate or interact with solutes to be separated and provide highly efficient separations. These materials include polymerized surfactants, linear carbonaceous and silicone polymers, dendrimers and polymer nanoparticles. In many cases the polymer or dendrimer itself provides for the separation. In other cases polymers or dendrimers are used as support materials for pendant groups that effect the separation. The structures of several polymeric PSPs are shown in Figures 7.1, 7.5, and 7.7. This chapter provides an introduction and brief overview of the use of polymeric PSPs. Several detailed reviews concerning the introduction, characterization and application of polymeric PSPs have appeared in the literature [1–6]. The interested reader is referred to those reviews and the citations therein for experimental details.

7.2 Practical Considerations In most cases polymeric PSPs can simply be dissolved in the separation buffer and used in much the same fashion as micellar media. Retention factors are directly proportional to polymer concentration, so optimization of retention can be achieved by adjusting the PSP concentration. Polymers are typically used in the concentration range of 0.5–2 % w/v. Polymers with carboxylate ionic groups require buffers with pH > 7–8, but polymers with sulfate, sulfonate or quaternary ammonium head groups can be used at lower pH. Retention can also be adjusted by the addition of organic solvents, cyclodextrins, or other modifiers. Changes in retention factors with the addition of modifiers are often predictable, but changes in migration times can be more difficult to predict due to associated changes in electroosmotic flow and the electrophoretic mobility of the PSP. In most cases, polymeric PSPs are designed such that solutions containing the PSPs at the desired concentration are transparent in the UV–visible region. This facilitates UV detection, but prevents the use of polymers with aromatic functionality. Polymers can also interfere with detection if they are not completely pure. This can be particularly problematic when polymers are to be used with fluorescence detection where very low levels of fluorescent impurities can cause significant background. When the polymers are not transparent or cause significant background through fluorescence or scattering, they can be employed using the technique of partial filling [7]. This approach requires greater effort for optimization, and can lead to losses in separation efficiency.

POLYMERIC PSEUDOSTATIONARY PHASES AND DENDRIMERS

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Figure 7.1 Structures of polymerized surfactants. A, pSUA; B, pSUS; C, poly(sodium 11acrylamidoundecanoate); D, single amino acid chiral polymer; E, dual amino acid chiral polymer; F, poly(SUCL)

7.3 Polymerized Surfactants The most commonly utilized polymeric PSPs are the polymerized surfactants (a.k.a. micelle polymers or polysoaps, Figure 7.1). These are synthesized from surfactants having a polymerizable group on the hydrophobic tail end. The surfactants are dissolved above the critical micelle concentration and are then polymerized in more or less micellar form. The structures are thus micelle like in many respects, and can solvate analytes in much the same way as do micelles. However, the covalent stabilization of the structures provides some significant advantages, and leads to some differences in separation selectivity. The polymers of sodium undecylenate (pSUA, Figure 7.1A) and sodium undecenyl sulfate (pSUS, Figure 7.1B) allow for highly efficient separations of hydrophobic compounds in buffers modified with methanol, acetonitrile or tetrahydrofuran [8–14]. For example, all sixteen priority pollutant PAHs can be separated using pSUAwith THF [12] or pSUS in 57 % acetonitrile [8]. pSUS is also useful for the separation of monomethylbenz[a]anthracenes, methylated isomers of benzo[a]pyrene, and polychlorinated biphenyl congeners [8,9,11,13,14]. Representative separations of hydrophobic compounds utilizing pSUS are presented in Figures 7.2 and 7.3. pSUS permits much improved separations of hydrophobic compounds because it retains greater selectivity and greater electrophoretic mobility than SDS micelles in buffers modified with organic solvents. pSUS is more generally applicable than pSUA due to improved solubility at pH < 8. The polymerized surfactants are generally more polar and more cohesive (retention factors increase more slowly with analyte molecular volume) than micellar PSPs. Evidently, the increased structural rigidity induced by polymerization makes the materials more cohesive and prevents solutes from penetrating as deeply into the less polar interior. Although some differences in selectivity are observed when chain length [15] or the chemistry of the ionic head group [9,16] are varied, these changes do not cause drastic differences in separation selectivity.

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Figure 7.2 Electrokinetic separation of 16 PAHs using 0.5 % (w/v) pSUS in 12.5 mM each of Na2HPO4 and Na2B4O7 buffered at pH 9.2 with 40 % (v/v) of ACN. 1, naphthalene; 2, acenaphthylene; 3, acenaphthene; 4, fluorene; 5, phenanthrene; 6, anthracene; 7, fluoranthene; 8, pyrene; 9, benz[a]anthracene; 10, chrysene; 11, benzo[b]fluoranthene; 13, benzo[a]pyrene; 14, dibenz[ah]anthracene; 15, benzo[ghi]perylene; 16, indeno[123cd]pyrene. (Reprinted with permission from Ref. [8], copyright 1998 American Chemical Society)

Very high molecular weight polymers of sodium 11-acrylamidoundecanoate (Figure 7.1C) have selectivity considerably different from SDS micelles and can be used in acetonitrile-modified buffers for the separation of PAHs [17,18]. The polymer interacts more strongly with polar and polarizable groups than does water, providing selectivity that cannot be achieved with micelles. Polymerized surfactants with one or more amino acid head groups (Figure 7.1D, E) can be used for chiral separations. Figure 7.4 shows representative separations using such amino acid polymeric PSPs. An extensive body of literature generally indicates that these materials provide improved enantiomeric resolution relative to their conventional micellar counterparts. Many variations are available with different combinations of amino acids. Steric factors and hydrophobicity at the ionic head group play a significant role in selectivity [19]. The migration order of enantiomers is reversed when D- vs L- amino acid head groups are used, which can be advantageous for the trace analysis of one enantiomer in the presence of the second [20]. The many variations in structure provide a wide range of applicability, but it remains difficult to predict which polymeric structures are most likely to be successful for a given separation. Some general guidance for the applicability of these polymers can be found in the performance of the


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Figure 7.3 Electrokinetic separation of eight PCB congeners in EPA PCB 525.1 test mixture using 0.50 % (w/v) pSUS and 40 % (v/v) ACN with sodium borate as BGE (pH 9.2). 1, PCB 1; 2, PCB 5; 3, PCB 29; 4, PCB 47; 5, PCB 98; 6, PCB 154; 7, PCB 171; 8, PCB 200 [13]. (Reprinted from J. Chromatogr. A., 903, Edwards and Shamsi, pp. 227–236, copyright 2000, with permission from Elsevier)

L,L-leucylvalinate polymer, which affords some level of chiral resolution for fifty-eight of seventy-five cationic, neutral and anionic enantiomers [21]. Ionic repulsion makes the separation of anionic compounds more difficult. Variations in the structure of the ionic head group and the combined use of chiral polymers with cyclodextrins can lead to improved chiral resolution. The presence of an additional oxygen near the polar head group in the polymers of sodium N-undecenoxy carbonyl-L-leucinate (polySUCL, Figure 7.1F) and sodium N-undecenoxy carbonyl-Lisoleucinate (polySUCIL) allows for better chiral separations of b-blockers [22]. Polymeric chiral PSPs do not interfere with the chiral recognition provided by the cyclodextrin because they cannot be included in the cyclodextrin cavity due to their large size. This makes the cyclodextrin more effective, resulting in improved chiral resolution [23,24]. The optimal combination of polymeric surfactant and cyclodextrin is analyte specific.

7.4 Linear Polymers A variety of amphiphilic water-soluble polymers with linear backbones can be used as PSPs. These polymers provide the stability necessary for the separation of hydrophobic compounds and also provide a greater diversity in structure, leading to greater variation in separation selectivity. Commercial availability makes the application of many of these

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Figure 7.4 Simultaneous separation and enantioseparation of (a) binaphthyl derivatives using 15 mM poly(sodium undecenyl-L-valinate) in 100 mM Tris/10 mM borate buffer, pH 10. BNP ¼ 1,1’-binaphthyl-2,2’-diyl hydrogen phosphate; BOH ¼ 1,1’-bi-2-naphthol; BNA ¼ 1,1’-bi-2-naphthylamine; (b) paveroline derivatives using 20 mM poly(sodium undecenyl-L-valinate) in 50 mM phosphate buffer, pH 7.0; (c) benzodiazepinones using 25 mM poly(sodium undecenyl-L-valinate) in 100 mM Tris/10 mM borate buffer, pH 8.5. (Reprinted with permission from [21], copyright 2003 American Chemical Society)

polymers more convenient. Figure 7.5 shows the major linear polymers used to date as PSPs. 7.4.1

Acrylate and Acrylamide Polymers

Acrylate and acrylamide copolymers are either commercially available or can be synthesized from commercially available monomers. A great variety in acrylate and acrylamide monomers is available, allowing for high structural diversity. Butyl acrylate– butyl methacrylate–methacrylic acid (BBMA, Figure 7.5A) is useful for the separation of benzene derivatives, naphthalene derivatives, and cold medicine ingredients [25]. The polymer is also useful in combination with cyclodextrins for chiral separations [26], Elvacite 2669 (Figure 7.5B), is useful as a PSP for the separation of hydrophobic compounds [27]. The polymer is more cohesive and interacts more strongly with hydrogen bond donor solutes than do hydrocarbon micelles [28]. Mixed phases of Elvacite 2669 and SDS provide wide migration windows and unique separation selectivity [29].


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Figure 7.5 Structures of linear anionic polymers. A, BBMA; B, Elvacite 2669; C, AMPS copolymer; D, poly(allylamine); E, AGENT; F, AGESS

Copolymers of 2-acrylamido-2-methyl-1-propanesulfonic acid (AMPS) with a variety of (meth)acrylate and (meth)acrylamide comonomers (Figure 7.5C) have been studied extensively as PSPs [30–34]. The electrophoretic mobility of the polymers increases and the hydrophobicity and efficiency decrease as the fraction of AMPS in the backbone increases. The optimal balance between these effects is realized with an AMPS mole fraction of 0.80. Significant differences in the selectivity of the AMPS copolymers and SDS micelles exist. Unlike most polymeric PSPs, AMPS copolymers are less cohesive than SDS micelles. When AMPS is copolymerized with acrylamides, the resulting copolymers are better able to donate and accept hydrogen bonds and are more polar than their acrylate counterparts. The copolymer of AMPS with dihydrocholesteryl acrylate (DHCHAt ) provides very high separation efficiency. Representative separations utilizing the DHCHAt copolymer in acetonitrile-modified buffers are presented in Figure 7.6. Low conductivity and high separation efficiency of the DHCHAt permits the use of high field strengths and short capillaries to achieve fast separations [33]. The strongly acidic sulfonate functionality, low cohesivity, low polarity and high stability of the AMPS copolymers allows for effective online preconcentration of solutes by sweeping [31]. 7.4.2

Polyallylamines

Polyallylamine (PAA) modified to different extents with alkyl chains of varied lengths (Figure 7.5D) can be used for the separation of hydrophobic compounds [35–37]. Greater substitution leads to a narrower migration range, greater sample capacity, and lower polarity. These polymers provide a wide migration range in methanol-modified buffers, allowing separations of hydrophobic compounds to be optimized in a similar manner to reversed-phase liquid chromatography. Mixtures of decyl- and hexadecyl-modified PAA

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Figure 7.6 Separations using the copolymer of AMPS with dihydrocholesteryl acrylate at a concentration of 0.72 % w/v in 29.6 % ACN/70.4 % 35.2 mM borate buffer, pH 9.2. (a) Homologous series of alkyl phenones: V ¼ valerophenone, Hx ¼ hexanophenone, Hp ¼ heptanophenone, D ¼ n-dodecanophenone. (b) PAHs: 1, acenaphthalene; 2, acenaphthene; 3, fluorene; 4, phenanthrene; 5, anthracene; 6, fluoranthene; 7, pyrene; 8, chrysene; 9, benz[a]anthracene; 10, benzo[a]pyrene; 11, benzo[e]pyrene; 12, benzo[k]fluoranthene; 13, benz[e]acephenanthrylene; 14, benzo[ghi]perylene; 15, dibenz[ah]anthracene. (Reprinted from Ref. [34] by permission of Wiley-VCH Verlag)

can be used to modify the migration window and the selectivity of separations, providing adequate peak capacities for both early and late eluting compounds [37]. 7.4.3

Siloxane Polymers

The siloxane polymers such as those shown in Figures 7.5E (AGENT) and F (AGESS) can be synthesized with a variety of ionic head group and pendant group chemistries by chemical modification of commercially available hydrosiloxane polymers [38–42]. The degree of substitution of AGENT or AGESS with octyl, dodecyl or octadecyl pendant groups must be less than about 30 % for the polymers to have sufficient aqueous solubility. For AGENT, both electrophoretic mobility and separation efficiency pass through a maximum at 10–20 % substitution with alkyl chains [38]. Depending on the extent of substitution and the length of the pendant alkyl chains, the polymers vary from being less hydrophobic than SDS micelles to being more hydrophobic than SDS micelles [38]. The polymers provide very different selectivity from SDS micelles, but selectivity does not vary greatly between polymers with different alkyl chain length or extent of substitution [38]. AGESS polymers provide significantly different chemical selectivity from AGENT polymers of similar structure [39,42]. AGENT polymers interact very weakly with polar or polarizable compounds, while AGESS is a more polar PSP. Both


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AGENT and AGESS polymers interact strongly with hydrogen bond donors. AGENT polymers can be used in buffers modified with up to 50 % acetonitrile or 60 % methanol for the separation of hydrophobic compounds, but their performance under these conditions is generally not as good as other polymeric PSPs [41]. 7.4.4

Cationic Polymers

When employed as PSPs, cationic polymers adsorb to the capillary walls and cause a reversal in the direction of electroosmotic flow. Adsorption to the walls can also stabilize the electroosmotic flow, improving reproducibility. The polymers migrate counter to the electroosmotic flow, permitting EKC separations. A small fraction of the analytes studied may interact with polymers at the capillary wall, but for most solutes this is not a significant contribution to retention [43]. Strong interactions are observed between phenols and polyethyleneimine (pEI, Figure 7.7A) at both high and low pH [44], and the separation selectivity is very different from that of other PSPs [45]. The migration time of phenols depends on the number of hydroxyl groups, but no selectivity is observed between mono-, di- and trimethyl substituted phenols. Polydiallyldimethylammonium bromide (pDADMA, Figure 7.7B) and ionenes (Figure 7.7C) are polymers with relatively little lipophilic character and with their ionic groups on or near the polymer backbone [46,47]. Polybrene (3,6-ionene) is commercially available, and has been the most frequently used in EKC. Other ionenes, especially 2,10-ionene, can provide stronger hydrophobic interactions than the more hydrophilic polybrene or pDADMA. Hydrophobic interactions play an important role in the separations using ionenes. Changing the charge density and the length or chemistry of the connecting groups significantly affects performance and selectivity [47]. Polybrene and pDADMA display very different selectivity from conventional micelles and other polymeric PSPs [46,48]. They are much more cohesive than SDS micelles and other polymeric PSPs, and are also strong hydrogen bond donors. Polybrene shows a very strong tendency to interact with solutes having nonbonding electrons.

Figure 7.7 Structures of cationic polymeric PSPs. A, polyethyleneimine; B, poly(diallyldimethylammonium bromide) (pDADMA); C, x,y-ionene [6]. (Reprinted from J. Chromatogr. A., 1044, Palmer and McCarney, pp. 159–176, copyright 2004, with permission from Elsevier)

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7.5 Dendrimers Dendrimers are branched structures synthesized from a central core. Multicycle repetitive syntheses introduce branching in each cycle. A cycle is called a generation, and the complexity and steric crowding of dendrimers increase with each generation. In principle, and unlike conventional polymers, each dendrimer resulting from a given synthesis has the same molecular weight, structure, and dimensions [49,50]. This uniformity of structure can lead to superior performance when dendrimers are used as PSPs [51]. Dendrimeric PSPs also provide unique selectivity that depends on their structure, concentration, generation, the presence of organic modifiers, and pH [51]. Various dendrimers and modified dendrimers provide efficient and selective separations in EKC [51–59]. PAMAM (poly[amidoamine]) dendrimers have unique selectivity based on solute structure rather than hydrophobicity [57,58]. Modification of the exterior surface of a PAMAM dendrimer with alkyl chains provides increased solute capacity and selectivity more like that of micelles [55,57]. The modified dendrimers provide stronger interactions with hydrophobic compounds, and can also be used in organic modified buffers for the separation of such compounds. Introduction of sulfonic acid functionality on the outer surface of PAMAM dendrimers yields PSPs with better efficiency and peak shape than SDS micelles [53]. Highly efficient and selective separations are also possible using poly(propyleneimine) dendrimers as PSPs [52].

7.6 Polymer Nanoparticles Polymer nanoparticles with a narrow distribution of diameters from 0.2–0.5 mm diameter, many of them molecularly imprinted polymers (MIP), can be used as slurries or suspensions in aqueous and modified aqueous buffers to effect separations in EKC [60–66]. Because the suspended particles scatter light, a partial-filling protocol must be used when optical detection is employed. Highly tuned separation selectivity can be achieved when MIP nanoparticles are used. MIP nanoparticles templated with S-propanolol [61] or (þ)-ephedrine [65] allow for separation of the respective enantiomers and, as illustrated in Figure 7.8, enantiomeric selectivity for pindolol and atenolol can also be achieved using the particles templated for S-propanolol [60]. Synthetic conditions, including the choice of monomers and crosslinkers, have significant effects on the performance of the nanoparticles [62,64]. Selectivity towards more than one predetermined target can be realized by using a mixture of nanoparticles synthesized separately using different templates or by utilizing an MIP synthesized in a single batch using two templates [66]. The mixed-MIP approach is generally easier to optimize.

7.7 EKC with Mass Spectrometric Detection The absence of free surfactant, low surface activity, low volatility, high electrophoretic mobility, suitable performance at low concentration, and lack of signal in the mass region


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Figure 7.8 Simultaneous enantiomer separation of (1) atenolol, (2) pindolol and (3) propanolol using MIP nanoparticles templated for S-propanolol in 90 % ACN/10 % acetic acid/triethanolamine solution at pH 3.5. (Reprinted from Ref. [60] by permission of WileyVCH Verlag)

of interest make polymeric PSPs attractive for the combination of EKC with MS detection. Polymeric PSPs can be utilized with electrospray ionization MS without resorting to partial filling and without undue fouling of the interface, particularly when an orthogonal ESI interface is used. In most cases, the polymers do not interfere with detection or have adverse effects on sensitivity when the PSP concentration is maintained below about 0.1–0.5 % w/v, but signal can be severely diminished at concentrations approaching 1 % w/v. Often, a compromise between sensitivity and resolution must be made, but the loss in resolution can be partly overcome by the selective detection offered by the MS. BBMA [67], pSUS [68], poly(sodium undecenyl-L-valinate) [69], and polymer nanoparticles (at 0.01–0.04 % w/v.)[63] have all been used with MS detection.

7.8 Conclusion Polymers provide useful alternatives to conventional micelles as PSPs, especially for the separation of hydrophobic compounds and when different selectivity is needed to achieve a separation. A variety of polymeric materials provides chiral selectivity, and polymers perform better than do conventional micelles when employed in combination with cyclodextrins. Polymeric PSPs also simplify the union of EKC with MS. Although a wide variety of polymeric structures has been studied and employed as PSPs, applications are relatively few. There have been many studies concerning the selectivity of polymeric phases, but choosing an appropriate polymer for a given separation remains rather empirical. Perhaps the factor that has most prevented more general application of polymeric PSPs is that few are commercially available. Several of the acrylate and cationic polymers are commercially available, as are PAMAM dendrimers. Sodium undecylenate is commercially available, as are the starting materials for most of the acrylate and siloxane PSPs. The synthesis of these PSPs is not difficult, but the need to synthesize and purify the polymers still remains as a barrier to their use.

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[19] S.J. Thibodeaux, E. Billiot, E. Torres, B.C. Valle and I.M. Warner. Enantiomeric separations using polymeric L-glutamate surfactant derivatives: effect of increasing steric factors, Electrophoresis, 24, 1077–1082 (2003). [20] J. Wang and I.M. Warner. Chiral separations using micellar electrokinetic capillary chromatography and a polymerized chiral micelle, Anal. Chem., 66, 3773–3776 (1994). [21] S.A. Shamsi, B.C. Valle, F. Billiot and I.M. Warner. Polysodium N-undecanoyl-L-leucylvalinate: a versatile chiral selector for micellar electrokinetic chromatography, Anal. Chem., 75, 379–387 (2003). [22] S.A.A. Rizvi and S.A. Shamsi. Polymeric alkenoxy amino acid surfactants: I. Highly selective class of molecular micelles for chiral separation of b-blockers, Electrophoresis, 24, 2514–2526 (2003). [23] J. Wang and I.M. Warner. Combined polymerized chiral micelle and g-cyclodextrin for chiral separation in capillary electrophoresis, J. Chromatogr. A., 711, 297–304 (1995). [24] B.C. Valle, F.H. Billiot, S.A. Shamsi, X. Zhu, A.M. Powe and I.M. Warner. Combination of cyclodextrins and polymeric surfactants for chiral separations, Electrophoresis, 25, 743–752 (2004). [25] H. Ozaki, S. Terabe and A. Ichihara. Micellar electrokinetic chromatography using highmolecular surfactants. Use of butyl acrylate–butyl methacrylate–methacrylic acid copolymers sodium salts as pseudo-stationary phases, J. Chromatogr. A., 680, 117–123 (1994). [26] H. Ozaki, A. Ichihara and S. Terabe. Micellar electrokinetic chromatography using highmolecular-mass surfactants: comparison between anionic and cationic surfactants and effects of modifiers, J. Chromatogr. A., 709, 3–10 (1995). [27] S.Y. Yang, J.G. Bumgarner and M.G. Khaledi. Separation of highly hydrophobic compounds in MEKC with an ionic polymer, J. High Resolut. Chromatogr., 18, 443–445 (1995). [28] S.Y. Yang, J.G. Bumgarner and M.G. Khaledi. Chemical selectivity in micellar electrokinetic chromatography: 2. Rationalization of elution patterns in different surfactant systems, J. Chromatogr. A., 738, 265–274 (1996). [29] M.S. Leonard and M.G. Khaledi. A mixed ionic block copolymer-surfactant pseudo-stationary phase in micellar electrokinetic chromatography, J. Sep. Sci., 25, 1019–1026 (2002). [30] W. Shi, D.S. Peterson and C.P. Palmer. Effect of pendant chain lengths and backbone functionalities on the chemical selectivity of sulfonated amphiphilic copolymers as pseudo-stationary phases in electrokinetic chromatography, J. Chromatogr. A., 924, 123–135 (2001). [31] W. Shi and C.P. Palmer. On-column sample preconcentration using polymeric pseudostationary phases in reversed-flow electrokinetic chromatography, J. Sep. Sci., 25, 215–221 (2002). [32] W. Shi, C.J. Watson and C.P. Palmer. Sulfonated acrylamide copolymers as pseudo-stationary phases in electrokinetic chromatography, J. Chromatogr. A., 905, 281–290 (2001). [33] W. Shi and C.P. Palmer. High speed separations by electrokinetic chromatography using polymeric pseudo-stationary phases, J. Sep. Sci., 25, 543–546 (2002). [34] W. Shi and C.P. Palmer. Effect of pendent group structures on the chemical selectivity and performance of sulfonated copolymers as novel pseudo phases in electrokinetic chromatography, Electrophoresis, 23, 1285–1295 (2002). [35] N. Tanaka, K. Nakagawa, H. Nagayama, K. Hosoya, T. Ikegami, A. Itaya and M. Shibayama. Effects of electrokinetic chromatography conditions on the structure and properties of polyallylamine-supported pseudo-stationary phase: a study by dynamic light scattering, J. Chromatogr. A., 836, 295–303 (1999). [36] N. Tanaka, K. Nakagawa, H. Iwasaki, K. Hosoya, K. Kimata, T. Araki and D.G. Patterson. Polyallylamine-supported pseudo-stationary phases for electrokinetic chromatography: effect

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[38]

[39]

[40]

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[42] [43]

[44] [45]

[46]

[47] [48]

[49]

[50] [51]

[52] [53] [54]

ELECTROKINETIC CHROMATOGRAPHY of alkyl chain length of the pseudo-stationary phase and methanol content of aqueous buffer on the separation of hydrophobic compounds, J. Chromatogr. A., 781, 139–150 ( 1997). N. Tanaka, K. Nakagawa, K. Hosoya, C.P. Palmer and S. Kunugi. Control of migration time window and selectivity in electrokinetic chromatography with mixed polymeric pseudostationary phases, J. Chromatogr. A., 802, 23–33 (1998). D.S. Peterson and C.P. Palmer. Alkyl modified anionic siloxanes as pseudostationary phases for electrokinetic chromatography: I. Synthesis and characterization, J. Chromatogr. A., 924, 103–110 (2001). D.S. Peterson and C.P. Palmer. Novel alkyl-modified anionic siloxanes as pseudostationary phases for electrokinetic chromatography: II. Selectivity studied by linear solvation energy relationships, Electrophoresis, 22, 3562–3566 (2001). D.S. Peterson and C.P. Palmer. Synthesis and characterization of novel anionic siloxane polymers as pseudostationary phases for electrokinetic chromatography, Electrophoresis, 22, 1314–1321 (2001). D.S. Peterson and C.P. Palmer. Novel alkyl-modified anionic siloxanes as pseudostationary phases for electrokinetic chromatography: III. Performance in organic-modified buffers, J. Chromatogr. A., 959, 255–261 (2002). S. Schulte and C.P. Palmer. Alkyl-modified siloxanes as pseudostationary phases for electrokinetic chromatography, Electrophoresis, 24, 978–983 (2003). B. Maichel, K. Gogova, B. Gas and E. Kenndler. Comparison of separation selectivity in capillary electrokinetic chromatography using a cationic linear polymeric pseudo-stationary phase or monomeric additives of similar structure, J. Chromatogr. A., 894, 25–34 (2000). F.B. Erim. Effect of cationic polymer on the separation of phenols by capillary electrophoresis, J. Chromatogr. A., 768, 161–167 (1997). B. Maichel, B. Potocek, B. Gas, M. Chiari and E. Kenndler. Separation of neutral compounds by capillary electrokinetic chromatography using polyethyleneimine as replaceable cationic pseudostationary phase, Electrophoresis, 19, 2124–2128 (1998). B. Potocek, E. Chmela, B. Maichel, E. Tesarova, E. Kenndler and B. Gas. Capillary electrokinetic chromatography with charged linear polymers as a nonmicellar pseudostationary phase: determination of capacity factors and characterization by solvation parameters, Anal. Chem., 72, 74–80 (2000). K. Kopecka, E. Tesarova, A. Pirogov and B. Gas. Ionenes acting as pseudostationary phases in capillary electrokinetic chromatography, J. Sep. Sci., 25, 1027–1034 (2002). K. Gogova, B. Maichel, B. Gas and E. Kenndler. Electrokinetic chromatography with micelles, polymeric and monomeric additives with similar chemical functionality as pseudo-stationary phases, J. Chromatogr. A., 916, 79–87 (2001). D.A. Tomalia, A.M. Naylor and W.A. Goddard III. Starburst dendrimers: molecular-level control of size, shape, surface chemistry, topology, and flexibility from atoms to macroscopic matter, Angew. Chem. Int. Ed. Engl., 29, 138–175 (1990). A.W. Bosman, H.M. Janssen and E.W. Meijer. About dendrimers: structure, physical properties, and applications, Chemical Reviews (Washington, D. C.), 99, 1665–1688 (1999). M. Castagnola, C. Zuppi, D.V. Rossetti, F. Vincenzoni, A. Lupi, A. Vitali, E. Meucci and I. Messana. Characterization of dendrimer properties by capillary electrophoresis and their use as pseudostationary phases, Electrophoresis, 23, 1769–1778 (2002). P.G.H.M. Muijselaar, H.A. Claessens and C.A. Cramers. Dendrimers as pseudo-stationary phases in electrokinetic chromatography, J. High Res. Chromatogr., 18, 121–123 (1995). A.L. Gray and J.T. Hsu. Novel sulfonic acid-modified starburst dendrimer used as a pseudostationary phase in electrokinetic chromatography, J. Chromatogr. A., 824, 119–124 (1998). S.A. Kuzdzal. Dendrimer electrokinetic chromatography: fundamentals and applications, PhD. Dissertation, University of California, Riverside, CA, USA (1997).


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8 Pseudostationary Ion-exchange Phases Philip J. Zakaria and Paul R. Haddad

8.1 Introduction In capillary electrophoresis (CE), separation is normally achieved as a result of the difference in migration velocities (electrophoretic mobilities) of the analytes of interest. Therefore, analytes with sufficiently different mobilities are reasonably easy to separate in a CE system. However, analytes with similar mobilities often do not separate fully and neutral analytes also cannot be separated by CE due to their lack of mobility, and these migrate as a single peak with the electroosmotic flow (EOF). The mobility of an analyte in a given electrolyte system is a physical property of that analyte and is related to its charge-to-size ratio. That is, smaller analytes with higher charge migrate faster than larger analytes with lower charge. Generally then, the mobility of an analyte can be modified via two means: either by varying its effective charge, or by varying its size. For the purpose of the present discussion, CE here is assumed to be any separation where no additives to the electrolyte, such as micelles, ion-pair reagents, polymers, etc., are used. Separations where such additives are used are termed electrokinetic chromatography separations and will be discussed below. Modifying the selectivity in straight CE systems is generally achieved by varying electrolyte conditions such as pH, ionic strength, temperature, voltage or by using organic modifiers. Instrumental parameters such as temperature, voltage, use of external pressure or capillary dimensions generally have a limited effect on selectivity since they tend to affect all analytes in a similar manner. Varying the pH is one of the most effective means of changing the selectivity of a system. It is especially useful for the separation of


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weak acids and bases as the pH directly affects the degree of charge on the analytes, and hence their effective mobility. Use of organic modifiers is also a popular approach when trying to control the selectivity of a system. Modifiers can act in a variety of ways including changing the relative solvation enthalpies of ions or varying their effective pKa values. A more universal and powerful method of varying the selectivity of any separation technique, whether it be gas or liquid chromatography or an electro-driven system, is the introduction of a stationary phase (SP) to the particular separation medium. Thus, separations are facilitated by differing interaction strengths between the species to be separated and the SP contained within the system. Although the use of solid SPs packed into separation columns is applicable when separations are performed using relatively large diameter columns (>1 mm), problems arise when applying this approach to miniaturized systems, such as CE capillaries. The main problems encountered are how to pack the stationary phase and how to retain the packing material inside the capillary. These tasks are not straightforward and require patience, skill and an associated amount of luck to produce reproducible columns. These problems have provided impetus to the recent development of monolithic columns where the SP is composed of a continuous, highly porous structure that can be formed directly within the column and can be bound to the inner wall, thereby removing the need for retaining frits. Despite the problems of packed bed columns, their use in capillary electrochromatography (CEC) continues to be a topic of much research as evidenced by the publication of several reviews [1–3]. Although the use of solid SPs was an obvious approach to the introduction of selectivity changes in electro-driven separations, a much simpler way of achieving the same goal is the use of a pseudostationary phase (PSP) added to the background electrolyte. The use of the term ‘pseudo’ implies that the stationary phase is not truly stationary but moves under the conditions used for separation. Such separation systems are termed ‘electrokinetic chromatography (EKC)’ and the PSP is chosen so as to interact with the analyte of interest, thereby varying its effective mobility. Differences in the strength of interaction between the additive and the different analytes present in the sample lead to selectivity changes in the system. Potentially, any additive that interacts with the analytes to be separated and is soluble in the electrolyte is suitable for EKC. The range of possible PSPs is therefore extensive and several mechanisms of interaction between the analyte and the PSP are possible, such as hydrophobic, ionexchange, and chelation interactions. The purpose of the current chapter is to introduce the reader to the use of electrostatic and ion-exchange (IE) type PSPs for the separation and improved selectivity of a range of different analytes. Included in this overall aim will be the use of ion-pair (IP) type reagents since these effectively work in exactly the same way as ion-exchange type additives, namely through an electrostatic interaction with the analyte. Charged PSPs interact with the desired analytes through attraction due to the presence of oppositely charged functional groups. This necessarily means that the electrophoretic mobility of the PSP will always be in the opposite direction to that of the analyte. Upon interaction of the PSP and the analyte, the mobility of the resultant pair will differ from the original mobility of the analyte due to a change in the charge-to-size ratio. Various PSPs will change this ratio to differing extents, for example a small ion-pair reagent may simply neutralize the analyte and lead to zero mobility whereas a high

PSEUDOSTATIONARY ION-EXCHANGE PHASES

µA

A–

Anion Exchange

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KA

-

µSP-A µSP(+ve)

EOF Depending on surface charge

µC

µSP(–ve)

SP

µSP-C

+

KC C+

Cation Exchange

Figure 8.1 Schematic representing the process of ion-exchange electrokinetic chromatography using pseudostationary phases (PSP). SP is the PSP and can take the form of a soluble polymer, surfactant, cyclodextrin, solid ion-exchange particle, etc., as discussed in the text. mSP(þve) and mSP(ve) are the mobilities of positive and negative PSPs, respectively, while mSP-C and mSP-A are the mobilities of the combined analyte–PSP complex. KA and KC are the associated equilibrium constants for the electrostatic interactions between analyte anions and analyte cations respectively

molecular mass ionic polymer may not show a significant change in mobility on interaction with a substantially smaller analyte. Selectivity changes in these systems arise from the different electrostatic interaction strengths of the particular analytes with the PSP being used, meaning that the mobility of each analyte will be affected to differing degrees, resulting in selectivity changes. The general process of electrostatic (or ion-exchange) EKC is shown schematically in Figure 8.1 where selectivity changes are introduced due to differences in KA and KC between the target analyte anions and cations, respectively. In the following discussion, the use of a range of PSPs (including micelles, surfactants, small additives, soluble polymers, cyclodextrins, macrocyclic polyamines and diazacrown ethers, dendrimers, and solid ion-exchange particles) is covered.

8.2 Micelles and Surfactants as Pseudostationary Phases 8.2.1

Cationic Surfactants

Micelles were first used as PSPs by Terabe et al. in 1984 [4] with the technique being termed ‘micellar electrokinetic chromatography’ (MEKC). Although the technique relies on the different partitioning of analytes between the hydrophilic electrolyte and hydrophobic surfactant phases, electrostatic interactions also play a significant role in the observed selectivity. As well as introducing hydrophobic interactions, cationic surfactants have also been used extensively in CE to reverse the direction of the EOF, allowing anions to be separated in the co-EOF mode. In these cases, the capillary is normally coated with a solution of the surfactant at a concentration below the critical micelle concentration (cmc). However, to give reproducible EOF values it is usually necessary also to include the

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surfactant (generally a long chain quaternary ammonium surfactant) in the electrolyte during the separation step. For the analysis of anions, this of course introduces the possibility of electrostatic interactions between the cationic surfactant and the analyte anions. The effect of cationic surfactants on the separation of inorganic anions was first investigated by Jones and Jandik [5]. In their work, an increased concentration of the surfactant (in this case, the proprietary Waters product NICE-Pak OFM Anion-BT) led to reduced mobility for bromide, sulfate and nitrate, while nitrite, fluoride, hydrogen phosphate and hydrogen carbonate showed little change in mobility, at least relative to chloride, see Figure 8.2. This decrease in mobility was only observed for surfactant concentrations above 1 mM, which was approximately the cmc of the surfactant. This would imply that only micelles (rather than individual surfactant molecules) showed sufficiently strong electrostatic attraction to the inorganic anions to permit selectivity changes. Furthermore, it was also found that increasing the concentration of a competing ion (having the same charge polarity as the analyte ions) in the electrolyte suppressed the analyte–micelle interactions and led to increased mobilities, further supporting the electrostatic separation mechanism. A similar investigation into the effect of surfactant concentration on the separation of inorganic anions was conducted by Buchberger and Haddad [6] who used quaternary ammonium surfactants of varying alkyl chain length. They found that the length of the

Figure 8.2 Effect on migration time (normalized with respect to chloride) of increasing surfactant concentration (NICE-Pak OFM Anion-BT) in a 5 mM chromate electrolyte [5]. (Reprinted from J. Chromatogr. A., 546, Jones and Jandik, pp. 445–488, copyright 1991, with permission from Elsevier)


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alkyl chain had a pronounced effect on the observed selectivity, with the longer chain surfactants interacting more strongly with thiosulfate, iodide and thiocyanate. Not surprisingly, these ions also show high retention factors when separated by ion chromatography using quaternary ammonium ion-exchange columns [7]. Further investigation into the use of similar quaternary ammonium surfactants for the separation of inorganic anions has been undertaken by a number of authors, with similar conclusions being drawn in each of these reports [8–10]. As well as inorganic anions, cationic surfactants have also been used in the separation of a variety of other anionic samples, including metal complexes [11] and carboxylic acids [12] and sulfonic acids [13]. In such separations where the analytes possess both ionic and hydrophobic regions the resultant separation mechanism is likely to be a combination of partitioning into the hydrophobic portion of the micelle, and electrostatic interactions with the charged surface. Harvey reported the use of cetyltrimethylammonium bromide (CTAB) for the separation of copper–polyaminopolycarboxylic acid complexes [11]. It was found that the addition of the cationic surfactant permitted a highly selective separation of the Cu(II) complexes and this was attributed, at least in part, to electrostatic interactions between the anionic complexes and the cationic surfactant. Although it is likely that electrostatic interactions play a role, subsequent separations performed using the anionic surfactant sodium dodecylsulfate (SDS) also facilitated separation, though in a longer time frame, indicating that hydrophobic partitioning was also occurring to a significant extent. Separation of structural isomers is a particular problem in CE since these analytes exhibit very similar charge-to-size ratios and hence very similar mobilities. The separation of a group of naphthalenedisulfonate isomers using various surfactants was demonstrated by Cugat et al. [13]. It was found that the use of CTAB in the absence of organic modifier led to broad, poorly separated peaks, presumably due to unfavourable transfer kinetics of the analyte with the PSP. However, the use of 34 % v/v propan-2-ol improved the observed separation and allowed for resolution of components that could not be separated in free zone electrophoresis or by using SDS or Brij 35 (a neutral surfactant). This was attributed to the lack of micelle formation when using the organic modifier, meaning that the analyte interacted with monomers only, presumably through electrostatic interactions. Interestingly, this result is contrary to that observed with inorganic anions [5] and suggests that the hydrophobicity of the analytes may also play a role. Cationic surfactant systems have also been applied to the analysis of real samples, including chromate in chromium plating baths [14], inorganic and organic anions in Bayer liquor [15] and cyanide leaching solutions from catalytic converters [16]. In each of these examples the electrostatic interaction between the anions and the cationic surfactants played a major role in the observed separations. The use of mixed micellar systems, i.e. those where two surfactants are present in the same electrolyte, has also been exploited for additional selectivity control. Harakuwe et al. [17] found that the selectivity offered when using dodecyltrimethylammonium bromide (DTAB) and tetradecyltrimethylammonium bromide (TTAB) differed, with a significant portion of each interaction being attributed to electrostatic attraction. The use of mixed DTAB/TTAB electrolytes was found to give separation selectivities which could not be achieved when using either surfactant alone. These mixed-surfactant

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systems were successfully applied to Bayer liquor samples allowing baseline resolution of most of the species of interest [15,17]. A major advantage of the surfactant systems is their predictable effect on the retention of anions. This point was used by Jimidar and coworkers to model successfully the separation of inorganic anions using CTAB as surfactant to control both the direction of the EOF and also to modify the separation selectivity [18,19]. The models, which took into account only electrostatic interactions, accurately predicted the mobility of the anions in electrolytes of differing pH and surfactant concentration and allowed optimization of the systems to maximize separation selectivity. 8.2.2

Anionic Surfactants

Although the use of cationic surfactants has been relatively widespread, due mainly to their ability to reverse the EOF, the most common surfactant used in MEKC has been sodium dodecylsulfate (SDS). This anionic surfactant has been applied widely to the separation of neutral compounds through their partitioning into the hydrophobic region of the micelles. However, SDS and other anionic surfactants also have the potential to exhibit electrostatic interactions when separating cationic species. This potential was first demonstrated over 15 years ago for the separation of water-soluble vitamins [20]. It was noted that the migration of the cationic vitamins was retarded significantly with increased SDS concentration compared with other vitamins, and this was attributed to an electrostatic interaction. This same effect was again noted in a subsequent paper also dealing with the separation of water soluble vitamins using SDS [21]. One advantage of anionic surfactants as compared with their cationic counterparts is the wider range of functional groups that is available, e.g. carboxylate, sulfonate, sulfate, etc. This creates opportunities for differing selectivities to be attained, depending on the particular functional group present on the surfactant. This effect has been demonstrated by Takeda and coworkers [22,23] who obtained different selectivities for phenol and aniline derivatives using surfactants containing carboxylate, sulfonate and sulfate functionalities. The analyte–micelle interaction was found to be not only associated with hydrophobic partitioning into the micellar phase, but to also be affected by electrostatic interactions between the protonated analytes and the anionic surfactants. Analytes possessing higher pKa values interacted more strongly with SDS due to a higher degree of protonation. Modelling the observed separation of cationic species in the presence of SDS has been reported by Khaledi and coworkers [24,25]. In their first report the separation of a set of catecholamines at a range of pH values was demonstrated [24]. The migration model took into account both the interaction of the neutral and protonated species with the micelle as well as the electrostatic interaction between the protonated species and the anionic surfactant. The model was used to predict mobilities of the catecholamines accurately at a range of different pH values and SDS concentrations. Related equilibrium constants for the interaction of the analytes with SDS were also calculated and it was found that positively charged species (norephedrine and ephedrine) showed very high values due to a combination of electrostatic and hydrophobic interactions. In a subsequent report this modelling process was extended to include both acidic and basic solutes [25] where it was found that the migration behaviour of basic solutes


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using anionic surfactants (SDS) was more complicated than for anionic solutes due to the additional electrostatic interactions. Despite this, the model was able accurately to predict separations obtained for differing pH and SDS concentrations. 8.2.3

Zwitterionic Surfactants

A further class of surfactants used to exploit electrostatic interactions with inorganic anions is zwitterionic surfactants. Initially these were investigated by Yeung and Lucy [26], who found that the zwitterionic surfactant coco amidopropylhydroxyldimethylsulfobetaine (CAS U) used in combination with TTAB permitted the EOF to be manipulated from the high mobility, reversed EOF exhibited by a 100 % TTAB system to almost zero EOF with a 100 % CAS U electrolyte. As well as controlling EOF, the mixed micelle systems exerted small effects on analyte mobility, attributable to electrostatic interactions between the mixed micelles and the inorganic anions. A more detailed study of the effect of a zwitterionic surfactant, in this case 3-(N,N-dimethyldodecylammonio)propanesulfonate (DDAPS), on the mobility of inorganic anions was undertaken by Woodland and Lucy [27]. It was shown that when DDAPS was used for the separation of inorganic anions, dramatic changes in selectivity occurred, particularly for the more polarizable anions such as thiocyanate, iodide, nitrate and bromide, see Figure 8.3. This behaviour was consistent with the retention of these ions observed in electrostatic ion chromatography using zwitterionic stationary phases. The separation mechanism was attributed to

Figure 8.3 Effect of concentration of zwitterionic surfactant on the selectivity of inorganic anions separated in a chromate electrolyte. (Reprinted from Ref. [27] by permission of the Royal Society of Chemistry)

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simultaneous electrostatic attraction and repulsion of the analyte anions by the zwitterionic surfactant. 8.2.4

Charged Additives

The use of small charged additives, i.e. those that do not form micelles, to exploit electrostatic interactions in CE separations has been commonplace. As with surfactants, interactions occur with oppositely charged analytes, but unlike micelles where the net migration of the highly charged micelle is not altered significantly by analyte interactions, the formation of an ion pair between the analyte and additive now results in a neutral species. This ion pair has no electrophoretic mobility and separation selectivity arises as a result of differences in interaction strength between the analyte and the additive for the analytes to be separated. The use of neutral ion pairs to increase the solubility of anionic species into SDS micelles has been investigated by several groups and has been shown to improve the separation of a range of analytes [28–30]. A range of quaternary ammonium functionalized ion-pair (IP) reagents has been used for the CE based separation of anionic metal complexes [31–33], naphthalenesulfonates [34,35] and pyrroloquinoline quinone compounds [36]. Takayanagi et al. [35] determined the association constants between naphthalenedisulfonates and several quaternary ammonium ions, and concluded that the bulkiness of the pairing cation was related to the association strength, with tetrabutylammonium showing a stronger interaction than tetramethylammonium with the naphthalenedisulfonates. A more detailed study of the exact mechanism of separation was undertaken by Okada [37] who separated aromatic disulfonates using polyammonium ions with differing spacer lengths between the quaternary ammonium functional groups. It was found that although electrostatic IP formation was the mechanism of interaction, the best separation of the naphthalenedisulfonates was achieved using the diethylenetriammonium ion, which has a molecular length almost equal to the charge separation (i.e. the distance between the two sulfonate groups) on the naphthalenedisulfonates. This work was extended by Takayanagi et al. [38] who separated a range of divalent aromatic anions using both monovalent and divalent quaternary ammonium compounds. Again, it was found that interactions of the organic anions were stronger with the divalent cations, and the charge spacing on the IP reagent played a major role in the observed strength of interactions. This implied that the IP reagent orientates itself so that each charged site is in close proximity to the anionic sites on the organic anions. Anionic IP reagents have also been used to exploit electrostatic interactions in the separation of cations, with alkylsulfonates being used most commonly. Weldon et al. [39] used several alkylsulfonates for the separation of neurotransmitters, peptides and proteins. The rapid, reversible, electrostatic interactions between the anionic IP reagents and the cationic analytes were found to facilitate good separation and the selectivity could be optimized systematically by varying the size and concentration of the IP reagent in the electrolyte. The authors also investigated the effect of adding cationic IP reagents and found that no selectivity changes were observed, suggesting that hydrophobic interactions between the solutes and the alkyl chains on the IP reagents were negligible. Similar systems have also been reported by Fritz and coworkers who used ethanesulfonate as the IP reagent for the separation of basic drugs [40] and anilines [41].


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An alternative anionic IP reagent that has been successfully used is phytic acid. Phytic acid consists of cyclohexane with six phosphoric acid groups connected to the six carbons and exhibits very little hydrophobicity. Due to its large number of acidic groups, phytic acid interacts strongly with cationic analytes under basic conditions. Kornfelt et al. [42] used phytic acid as an IP reagent for the separation of peptides and found that peptides with pI values above that of the electrolyte interacted most strongly with phytic acid. Peptides satisfying these conditions were cationic at the electrolyte pH, leading to a strong interaction with the anionic phytic acid.

8.3 Soluble Polymers as Pseudostationary Phases Soluble polymers have probably been the most common PSP used for introducing electrostatic interactions into CE separations. Soluble polymers have the advantage over micelles in that they retain a stable, specific structure in electrolytes containing high concentrations of organic modifiers. 8.3.1

Cationic Polymers

Cationic polymers were first used by Terabe and Isemura in 1990 for the separation of naphthalenesulfonic acid isomers [43] and aromatic carboxylic acids [44]. The cationic polymer poly(diallyldimethylammonium chloride) (PDDAC) was used for the separation of naphthalenesulfonic acid isomers. It was found that in the absence of the polymer the disulfonates migrated faster than the monosulfonates (due to a greater charge), but all monosulfonate and disulfonate isomers comigrated. The addition of PDDAC to the electrolyte enabled separation of all isomers and also reversed the migration order between the mono- and disulfonates. The separation mechanism was attributed to ionexchange (IE) interactions between the anionic analytes and the PDDAC, meaning that divalent ions should have a stronger interaction than monovalent ions. This agreed with the observation that the disulfonates showed larger changes in migration time in the presence of PDDAC than the monosulfonates. Similar effects were observed for aromatic carboxylic acids [44], with the divalent acids showing a greater interaction with PDDAC than the monovalent acids. In this work PDDAC was also compared to another cationic polymer, polybrene, and it was found that although PDDAC showed a greater interaction with the analyte acids, the selectivity offered by each PSP was similar. Figure 8.4 shows a typical IE electrokinetic separation of monobasic acids in the presence of 0.3 % PDDAC. Many of these acids, e.g. the aminobenzoic acids, are difficult to separate by straight CE, but good separation was achieved when using PDDAC as a PSP. PDDAC and similar polymers have also been used in combination with indirect detection. Stathakis and Cassidy [45] have used PDDAC, polybrene and associated polymers for the separation of inorganic anions using chromate as the indirect detection probe. Since most of the polymers are obtained as chloride salts, conversion to the associated chromate salt was required to minimize system peak problems. Selectivity changes for the analyte anions were observed for all the polymers tested, with the divalent anion sulfate showing the strongest interaction with all the polymers except diethylaminoethyl dextran chromate (DEAEDCr). This was attributed to steric effects

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Figure 8.4 IE EKC separation of monobasic acids separated in a phosphate electrolyte (pH 7.0) with 0.3 % PDDAC added. Peaks are 1 ¼ benzoic acid, 2 ¼ o-aminobenzoic acid, 3 ¼ m-aminobenzoic acid, 4 ¼ p-aminobenzoic acid, 5 ¼ 1-naphthoic acid, 6 ¼ o-hydroxybenzoic acid, 7 ¼ m-hydroxybenzoic acid, 8 ¼ p-hydroxybenzoic acid, 9 ¼ 2-naphthoic acid, 10 ¼ 2-naphthalenesulfonic acid, 11 ¼ 1-naphthalenesulfonic acid [43]. (Reprinted from J. Chromatogr. A., 515, Terabe and Isemura, pp. 667–676, copyright 1990, with permission from Elsevier)

associated with the bulkier polymeric cation and/or reduced charge density within the polymer. Krokhin and coworkers have published extensively on the separation of anionic metal complexes using PDDAC as an IE PSP using both direct [46–50] and indirect detection [51]. In all cases PDDAC was found to give good selectivity and separation for the metal complexes studied. Furthermore, as with conventional ion chromatography, the nature and concentration of the competing ion in the electrolyte was often an important variable when trying to achieve optimal separations. A more detailed investigation into the observed migration behaviour of metal complexes in the presence of PDDAC was undertaken by Timerbaev et al. [52] who used quantitative structure–mobility relationships (QSMRs) to describe the observed separations. It was found that IE interactions were the predominant mode of separation especially at higher concentrations of the polymer. This was in agreement with work done by Krokhin et al. who compared the migration of the metal complexes with their elution order under IE chromatographic conditions [48]. The use of PDDAC as an IE PSP for the separation of inorganic and small organic anions was comprehensibly investigated by Breadmore et al. [53] who examined the effects of polymer concentration as well as the effect of different competing ions for selectivity control. The strength of the competing ion was found to increase in the order


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fluoride < acetate < chloride < sulfate, while the selectivity was found to be similar to that observed when using a strong-base anion-exchange resin. An equilibrium model based on IE theory was also developed that accurately described the observed separations. This model was then used successfully to optimise the separation of 16 anions in systems comprising the three different competing ions used, see Figure 8.5. The same authors extended this work to indirect detection [54] with the determination of 24 inorganic and small organic anions using probes of differing elution strength (benzoate, chromate and phthalate). As in previous work, the chloride salt of PDDAC had to be converted with the corresponding probe anion so as to minimize system peaks that interfered with the analysis. Zakaria et al. [55] extended the IE PDDAC systems for the separation of inorganic and small organic anions. As well as the IE component of the EKC separation provided by the PDDAC, a neutral b-cyclodextrin was also included in the electrolyte to introduce hydrophobic interactions into the separation. It was found that this secondary interaction did not affect the IE component of the separation and controlled changes in selectivity could be introduced for both inorganic anions and organic acids of varying hydrophobicity if the two PSPs were used simultaneously. A modelling approach similar to that used by Breadmore et al. [53] was undertaken, which could be used both for optimization of the entire separation or for the attainment of a desired separation selectivity (i.e. migration order of the analytes). In a subsequent report, Zakaria et al. further extended the PDDAC-based separation system by including hexanesulfonate in the electrolyte [56]. This system was used for the simultaneous separation of inorganic and small organic anions as well as organic cations (in this case, opiates). The various components of the electrolyte interacted differently with the analytes, with PDDAC exhibiting typical IE interactions with the anions, hexanesulfonate exhibiting electrostatic IP interactions with the cations, and a third hydrophobic interaction being exhibited between all the analytes and the PDDAC-hexanesulfonate ion pair. This is shown in Figure 8.6 where it can be seen that an initial increase in the hexanesulfonate concentration caused it to act as a competing ion, thus increasing the mobility of all the anions. However, as the concentration increased beyond about 80 mM, the more hydrophobic anions such as heptylbenzoate showed interaction with the PDDAChexanesulfonate ion pair. The effect on the cationic opiates can be seen to be a simple ion-pair interaction, with decreased mobilities being observed on increasing hexanesulfonate concentration. Furthermore, this interaction occurred to differing extents for different opiates and was therefore a source of additional separation selectivity. All these interactions were successfully included into an equilibrium-based migration model that allowed quantification of each of the observed interactions, as well as optimization of the separation system as a whole. 8.3.2

Anionic Polymers

The use of anionic polymers in EKC systems has mainly been applied to the separation of neutral analytes, with the charge on the PSP being used mainly to increase the solubility of the polymer and to impart some mobility to the PSP. Unlike cationic polymers, the potential for introducing IE interactions between anionic polymers and cationic analytes has been exploited to only a limited extent. However, there are some reports where brief

164

ELECTROKINETIC CHROMATOGRAPHY (a)

4 15 7

2

9 3 1

11

6 8

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4

15 3

7 9 2

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11 5

6

12 14

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13

10

SO42 –

8

4

6

Time (min)

Figure 8.5 Optimized separations using different competing ions. Optimum conditions are (a) for fluoride: 150 mM NaF, 0.05 % PDDAC; (b) for chloride: 110 mM NaCl, 0.35 % PDDAC, and (c) for sulfate: 50 mM SO42 and 0.30 % PDDAC. Peaks are 1 ¼ Br, 2 ¼ I, 3 ¼ NO2, 4 ¼ NO3, 5 ¼ CrO42, 6 ¼ SCN, 7 ¼ MoO42, 8 ¼ BrO3, 9 ¼ phthalate, 10 ¼ 1,2-benzenedisulfonate, 11 ¼ IO3, 12 ¼ benzenesulfonate, 13 ¼ benzoate, 14 ¼ p-toluenesulfonate, 15 ¼ 2-naphthalenesulfonate, and 16 ¼ 3–5-dihydroxybenzoate. (Reprinted from Ref. [53] by permission of Wiley-VCH)

PSEUDOSTATIONARY ION-EXCHANGE PHASES 20

Opiates

(a)

10 Mobility (×10–9m2V–1s–1)

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[hexanesulfonate] (mM) 0 0

10

20

30

40

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110 7 13

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16 15 14 13 12

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18 16

10

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9 0

10

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40

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100

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[hexanesulfonate] (mM)

Figure 8.6 Mobility changes resulting from varying the concentration of hexanesulfonate in an electrolyte containing 0.5 % PDDAC. (a) Mobility changes for a selection of anions and opiates. (b) Expanded section for the opiates only. Peaks are 2 ¼ iodide, 4 ¼ benzenesulfonate, 6 ¼ ethylbenzenesulfonate, 7 ¼ naphthalenesulfonate, 8 ¼ phthalate, 9 ¼ benzoate, 11 ¼ propylbenzoate, 13 ¼ heptylbenzoate, 14 ¼ morphine, 15 ¼ 10-OH thebaine, 16 ¼ thebaine, 17 ¼ codeine, 18 ¼ oripavine and 19 ¼ laudanine. Conditions: 20 mM Tris, 10 mM HCl to pH 8.0. (Reprinted from Ref. [56] by permission of Wiley-VCH)

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reference to possible electrostatic interactions have been made [57,58]. A more detailed examination of the effect of an anionic polymer on the separation of cationic solutes was performed by Bendahl et al. [59]. Here, a relatively small amount of polyvinylsulfonate (PVS) was added to the electrolyte and this induced small mobility changes for the cationic analytes, which was attributed to IE interactions. Although the changes were relatively small, only 0–0.1 % PVS was tested and it is likely that larger changes would have been observed at higher concentration of PVS. Zakaria et al. [60] demonstrated the use of PVS combined with a neutral bcyclodextrin for the separation of aromatic bases. It was shown that the PVS interacted via an IE mechanism while the cyclodextrin exhibited hydrophobic interactions with the aromatic bases. Furthermore, the strength of interaction between the PVS and the cations differed between analytes, causing selectivity changes to be observed on addition of the PVS, see Figure 8.7. The extent of IE interactions could be varied either by changing the concentration of PVS in the electrolyte or changing the concentration of a competing ion. A divalent competing ion such as Mg2þ was more effective in suppressing the IE interactions with PVS than a monovalent ion such as Naþ, confirming the IE nature of these interactions. The whole system was also successfully modelled as in previous reports, allowing for individual solute–PVS interaction coefficients to be obtained as well as optimization of the electrolyte system. In a subsequent paper the anionic polymer dextran sulfate was combined with a sulfated-bcyclodextrin for the enantiomeric separation of UV-absorbing amino acids [61]. While the presence of the cyclodextrin facilitated enantiomeric separation, the dextran sulfate acted as an IE PSP and allowed for ‘fine tuning’ of the separation selectivity. The concentration of a competing ion in the electrolyte could also be used to modify the extent of IE interactions between the anionic polymer and the cationic amino acids. This could be used as a further means to vary the separation selectivity between the extremes of a pure CE separation and an IE separation. The whole system was again modelled successfully, with interactions with the dextran sulfate being described accurately using equations similar to those used to describe retention in conventional ion chromatography.

8.4 Cyclodextrins as Pseudostationary Phases Cyclodextrins (CDs) are oligosaccharides made up of several D(þ)-glucopyranose units. Those with six, seven and eight glucopyranose units, termed a-, b- and g-cyclodextrins, are the most commonly used. CDs can be thought of as truncated cones comprising a hydrophobic central cavity with hydroxyl groups situated on the rim that aid in increasing its solubility in aqueous solutions. Analytes are separated due to partitioning into the hydrophobic core of the cyclodextrin, with secondary interactions (e.g. IE) also being possible between the analyte and the hydroxyl or other functional groups present on the CD rim. The advantages of cyclodextrins are their relatively high solubility, precisely defined structure and the ability to add functional groups to introduce charge, modify the selectivity or to increase solubility. Cyclodextrins have been used extensively for enantiomeric separations, particularly in electromigration separation methods.


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0 % PVS 2

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11 12 6 4,5

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4,7

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10

1

2.5

3

3.5

4

13

4.5

5

5.5

6

Migration time (min)

Figure 8.7 Effect of polyvinylsulfonate on the separation of aromatic bases using a citrate electrolyte at pH 3.50. Peaks are 1 ¼ pyridine, 2 ¼ m-aminopyridine, 3 ¼ p-aminopyridine, 4 ¼ o-aminopyridine, 5 ¼ picoline, 6 ¼ ethylpyridine, 7 ¼ quinoline, 8 ¼ aniline, 9 ¼ benzylamine, 10 ¼ tert-butylpyridine, 11 ¼ methylbenzylamine, 12 ¼ ethylaniline and 13 ¼ pentylaniline [60]. (Reprinted from J. Chromatogr. A., 997, Zakaria et al., pp. 207–218, copyright 2003, with permission from Elsevier)

8.4.1

Anionic Cyclodextrins

Analyte–cyclodextrin interactions arise predominantly as a result of hydrophobic partitioning of analytes into the relatively hydrophobic core of the cyclodextrin. Analytes that fit best into the cavity will show the greatest change in mobility on addition of the

168


cyclodextrin (highest complex stability constant). However, in the case of anionic cyclodextrins a further electrostatic interaction is possible between cationic analytes and the anionic functionalities contained on the cyclodextrins. Hellriegel et al. [62] used ultraviolet (UV) spectrophotometry, mass spectrometry (MS) and nuclear magnetic resonance (NMR) experiments to elucidate the exact chiral separation mechanism of ephedrines in the presence of neutral and anionic cyclodextrins. They found that in the case of neutral cyclodextrins 1:1 inclusion complexes were formed by inclusion of the phenyl ring (agreeing with the three point interaction mechanism proposed by Quang and Khaledi [63]). However, in the case of anionic cyclodextrins a different orientation was adopted which was likely to stabilize electrostatic interactions between cationic groups on the analyte and the anionic functionalities on the cyclodextrin. This could lead to different selectivities when using anionic cyclodextrins and also introduced the possibility of achieving an IE type interaction between analytes and charged cyclodextrins. An IE interaction between anionic cyclodextrins and metal cations has been demonstrated by Muzikar et al. [64]. They found that divalent cations interacted far more strongly with the sulfated-b-CD than monovalent cations and likened this to the effect observed on a sulfonated cation exchanger. It was also noted that no interaction between the cations and neutral cyclodextrins was observed, and they concluded that it was unlikely that the cations were complexed into the cyclodextrin cavity but rather were associated with the anionic groups on the surface of the cyclodextrin. IE interactions between an anionic cyclodextrin and protonated opiate compounds have also been reported [65]. It is unlikely that significant incorporation of the bulky opiate compounds into the sulfated-b-cyclodextrin occurred, suggesting that most of the interaction observed between the opiates and the cyclodextrin was electrostatic in nature. This conclusion was supported by the fact that as the concentration of competing ion in the electrolyte was increased mobilities for the opiates tended to move toward their CE value in the absence of any cyclodextrin. Furthermore, this effect was more pronounced for divalent competing ions such as Mg2þ than for monovalent ions such as Naþ, see Figure 8.8. A physical model based on ion chromatography theory was developed to describe the observed separations and was shown to predict accurately mobilities over a range of cyclodextrin and competing ion concentrations. A subsequent report into the use of a sulfated b-cyclodextrin for the enantiomeric separation of some aromatic amino acids further demonstrated the extent to which electrostatic interactions play a role [66]. The separations were undertaken at pH 2 so as to ensure full protonation of the amino acids, with a significant interaction being observed between the cyclodextrin and the amino acids. This allowed for full separation of all six enantiomers within 6 min. Although it was likely in this case that a significant contribution to the observed separation was due to complexation within the cyclodextrin cavity (giving rise to the enantiomeric selectivity) it was also shown that the concentration of competing ion in the electrolyte had a major effect on the strength of the analyte– additive interaction. This would imply that an electrostatic interaction also played a major role and also facilitated complexation of the analyte into the cavity. This was supported by the fact that limited selectivity was observed when a neutral b-cyclodextrin was used instead of its sulfated derivative. It was also observed that the extent of this complexation/electrostatic interaction was strongly affected by the surrounding temperature of the electrolyte, with significant selectivity changes being observed on varying the

PSEUDOSTATIONARY ION-EXCHANGE PHASES 1,4

20

3,5 2

(a)

6

1 4 2,3 5

15

(c) 2,4 1 3

6

Mobility (×10–9m2V–1s–1)

169

(b)

6 5

10

5

0 0

20

40 [Na+ or

60 Mg2+]

80

100

(mM)

Figure 8.8 Effect of competing ion on the separation of opiates in a citrate electrolyte at pH 3.50 containing 3.0 mM sulfated-b-cyclodextrin. (a) Observed electrophoretic mobility with no ion-exchange interaction (i.e. no PSPs in the electrolyte); (b) effect on mobility of increasing Naþ concentration; and (c) effect on mobility of increasing Mg2þ concentration. Analytes are 1 ¼ morphine, 2 ¼ 10-hydroxythebaine, 3 ¼ thebaine, 4 ¼ codeine, 5 ¼ oripavine and 6 ¼ laudanine [65]. (Reprinted from J. Chromatogr. A., 985, Zakaria et al., pp. 493–501, copyright 2003, with permission from Elsevier)

electrolyte temperature between 15–60 C. The entire system was successfully modelled using an artificial neural network (ANN) that allowed optimization of both the concentration of cyclodextrin and operating temperature of the electrolyte. 8.4.2

Cationic Cyclodextrins

The use of cationic cyclodextrins has been more limited than corresponding anionic cyclodextrins. Bunke and Jira [67] have shown that cationic cyclodextrins could be used for the separation of acidic and basic aromatic organic compounds. The separation mechanism was generally attributed to partitioning of the phenyl group into the cyclodextrin cavity as well as hydrogen bonding. Electrostatic interactions

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appeared to play a much smaller role with cationic cyclodextrins than with anionic cyclodextrins. The reasons for this are unclear and may be due more to the analytes investigated rather than to a more general lack of electrostatic interaction with these cationic cyclodextrins.

8.5 Other Ion Exchange Pseudostationary Phases 8.5.1

Macrocyclic Polyamines and Diazacrown Ethers

As with the use of cationic surfactants and smaller cationic ion-pair reagents, macrocyclic polyamines have also been successfully used for CE separations using electrostatic interactions to modify the observed selectivity. Takahashi et al. [68] demonstrated the effect of using [9]aneN3 and [14]aneN4 as PSPs for the separation of naphthalenesulfonate isomers. The use of an acidic electrolyte (pH 2.0) ensured that the polyamines were fully protonated and exhibited maximum electrostatic interaction with the naphthalenesulfonates. It was found that the larger [14]aneN4 gave a more complete separation than [9]aneN3, presumably due to a greater charge and hence stronger interaction with the analytes. As well as offering selectivity changes between the mono- and disulfonates, both PSPs also allowed for selectivity changes between individual naphthalenesulfonate isomers, possibly due to ion paring between the macrocyclic polyamines and the differently orientated functional groups on the individual isomers. The use of the macrocyclic polyether cryptand-22 has also been demonstrated for the separation of inorganic and organic anions. Again, the electrolyte was maintained at pH < 7 to ensure full protonation of the PSP. The effect on mobility resulting from the addition of cryptand-22 was studied for a range of inorganic anions and a reduction in mobilities was observed for I, NO3, SCN, BrO3 and IO3. A stronger effect was noted for the divalent anion CrO42 which showed a very significant change in mobility on increasing cryptand-22 concentration, presumably due to a stronger electrostatic interaction. Although electrostatic interactions are likely to be predominantly responsible for the observed separations, it is interesting to note that cryptand-22 exhibits interactions of similar extent with all the monovalent anions investigated, even for I and SCN, which normally show strong interaction with quaternary ammonium stationary phases. A similar investigation into the use of cationic diazacrown ether derivatives for the separation of inorganic anions was performed by More et al. [69]. In this study ionassociation constants between the diazacrowns and the inorganic anions were determined and their magnitudes resembled ion-exchange selectivity coefficients observed on a conventional IE system using a quaternary ammonium stationary phase (i.e. BrO3 < NO2 < NO3 < SCN < I MoO42 < CrO42). Of the two diazacrowns investigated it was found that the smaller derivative exhibited about three-fold greater interactions with the analytes than the larger derivative, see Figure 8.9. It was also noted that the solubility of the smaller derivative was lower than that of the larger derivative, suggesting that the hydration energy of the diazacrown itself also played a role in ion association. The larger derivative in this study was also used by the same authors for the separation of naphthalenesulfonates and aromatic carboxylates [70]. Again, ion-association constants were determined and showed that the sulfonates exhibited a stronger


171

Figure 8.9 Effect of the concentration of the (a) smaller and (b) larger diazacrown ether on the mobility of inorganic anions using a phosphate electrolyte at pH 7.0. Peaks are & ¼ I, } ¼ CrO42, ¼ NO2, þ ¼ NO3, . ¼ SCN, r ¼ MoO42 and ^ ¼ BrO3. (Reprinted from [69] by permission of the Royal Society of Chemistry)

interaction than the carboxylates, as observed in ion chromatography. Furthermore, interatomic distances were found to be important factors for the separation of the anions with the qualitative conclusion being reached that when the charged sites on the anions ˚ longer than that in the diazacrown cation, the interactions were at their were about 2 A strongest.

172

8.5.2


Dendrimers

Dendrimers are large molecules obtained by repetitive ‘cascade’ synthesis starting from an initiator core of a branched building block [71]. Dendrimers based on a initiator core of ethylenediamine are now commercially available and are collectively termed StarburstTM (poly-[amidoamine]; PAMAM) dendrimers. StarburstTM dendrimers have proved to be a popular choice as PSPs for EKC separations. Due to the cascade synthesis of these dendrimers, both anionic (carboxylate) and cationic (amino) dendrimers are possible depending on where the synthesis is halted. Dendrimers can therefore be used as IE PSPs for both anionic and cationic analytes. The hydrophobic core of the dendrimers also introduces the possibility of hydrophobic interactions with organic analytes, similar to that seen when using micelles. Dendrimers have been shown to exhibit IE interactions with charged analytes. Castagnola et al. [72] used different generations of anionic StarburstTM dendrimer for the separation of dansyl amino acids and found that the predominant interaction with the dendrimers was IE in nature. It was also concluded that the observed selectivity of the system could be varied, depending on the generation of dendrimer used. This was attributed to the difference in size and amount of charge present on the dendrimer. Dendrimers have also been used for protein profiling using CE. Stathakis et al. [73] showed the effects of anionic and cationic dendrimers on the separations of chicken sarcoplasmic proteins. It was found that there was a dramatic improvement in the observed separation upon the addition of 0.001 % g/ml of the anionic dendrimer, while further increase in the dendrimer concentration showed little improvement. As the generation (size) of dendrimer was increased, the resolution for the protein separations was also improved. Although this was attributed mainly to increased hydrophobic interaction with the proteins, a concurrent increase in the charge density, and hence capacity, of the dendrimers was also likely to play a significant role.

8.5.3

Solid Ion-exchange Particles

An alternative way to introduce IE interactions into a CE separation is simply to add the ion-exchange particles to the electrolyte. This approach has been used by Breadmore et al. [74] who demonstrated the separation of alkali metal and ammonium ions using sulfonated polystyrene–divinylbenzene (PS/DVB) particles (distributed by Waters Corporation under the name of solid phase reagent (SPR)). The particles were approximately 225 in diameter and were supplied as a 15 % w/v suspension. To facilitate indirect UV detection, imidazole was used as a probe ion and its influence as a competing ion was also investigated. The addition of the SPR was shown to reduce the mobility of all the analyte cations studied, but the SPR could only be used at levels up to 1:1000 dilution of the stock SPR standard due to increased light scattering and hence increased baseline noise. Despite this, selectivity changes were noted on increasing the concentration of SPR up to this limit, with the separation mechanism being attributed to IE interactions between the analyte cations and the anionic SPR. This was supported by the fact that plots of retention factor versus SPR concentration were linear and the slope increased in the order Liþ < Naþ < NH4þ < Kþ < Rbþ < Csþ (see Figure 8.10), which is the same as that observed in traditional IE chromatography using sulfonated stationary phases. It was also


173

0.14 0.12 0.10

k'

0.08

K Na Li Cs Rb NH4

0.06 0.04 0.02 0.00 0

1

2

3

Concentration of SPR (Relative units)

Figure 8.10 Change in retention factor (k0 ) with increasing concentration of SPR in the electrolyte. A concentration of 1 relative unit corresponds to a dilution of 1:3000, 2 to 1:1500 and 3 to 1:1000 dilution of SPR in the electrolyte. Detection was by indirect UV using an imidazole/MES electrolyte at pH 6.15. (Reprinted from Ref. [74] by permission of Wiley-VCH)

noted that as the concentration of imidazole in the electrolyte was increased, suppression of the cation–SPR interaction was observed, again supporting the proposed IE separation mechanism. As well as PS/DVB particles, gold nanoparticles have been used to modify the selectivity of CE separations [75]. In contrast to the PS/DVB particles used above, the gold nanoparticles used by Neiman et al. [75] were of 5–18 nm diameter, depending on the method used to stabilize the particles. These anionic gold nanoparticles were used to separate aromatic acids and bases with unique selectivity attributable to electrostatic interactions. It was also found that relatively small amounts (around 0.02 nM) of the gold nanoparticles were needed to alter the observed mobilities of the cations.

8.6 Conclusions It can be seen that the use of ion-exchange PSPs in capillary electromigration separation techniques has been widespread over the last 15 years. These PSPs permit substantial control over the observed separation selectivity for a wide range of charged analytes. This approach is perfectly suited to CE separations that normally rely on some form of charge to be present on the analytes of interest. The use of IE PSPs is inherently simpler than other approaches, such as capillary electrochromatography with packed columns, for the control of separation selectivity in electrodriven separations of charged analytes because the problems of packing columns and preparing frits are avoided. Furthermore, there is a very wide variety of potential IE PSPs that can be used for the technique. The only two prerequisites are that the PSP is soluble (or can be suspended) in the electrolyte, and that

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it exhibits some significant electrostatic interaction with the analytes of interest. Finally, EKC systems using IE PSPs are amenable to relatively straightforward mathematical modelling, so that they can be easily optimized or conditions leading to a desired separation selectivity can be identified rapidly.

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9 Principles of Enantiomer Separations in Electrokinetic Chromatography Bezhan Chankvetadze

9.1 Introduction This chapter deals with basic theory of enantioseparations in electrokinetic chromatography (EKC). Some heterogeneity of the viewpoints can be observed in the literature regarding several principal concepts of enantioseparations in capillary electrophoresis (CE) in general, and in EKC in particular. In one group of published papers, for example, the electroosmotic flow (EOF) is considered to be a nonenantioselective driving force compared with the electrophoretic mobility of a chiral analyte. In another group of publications a principal difference is made between chiral separations with charged and uncharged chiral selectors. In the third group of published work the formation of a micellar phase is considered as a necessary prerequisite for separation, etc. The subject of this chapter is a critical discussion of already established viewpoints and tracing the most likely future trends in the field of enantioseparations using EKC.

9.2 Separation Principle in Chiral CE: Electrophoretic or Chromatographic? One important conceptual point in enantioselective capillary electromigration separation techniques is to realize that the enantioseparation is commonly not based on the classical principle of zonal electrophoretic separation. This principle postulates the separation as a result of different migration velocities caused by different charge densities of analytes. Electrokinetic Chromatography: Theory, Instrumentation and Applications Edited by U. Pyell # 2006 John Wiley & Sons, Ltd. ISBN: 0-470-87102-4

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The enantiomers of a chiral compound possess the same charge densities. Therefore, none of the potential migration forces in CE, such as the electrophoretic mobility of the analyte, the EOF, their combination or a transport by a nonenantioselective carrier is, in principle, able to differentiate between the enantiomers. The prerequisite for separation of enantiomers in CE is their enantioselective interaction with a chiral selector. This interaction is an analog to differential partition of analytes between different phases in chromatographic techniques. The immiscibility of two media as stated in the definition of chromatography according the IUPAC nomenclature [1] is the secondary prerequisite. It is introduced in the definition of chromatography because the pressure as a migration force does not allow different velocities of miscible phases or different velocities of the components residing in the same phase to be realized. Contrary to this, the electrophoretic migration mechanism allows the species residing in the same phase to migrate with different velocities. It must be stated that for this reason even the enantioseparations performed in a monophasic physical system are based on the selective distribution of the analyte enantiomers between at least two constituents of the liquid phase having a different mobility, i.e. the separation principle in vaste majority of chiral CE separations is chromatographic. In other words, most CE enantioseparations belong actually to EKC [2]. At first glance a small number of enantioseparations in CE based on the mobility difference between the noncovalent analyte–chiral selector complexes [3] may appear to be based on true electrophoretic separation principles. However, this is not the case, because here the analyte–chiral selector interaction is a necessary prerequisite for the formation of diastereomeric complexes. Some confusion also exists regarding the classification of enantioseparations into groups such as capillary zone electrophoresis (CZE), capillary gel electrophoresis (CGE), capillary isoelectric focusing (CIF), etc. The separation principle in CZE is mainly a spatial distribution of the sample components into separated analyte zones in a free solution according to their charge-to-radius ratio, which is equal for the enantiomers. This means that it is impossible to separate enantiomers based on the separation principle of CZE. The separation principle in gel electrophoresis is a sieving effect of the charged analyte molecules depending on their size. Again, the enantiomers as such do not differ in their original size and therefore are unresolvable with an achiral gel. The separation principle in CIEF is based on the pKa difference between the analytes. However, enantiomers have identical pKa values. Thus, the enantiomer separation in all of these techniques relies basically on enantioselective noncovalent/intermolecular interactions between the analyte and a chiral selector, which may be expressed as the effective mobility difference (CZE and CGE), stereoselective shift of the acid–base equilibrium (CIEF), etc. Thus, most of enantioseparations in chiral CE may be unified under the term EKC. This term was introduced by Terabe and coworkers in 1985 [4]. Micellar electrokinetic chromatography (MEKC) represents one particular mode of EKC. Theoretically, it is possible that the binding constants of the two enantiomers are the same with the chiral selector but the electrophoretic mobility, pKa values, sizes/shapes, etc., of the resulting diastereomeric complexes are different [3]. Then the latter might be separated based on the separation principles of CZE, CIEF or CGE. However, to the author’s knowledge only very few examples of such separations are published at present [5–8].

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9.3 Enantioseparations with Charged and Uncharged Chiral Selectors In many published papers, enantioseparations of charged analytes with neutral chiral selectors are attributed to CZE, and the enantioseparations of neutral analytes with charged chiral selectors to EKC. However, from the mechanistic point of view there is no principal difference whether an analyte or a chiral selector is charged. Actually, it is the subject of convention as to which counterpart of the chiral recognition process will be named selectand and which one chiral selector. The reciprocal chiral recognition strategy for a design of effective chiral selectors proposed by Pirkle and Pochapsky in HPLC is based on this philosophy [9] and that principle certainly applies also for enantioseparations in EKC [10]. The enantioseparation of neutral chiral analytes with charged chiral selectors that was considered impossible in the earlier studies on chiral EKC, was successfully realized based on the understanding of the aforementioned concept [11]. The philosophy behind this attempt can be simply expressed in the following way: If a neutral chiral selector can resolve the enantiomers of a charged chiral analyte then the enantioseparation of the neutral chiral analyte should also be possible with the charged chiral selector [2].

9.4 Enantioselective and Nonenantioselective Phenomena in Chiral EKC For many years the role of electrophoretic and electroosmotic mobilities (mep and meo , respectively) in enantioseparations has represented a topic for discussions [2,12]. In many pblications mep was considered to be a selective transport able to make a difference between the enantiomers while meo was considered to be a nonselective transport. This idea does not seem to be correct for chiral (enantioselective) EKC although it applies without any limitation for true electrophoretic separations, i.e. for those separations which are based on a different charge-to-radius ratio of the sample components [2]. The analyte specific quantities such as the effective charge q and radius r enter Equation (9.1) for the calculation of mep [13]: q ð9:1Þ mep ¼ 6prZ where Z ¼ dynamic viscosity of the medium. This means that mep is an analyte-specific property, modified by properties of the medium. On the other hand, meo which can be calculated according to Equation (9.2): meo ¼

er e0 Z

ð9:2Þ

depends on the dielectric constant er of the medium, the permittivity of vacuum e0 , the zeta potential at the solid–liquid interface and the dynamic viscosity Z of the medium. The terms entering Equation (9.2) are entirely system specific and not analyte specific. For this reason mep is selective and meo is a nonselective transport in true electrophoretic separations. Enantioseparations in CE, however, are mostly based on the chromatographic separation principle as mentioned before. Those quantities entering

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Equation (9.1) might be different for other charged analytes; however, they are identical for the enantiomers. For this reason, transport via mep is as nonenantioselective as transport via meo [2,12]. Only in those enantioseparations in which the binding constants of both enantiomers with the chiral selector are equal but the electrophoretic mobilities, pKa values or sizes of the transient diastereomeric associates are different, will the role of the electroosmotic and the electrophoretic mobility be the same as in classical (achiral) electrophoretic separations. Another reason for the above mentioned misunderstanding of the role of mep and meo in enantioseparations in EKC seems to be the fact that, in early studies, it was possible to observe a significant improvement of enantioseparations under those conditions when the EOF was suppressed. However, no attention was paid to the fact that the same apparent effect may, in principle, be observed when one suppresses mep instead of meo under appropriate conditions. However, a principal difference between mep and meo remains: the former causes a substance-specific transport whereas the latter causes a system-specific transport [2].

9.5 Similarities and Differences between Enantioseparations by Pressure Driven Chromatography and EKC As mentioned above, enantioseparations in EKC rely on a chromatographic separation principle. Despite this fact, there are significant differences between these techniques. Responsible for all differences between chromatographic and electrophoretic enantioseparations is the property of the effective electrophoretic mobility being selective for the analytes residing in the same phase [2]. Another important point is that in chromatographic techniques, except that with a chiral mobile phase additive (CMPA) the analyte is virtually immobile when associated with a chiral selector. In EKC the analyte selector complex is commonly mobile. Basic differences between chromatographic and electrophoretic enantioseparations can be derived analyzing the equation proposed for the calculation of the effective electrophoretic mobility difference m between enantiomers [14]: m ¼ m1 m2 ¼

mf þ mC1 K1 ½C mf þ mC2 K2 ½C 1 þ K1 ½C 1 þ K2 ½C

ð9:3Þ

where m1 and m2 are the effective electrophoretic mobilities of the first and the second migrating enantiomer, respectively. K1 and K2 are the binding constants between enantiomers 1 and 2 and the chiral selector, mf and mc are the effective mobilities of the free and the complexed analyte and [C] is the concentration of a chiral selector. It is important to note that m is identical to the difference in the observed mobilities for the two enantiomers, if the observed mobility is defined as the sum of the effective electrophoretic mobility and the electroosmotic mobility. One important point obviously seen from Equation (9.3) is the crucial role of mobilities in enantioseparations in EKC. This parameter is absent in the major chromatographic techniques except the above mentioned mode with CMPA. The


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contribution of mobilities in chiral EKC separations may allow the observation of the following distinguished effects: It is feasible in chiral EKC but not in chromatographic techniques for the selectivity of enantioseparation to exceed the thermodynamic selectivity of chiral recognition. It is possible in chiral EKC to adjust the enantiomer migration order without reversing the affinity pattern between the enantiomers of the analyte and a chiral selector. This is impossible in chromatographic techniques, at least in the mode when the chiral selector is immobilized and not used as a CMPA. The most striking difference between these two techniques seems to be that EKC allows, in principle, the enantioseparation in the case when the binding constants of both enantiomers with the chiral selector are equal [8]. Below, these differences between EKC and chromatographic enantioseparations are illustrated using examples from the literature. As already mentioned, in chromatographic techniques the selectivity of enantioseparation is entirely defined by chiral recognition, i.e. by the difference between the affinity of enantiomers towards the chiral selector. Therefore, the selectivity of enantioseparations in common chromatographic techniques may, at best, maximally approach the thermodynamic selectivity of the chiral recognition but will never exceed it. In contrast to this, in EKC the separation selectivity may exceed the thermodynamic selectivity of recognition. This is experimentally illustrated in Figure 9.1 [15]. In all separations of the chlorpheniramine enantiomers with carboxymethyl-b-cyclodextrin (CM-b-CD) shown in this figure, the components involved in chiral recognition on the molecular level are invariant. This means that chiral recognition itself does not change significantly. However, an enormous (in principle unlimited) enhancement of the separation selectivity

Figure 9.1 Effect of increasing counterpressure on the separation of ( )-chlorpheniramine in the presence of 2 mg/ml CM-b-CD. (Reproduced with permission from Ref. [15])

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Figure 9.2 Schematic representation of flow-counterbalanced separation principle in EKC: (a) without counterbalanced flow; (b) with counterbalanced flow; (c) resulting mobilities. (Reproduced with permission from Ref. [15])

becomes possible on transforming the chiral recognition into a chiral separation. In this particular example, this was achieved by applying a counterbalancing pressure to the separation capillary in the opposite direction to the analyte migration. The principle of resolution (Rs) enhancement without any change in recognition selectivity is a decrease of the observed averaged mobility term mav ¼ 12 ðm1;ob þ m2;ob Þ while retaining the electrophoretic mobility difference (m ¼ m1 m2 ) constant in Equation 9.4 [16]: 1 pffiffiffiffi m Rs ¼ ð9:4Þ N 4 mav As shown in Ref. [15] this concept may allow the design of separation system in a way that two enantiomers certainly possessing the electric charge of the same sign will migrate towards opposite electrodes, which means that the resolution becomes infinitely large (Figure 9.2) [15]. By analogy with electrolysis this phenomenon has been named ‘enantiolysis’. This technique may certainly be applied also for micropreparative purposes as well as for separations of achiral analytes, not only in a binary mixture but also in multicomponent mixtures. Another important point is that a manipulation of the mobility terms in EKC allows not only an adjustment of the selectivity of enantioseparation but also a reversal of the enantiomer migration order without changing the affinity pattern of the enantiomers towards the chiral selector. This is again impossible in chromatographic techniques. This significant difference between chromatographic and electrophoretic separations from the viewpoint of the enantiomer migration order has been noted in previous studies [2,17–19]. Thus, taking into account that the mobility in EKC is a vectorial quantity, one can imagine that just reversing the sign of m even without any change of chiral recognition, will result in a reversal of the enantiomer migration order [17]. Similarly to the case shown in Figure 9.1, the components of a separation system immediately involved in chiral recognition are not significantly modified in the separation depicted in Figure 9.3 [18]. However, the pH of the separation buffer is changed by a designed way to allow the detection of the analyte on the anodic or cathodic ends of the separation capillary,


185

Figure 9.3 Reversal of the enantiomer migration order in EKC without principal modification of chiral recognition. (Reproduced with permission from Ref. [19])

alternatively. This means the reversal of the direction of the vector m and consequently, a reversal of the enantiomer migration order. The idea of the experiment shown in Figure 9.3 is schematically described in references [2,17,19]. A simplified form of Equation (9.3) can be obtained upon assuming that the diastereomeric complexes of both enantiomers with a given chiral selector possess equal electrophoretic mobility ðmC1 ¼ mC2 ¼ mC ) [14]. m ¼

Cðmf mc ÞðK1 K2 Þ 1 þ C½K1 þ K2 þ C 2 K1 K2

ð9:5Þ

This equation indicates some ways of affecting the direction of m without affecting the affinity characteristics between a chiral analyte and a selector. In particular, from Equation (9.5) it is obvious that not only a reversal of the algebraic sign of (K1 K2 ) term but also that of ðmf mcÞ term may result in a change of the algebraic sign of m. This means, reversal of the enantiomer migration order. Changing the algebraic sign of mf mc may be achieved by changing the effective electrophoretic mobility of the analyte or the chiral selector or both of them. The examples of the reversal of the enantiomer migration order based on mobility adjustments have been summarized in Ref. [17,18]. Equation (9.5) does not explicitly contain separation parameters such as

186


charge-to-radius ratio of the chiral selector, pH of the background electrolyte, or electroosmotic mobility. However, all of these parameters may affect the mobility term ðmf mc Þ in Equation (9.5). Therefore, all of them may affect the enantiomer migration order implicitly [17]. It should be noted that it is not the intrinsic electrophoretic mobility of the free and complexed analyte but the observed mobilities that determine the enantiomer migration order in EKC. Thus, if one can manage (even using external parameters such as pressure) the separation conditions requiring the polarity change of the high voltage supply to enable detection of the analytes, then the reversal of the enantiomer migration order can be observed [17,19]. Another difference between enantioseparations in EKC and HPLC is the fact that an enantioseparation is, in principle, feasible in EKC even when the binding constants of the enantiomers with the chiral selector are identical. This conclusion can be derived from Equation (9.3). According to this equation, for the generation of a mobility difference between the enantiomers, e.g. enantioseparation in EKC, the following is required: (a) Formation of transient diastereomeric complexes between the analyte and the chiral selector; this means that enantioseparation is impossible in CE without a chiral selector. (b) Electrophoretic mobilities must be different for the free and the complexed analyte ðmf 6¼ mc Þ. If both above mentioned prerequisites apply, then enantiomers may be resolved with equal success by following two alternative mechanisms: (i) For a given overal migration time the ratio of residence times in the free and in the complexed form is not identical for both enantiomers. The time fraction in which the enantiomers reside in the free and in the complexed form is defined by the degree of complexation (which is dependent on the binding constants and the concentration of the chiral selector), e.g. in this case a difference in binding constants is required. This means that the enantioseparation will be based on the same principle as in chromatographic techniques. (ii) Alternatively, both enantiomers may reside the same time fraction in the free and in the complexed form, e.g. K1 ¼ K2 ¼ K. Equation (9.3) under these conditions may be rewritten in the following form: m ¼ m1 m2 ¼

K ½C ðmC1 mC2 Þ 1 þ K ½C

ð9:6Þ

From Equation (9.6) it is clear that the prerequisite for the enantioseparation in this case is a formation of the transient diastereomeric complexes of both enantiomers with different electrophoretic mobilities mc1 and mc2 , e.g. mC1 6¼ mC2 . The enantioseparations based on the mechanism described by Equation (9.6) can be understood as classical CZE separations. However, it must not be overlooked that interaction of the enantiomers with the chiral selector (as in EKC) is a prerequisite of this separation mechanism. Thus both, either the binding constant difference (chiral recognition) or electrophoretic mobility difference of the corresponding diastereomeric complexes may result in enantioseparations [2,8,18]. Rather common is the case K1 6¼ K2 or a combination of both principles. Thus, as summarized in this section, there are significant differences between enantioseparations in pressure-driven and in electrically driven systems. On one hand, these differences make the techniques complementary. This is an advantage. On the other


187

hand, the rules and dependencies observed in one technique should be applied to the other one with some care in order to avoid serious mistakes in the interpretation of the experimental results.

9.6 Modes of Enantioseparation in EKC The most traditional mode of enantioseparation in EKC is when a separation capillary and both inlet and outlet vials are filled with a buffer solution containing a chiral selector, and the analyte migrates depending on its observed mobility ( ¼ effective electrophoretic mobility þ electroosmotic mobility) from the inlet vial towards the outlet vial, passing a detector. Enantioselective interactions between the analyte and a chiral selector selectively affect the effective electrophoretic mobilites of the enantiomers and this is the most common phenomenon responsible for enantioseparations in EKC. Together with this mode some alternative modes of CE enantioseparation have been proposed, which are briefly summarized below. 9.6.1

Partial-filling and Counter-current Techniques

The partial filling technique has been proposed by Hjerten and coworkers [20] and involves the partial filling of a separation capillary with a chiral selector. Later it was found that in the case when a chiral selector possesses sufficient electrophoretic mobility in the opposite direction to the velocity of the chiral analyte, it is possible to fill the entire capillary with a chiral selector [11]. This technique was named counter-current separation. In both of the above mentioned techniques the outlet vial is free of chiral selector. The advantages of these techniques are the following: (a) Chiral selectors which produce a significant detector response may be used for chiral separations. This relates not only to UV-absorbing chiral selectors as commonly described in the literature [21,22] but also allows on-line CE–MS coupling [23–25] and, in principle, may allow the use of chiroptical detectors also in chiral EKC; (b) Some expensive and exotic chiral selectors may be used in smaller amounts in this mode; (c) Binding constants between an analyte and a chiral selector can be calculated by variation of plug length and concentration of a chiral selector in a plug [26,27]. More comprehensive descriptions of partial filling and counter-current migration principles are given in a recent review by Amini and Westerlund [28]. 9.6.2

Mobility Counterbalanced Mode

Another promising mode of chiral EKC separations seems to be the mobility counterbalanced mode. Counterbalancing of the analyte effective electrophoretic mobility by pressure has been applied by Culbertson and Jorgenson for the enhancement of the detection sensitivity in achiral CE [29]. Later the same technique was used for the separation of isotopomers of phenylalanine [30]. The potential advantage of flow counterbalanced capillary electrophoresis (FCCE) can be seen from Equation (9.7) [31]: pffi E t ð9:7Þ Rs ¼ ðm1 m2 Þ pffiffiffiffiffiffi 4 2D

188


where E is the electric field strength, D is the average effective diffusion coefficient of two analytes, and t p is ffithe electrophoretic migration time. The resolution Rs is expected to be proportional to t. In FCCE the sample is driven forward by electromigration and then backward by pressure induced flow. The samples travel back and forth in the capillary until sufficient separation is obtained [31]. In the FCCE mode as proposed by Culbertson and Jorgenson [29], the electric field and the pressure are applied alternatively as the driving forces. In another mode of FCCE, the counterbalancing driving force such as pressure may be applied to the separation chamber continuously during the entire time of separation [15]. An enormous increase of the separation factor (ratio of migration times for two analytes) in chiral and achiral EKC separations may be achieved using this technique as already mentioned above [15]. The difference between counter-current [11] and flow-counterbalancing CE [15] techniques is that in the latter a chiral selector and a chiral analyte do not migrate in the opposite direction to each other but the bulk flow moves with a definite velocity in the opposite direction to the effective mobility of the analyte zone. The principle of this technique is schematically shown in Figure 9.2 [15]. The advantages of the mobility counterbalancing technique include the following: (a) enormous, in principle unlimited, enhancement of the separation factor may be achieved; (b) this technique allows easy transformation of a discontinuous zonal separation of a binary mixture into a continuous separation with stepwise migration of the sample components from the inlet towards the outlet vial (Figure 9.4) [15]; (c) This technique may be used for micropreparative purposes and offers a significantly higher sample capacity compared with discontinuous separations. Other potential advantages of mobility counterbalancing techniques are discussed in Ref. [15].

Absorbence

0.10

0.08

0.06

a (+)-Chlorpheniramine (–)-Chlorpheniramine

0.04 b 0.02

(–)-Chlorpheniramine

50

100

150 200 Time (min)

250

300

350

Figure 9.4 Continuous separation of ( )-chlorpheniramine with 3.5 mg/ml CM-b-CD (a) in the absence and (b) in the presence of a low counterpressure. (Reproduced with permission from Ref. [15])


189

The mobility counterbalancing technique is certainly not limited to binary mixtures and it can easily be applied in stepwise mode for the separation of multicomponent samples. Pressure/vacuum, the EOF, or a different leveling of the inlet and outlet vials, etc., can be used as a driving force for a generated counterflow in this technique [15]. 9.6.3

Synchronous Cyclic Capillary Electrophoresis

Synchronous cyclic capillary electrophoresis (SCCE) was proposed by Jorgenson’s group as a technique that allows the dispersion problems in FCCE caused by the parabolic counterflow profile to be overcome [31]. High resolution is achieved in SCCE by driving the samples in a virtually closed loop until the desired resolution is achieved. According to the authors the system operates analogously to a CE system with direct current voltage over a very long capillary. This technique was applied for isotopic and chiral separations. The dynamics of the chiral separation of a mixture of (1-hydroxy-1-phenyl)ethyltrimethylammonium chloride and (2-hydroxy-1-phenyl)ethyltrimethylammonium chloride in SCCE clearly illustrated the power of SCCE for solving complex separation problems. In the third cycle, the enantiomers of (a-hydroxybenzyl)methyltrimethylammonium chloride with a selectivity factor of 1.0078 were almost baseline separated in 3.5 h. As mentioned by the authors, similar separations with a multicycle LC system as described in Ref. [32] would be also possible but would have taken 43 h. 9.6.4

Carrier-mode Separations

In the carrier mode of EKC a chiral selector is not only responsible for the enantioselectivity of the separation system but also for the transport of the analytes to the detector. The most important advantage of this mode is that the analyte migrates to the detector only when associated with the chiral selector, i.e. when participating in the chiral recognition process. The uncomplexed analyte remains immobile or in certain circumstances may possess an observed mobility directed towards the inlet vial. Among the chiral selectors, charged ones having an (intrinsic) electrophoretic mobility may be used as separation carriers in EKC as noted by Terabe in 1989 [33]. Carrier mode chiral separations offer significant advantages and may become a very useful technique for biomedical applications where structurally similar analytes, such as chiral drugs and their metabolites must be separated from each other and enantioseparated simultaneously. Such a complex separation problem implies very high enantio- and chemoselectivity requirements on the separation system (Fig 9.5) [34]. Carrier mode separations might also be realized beside charged CDs with other chiral selectors possessing an (intrinsic) electrophoretic mobility as reported earlier [35]. With increasing application of combined chiral selectors, the carrier ability of one chiral selector is often employed in this mode, which is briefly summarized in the next section. 9.6.5

Combination of Chiral Selectors

The combination of chiral selectors is a well-known approach in chiral EKC and has been summarized in several reviews [36,37]. Our insights into the optimization of this technique are summarized in previous papers [2,12,38].

190

ELECTROKINETIC CHROMATOGRAPHY O

2

N

O H *

1

O

N H

H O

UV absorbance at 230 nm

N * O

N H

O

trans -5·-Hydroxythalidomide [3,4] cis -5·-Hydroxythalidomide [5,6]

O

O

*

O

O

5

6

5-Hydroxythalidomide [1,2]

O N *

O O

3

4 7

0

5

10

15 Time (min)

20

8

N H

O

Thalidomide [7,8]

25

30

Figure 9.5 Simultaneous carrier mode separation and enantioseparation of thalidomide and its hydroxylated metabolites. (Reproduced with permission from Ref. [34])

As mentioned above, a chiral separation in EKC may be decoupled in two basic steps: (a) chiral recognition which occurs on the molecular level, and (b) transformation of chiral recognition into chiral separation. According to our approach, in order to design a dual chiral separation system it is useful to investigate the two above mentioned steps separately. When two chiral selectors cooperate in the first step, design of the dual system becomes almost impossible without involving additional techniques and cannot be optimized according to the simplified approach described below [2,38]. An additional point is that both, mobility and affinity effects must be considered and a conclusion about a favorable affinity pattern for an enhancement of a chiral separation may be drawn depending on the effect of both chiral selectors on the observed mobility of the analyte. Some of these points are illustrated below taking warfarin (WF) as chiral analyte [39]. Before designing a dual chiral recognition system, the affinity pattern of the enantiomers under study must be determined for each chiral selector. The enantiomer migration order of WF when using various cyclodextrins as chiral selectors is summarized in Table 9.1. The following seems noteworthy when discussing the results shown in Table 9.1. Although the enantiomer migration order is the same when using the neutral CDs (except a-CD) and heptakis(2,3-diacetyl-6-sulfo)-b-CD (HDAS-b-CD) actually the affinity pattern is opposite [39]. The reason why the CDs with opposite affinity patterns result in the same enantiomer migration order is their opposite effect on the observed mobility of the analyte. Neutral CDs decelerate the observed velocity of the analyte WF towards the detector whereas charged HDAS-b-CD (under the given experimental conditions) accelerates it. Based on the results summarized in Table 9.1 and previous considerations [2,38,39], a combination of neutral CDs (except a-CD) and HDAS-b-CD may be beneficial for the enhancement of the enantioselectivity, whereas a combination of HDAS-b-CD and the other sulfated b-CD derivative, heptakis(6-sulfo)-b-CD (HS-b-CD) may disfavor the enantioseparation. This was actually observed (Figure 9.6) [39].


191

Table 9.1 Enantioseparation of WF with various CDs (Reproduced with permission from Ref. [39]) Cyclodextrin Without CD a-CD b-CD

Me-b-CD (0.6) Me-b-CD (1.8) DM-b-CD TM-b-CD HS-b-CD

HDMS-b-CD HDAS-b-CD SBE-b-CD g-CD

Concentration of CD, (mg mL1) 20 40 60 3 6 12 15 5 2 6 1 5 10 5 10 15 25 50 20 40 60 20 1 2 5 10

Migration time (min) t1 t2 29.796 41.047 51.130 60.834 50.589 51.934 73.838 74.431 46.539 51.140 113.343 32.208 34.987 39.441 22.417 22.058 19.679 16.975 14.550 32.993 32.346 31.112 27.917 21.345 33.765 38.415 42.609

29.796 41.047 52.039 62.838 50.589 51.934 75.575 76.504 48.118 54.105 128.539 32.208 36.037 42.241 23.075 22.746 20.567 17.396 14.642 32.993 33.008 31.900 30.575 22.100 33.765 38.415 44.012

Optical rotation sign of first migrating enantiomer

() () (þ) (þ) (þ) (þ) (þ) (þ) (þ) () () () () () () () (þ) (þ) (þ)

A mathematical model describing the enantioseparation in a dual chiral selector system has been proposed by several groups [40–43]. In selected cases the application of a dual chiral separation system allows observation of very high enantioselectivities [44]. This technique bears some potential also for practical biomedical problem solving [34] as well as for a better understanding of the mechanisms of chiral separations, which are sometimes difficult to observe in a single selector system [2]. In the papers dealing with a combination of chiral selectors, basically multiple CD systems are discussed. However, it should be noted that CDs may be combined with other types of chiral selector, or a combined chiral selector system without a CD component can also be used [45–55]. The very first example of combined chiral selectors in EKC seems to be that reported by Fanali et al. [45] in 1989, when 15 mM L-(þ)-tartaric acid buffer was used in combination with 15 mM b-CD in order to separate the enantiomers of racemic cobalt complexes. CDs have also been combined with chiral surfactants such as cholic acids or synthetic micelle-forming agents [48]. Several studies have been published on the combination of CDs with chiral [49] and achiral [50,51] crown ethers.

192

ELECTROKINETIC CHROMATOGRAPHY (OCH3)7

β

(+)

+

+ (OSO2O–Na+) 7

(OSO2O–Na+)7

β

β (OAc) 7

(OAc) 7

(+)

(OCH3)7

(CH3O)7

(OH) 7

(OH) 7

(+)

(–) (–) (–)

(a) 35

(b) 40 45 Time (min)

35 40 45 Time (min)

25 30 Time (min)

Figure 9.6 Enantioseparation of warfarin with TM-b-CD and with a combination of TM-b-CD and HDAS-b-CD (a), and a combination of TM-b-CD and HS-b-CD (b), as chiral selectors. (Reproduced with permission from Ref. [39])

Other interesting publications on dual chiral separation systems are those involving chiral (and achiral) ion-pair additives [52] and other low-molecular weight additives [53,54] in combination with CDs. 9.6.6

Enantioseparations in Nonaqueous Media

Enantioseparations in nonaqueous media have been reported since 1994 [55]. Nonaqueous buffers offer certain advantages compared with aqueous ones from the viewpoints of the alternative chiral recognition mechanisms involved in the separation [56], lower electric current and Joule heat generation, higher solubility and stability of certain analytes and chiral selectors in nonaqueous buffers [57–60], easier on-line coupling to mass spectrometers, etc. Among the nonaqueous solvents N-methylformamide (NMF), N,N 0 -dimethylformamide (DMF), dimethylacetamide (DMA) and short-chain alcohols represent certain interesting separation media for nonaqueous chiral EKC. The protic organic solvents such as NMF, DMF, etc., possess advantages for on-line chiral CE-MS coupling because they do not necessarily require electrolytes as conductive additives. However, these solvents strongly inhibit an inclusion complex formation and hydrogen-bonding interactions,


193

which are often essential contributors to chiral recognition. For this reason the concentrations of chiral selectors required for enantioseparation in these organic solvents are relatively high and sometimes it becomes questionable as to whether nonaqueous EKC is really beneficial compared to the enantioseparation in an aqueous buffer with the same chiral selector. It has been considered that pure water, alcohols and many organic solvents require some ionizable additives such as ammonium formate, ammonium acetate, etc. These may create some problems for on-line coupling of chiral CE with MS. However, many chiral selectors work rather effectively in solvents such as alcohols [57–60] compared with more polar solvents (DMF, NMF, etc.). Valko et al. reported a significant EOF velocity in methanol, ethanol, acetone, acetonitrile and several other organic solvents without the addition of electrolytes [61]. Nonaqueous EKC enantioseparations using chiral selectors, which are impossible to use in aqueous solvents, are more interesting [56–59]. It would obviously be of some interest to compare the same chiral selector in both aqueous and nonaqueous buffers from the mechanistic point of view (enantiomer migration order, intermolecular forces involved in complex formation and chiral recognition, structure of complexes, etc.). Enantioseparations of many chiral analytes have already been described with the same chiral selector in aqueous and nonaqueous buffers [59,60]. However, to the best of our knowledge, until now no comparative study has been published that clearly illustrates that alternative chiral recognition mechanisms are involved when performing chiral separation with the same chiral selector in either aqueous or nonaqueous buffers. Nevertheless, Wang and Khaledi have shown that performing enantioseparations in nonaqueous media may in some cases allow severe electrodispersion resulting from the mobility mismatch between a charged CD-analyte complex and coions of the running buffer to be avoided [62]. Some details of enantiomeric separations by nonaqueous EKC are summarized in the review paper by Wang and Khaledi [63]. 9.6.7

Enantioseparations by Capillary Isoelectric Focusing

Although there are early examples of enantioseparations described by Righetti and coworkers based on the isoelectric focusing principle in the slab-gel format [64] for a long time capillary isoelectric focusing (CIEF) was considered to be the only mode of capillary electromigration techniques in which an enantioseparation was impossible. It was clearly realized in the early days of the development of chiral EKC that enantiomers possess identical pKa values and identical apparent isoelectric points. For this reason enantiomers have been considered not to be separable in CEIF. However, if the chiral analyte is involved in multiple interdependent equilibria and at least one of these equilibria is enantioselective then the entire process may become enantioselective. Although not clearly emphasized in the original paper, the first application of interdependent multiple equilibria for enantioseparations in the CE format seems to be that described by Vigh and coworkers [65]. These authors reported the enantioseparation of fenoprofen and ibuprofen with neutral b-CD at pH 4.50. It was found that only the neutral forms of these chiral compounds are stereoselectively recognized by b-CD. However, this can not generate a measurable mobility difference between the enantiomers

194


because mf ¼ mc in Equation (9.5). The phenomenon responsible for the generation of a mobility difference between the enantiomers in this system seems to be the following: the neutral forms (as well as the ionic forms) of these compounds are involved simultaneously in two interdependent equilibria – the acid–base equilibrium and an interaction with b-CD. When the latter is enantioselective, the molar fractions of the neutral forms of the R- and S-enantiomers which are available for participation in the acid-base equilibrium are different, and this turns the inherently nonstereoselective dissociation process into an apparently enantioselective one. Thus, the two enantiomers will be ionized to different degrees, which results in a difference between their effective electrophoretic mobilities, e.g. resulting in enantioseparation [2,12]. For the above mentioned reason, the apparent pKa values (or the apparent isoelectric points) of the enantiomers may become different (in analogy to their effective mobilities in CZE). The difference in the apparent pKa values between the analyte components is responsible for an enantioseparation in CIF. The feasibility of enantioseparations in the CIEF mode has recently been shown experimentally by two groups. Glukhovskiy and Vigh described analytical-scale enantioseparations in the CIEF mode as well as micropreparative separations using the commercially available continuous free-flow electrophoretic unit Octopus and proposed a mathematical model considering the simultaneous multiple equilibria involved in the chiral recognition process [66]. A fundamental treatment of pKa-shift associated effects in enantioseparations by CD-mediated CE was given by Rizzi and Kremser [5]. The authors used this effect for enantioseparations by CIEF and noted the preparative potential of the technique [67]. 9.6.8

Enantioseparations on Microfabricated Devices

Microfabricated devices offer important advantages from the viewpoint of analysis time, costs and throughput. The problems with pressure-driven microchip technologies are basically connected to the management of fluid flow with acceptable characteristics through the miniaturized channels. The velocity of the electrokinetically driven flow can be precisely controlled by regulating the applied potentials at the terminus of each microchannel. Using electric fields to direct and control the flow inside the microchannels eliminates the need for micromoving parts such as pumps and valves allowing for a convenient integration process of complete assays. Due to the flat cross section of the channel and the large thermal mass of the glass chip, temperature dissipation on chips is greatly improved compared with conventional capillaries. This allows to apply higher electric field strengths, which in combination with a short separation length enables very fast separations [68,69]. Enantiomeric separations on microfabricated electrophoretic devices have been reported only recently and about ten research papers [68–78] and one review paper [79] summarize the developments in this field. In all enantioseparations performed using microfabricated electrophoretic devices, CDs have been used as chiral selectors except in one case [69], where a chiral crown ether, ()-(18-crown-6)-tetracarboxylic acid (18C6H4), was used as chiral selector. In the very first enantioseparation using microfabricated electrophoretic devices, Hutt et al. reported the enantioseparation of amino acids extracted from the Murchison meteorite using g-CD as a chiral selector [68]. With charged chiral analytes, neutral


195

native or derivatized CDs can be used as chiral selectors, as is commonly done in chiral EKC. However, conversion into fluorescing derivatives might be required for some analytes in order to enhance the detection sensitivity, which represents a serious challenge in separations using microfabricated electrophoretic devices. The derivatization may convert the analytes into neutral compounds which can be separated with charged CDs or with a combination of neutral (or charged) CDs and micelles. Another argument for using charged CDs as chiral selectors in microfabricated electrophoretic devices for enantioseparations can be their commonly higher enantiomer separation ability as illustrated in the studies by Belder and coworkers [77,78]. These authors were able to perform enantioseparations within a few seconds [78,79].

9.7 Chiral Selectors Although CDs and their derivatives remain the most widely used chiral selectors in EKC, new chiral selectors are intensively proposed. Not all of the novel chiral selectors become widely used for different reasons such as availability, cost, compatibility and competitivity with established chiral selectors, etc. However, some of them are interesting from the mechanistic point of view. Several randomly and selectively substituted CD derivatives have been used as chiral selectors in EKC. The suppliers of randomly substituted CD derivatives try to provide their products in a reproducible quality and well characterized form. Nevertheless, CD derivatives with a known derivatization pattern are recommended for use for more or less thorough mechanistic studies as well as for the development of validated chiral EKC assays. Derivatization of a CD designed by selective activation and protection of the hydroxyl groups on the CD rim is a well known technique in carbohydrate chemistry. The application of selectively substituted CDs in achiral EKC has also a relatively long history. The first charged CD derivative used for enantioseparation by Terabe was a single isomer 6-b-monoaminoethylamino-6-monodeoxy-b-CD [33]. Later, Nardi et al. [80] also used two single-isomer positively charged b-CD derivatives, 6-monoethylamino-6deoxy-b-CD and 6,A6D-dimethylaminodideoxy-b-CD for the enantioseparation of chiral 2-hydroxy acids. This topic attracted increased attention after describing the syntheses and applications of the negatively charged single-isomer CD sulfates by Vigh’s group [81–83]. The first nine members of this family have been commercialized. Although useful for the enantioseparation of chiral cationic, anionic, neutral and zwitterionic analytes, the single isomer CD sulfates do not seem to be superior from the viewpoint of chiral separation performance as compared with randomly substituted analogues such as commercially available b-CD-sulfate or sulfobutyl-b-CD. However, unambiguous advantages of the single-isomer CD-sulfates are better reproducibility of separation results achieved with this kind of chiral selector. Other, still less recognized advantage of these CDs is their perfect suitability for mechanistic studies. This relates not only to the reliable thermodynamic quantities obtained in binding studies or developing mathematical models but also to clear, well resolved signals in 1H- and 13C-NMR spectra. The latter makes single-isomer CD sulfates especially suitable as probes for studies of the structure of CD-analyte complexes in solutions using intermolecular nuclear Overhauser experiments (NOE) in NMR spectroscopy. One additional, again not yet well studied,

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advantage of the CD derivatives described in Refs [81–84], especially of heptakis-(2,3diacetyl-6-sulfo)-b-CD, seems to be its opposite enantiomer binding pattern for many racemates compared with other CDs [2]. This property is interesting from both a practical and a theoretical point of view. The syntheses and applications of single-isomer cationic derivatives of CDs have also been reported [40,85–90]. In addition, the first two members of the family of singleisomer cationic CDs, namely 6-monodeoxy-6-monoamino-b-CD and 6-monodeoxy-6monoaminohexakis-(6-O-methyl)-heptakis-(2,3-di-O-methyl)-b-CD became commercially available from Cyclolab Ltd (Budapest, Hungary). Although both of these derivatives are rather expensive, the minute amounts of chiral selector required in CE/EKC may facilitate a more extensive study of at least the commercially available single isomer cationic CD derivatives as chiral selectors in EKC. Together with the above mentioned cationic and anionic CD derivatives, few other representatives of this family such as the sodium salts of b-CD-6-monophosphate, the sodium salts of b-CD-6-monocarboxylic acid and mono- and dicarboxymethyl b-CDs were used for mechanistic studies [91]. Zwitterionic CD derivatives may represent some interest as chiral EKC selectors. Several interesting applications have been reported [92,93]. In these CDs anionic, neutral and cationic forms may be switched pH-dependent and this property seems to be attractive. However, it remains still to be proved that these derivatives may successfully cover the wide spectrum of cationic, anionic, zwitterionic and neutral chiral analytes enantioseparable with the anionic or cationic CDs available. It seems noteworthy that zwitterionic mono-(6-d-glutamylamino-6-deoxy)-b-CD described in Ref. [92] also represents a single-isomer chiral selector. Also neutral single-component CD derivatives are commercially available. Cyclolab provides several single-component methylated, ethylated and acetylated derivatives of a-, b- and g-CD. Chiari et al. [94] reported the use of one additional member of the neutral CD polymer family for enantioseparations of cationic chiral analytes. Summarizing this subsection it can be noted that there is no longer any urgent need to introduce new chiral selectors belonging to the CD family. In contrast, despite of rather long-term studies it seems that the binding and chiral recognition mechanisms of CDs are still not well understood. Therefore, the designed synthesis of CD derivatives with the desired properties and the study of their interaction with chiral analytes using other instrumental and computation techniques in combination with EKC seems to be rather important. Besides CDs also other chiral selectors such as noncyclic oligosaccharides and polysaccharides [2,95,96], chiral surfactants [2,97–100], macrocyclic antibiotics [101,102], proteins, peptides [2,103,104], peptide libraries [105,106], ligand exchange materials [107], synthetic macrocyclic compounds [108], etc. can be used as chiral selectors in EKC.

9.8 Design and Adjustment of Enantioseparations in EKC Rational design of a separation experiment is as complex as it is important. Once a decision has been made to perform an enantioseparation by EKC, then the questions


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concerning the most suitable mode, chiral selector and separation conditions need to be answered. For the latter it is possible to use a more traditional univariate as well as multivariate approaches. 9.8.1

Univariate Approach

Most commonly, the enantioseparations in EKC have been optimized by using the univariate approach. According to this strategy, the effect of one selected experimental parameter on selected separation parameters is studied while other parameters are fixed at a defined constant value. In chiral EKC the experimental parameters to be optimized are: the nature and concentration of the chiral selector, the ionic strength, the pH, achiral additives to the separation buffer, the separation temperature, the material, dimensions and the inner surface of the capillary, etc. In many research papers enantioseparations are studied with regard to the above listed or some additional variables. These studies, as well as simple screening of chiral selectors for a wide variety of chiral analytes, have become currently somewhat less useful because much material of this kind has already been accumulated. It is rather interesting to rationalize our knowledge of chiral EKC by studying structure-binding and structure-chiral recognition dependencies in more detail. For a particular separation problem, however, an adjustment of the separation by a variation of the separation conditions will still remain important. To this group of problems may belong a particular drug and its metabolites, environmental pollutants and their degradation products, important synthetic chemicals in combination with their precursors and possible side and/or degradation products. This review does not summarize the effect of particular variables on the enantioseparation in EKC because this topic has been extensively discussed in many review articles [109–111]. As mentioned above, many papers have been published concerning the effect of different variables on chiral EKC separations. However, only few of them represent a systematic approach to cost and time effective method development [112,113] based on the univariate approach. The subject has been reviewed by Fillet et al. [113] who, in analogy to other published works [112] also suggested a method development chart and illustrated its suitability for achieving the enantioseparation of 48 of 50 chiral analytes tested. There is no need to discuss the usefulness of these schemes. However, one has to keep in mind that every chart is somewhat intuitive and based on empirical knowledge, and even on the personal experience of the authors. Because the charts are a priori based on a limited number of experiments, their predictivity may be limited. For instance, the scheme proposed in Ref. [112] suggests that the enantiomers of phenprecoumon as an analyte containing a condensed aromatic structure unit can be separated with g-CD, and not separated with a-CD. This suggestion is based on the idea that those analytes which fit better into the cavity of a CD are better enantioselectively recognized. However, as recent mechanistic studies indicate, the complete inclusion of the analyte into the cavity of CD is not a necessary prerequisite for enantioseparation. A partial inclusion or external intermolecular interaction may also be sufficient. Thus, when contrary to the above mentioned suggestion, no enantioseparation of phenprecoumon in the presence of g-CD but baseline enantioseparation with a-CD was observed, the authors explained this effect by an interaction of the side-chain of phenprocoumon with the a-CD cavity [112]. Thus, the contradiction was apparently correctly solved but, unfortunately, this does not

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improve the predictivity of the scheme. The predictivity of such charts may significantly be improved when they are based on the rules of mathematical statistics and large databases (for instance, Chirbase CE [114]). Although widely used, the univariate approach requires a large number of independent experiments because it typically involves keeping all parameters constant while varying one parameter at a time and measuring the method responses of interest (separation factor, efficiency, resolution, analysis time, etc.). This approach is experimentally reliable and when properly designed provides, besides the optimization of the separation conditions, some direct or indirect information about the separation mechanism. However, the univariate approach is not ideal from the viewpoints of method development with respect to time and costs (personal and equipment time, reagents, etc.). The chemometric experimental designs may provide significant help in the development of chiral EKC methods. 9.8.2

Chemometric Experimental Designs

The goal of statistical design techniques is the reduction of the number of experiments required for optimization and to consider the possible interdependence of parameters [115]. This is very important in EKC because the separation variables are usually interdependent in this technique. Several types of design are available, and the choice of design depends on the number of variables and how detailed the information has to be. A full factorial design is a good choice when the number of variables is four or less. When more than four variables are of interest, a fractional design is applicable. With a large number of variables a Plackett–Burman design (PBD) [116,117] is the preferred choice. A factorial design is a statistical method in which all possible factor combinations are considered, allowing the calculation of the single effects of each factor and any factor interactions. The number of experiments required in this technique can be calculated using the following equation: Nexp ¼ mn

ð9:8Þ

where n is the number of factors and m is the number of levels (number of values of each factor). The number of experiments required for factorial designs increases rapidly with an increasing number of factors to be optimized. If, for example, one needs to optimize the concentration of the chiral selector, the ionic strength and pH of the buffer, the applied voltage and the amount of organic modifier in the background electrolyte (five parameters), each one at three levels, the number of experiments required will be Nexp ¼ 35 ¼ 243. Statistical techniques such as central composite designs (CCD) developed by Box and Wilson [118] and the PBD [116] require a smaller number of experiments and lead in general to the same result. The number of experiments required in CCD is Nexp ¼ 2n þ 2n þ 1

ð9:9Þ

where n is the number of factors to be optimized [119]. CCD provides data that are sufficient for the fitting of a linear polynomial model to a set of data. Regression analysis can be used for such a model, which enables one to


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predict the response at levels of the variables within the factor space not investigated in the design. The response in the case of EKC can be resolution of the peak pair or selectivity, and factors can be the concentration of the chiral selector, pH and ionic strength of the buffer, etc. Small et al. [120] achieved rapid optimization of the chiral separation of amlodipine using the CCD technique. In this study the response surface was modeled for three factors by fitting a second-order polynomial in four dimensions. The number of experiments was Nexp ¼ 23 þ ð2 3Þ þ 1 ¼ 15 by taking the pH of the background electrolyte, the separation temperature and a-CD concentration as factors. The data acquired from this CCD were analyzed to model a four-dimensional response surface. The optimum conditions predicted by CCD were used experimentally and resulted in a baseline separation of the enantiomers. The experimental results observed are in excellent agreement with the predicted values. Although the response surface is four-dimensional, it can be readily visualized as a three-dimensional graphic by presenting the response to two factors, while the third is kept constant at its optimum value. Wan et al. [121] reported the use of a full factorial design for the optimization of the pH and the sodium dodecyl sulfate (SDS) concentration in the enantiomeric separation of amino acids (AA) which were derivatized with ()-1-(9-fluorenyl)ethyl chloroformate (FLEC). For the design, ten experiments, including two centre points, were performed utilizing a mixture of four different FLEC-AAs [threonine (Thr), isoleucine (Ile), valine (Val) and phenylalanine (Phe)]. The results obtained from the optimization indicated that a high pH was necessary for the enantiomeric separation of these four FLEC-AAs and that the different AAs showed optimum resolution (for the enantiomeric separation) at different SDS concentrations. For example, for the first-eluted analyte, Thr, the optimal SDS concentration is relatively high, of about 60 mM. In contrast, for the last-eluted analyte, Phe, the SDS concentration should be as low as possible. This result was explained by the higher hydrophobicity of Phe compared to Thr. A buffer containing an intermediate concentration of SDS, 20 mM, and with a high pH, 9.2, was therefore selected in order to facilitate the enantiomeric separation of a maximum number of FLEC-AAs. As a result, for 11 of the 19 FLEC-AA s examined the enantiomers were baseline separated. The important advantage of a full factorial design for the optimization of EKC separations is that it considers nonlinear changes of parameters and the interrelation between them [122]. The most critical point of this technique is the selection of the low and high limits of the designed parameters. A good knowledge of the separation system is generally required to do this properly. In a situation where the high and low limits have been incorrectly selected, the experiment will be misleading concerning the direction in which the optimum will be found [121]. CCD was shown to be a useful approach for optimizing EKC enantioseparation conditions of a mixture of five racemic (chiral) amphetamines. The same group illustrated that experimental designs offer an efficient test for the robustness of the analytical method [122]. Several papers have described the use of PBD [116] for the optimization of EKC enantioseparations [122–126]. A simultaneous application of a fractional factorial design and a central composite design for the optimization of the EKC separation of epinephrine enantiomers has also

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been reported [125,126]. In this study a compromise between conflicting goals, such as maximization of resolution and minimization of analysis time, was achieved by introducing a desirability function D. Balancing these goals, the most acceptable solution to the problem was found and the optimized method gave a fast separation with baseline resolution of the epinephrine enantiomers. The PBD focuses on the main effect of the factors and is especially effective when the number of variables is high. The limitation of this technique compared with full factorial designs is that the former does not allow the interdependence between the parameters to be considered easily. In addition, similarly to all first-degree factorial designs, the Plackett–Burman design also assumes a linearity of the estimated variables over the whole range of the experiment. In chiral EKC, however, nonlinear dependencies are quite common. 9.8.3

Mathematical Models of EKC Enantioseparations

Mathematical models have the advantage that, in an ideal case, they not only describe a separation as an entire process but also may allow effects that are difficult to isolate to be identified based either on the intuitive or empirical approach. The first mathematical model proposed for the optimization of the selector concentration in chiral EKC was proposed by Wren and Rowe [14, 127]. This model is based on the same equation as an earlier developed model by Stepanova and Stepanov [128] for the electrophoretic separation of cations. The model described in [14,127] allows optimization of the concentration of a chiral selector, which may result in a maximum mobility difference between the enantiomers. Although the model proposed by Wren and Rowe allows optimization of only one separation parameter, in particular the concentration of a chiral selector, among many variables, it attracts much attention from researchers, perhaps most likely due to its relative simplicity. The second reason for the wide acceptance of this model seems to be the fact that the chiral selector concentration that this model allows to optimize, represents one of the major variables in chiral EKC. Two critical points should be mentioned when applying the aforementioned model for optimization purposes in chiral EKC: (i) The maximum effective electrophoretic mobility difference between the enantiomers does not a priori mean the maximum resolution; and (ii) The model does not cover several important parameters affecting chiral EKC separations. However, this model without any doubt markedly contributed to the development of chiral EKC and good correlations between optimal chiral selector concentrations calculated based on this model and observed experimentally have been reported [129–133]. The duoselective chiral separation model proposed by Vigh and coworkers [65,134–138] in the initial form covers, besides the selector–selectand interactions, also the acid–base equilibrium of the analyte and thus also allows optimization of the pH of a buffer solution. This is a rather advanced model compared to that described in Refs [14,127]. The authors of the duoselective separation model made interesting predictions about the reversal of the enantiomer migration order based on their calculations. Although this effect in most cases may be predicted intuitively without any cumbersome calculations, the above mentioned prediction proves the correctness and the power of the model. Later


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the duoselective separation model was extended to other separation parameters [136], among them the inclusion of the effect of the EOF velocity seems to be the most important point. The authors of Refs [134–137] consider the EOF to be a nonenantioselective transport in chiral EKC. Although the mathematics is elegant as well as the examples being illustrative in the papers [134–137], we consider the EOF and the electrophoretic migration of the analyte as equal transport phenomena from the viewpoint of enantioseparations. A further advancement in mathematical models of chiral EKC was the development of a chiral charged resolving agent migration model (CHARM) by the same group [137]. This model allows prediction of several nontrivial phenomena. Many of these predictions were experimentally verified mainly by the authors’ group as well as by other research groups [138–141]. One conclusion of the CHARM model seems worth to be discussed in more detail. As concluded in several papers in this series a chiral selector possessing the highest possible charge will be advantageous for chiral EKC separations [138]. It is true that highly charged analytes in EKC commonly (but not always) migrate faster and allow less time for band broadening due to diffusion. With some approximation one may also suggest that a chiral selector with a high charge will migrate fast and result in a less diffused zone, which may favor a higher efficiency (lower band broadening) for the analyte. However, this discussion relates only to the dynamic part of a separation process. It does not address the chiral recognition part of the entire separation process. How does the charge of the chiral selector affect the selector–selectand interactions (thermodynamics and kinetics)? This remains beyond the scope of the model. However, this is an important point because there is no chiral separation in EKC without selector–selectand interactions. Zhu and Vigh extended the CHARM model by introducing three parameters as follows [142]: b ¼ KRCD =KSCD

ð9:10Þ

m0RCD =m0SCD m0RCD =m0

ð9:11Þ

s¼ a¼

ð9:12Þ

where the coefficient b represents the binding selectivity, the parameter s is the size selectivity and actually represents the electrophoretic mobility ratio of two diastereomeric complexes, and the parameter a describes how the analyte effective electrophoretic mobility is altered by complexation with a chiral selector. Analyzing Equations (9.10)–(9.12) together with mentioned Equations (9.5) and (9.6), one may easily find the similarities between them. In particular, Equations (9.10)–(9.12) use the ratio of the parameters instead of their differences in Equations (9.5) and (9.6). Thus, the coefficient b in Equation (9.10) closely relates to the term K2 K1 in Equation (9.6), the coefficient s [Equation (9.11)] relates to mc1 mc2 in Equation (9.6) and the coefficient a [Equation (9.12)] relates to mf mc in Equation (9.5). Both the analysis of Equations (9.5) and (9.6) and Equations (9.10)–(9.12) allow separate evaluation of the contribution of different factors to the overall separation factor. Although both of these approaches lead to the same principal results, Equations (9.10) to (9.12) seem to be more convenient for mathematical calculations.

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Gareil et al. [40], Surapaneni et al. [41], and Crommen and coworkers [36,42,43] have proposed mathematical models that optimize dual chiral separation systems. All of these models allow, in principle, a more or less complete description of the separation system if one suggests that the boundary conditions are correctly selected. However, the last is the bottleneck of every imaginable (mathematical) model. When developing a model, a criterion must be found allowing an estimation of the model validity. A model in an ideal case should allow effects to be predicted that are nontrivial and impossible to derive by a simple logistic or intuitive way. One of the most important requirements for a model is to be elegant, simple and understandable for most of the researchers working in the field. Thus, the scientists involved in the development of models have to consider the old wisdom: ‘One of the principal objects of theoretical research in any department of knowledge is to find the point of view from which the subject appears in its greatest simplicity’ [143].

9.9 Summary This chapter emphasizes that the vast majority of enantioseparations in CE are actually to be attributed to EKC. The major fundamental aspects of this technique are discussed from the author’s point of view. Application of chiral EKC in different areas of research is the subject of a separate chapter (Chapter 20).

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10 On-line Sample Enrichment in Electrokinetic Chromatography Joselito P. Quirino

10.1 Introduction A challenging aspect in electrokinetic chromatography (EKC) method development is that of improving the limits of detection and quantitation. In fact, EKC and other capillary electrophoresis (CE) modes suffer from poor detection sensitivity with conventional photometric detection. This problem generally arises from the low injected sample volume and from the limited optical pathlength. In application areas such as environmental trace analysis, EKC might provide a good separation of the analytes to be determined, however, a certain type of preconcentration step is often necessary in order to obtain sufficiently low limits of detection for the target analytes to be determined in real samples (e.g. lake water). Generally, preconcentration is possible in two modes: (i) off-line, i.e. preconcentration performed outside the capillary, and (ii) on-line, i.e. preconcentration performed inside the capillary. There are several off-line preconcentration methods that can be adapted to EKC, e.g. liquid-phase or solidphase extraction followed by dilution or extraction into a suitable sample matrix. From a CE scientist’s point of view, the development of an on-line preconcentration method is more interesting than the development of an off-line preconcentration method. In some cases, in order to achieve sufficient sensitivity, off-line and on-line preconcentration techniques have to be utilized simultaneously [1]. Results from on-line preconcentration are often satisfactory without the troubles associated with off-line preconcentration. Offline preconcentration is often cumbersome, time consuming and in some cases prone to systematic errors.


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Compared with other separation techniques (e.g. liquid chromatography), a wider array of on-line preconcentration techniques has been discovered and studied in CE or EKC, and perhaps a whole book may be devoted on this topic alone. This chapter will therefore focus only on on-line sample enrichment procedures employed in electrokinetic chromatography (EKC). In EKC, on-line sample enrichment techniques are based on two different principles: (i) On-line enrichment based on chromatographic retention using an immobilized stationary phase or another immobilized material that will act as an adsorptive phase; (ii) On-line enrichment based on electrokinetic effects (electrophoresis and electroosmosis). There are several approaches to performing on-line enrichment based on chromatographic retention or use of an adsorptive phase. In general, analytes are trapped and concentrated at the tip of the capillary containing the adsorptive phase. In a second step, the adsorbed analytes are eluted from the adsorptive phase and are subsequently separated by CE or EKC. For example, a hollow fiber containing a sorbent may be used to capture and enrich the analytes of interest [2]. On-line enrichment based on electrokinetic effects is caused by the change in the analyte velocity inside the capillary when passing a zone boundary, and the local change in analyte velocity causes the narrowing of zones. The extent by which the injected sample zone is narrowed can be estimated from the ratio of the initial velocity of the analyte and the velocity of the analyte during enrichment/separation. If there is a large difference between the initial and the final velocity, a high degree of preconcentration can be obtained.

10.2 Sample Stacking A widely used on-line concentration method in capillary electrophoresis is sample stacking. The enrichment phenomenon was first described by Everaerts et al. [cited in 3] observing the sharpening of charged analyte zones if the sample is prepared in a lower conductivity matrix compared with the separation electrolyte. In capillary zone electrophoresis, substantial studies done by Chien et al. [cited in 3] resulted in the understanding and development of different modes of sample stacking for charged analytes. These sample stacking modes can be easily applied to charged analytes in EKC. Sample stacking of neutral analytes with help of a pseudostationary phase was first reported by Liu et al. [cited in 3]. 10.2.1

Sample Stacking of Charged Analytes

Sample stacking is caused by the motion of sample ions across a boundary that is formed between the sample and the separation zone inside the capillary. The sample is prepared in a matrix having an electric conductivity lower than that of the separation electrolyte. A long plug of the sample solution is injected into the capillary. During the application of voltage, the low conductivity sample zone experiences a higher electric field strength compared with the separation electrolyte. Since the electrophoretic velocity is the product of the analyte effective electrophoretic mobility and the electric field strength, the electrophoretic velocity of the analyte ions in the sample zone is therefore higher than that in the separation zone. The sudden change in the velocity of the analyte ions moving

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Figure 10.1 (a) The region containing the analyte ions (not shaded) is a solution of low electric conductivity (high electric field strength) while the separation region (shaded) has a higher electric conductivity (low electric field strength). As a consequence analyte ions migrate faster in the sample than in the separation region. (b) The abrupt change in the analyte velocity when moving across the boundary results in a shortening of the analyte zone length (increase in analyte concentration). In this example the electroosmotic flow velocity is assumed to be zero. (Reprinted with permission from Ref. [3])

across the boundary between the sample and separation zone results in the narrowing of the analyte zone length. The resulting analyte zones will therefore have concentrations higher than the original concentration in the sample. The concentration effect obtainable with this technique is dependent on the ratio in the electric field strength in the sample zone and in the separation zone (see Figure 10.1). In sample stacking the length of the injected zone (linj) is narrowed by a value approximately equal to the quotient of the electric field strength in the separation zone and in the sample zone. The length of the zone after enrichment by sample stacking, lstack is given by: lstack ¼ linj ð1=gÞ, where g is the quotient of the electric field strength in the sample zone and in the separation zone. The larger is g, the higher is the increase in detection sensitivity. 10.2.1.1 Sample Stacking with Hydrodynamic Injection. Sample stacking of charged analytes in EKC can be accomplished with a single polarity voltage or with polarity switching. With single polarity voltage application, commonly known as normal polarity sample stacking, the sample prepared in a low conductivity matrix is injected hydrodynamically into the capillary. Voltage is then applied for sample stacking and separation. The volume of sample that can be loaded is limited because of zone dispersion caused by the mismatch of local electroosmotic flow velocities between the sample and separation electrolyte zones. With this technique, a tenfold increase in detection sensitivity can be achieved. In sample stacking with polarity switching, the sample is also prepared in a low conductivity matrix and injected into the capillary. The sample stacking voltage, however, is opposite to that of the separation voltage. This technique makes it possible

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to remove the low conductivity sample matrix during sample stacking and therefore minimizes the dispersive effects caused by the mismatch of local electroosmotic flow velocities. Consequently, longer sample zones can be injected. This technique is commonly called large volume sample stacking (LVSS). Better preconcentration factors (>100-fold) can be achieved compared to the normal stacking mode. In capillary electrophoresis, LVSS can be achieved without polarity switching by the use of electroosmotic flow modifiers. 10.2.1.2 Sample Stacking with Electrokinetic Injection. In sample stacking of charged analytes with electrokinetic injection, the sample is also prepared in a matrix with an electric conductivity lower than that of the separation electrolyte. Sample stacking of charged analytes with electrokinetic injection was first developed in capillary electrophoresis. In EKC, this technique is commonly called field amplified sample injection. After preparing the sample in a low conductivity matrix (e.g. water), the sample is electrokinetically injected into the capillary. The change in the electrophoretic velocity when crossing the zone boundary between the sample and the separation zone causes the narrowing of the analyte zones. Hydrodynamic injection of a very short plug of a zone of very low electric conductivity prior to sample injection improves the enrichment effect of sample stacking. A high viscosity/high conductivity plug injection prior to the low conductivity zone further improves the stacking efficiency. More than a thousand-fold improvement in detection sensitivity has been accomplished [4]. 10.2.2

Sample Stacking of Neutral Analytes

Neutral analytes do not have an electrophoretic mobility, thus are unaffected in their migration behavior by an amplified electric field. The application of sample stacking to neutral analytes in CE was therefore thought not to be possible. Pseudostationary phases in EKC, however, can provide an effective electrophoretic mobility to neutral analytes via a partitioning mechanism. Liu et al. [5] demonstrated this principle by preparing a sample solution with a matrix containing sodium dodecyl sulfate (SDS) just above the critical micelle concentration. The electric conductivity of the sample matrix was kept low (low concentration of other buffering components). The effective electrophoretic velocity of the analytes that partition into the SDS micelles is higher in the sample zone compared with the separation zone (with higher SDS concentration) due to the amplified electric field in the sample zone. Terabe’s laboratory explored the application of stacking in EKC with neutral analytes with samples of low electric conductivity both in the presence and in the absence of pseudostationary phase in the sample solution. In normal migration EKC (NM-EKC), where the (inversely directed) absolute electrophoretic velocity of the pseudostationary phase is lower than the absolute electroosmotic flow velocity, following modes have been developed: (i) normal stacking mode (NSM); (ii) reversed electrode polarity stacking mode (REPSM); and (iii) field enhanced/amplified sample stacking (FESI). In reversed migration EKC (RM-EKC), where the (inversely directed) absolute electrophoretic velocity of the pseudostationary phase is larger than the absolute electroosmotic flow velocity, (i) stacking with reverse migrating pseudostationary phase (SRMP); (ii) field enhanced sample injection with reverse migrating micelles (FESI-RMP), and (iii) stacking using a reverse migrating pseudostationary phase and a water plug (SRW) have


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been developed. Hydrodynamic (pressure) injection was used in NSM, REPSM, SRMP and SRW, while electrokinetic (voltage) injection was utilized for FESI-RMP [6]. 10.2.2.1 Normal Migration EKC Stacking Techniques 10.2.2.1.1 Normal stacking mode (NSM). Samples are prepared in water and are hydrodynamically injected as long plugs. After application of voltage, stacking and separation occurs. Pseudostationary phase enters the sample zone from the detection side, mobilizes the analytes by partitioning and stacks the mobilized neutral analytes in the rear (injection side) stacking boundary (see Figure 10.2). The stacking boundary is the zone boundary that separates the sample zone from the separation zone versus the inlet end of the capillary. Here, the extent of stacking is governed by the retention factor as well as the conductivity difference between the sample and background solution zones [7]. Similarly to stacking of charged analytes without polarity switching, the dispersive effect brought by the local electroosmotic flow mismatch causes band broadening of the stacked zones. 10.2.2.1.2 Reversed electrode polarity stacking mode (REPSM). Samples are also prepared in water as in NSM but a longer sample plug is hydrodynamically injected into the capillary. A negative polarity voltage is then applied with separation electrolyte at both ends of the capillary (see Figure 10.3). At this polarity, the sample matrix is driven out of the capillary with help of the electroosmotic flow (while in the sample zone the absolute electrophoretic velocity of the micelles (and the analyte zones) is higher than that of the electroosmotic flow), thus reducing the dispersive effects caused by the low

Figure 10.2 Enrichment of neutral analytes in the sample zone (S) and the separation zone (BGS) during stacking. (a) starting situation; (b) high-velocity micelles in S carry the neutral analytes to the opposite zone boundary B1 in the order of decreasing retention factor k(x) > k(y) > k(z); (c) neutral analytes stack in B1 into thin concentrated zones: (d) analyte zones separate by virtue of MEKC. (Reprinted with permission from Ref. [7])

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Figure 10.3 Behavior of micelles and neutral analytes during REPSM MEKC. (a) Starting situation; (b) micelles enter the capillary and carry neutral analytes to the opposite zone boundary, k(ax) > k(ay) > k(az); (c) micelles and neutral analytes stack at the zone boundary B1, polarity is switched to positive; (d) separation of zones by virtue of MEKC. (Reproduced with permission from Ref. [8])

conductivity sample matrix. The current is monitored and once 97 to 99 % of the original current is reached, the polarity is switched to normal/positive. The stacked analyte zones are then separated and carried to the detector by virtue of NM–EKC (see Figure 10.3). Removal of the sample matrix at negative polarity allows for a much longer volume of sample that can be injected into the capillary resulting in improved sensitivity enhancements [8]. The polarity-switching step, however can lead to irreproducibility problems due to the varying amounts of sample solution that can remain inside the capillary after stacking at negative polarity. 10.2.2.1.3 Field enhanced sample injection (FESI). The sample is prepared in a matrix containing a low concentration of pseudostationary phase and low concentrations of buffer components (low electric conductivity). A water plug is injected into the capillary initially filled completely with separation electrolyte. Sample components that partition into the pseudostationary phase are electrokinetically injected at negative polarity. Injection is stopped when the current reaches 97 to 99 % of the original value. The vial with sample is replaced by a vial with separation buffer at the injection end and voltage is now applied at normal polarity for separation and detection (see Figure 10.4). Only high molecular mass surfactants (polymeric stationary phases) were successfully applied for this technique [9]. As a second prerequisite, the analytes to be enriched and determined must have sufficiently high retention factors. Reproducibility is also an issue with this mode of stacking.


213

Figure 10.4 Behavior of micelles and neutral analytes during FESI–MEKC. (a) initial situation (water plug, unshaded; BGS, shaded); (b) micelles enter the capillary and carry with them neutral analytes emanating from the cathodic vial, k(x) > k(y) > k(z); (c) micelles and neutral analytes stack at the concentration boundary, voltage is cut and the sample vial is replaced by another BGS vial when the measured current is approximately 97–99 % of the predetermined current, voltage is then applied at positive polarity; (d) separation of zones occurs. (Reproduced with permission from Ref. [9])

10.2.2.2 Reversed Migration EKC Stacking Techniques. The techniques described here were initially developed using a low pH background buffer (e.g. phosphate buffer) containing a micellar pseudostationary phase obtained with sodium dodecyl sulfate (SDS). The reduction of the zeta potential at the capillary walls due to the low pH makes it possible to reduce the velocity of the electroosmotic flow to the extent that the (inversely directed) absolute electrophoretic velocity of the pseudostationary phase is higher than the absolute electroosmotic flow velocity. 10.2.2.2.1 Stacking with reverse migrating pseudostationary phase (SRMP) The sample is prepared in a low conductivity matrix, preferably water, and hydrodynamically injected into the fused silica capillary as a long plug. The separation electrolyte consists of an anionic pseudostationary phase (e.g. SDS) and a buffer at low pH. The application of voltage at reversed polarity with separation electrolyte at both ends of the capillary results in the stacking and removal of the sample matrix (see Figure 10.5). The presence of a low conductivity sample matrix inside the capillary increases the bulk electroosmotic flow of the liquid inside the capillary. However, the effective electrophoretic velocity of the analytes that are picked up by the fast moving pseudostationary phase is still higher than the bulk electroosmotic flow velocity. The picking of the analytes by the entering pseudostationary phase will be mentioned again in the section on

214


Figure 10.5 Evolution of micelles and neutral analytes in the sample solution (S) zone and separation electrolyte (BGS) zone during and after stacking at acidic pH: (a) starting situation; (b) high-velocity micelles in the S zone emanating from the cathodic vial carry the neutral analytes to the concentration boundary B1 in the order of decreasing retention factor k(ax) > k(ay) > k(az); (c) neutral analytes after stacking leave B1 prior to the removal of the sample matrix due to electrophoresis in the BGS zone; (d) neutral analyte zones migrate towards the detector and continue to separate. Shaded parts indicate the presence of micelles. (Reproduced with permission from Ref. [10])

sweeping under an enhanced electric field. As the sample matrix is removed, the bulk electroosmotic flow becomes very small and the focused analyte zones concentrated at the interface between the sample and separation zones are separated and driven to the detection window. No polarity switching is involved to remove the sample matrix, resulting in significantly better reproducibility [10]. Instability of SDS solutions at low pH should be taken into account when storing such solutions. 10.2.2.2.2 Field enhanced sample injection with reverse migrating pseudostationary phase (FESI–RMP). The sample is prepared in a low conductivity matrix containing a low concentration of a pseudostationary phase and low concentrations of buffer components. The capillary is completely filled with the separation electrolyte and a short water plug is hydrodynamically injected to provide field amplification during subsequent electrokinetic injection of the sample at negative polarity. This technique is similar to FESI except that the mode of EKC here is with reverse migrating pseudostationary phase and no polarity switching is involved (see Figure 10.6). After electrokinetic injection, the sample vial is replaced with a vial containing the separation electrolyte when 70–90 % of the original current is reached. The percentage of original current is


215

detector x x x y y z y x y z z z x z y

(a)

(b)

z

x

B

y

water plug

BGS

B x y y y zz x x y x z x x x y z y x z y x x z y xx z y x x z x z z x B

(c)

xx yy y x zz

(d) az

ay

ax

Figure 10.6 Evolution of micelles and neutral analytes in the water plug and separation electrolyte (BGS) zone during and after FESI-RMM. (a) hydrodynamic injection of water after conditioning the capillary with BGS; (b) electrokinetic injection of neutral analytes prepared in a micellar matrix (shading part of the water plug indicates the presence of micelles; neutral analytes mobilized by these micelles enter the water plug in the order of decreasing retention factor k(ax) > k(ay) > k(az)); (c) voltage is shut, the sample vial is replaced by another BGS vial and voltage is applied at negative polarity again, neutral analytes stack at the zone boundary B; (d) focused bands separate by virtue of MEKC. (Reproduced with permission from Ref. [11])

determined experimentally and varies with the kind of sample to be analyzed. It has been verified experimentally that SDS can be employed as pseudostationary phase when applying FESI–RMP [11]. 10.2.2.2.3 Stacking using reverse migrating pseudostationary phase and a water plug (SRW). The sample is prepared in a matrix containing a low concentration of a pseudostationary phase and low concentrations of buffer components. The concentration of the pseudostationary phase (e.g. SDS) must be above the critical micelle concentration. A water plug is first injected into the capillary initially filled completely with separation electrolyte. The sample solution is then injected hydrodynamically. Voltage is applied at reversed polarity. Due to the amplified electric field strength in the low conductivity sample zone, the mobilized analytes migrate fast into the water zone. In the water zone, the velocity of the mobilized analytes is accelerated further because this zone has a higher electric field strength. This acceleration results in an improved stacking efficiency at the boundary between the water zone and the separation electrolyte [12]

216

ELECTROKINETIC CHROMATOGRAPHY detector

B2 x z x x x y z x x

S

(a)

B1

y

B2

B1

z

z

y y

z z

(b)

BGS

water plug

y x y z x

y

x x x x y x

B1

(c) az ay ax

(d) az

ay

ax

Figure 10.7 Evolution of micelles and neutral analytes in the water zone, sample solution (S) and separation electrolyte (BGS) zones during SRW-MEKC analysis. (a) Hydrodynamic injection of water followed by sample solution (S) after conditioning the capillary with BGS (shaded parts indicate the presence of micelles); (b) application of voltage at negative polarity with the BGS in the inlet and outlet vials (neutral analytes mobilized by the micelles enter the water zone and stack in the zone boundary B1 in the order of decreasing retention factor k(ax) > k(ay) > k(az)); (c) separation of stacked zones prior to the total removal of the low conductivity zones; (d) focused bands separate by virtue of MEKC. (Reproduced with permission from Ref. [12])

(see Figure 10.7). At reversed polarity, similar to SRMP, the sample matrix as well as the water plug is removed by the action of the bulk electroosmotic flow.

10.3 Sweeping The mechanism of analyte focusing in sweeping relies on partitioning or complexation. Sweeping occurs when the analyte zone without the pseudostationary phase traverses a pseudostationary phase zone. It is a universal technique since it is both applicable for neutral and charged analytes. More than 5000-fold enrichments have been reported for this technique. Discussion here will be based on the nature of the analyte, neutral or charged, and the strength of the electric field in the sample zone: lower, similar, or higher electric field strength compared with the background solution. Sweeping occurs whenever the sample matrix is devoid of the pseudostationary phase used in the background solution. An anionic pseudostationary phase will be used as an example in most of the discussions. Sweeping of charged analytes with an uncharged or nonionic pseudostationary phase will also be given.


10.3.1

217

Neutral Analytes

The first paper on sweeping showed the exceptional narrowing of neutral analyte zones in EKC at constant electric field strength [13]. Sweeping, in theory, provides unlimited increase in detection sensitivity. The concentration effect works well for all analytes with great affinities towards the pseudostationary phase (high retention factors). Sweeping in EKC is defined as the picking and accumulating of analytes by the pseudostationary phase that fills the sample zone during the application of voltage. It can be compared to a broom (pseudostationary phase) that carefully carries along grains of rice (analytes) scattered on the floor. The absolute difference between the initial velocity and the final velocity is dependent on the retention factor. For neutral analytes, the electrophoretic velocity shoots from zero to a value dictated by the affinity of the analyte towards the pseudostationary phase (the retention factor). For charged analytes, the electrophoretic velocity shifts from the electrophoretic velocity of the ‘free’ ion/acid/base to the effective electrophoretic velocity, which is dependent on the interaction of the (partially) charged analyte with the pseudostationary phase. It will be shown that the preconcentration effect obtainable by sweeping of analytes is mainly dependent on the retention factor. 10.3.1.1 Sweeping of Neutral Analytes in a Zero Electroosmotic Flow Environment. Figure 10.8 is an example to show the mechanism of sample preconcentration by sweeping, the conditions use an anionic micelle in a zero electroosmotic flow environment. The analytes are neutral and are prepared in a matrix with the same conductivity as the background solution (BGS). If a sample solution (S) is injected into the capillary tube [Figure 10.8(a)], SDS micelles from the BGS (cathode) will enter the S zone upon application of voltage and pick and accumulate (sweep) neutral analytes into concentrated zones [Figures 10.8(b) and (c)]. The last step is the separation of the narrowed zones. The concentration of the SDS micelles entering the S zone is assumed to be similar to the concentration of the micelles in the BGS zone. Also, the retention factors k in the S zone are assumed to be similar to the retention factors in the BGS zone. When the front of micelles that entered the S zone reaches the boundary between the S and BGS (I) [see Figure 10.8(c)], the process of sweeping stops. Note that micelles enter S from the injector end of the sample plug. The length of the swept zones (lsweep) is given by: lsweep ¼ dðmcÞ dðaÞ

ð10:1Þ

d(mc) is the traveled distance of the front of micelles, which is identical to the length of the zone injected (linj) and d(a) is the traveled distance of the rear front of the analyte zone, which is identical to linj multiplied with the factor k=(k þ 1). Therefore, lsweep can be calculated from k and linj [12]: lsweep ¼ linj ð1=1 þ kÞ

ð10:2Þ

Equation (10.2) reveals that at a fixed injection length, the swept zones of analytes of a high retention factor must be narrower than the swept zones of analytes with a lower retention factor. This dependence is illustrated in Figures 10.8(b) and (c).

218


Figure 10.8 Evolution of analyte zones in EKC under sweeping conditions (suppressed EOF). (a) Starting situation. Injection of sample solution S with length linj after conditioning the capillary with BGS (found at both electrode vials). (b) Micelles from the cathodic vial enter the S zone or capillary (mc) and sweep the analytes into narrower bands depending on the retention factor (ka1 > ka2, a1 and a2, respectively). (c) The front of micelles that entered the S zone reaches the boundary between S and BGS zones (I). (d) Separation of zones based on MEKC; other symbols, analytes (a1, a2), length of capillary (L). (Reproduced with permission from Ref. [13])

10.3.1.2 Sweeping of Neutral Analytes in a High Electroosmotic Flow Environment. Figure 10.9 shows the narrowing of a sample zone due to sweeping in the presence of a high electroosmotic flow velocity. Here the absolute electroosmotic flow velocity is higher than the (inversely directed) absolute electrophoretic velocity of the pseudostationary phase. The process of sweeping is completed when the front of micelles which entered the sample zone reaches the injector end of the sample zone (see Figure 10.9). ð10:3Þ lsweep ¼ dðac Þ dðmcc Þ d(mc) is the traveled distance of the front of micelles and dðac Þ is the traveled distance of the front of the analyte zone (versus detection end). Here the micelles enter S from the detector end of the sample zone [14]. dðac Þ ¼ ðvep ðaÞ þ veof Þtsweep

ð10:4Þ

dðmcc Þ ¼ ðvep ðmcÞ þ veof Þtsweep

ð10:5Þ

ON-LINE SAMPLE ENRICHMENT IN ELECTROKINETIC CHROMATOGRAPHY mca

mcc S Iinj

(a)

mcc

+

– aa

ac mcc

mca (c)

BGS

ac

mca (b)

to detector

EOF

aa

219

+

–

Isweep aa d(mcc)

ac

d(ac)

Figure 10.9 Evolution of micelles and neutral analytes during sweeping in the presence of an electroosmotic flow with high velocity. (a) Starting situation, injection of S prepared in a matrix void of pseudostationary phase having a conductivity similar to that of the BGS; (b) application of voltage at positive polarity, micelles emanating from the cathodic side sweeping analyte molecules; (c) the injected analyte zone is assumed to be completely swept. Other symbols and explanations in the text. (Reproduced with permission from Ref. [14])

vep ðaÞ is the effective electrophoretic velocity of analyte a, veof is the electroosmotic velocity, tsweep is the time when aa reaches mcc, and vep(mc) is the electrophoretic velocity of the micelles. vep ðaÞ ¼ ðk=ð1 þ kÞÞmep ðmcÞE veof ¼ meof E tsweep ¼ linj =ðveof vmc Þ vep ðmcÞ ¼ mep ðmcÞE

ð10:6Þ ð10:7Þ ð10:8Þ ð10:9Þ

mep(mc) is the electrophoretic mobility of the micelle, E is the electric field strength, and meof is the electroosomotic mobility. Replacing the variables in Equation (10.3) with expressions developed in Equation (10.4–10.9) results in Equation (10.2). Consequently, the process of sweeping is independent of the presence or absence of bulk electroosmotic flow, if sweeping has been completed before the relevant zones reach the detector. Equation (10.2) is also applicable to systems with low electroosmotic flow, where the absolute electroosmotic velocity is lower than the (inversely directed) absolute pseudostationary phase velocity [14].

220

10.3.2


Charged Analytes

10.3.2.1 Sweeping of Charged Analytes with a Charged Pseudostationary Phase. For a charged analyte a0 and a separation electrolyte containing a charged pseudostationary phase, the following approach is valid: lsweep ¼ dðmcÞ dða0 Þ

ð10:10Þ

The pseudostationary phase and the analytes can be negatively or positively charged. For the charged analyte, the distance traveled d(a0 ) is affected by two electrophoretic velocities, the electrophoretic velocity of the ‘free compound’ in the sample zone and the effective electrophoretic velocity resulting from interaction with the (charged) pseudostationary phase. Unlike a neutral analyte that has an electrophoretic velocity of zero, a charged analyte has an electrophoretic velocity equal to the electrophoretic mobility multiplied by the electric field strength. Once the analyte enters the pseudostationary phase zone, the resulting velocity (effective electrophoretic velocity) is affected by the electrophoretic mobility of the ‘free compound’, the electrophoretic mobility of the micellar phase, the retention factor, and possibly ion pair interactions with the nonaggregated dissolved surfactant ions (see first chapter of this book). 10.3.2.2 Sweeping of Charged Analytes with an Uncharged or Nonionic Pseudostationary Phase. Figure 10.10 shows the sweeping of a negatively charged solute, a0 , in MEKC using a nonionic pseudostationary phase. In this example the (inversely directed) absolute electroosmotic velocity is higher than the absolute effective electrophoretic velocity of the analytes. In Figure 10.10 (a), the shaded area S is a long

Figure 10.10 Sweeping of a negatively charged analyte in electrokinetic chromatography with a neutral pseudostationary phase. (Reproduced with permission from Ref. [15])


221

injection zone of sample prepared in a matrix having an electric conductivity identical to that of the BGS but devoid of the nonionic pseudostationary phase. Typical MEKC analysis [Figures 10.10(b)–10(d)] is performed after hydrodynamic injection of this sample. When the charged analytes enter the nonionic pseudostationary phase zone, they are reduced in velocity by the pseudostationary phase and form zones of higher concentration than in the injected sample solution [Figure 10.10(b)]. When crossing the zone boundary, the effective electrophoretic mobility of the analyte zone front drops 1 ep ða0 Þ. This process can be seen in analogy to a sample zone which is immediately to 1þk injected on top of a chromatographic separation column filled with stationary phase and is enriched at the column head dependent on the retention factor of the solutes in the sample solution (acting as mobile phase). The reduction in lsweep can also be described by Equation (10.2). 10.3.3

Sweeping in a Low Conductivity Zone

Here the discussion will be based on the sweeping of neutral analytes in a low conductivity sample zone devoid of the pseudostationary phase used. Figure 10.11 shows the focusing of neutral analyte zones prepared in a low conductivity matrix. In

Figure 10.11 Sweeping in an enhanced electric field. Evolution of the zone of a neutral analyte in EKC using a negatively charged PS and a zero EOF environment. (a) Starting situation, a longer than typical injection of sample solution (S) prepared in a matrix having a conductivity lower than that of the micellar background solution (BGS). (b) Application of voltage with the cathode at the inlet end and the anode at the outlet end; the capillary is dipped into two reservoirs filled with the BGS; PS enters the S zone at a lower concentration compared to the BGS; PS sweeps (concentrates) the analyte molecules. (c) The final swept zone is formed when the PS completely fills the S zone. (d) PS stacks or focuses at the initial boundary between the S and BGS zones; stacking of PS causes an additional focusing of the swept analyte zone. (Reproduced with permission from Ref. [17])

222


Figure 10.12 Peak shapes obtained from sweeping alone (a) and a combination of sweeping and sample stacking (b). Sample matrix, phosphoric acid solution having a conductivity similar to the separation buffer (a), water (b); injected lengths, 2.56 cm; identification of peaks, 2,3,5trimethylphenol(1), 4-ethylphenol (2), 3-chlorophenol (3), 2-chlorophenol (4), 4-methylphenol (5), 2-methylphenol (6), 4-nitrophenol (7), 2-fluorophenol (8), phenol (9); concentration of analytes in sample approx. 5 mg L1, separation buffer 50 mM SDS in 50 mM phosphoric acid (pH 1.9); applied voltage 20 kV. (Reproduced with permission from Ref. [16])

summary, the cumulative effect of sweeping and sample stacking narrows the length of the analyte zones [15,16]. Analytes with low to moderate retention factors are concentrated more effectively when prepared in a low conductivity matrix as compared with preparation in high conductivity matrices. This is demonstrated in Figure 10.12. Peaks 1 to 7 are due to analytes having a low to moderate retention factor. 10.3.4

Sweeping in a High Conductivity Zone

The discussion will be based on the sweeping of neutral analytes in a high conductivity sample zone without the pseudostationary phase used. There are three important processes, first is the stacking of the pseudostationary phase between the separation zone and the higher conductivity sample zone. Second is the sweeping of the neutral analytes by the stacked pseudostationary phase. Third is the destacking of the pseudostationary phase at the other boundary that separates the sample and separation zones [17,18]. In Figure 10.13 a scheme of the evolution of analyte zones is depicted for a sample prepared in a matrix devoid of the pseudostationary phase and having an electric conductivity higher than that of the separation electrolyte.


223

Figure 10.13 Sweeping of a neutral analyte in a reduced electric field. Evolution of an analyte zone in EKC using a negatively charged PS and a zero EOF environment. (a) Starting situation, a longer than typical injection of sample solution (S) prepared in a matrix having a conductivity value higher than the micellar background solution (BGS). (b) Application of a voltage with the cathode at the inlet end and the anode at the outlet end; the capillary is dipped in two reservoirs filled with the BGS, PS enters and stacks at the S zone, stacked PS sweeps (concentrates) the analyte molecules. (c) The final swept zone is formed when the stacked PS completely fills the S zone. (d) Stacked PS destacks at the initial boundary between the S and BGS zones; destacking of PS causes broadening of the swept analyte zone. (Reproduced with permission from Ref. [18])

The stacking of the pseudostationary phase provides locally higher retention factors for the analytes to be concentrated because of the increase in the concentration of the pseudostationary phase. This increase in retention factors in the sweeping zone results in narrower swept zones (compared with conditions with a sample solution having an electric conductivity identical to that of the separation buffer). However, subsequent destacking of the pseudostationary phase (when crossing the second boundary) causes, in a second step, an increase in the length of the swept zones. The stacking and destacking of the pseudostationary phase is visualized experimentally in Figure 10.14 [18] employing UV absorbing micelles and UV detection. The combined effects of stacking and destacking of the pseudostationary phase result in on-line enrichment factors virtually identical to those that are obtained with samples prepared in a matrix having an electric conductivity similar to that of the separation electrolyte [18]. 10.3.5 Improving Preconcentration by Sweeping via Manipulation of Retention Factors As described by Equation (10.2), increasing the retention factors of the analytes during the process of sweeping will improve the enrichment factor. There are several

224



225

Figure 10.15 Conventional MEKC and sweeping MEKC of naphthalenesulfonic acids using a separation electrolyte containing SDS and ion pair reagents. BGS, 80 mM SDS in 20 mM borate–phosphate buffer (pH 9.0) (a, b) containing (c) 20 mM tetrabutylammonium chloride, (d) 20 mM tetrapentylammonium chloride; sample solution: (a) BGS, (b–d) borate– phosphate buffer (pH 9.0) with a conductivity similar to that of the BGS; concentration of samples: (a) 1-naphthalenesulfonic acid (peak 1, 100 ppm), 1,5-naphthalenedisulfonic acid (peak 2, 100 ppm); (b–d) 100-fold dilution of samples employed in (a); injection time: (a) 1 s, (b–d) 80 s; voltage, þ25 kV; S, system peak. (Reproduced with permission from Ref. [19])

possibilities to increase the retention factor during the process of sweeping. One possibility is simply to increase the concentration of the pseudostationary phase. Another approach is the use of ion pairing agents that will increase the partitioning coefficients between the aqueous and the pseudostationary phase. In Figure 10.15 chromatograms

3————————————————————————————— Figure 10.14 Visualization of the stacking and destacking processes taking place at zone boundaries obtained from pressure-driven mobilization of the zones at different times after the application of voltage (UV absorbing micelles, UV detection). Schematic description of the experimental setup (a); concentration profiles obtained (b). Conditions in (b): nonmicellar BGS (1), ammonium phosphate buffer at pH 8.8 (5.9 mS/cm); nonmicellar BGS (2), ammonium phosphate buffer at pH 8.8 (15.2 mS/cm); micellar BGS, 15 mM glycyrrhizic acid in 12.5 mM ammonium phosphate at pH 8.8 (5.9 mS/cm); length of pertinent zones, nonmicellar BGS (2), approx. 6.6 cm, micellar BGS, approx.13.2 cm; time for application of voltage at 17 kV, 0 s (I), 120 s (II), 300 s (III); applied pressure for mobilization of zones, 50 mbar towards the detector. (Reproduced with permission from Ref. [18])

226


with conventional and with long plug injections (sweeping) with and without the addition of an ion-pairing reagent to the separation electrolyte are shown. It can be clearly seen that the addition of an ion-pairing reagent improved the sweeping efficiency for the test analytes investigated.

10.4 Field Amplified Sample Injection Combined with Sweeping Field amplified sample injection provides the best enhancements in detection sensitivity for charged analytes by sample stacking. As discussed earlier, sweeping is applicable to both neutral and charged analytes. A sample injection procedure, which combines field amplified sample injection and sweeping enrichment methods thus can be expected to offer a very powerful tool for the preconcentration of charged analytes [20–22]. Extreme enrichment factors by combining field amplified injection and sweeping were first achieved for cations. The main idea behind this procedure is to introduce selectively by field amplified sample injection (or field enhanced sample injection) a large portion of the cationic analyte from a very dilute sample solution and focus the resulting (broad) sample zone by subsequent sweeping. Approaching a million-fold increase in sensitivity has been achieved with this combination, termed as cation selective exhaustive injectionsweeping-EKC [20]. The evolution of zones in cation selective exhaustive injectionsweeping-EKC (CSEI-sweep-EKC) is shown in Figure 10.16. The electroosmotic flow was largely reduced by using a low pH buffer. SDS micelles were employed as the pseudostationary phase. A fairly similar approach was achieved for anions, termed as anion selective exhaustive injection-sweeping-EKC. Kim et al. [21] employed a capillary that was coated with polyacrylamide to suppress the electroosmotic flow. A cationic surfactant was used as pseudostationary phase. More than thousand-fold improvements in detection sensitivity were achieved. Zhu et al. [22] used SDS in a low pH buffer to suppress the electroosmotic flow. At the pH boundary between the water plug and the separation electrolyte, the anionic analytes injected during field amplified sample injection are neutralized forming a focused zone. The analytes are subsequently focused in a second step by sample stacking at the boundary between the water plug and the separation electrolyte. In a third step, sweeping and separation were obtained by the application of voltage with both ends of the capillary immersed in vials filled with the separation electrolyte. Around a hundred-thousandfold improvement in detection sensitivity was reported [22].

10.5 pH Junction Combined with Sweeping Britz–McKibbin et al. [23] employed a combination of dynamic pH junction and sweeping with a sample having a pH different from the pH of the separation electrolyte (dynamic pH junction condition) and being devoid of the pseudostationary phase SDS (sweeping condition). There is a similarity with the method reported by Zhu et al. [22] except that in the latter procedure the sample had been electrokinetically injected by field amplified sample stacking into a water plug. In the work reported by Britz–McKibbin


227

Figure 10.16 Evolution of analyte zones in CSEI-sweep-MEKC: (a) starting situation, conditioning of the capillary with a nonmicellar background buffer, injection of a highconductivity buffer void of organic solvent, and injection of a short water plug; (b) electrokinetic injection at positive polarity (FESI) of cationic analytes prepared in a lowconductivity matrix or water, nonmicellar background buffer found in the outlet end, cationic analytes focus or stack at the interface between the water zone and high-conductivity buffer zone; (c) injection is stopped and vials containing a micellar separation electrolyte are placed at both ends of the capillary; (d) application of voltage at negative polarity causes the entry of micelles from the cathodic vial into the capillary and sweeps the already stacked analyte zones to narrower bands; (e) separation of zones based on MEKC. (Reproduced with permission from Ref. [20])

et al. [23], however, classical sample stacking was not applied because of the high salt content of the sample. For the flavin test solutes studied by Britz–McKibbin et al., the pH of the separation electrolyte and the pH of the sample, borate complexation, and SDS concentration in the separation electrolyte were the most important parameters influencing focusing. A more than fourfold enhancement in the band narrowing of solute zones was achieved by dynamic pH junction sweeping compared to either sweeping or dynamic pH junction formats alone. Figure 10.17 compares focusing by exclusively sweeping and by the combination of dynamic pH junction with sweeping. By combination with LIF detection

228


Figure 10.17 Two electropherograms comparing the focusing obtained using large injection plugs (8.2 cm) with (a) conventional sweeping and (b) dynamic pH junction combined with sweeping. The separation electrolyte used in both electropherograms was 140 mM borate, 100 mM SDS, pH 8.5. Sample solutions contained 0.2 mM of each flavin coenzyme dissolved in (a) 140 mM borate, pH 8.5, and (b) 75 mM phosphate, pH 6.0. (Reproduced with permission from Ref. [23])

a LOD of about 4.0 pM for the flavin coenzymes, FAD and FMN, was realized with acceptable reproducibility.

10.6 Applications On-line enrichment techniques make it possible to perform trace analysis by EKC. Only a few examples of applications being developed so far will be discussed in this section. Nunez et al. [24] report the use of cation selective exhaustive injection sweeping–MEKC for the determination of three herbicides (paraquat, diquat, and difenzoquat) in spiked tap water in concentrations below the levels established by the US Environmental Protection Agency. Carabias-Martinez et al. [1] report the combination of SPE and sweeping for the multiresidue determination of 13 compounds in natural water samples with detection limits at levels established by current legislation in Spain. Yan et al. [25] employed sweeping for the determination of nateglinide (novel oral mealtime glucose regulator) with improved detection limits in animal body fluids (see Figure 10.18). Wang et al. [26] applied FESI-RMP for the determination of flavonoids in Epimedium brevicornum. A 40–360-fold improvement in detection limits was obtained. On-line


229

Figure 10.18 Electropherogram of nateglinide in plasma: (a) blank plasma sample; (b) quality control standard (0.5 mg/L); (c) plasma sample 4.0 h post administration of 5 mg nateglinide (peak 1, nateglinide). Experimental conditions: buffer solution (16 mmol/L NaH2PO4 þ 6 mmol/L Na2B4O7 þ 60 mmol/L SDS, pH 7.14); applied voltage 21 kV, 60 cm/75 mm; effective length 52 cm; UV detection wavelength 214 nm. (Reproduced with permission from Ref. [25])

230


enrichment techniques have proven to be useful in many application areas of EKC such as pharmaceutical, toxicological and phytochemical analysis.

References ´ lvarez. [1] R. Carabias-Martıńez, E. Rodrı´guez-Gonzalo, P. Revilla-Ruiz and J. Domıńguez-A Solid-phase extraction and sample stacking–micellar electrokinetic capillary chromatography for the determination of multiresidues of herbicides and metabolites, J. Chromatogr. A., 990, 291–302 (2003). [2] R. Zhang and S. Hjerten. A micromethod for concentration and desalting utilizing a hollow fiber, with special reference to capillary electrophoresis, Anal. Chem., 69, 1585–1592 (1997). [3] J.P. Quirino and S. Terabe. Sample stacking of cationic and anionic analytes in capillary electrophoresis, J. Chromatogr. A., 902, 119–135 (2000) and references cited therein. [4] C.-X. Zhang and W. Thormann. Head-column field-amplified sample stacking in binary system capillary electrophoresis: a robust approach providing over 1000-fold sensitivity enhancement, Anal. Chem., 68, 2523–2532 (1996). [5] Z. Liu, P. Sam, S.R. Sirimanne, P.C. McClure, J. Grainger and D.G. Patterson. Field-amplified sample stacking in micellar electrokinetic chromatography for on-column sample concentration of neutral molecules, J. Chromatogr. A., 673, 125–132 (1994). [6] J.P. Quirino and S. Terabe. Stacking of neutral analytes in micellar electrokinetic chromatography, J. Cap. Electrophoresis, 4, 233–245 (1997). [7] J.P. Quirino and S. Terabe. On-line concentration of neutral analytes for micellar electrokinetic chromatography: I. Normal stacking mode, J. Chromatogr. A., 781, 119–128 (1997). [8] J.P. Quirino and S. Terabe. On-line concentration of neutral analytes for micellar electrokinetic chromatography: II. Reversed electrode polarity stacking mode, J. Chromatogr. A., 791, 255–267 (1997). [9] J. P. Quirino and S. Terabe. On-line concentration of neutral analytes for micellar electrokinetic chromatography: IV. Field-enhanced sample injection, J. Chromatogr. A., 798, 251–257 (1998). [10] J.P. Quirino and S. Terabe. On-line concentration of neutral analytes for micellar electrokinetic chromatography: 3. Stacking with reverse migrating micelles, Anal. Chem. 70, 149–157 (1998). [11] J.P. Quirino and S. Terabe. On-line concentration of neutral analytes for micellar electrokinetic chromatography: 5. Field-enhanced sample injection with reverse migrating micelles, Anal. Chem., 70, 1893–1901 (1998). [12] J.P. Quirino, K. Otsuka and S. Terabe. On-line concentration of neutral analytes for micellar electrokinetic chromatography: VI. Stacking using reverse migrating micelles and a water plug, J. Chromatogr. B., 714, 29–38 (1998). [13] J.P. Quirino and S. Terabe. Exceeding 5000-fold concentration of dilute analytes in micellar electrokinetic chromatography, Science, 282, 465–468 (1998). [14] J.P. Quirino and S. Terabe. Sweeping of analyte zones in electrokinetic chromatography, Anal. Chem., 71, 1638–1644 (1999). [15] M. R. N. Monton, J. P. Quirino, K. Otsuka and S. Terabe. Separation and on-line preconcentration by sweeping of charged analytes in electrokinetic chromatography with nonionic micelles, J. Chromatogr. A., 939, 99–108 (2001). [16] J.P. Quirino and S. Terabe. Sweeping with an enhanced electric field of neutral analyte zones in electrokinetic chromatography, J. High Res. Chromatogr., 22, 367–372 (1999).


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[17] J.P. Quirino and S. Terabe. Sweeping: concentration mechanism and applications to highsensitivity analysis in capillary electrophoresis, J. Chromatogr. A., 965, 357–373 (2002). [18] J.P. Quirino, S. Terabe and P. Bocek. Sweeping of neutral analytes in electrokinetic chromatography with high-salt-containing matrixes, Anal. Chem., 71, 1934–1940 (2000). [19] J.-B. Kim, K. Otsuka and S. Terabe. On-line sample preconcentration in micellar electrokinetic chromatography using ion-pair reagents, J. Chromatogr. A., 979, 131–136 (2002). [20] J.P. Quirino and S. Terabe. Approaching a million-fold sensitivity increase in capillary electrophoresis with direct ultraviolet detection: cation-selective exhaustive injection and sweeping, Anal. Chem., 72, 1023–1030 (2000). [21] J.-B. Kim, K. Otsuka and S. Terabe. Anion selective exhaustive injection-sweep–micellar electrokinetic chromatography, J. Chromatogr. A., 932, 129–137 (2001). [22] L. Zhu, C. Tu, and H.K. Lee. On-line concentration of acidic compounds by anion-selective exhaustive injection-sweeping-micellar electrokinetic chromatography, Anal. Chem., 74, 5820–5825 (2002). [23] P. Britz-McKibbin, K. Otsuka, and S. Terabe. On-line focusing of flavin derivatives using dynamic pH junction-sweeping capillary electrophoresis with laser-induced fluorescence detection, Anal. Chem., 74, 3736–3743 (2002). [24] O. Nunez, J.-B. Kin, E. Moyano, M.T. Galceran and S. Terabe. Analysis of the herbicides paraquat, diquat and difenzoquat in drinking water by micellar electrokinetic chromatography using sweeping and cation selective exhaustive injection, J. Chromatogr. A., 961, 65–75 (2002). [25] H. Yan, G. Yang, F. Qiao and Y. Chen. Determination of nateglinide in animal plasma by micellar electrokinetic chromatography and on-line sweeping technique, J. Pharm. Biomedical Anal., 36, 169–174 (2004). [26] S. Wang, Y. Wu, Y. Ju, X. Chen, W. Zheng and Z. Hu. On-line concentration by field-enhanced sample injection with reverse migrating micelles in micellar electrokinetic capillary chromatography for the analysis of flavonoids in Epimedium brevicornum Maxim, J. Chromatogr. A., 1017, 27–34 (2003).

Part II Instrumentation


11 General Aspects of Instrumentation Jan Fischer and Pavel Jandera

11.1 Introduction Although introduced by Hjerteń as early as in late 1950s [1], electrophoretic separation methods in free solutions did not find widespread use for a long time, because of practical difficulties. The available commercial equipment employed a complicated electromechanical system with a rotating tube along its longitudal axis as separation channel. The pioneering work of Jorgenson and Lukacs in the early 1980s brought a major breakthrough in electromigration separation techniques by introducing open glass capillaries with i.d. less than 100 mm as the separation media and a relatively simple electrokinetic injection technique for nanoliter sample volume introduction [2–5]. Narrow bore capillaries permit application of high voltages because of improved dissipation of Joule heat, and reduced band broadening by diminishing convective effects. The invention of capillary zone electrophoresis (CZE) allowed the utilization of great separation efficiency of electromigration separations. Electrokinetic chromatography (EKC) employs the experimental technique of capillary zone electrophoresis. The main difference consists in employing working buffers which contain, in addition to buffers used in CZE, a pseudostationary phase additive. Using charged micelles, microemulsions or cyclodextrins as the pseudostationary phase into which analytes penetrate by partitioning process, the scope of electromigration separation techniques was largely broadened by allowing separation of noncharged compounds.


236


Figure 11.1 Basic scheme of the instrumentation for capillary electrophoresis. 1, 2, vials with background electrolytes; 3, sample vial(s); 4, 5, electrodes; 6, separation capillary; 7, high voltage power supply (HVPS); 8, detector (D); 9, computer (PC)

11.2 Basic Instrumental Set-up for Electrokinetic Chromatography The basic instrumentation for electrokinetic chromatography (EKC) is the same as in capillary zone electrophoresis (CZE) and is shown schematically in Figure 11.1. It consists of a separation capillary (mostly made of fused silica) with each end immersed in a vial filled with the running buffer, i.e. a current leading background electrolyte. In each vial, an electrode is placed, connected to a high voltage power source (HVPS). The sample is introduced into the separation capillary at the ‘injection end’ using electrokinetic, siphoning or overpressure methods of injection. The migrating zones of the sample are detected at the ‘detector end’ of the separation capillary by an appropriate detector (D). The detection technique employed depends on the nature and concentration of the compounds separated. Most frequently, UV–VIS spectrophotometric detection is used because of its relative simplicity. Fluorimetric (laser induced fluorescence, LIF), conductometric, amperometric and other detection techniques can also be used, such as coupling to mass spectrometry (CZE–MS), but the use of other than optical detectors in capillary electromigration techniques often requires major technical modification of the instrumentation. The detector signal is registered and processed by a suitable PC software, as in chromatographic techniques. A simple instrument for CZE or EKC can be assembled in the laboratory from individual parts (suitable high-voltage sources and modified HPLC detectors equipped with microcells designed for capillary LC or CZE are commercially available). However, for routine quantitative analysis, where the interest is focused on the automation, full computer control and complying with GLP protocol, more sophisticated instrumentation is needed. As a response to the growing interest in capillary electromigration separation methods in the 1980s and 1990s, several manufacturers launched on the market compact instruments satisfying demanding requirements. Table 11.1 surveys some commercial instruments for CZE and EKC, available to our best knowledge at the time of preparation of this manuscript. As the situation on the market is developing rapidly, the reader is referred to the manufacturers’ web sites or to product information leaflets for up-to-date information concerning the available instrumentation for CZE and EKC. Together with

Micro-Tech Scientific Vista, California, USA www.microlc.com

CE Resources Ayer Rajah Industrial Estate, Singapore www.ce-resources.com

32 position

þ/30 kV

CE-L1 plus

Ultra- Plus II þ50 kV Capillary HPLC-CE/CEC

þ/30 kV

50 position

50 position

Sample loop

Pressure, Air/liquid electrokinetic

Pressure, Air/liquid electrokinetic

Air/liquid

Pressure, Air electrokinetic

Pressure, Liquid vacuum, electrokinetic

Minimal capillary length 33 cm (7.5 cm effective)

Flexible modular construction

96 well plates injection possible

Bubble cell, Z cell, minimal capillary length 33 cm (8.5 cm effective)

Built-in potential gradient Combination of CE and micro HPLC

Only HPSV/injection unit, external detectors

UV, 254 nm Minimal capillary (modes 103, 104), length 30 cm variable UV wavelength (model 105)

Diode array

UV, diode array, fluorescence, conductivity

UV, diode array, LIF

Diode array

Capillary thermostating Detection

Pressure, Air electrokinetic

Injection

þ/25 kV 4 position Pressure (manual (model 103), reversal) 10 position (models 104, 105)

þ/30 kV

CE-L1

Lumex Capel series St. Petersburg, Russia www.lumex.ru/eng/product/

Series 700

32 position

þ/30 kV

36 position

4 position

P/ACE MDQ

Beckman Coulter Fullerton, California, USA www.beckman.com

48 position

Vial tray

þ/30 kV

þ/30 kV

3D CE

Agilent Palo Alto, California, USA www.chem.agilent.com

Prince Technologies Series 200 Emmen, The Netherlands www.princetechnologies.nl Series 400, 500, 600

Voltage

Instrument

Manufacturer

Table 11.1 Basic characteristics of some commercially available capillary electrophoretic instruments

238


Figure 11.2 Scheme of a modern instrument for routine analyses. 1, forced cooling/ temperature regulation; 2, separation capillary; 3, cassette holder for the capillary; 4, detector; 5, high voltage power supply; 6, autosampler; 7, buffer replenishment line; 8, buffers. (Reproduced by permission of HPST)

general-purpose instruments, equipment designed for special applications is available, namely for genomics and proteomics research [6]. In the commercial instruments, the separation capillary is usually placed either free, or in a special cassette holder (Fig 11.2), in an air-circulated thermostat compartment. The cassette holders enable simple capillary manipulation and are always used in connection with a liquid-heated/cooled thermostat. The minimum length of the separation capillary depends on the instrument construction; it is longer when external detectors are used than in the compact instruments with built-in detectors. Many instruments allow capillary end coupling to an MS detector. The commercial instruments are usually fully automated and are equipped with appropriate software allowing connection of the instrument to local data networks. In the common instrumental arrangement, both sample and detector end vials are filled with the same electrolyte. Beside this, instrumentation with programmable electrolyte composition was introduced for solvent-gradient EKC, which makes it possible to change, reproducibly, the electrolyte composition during the analysis [7,8]. Using different gradient profiles, the selectivity and resolution in micellar electrokinetic chromatography (MEKC) separations can be significantly modified and the separation accelerated. An organic modifier such as acetonitrile, 2-propanol, or a nonionic surfactant, can be added into the inlet-capillary side vessel containing the starting electrolyte in a programmed way, using two pumps controlled by a gradient programmer to deliver and withdraw solutions from a stirred conical inlet reservoir [8]. Time-controlled pH gradients in the background electrolyte can be formed using the same equipment as for solvent gradients, e.g. by continuously adding a free acid into the inlet vessel containing the starting-pH running buffer [8]. In another gradient set-up, two

GENERAL ASPECTS OF INSTRUMENTATION

239

electrode chambers filled with different background electrolytes are placed at the inlet capillary end, while the third electrode is immersed in the vessel at the detector end of the separation capillary. By controlling the voltage ratio at the two inlet-part electrodes, the electric currents and consequently the buffer flows through the two channels connected to the inlet vessels can be adjusted, enabling formation of various pH or ionic strength gradients [9]. The level of the liquids in the vials at the injector and detector ends of the capillaries should be the same during the analysis, otherwise a difference in level may cause additional hydrodynamic flow through the capillary during analysis, leading to irreproducible retention times and peak broadening due to the contribution to the dispersion by velocity differences connected with the laminar hydrodynamic flow profile. This effect increases with increasing inner capillary diameter. In some applications, the electrophoretic migration velocity is low, causing separation times to be too long. In this case, pressure-assisted electromigration separations may decrease the time of analysis. Some instruments allow the use of this technique by applying a pneumatically generated constant overpressure (typically 2500 Pa) on one end of the separation capillary during the analysis. For this purpose, pressurized air is introduced into a closed vial containing running buffer at the injector end of the capillary. This technique may even enable the separation of some sample compounds with relatively high electrophoretic mobilities directed in opposite direction to the electroosmotic mobility of the background electrolyte [10,11]. However, some additional band broadening and loss of efficiency and resolution may be observed in pressure-assisted separations, because of the parabolic laminar flow profile in the separation capillary. Further miniaturization in electromigration separation techniques was triggered by introduction of micromachined technologies that are standard in the semiconductor industry, including photolithography, wet chemical methods (etching) or laser ablation, to prepare microchip planar structures with channels of diameters comparable to those of the standard fused silica capillaries. Microchips based on glass or quartz [12–16], calcium fluoride [17], ceramic or polymer substrates [18–22] have been used for electromigration separations. Fluid manipulation and sample introduction on separation chips typically employ electrokinetically driven propulsion of liquids. Most frequently, the separated sample zones are detected using laser induced fluorescence (LIF) detection, on-chip electrochemical detection [23], or a combination with electrospray or nanospray mass spectrometry. Because of the very short length of separation channels on chips, linear imaging of the separation process is possible [16]. The first simple EKC experiments on microchips contrast with recently reported impressive separations exceeding 1 million theoretical plates, performed in a 25 cm long spiral separation channel fabricated on a glass microchip [24]. Large peak capacity can be accomplished in two-dimensional separations combining MEKC and open-channel electrophoresis [25]. Applications of solvent gradients in microchip MEKC separations have also been reported [26]. The principal advantage of microchip electrophoretic techniques is high speed of separation, less than 1 minute, enabling high throughput analyses. Minimum sample preparation requirements and low operation costs of microchip capillary electrophoretic and electrokinetic chromatography separation methods may revolutionize research in the life science area.

240


11.3 Separation Capillaries Capillaries used for electrophoretic and electrokinetic chromatography separations must be easily available, mechanically and chemically stable for reproducible analyses, and must efficiently dissipate the Joule heat generated in the capillaries by the electric current in order to avoid overheating and boiling of the buffers inside the capillaries. Further, good UV transparency is required for on-capillary spectrophotometric or fluorimetric detection. In the early applications of capillary electrophoresis, borosilicate glass was used as the material for the separation capillaries [2,4,27], but the high UV cut-off (280 nm) of this material severly limits the possibilities of on-capillary spectrophotometric detection. UVtransparent PTFE capillaries also have been used for direct on-capillary spectrophotometric detection [28]. Although the surface of PTFE capillaries is lipophilic and theoretically should not generate any electroosmotic flow (EOF) in electromigration techniques, in practice measurable EOF was detected in PTFE capillaries [29,30], possibly due to the breakdown of C–F bonds under applied high voltage [31]. Other disadvantages of these capillaries are low thermal conductivity and poor dissipation of Joule heat, so that PTFE capillaries easily get overheated at a higher applied potential. Fused silica (FS) capillaries with circular cross-section, which are nowadays used in almost all CZE and EKC applications, are more simple to handle and meet all the most important requirements. Open tubular capillaries with circular cross-section are cheap and can be obtained from various manufacturers. Capillaries with internal diameter 50 and 75 mm and external diameter of 365 mm are commonly used in CZE and EKC. The total capillary lengths vary from several centimetres up to 1 m, depending on the construction of the instrument and on the number of theoretical plates required. When high mass sensitivity is necessary, smaller diameter capillaries can be used, even 5 mm i.d. or less. Such narrow i.d. capillaries allow the injection of only very small sample volumes, requiring extreme detection sensitivity and picoliter detection cells to suppress detrimental extra-column effects on band broadening and a dramatic decrease in resolution. These requirements practically rule out most of the contemporary detection techniques, except for laser-induced fluorescence measurement (LIF) and mass spectrometry with electrospray (nanospray) ionization. However, Wahl et al. [32] reported that using a capillary with i.d. ¼ 5 mm instead of i.d. ¼ 75 mm with mass-spectrometric detection, the signal intensity decreased only four times when a 100-times lower sample volume was injected. Further, decreased sorption on the capillary walls was reported with 10 or 25 mm i.d. capillaries [33,34]. Another advantage of narrow diameter capillaries is decreased Joule heat production. Table 11.2 summarizes some geometric and hydrodynamic properties of capillaries with different inner diameters, which should be taken into account when selecting the sample injection volume, the concentration of the background electrolyte, the applied voltage and the detection technique. A fused silica (FS) capillary alone is very fragile, hence the outer surface of the capillary is usually coated with a polyimide layer, 12–25 mm thick, for better handling. The polyimide coated capillaries are flexible and can be easily bent without breaking. When the appropriate separation capillary length is prepared in the laboratory from a commercially supplied long piece of capillary tubing, the capillary should be carefully

19.6 0.02 15.7 0.80 3 0.09 0.0017

0.015 0.000046

5

3.1 0.003 6.28 2.00 0.46

2

0.03

0.38

78.5 0.08 31.4 0.40 12

10

c

b

Square cross section At electroosmotic flow velocity 150 mm min1 Water, in a capillary with L ¼ 0.5 m; pressure corresponds to the level difference 0.1 m

a

Cross section (mm2) Specific volume (ml m1) Specific surface (mm2 m1) Surface/volume (mm1) Electroosmotic flowb (nl min1) Pressure driven velocity at P ¼ 1000 Pac (mm min1) Pressure driven flow at P ¼ 1000 Pac (nl min1)

Column diameter (mm)

Table 11.2 Geometric and hydrodynamic properties of capillaries

0.47

1.5

310 0.31 62.8 0.20 46

20

18

9.3

1960 1.96 157 0.08 294

50

93

21

4420 4.42 236 0.05 663

75

290

37

7850 7.85 314 0.04 1180

100

2500 2.50 200 0.08 375

10000 10.00 400 0.04 1500

sq. 50 50a sq. 100 100a

242


cut with a ceramic or diamond cutter, so that the capillary ends have smooth edges to avoid band broadening and irreproducible sample injection. To facilitate accurate capillary cutting, special tools are available. It is recommended that approximately 2 mm of polyimide coating be removed from the injection end of the capillary to avoid sample diffusion under the coating, which may cause tailing of sample zones and memory effects. As the polyimide film on the FS capillaries is not transparent to UV radiation, it should be removed from a small capillary segment to create a detection window allowing direct on-capillary UV spectrophotometric detection. The creation of a detection window is a crucial point in the preparation of a separation capillary for electromigration experiments, as any irregularities and contamination of the bare capillary outer surface significantly decrease the detection sensitivity. Several techniques can be used to prepare a transparent detection window. Burning off a section of the polyimide coating at a fixed distance from the capillary end using a small gas torch or lighter [Figure 11.3(a)] is simple and easy, and detection windows as narrow as 0.5 mm can be prepared. However, the physicochemical properties of fused silica capillary walls can change at a high burning temperature. Alternatively, the detection window can be etched in the polyimide coating using a drop of hot (130–150 C) concentrated sulphuric acid [Figure 11.3(b)]. Sulphuric acid rapidly removes the polyimide layer, which first gets dark and then dissolves and disappears from the capillary surface. This method is more gentle than the burning procedure and even allows creation of detection windows on the capillaries with coated inner walls. The required length of the polyimide coating can be also removed mechanically using a razor blade, but great care should be taken not to scratch the capillary walls. Hence, this technique is recommended only when other window preparation techniques are not applicable. A commercial device with different burner filament lengths is available for reproducible creation of the detection windows with specified lengths (1–3 mm) [35]. Capillaries with UV transparent coatings do not require preparation of a detection window. Commercially available capillaries with PTFE or polyacrylate coatings are easier to handle than the FS capillaries with a fragile detection window in the polyimide coating [36,37]. Rectangular cross-section capillaries offer better optical properties than do cylindrical capillaries, and improve the detection sensitivity in the arrangement with the optical path following the longitudinal capillary axis [38]. Because of a higher surface area to volume ratio, rectangular capillaries enable efficient cooling. Although square cross-section capillaries are commercially available [36], they are still rarely used.

Figure 11.3 Methods for preparing of on-capillary detection windows by burning off a capillary coating (a) and by dissolving in hot sulphuric acid (b)


Figure 11.4 capillary

11.3.1

243

Electric double layer on capillary walls and electroosmotic flow in the separation

Electroosmosis and Modification of the Inner Surface of Capillaries

Electroosmosis gives rise to movement of a liquid in a capillary across which an electric potential is applied. It results from the presence of charged groups on the inner surface of the capillaries. Due to the voltage applied on the capillary, charge separation occurs between the capillary walls, creating an electric double layer with its own potential. The counter ions in the double layer adjacent to a charged capillary surface migrate towards the capillary end with opposite polarity, drawing the liquid contained in the capillary in the same direction. This phenomenon gives rise to the electroosmotic flow (EOF). The double layer is very thin (of the order of 4 [30]. The inner surface of a fresh capillary is nonhomogenous and possesses some nonionizable Si–O–Si bonds and may contain impurities (Figure 11.5). To obtain reproducible electroosmotic flow, a new capillary should be activated by consequent flushing with 0.5–1 mol l1 potassium or sodium hydroxide for at least 30 min, then with hydrochloric acid (1 mol l1, 30 min) and finally with distilled water until neutral pH. The electroosmotic mobility can be manipulated by sorption (dynamic coating) of a cationic surfactant such as hexadecyltrimethylammonium bromide (CTAB) on the capillary wall. At a low CTAB concentrations, the electroosmotic flow is first reduced and, at concentrations higher than 3 104 mol l1 CTAB, the direction of the electroosmotic flow is reversed (in 0.01 mol l1 phosphate buffer) [47]. Strong dependence of the properties of dynamically coated capillaries on the composition of the working electrolyte limits their use in practical applications. FS capillaries with chemically bonded inner wall coatings are more stable. In addition to strongly reduced EOF, coated capillaries usually show reduced adsorption of the analytes onto the capillary walls. For some electrokinetic chromatographic methods, the capillaries with strongly suppressed electroosmotic flow are required. Figure 11.6 illustrates schematically the migration of sodium dodecylsulphate (SDS) micelles and of a noncharged analyte in micellar electrokinetic chromatography in a noncoated FS capillary (MEKC) and in a coated capillary with electroosmotic flow reduced to zero (RF–MEKC) [46,48,49]. The first attempts to produce permanent capillary wall coatings were reported by Jorgenson and Lukacs [50]; many approaches have been adopted since then to improve the effectiveness and stability of the coatings. FS capillaries modified with polyacrylamide and polyethyleneglycol are most common, but other inner wall coating types based on polyethyleneimine, carbohydrates, alkylsiloxanes, pentafluorobenzoyl, polyvinylpyrrolidone, etc., have also been described. Hjerte´ n [51] introduced a simple two-step method for the capillary wall coating with linear polyacrylamide: in the first step the activated capillary wall is silylated with a bifunctional agent [(g-methacryloxypropyl)trimethoxysilane)],


245

Figure 11.6 Principles of separation in MEKC in a fused silica capillary with electroosmotic flow (EOF) (left) and in coated capillary with reduced electroosmotic flow (right). t(EOF), retention time of an EOF marker; t(MIC), retention time of a micelle marker; t(R), retention time of analyte. (Reproduced from Ref. [49] with permission of Vieweg-Publishing)

consecutive polymerization with acrylamide catalyzed with N,N,N0 ,N0 -tetramethylethylenediamine (TEMED) and ammonium persulphate follows in the second step (Figure 11.7). The Hjerte´ n’s method is fast, but yields capillaries with a low stability against hydrolysis due to the linking of the organosilane agent via Si–O–Si–C bonds. Si OH

OCH3

CH3O

Si OH

CH3O

Si

CH3

Si

OCH3

O Si

(CH2)3CO2C CH2

Si

O

CH3

(CH2)3CO2C CH2

(NH4)2S2O8 TEMED

Si

O

Si

O

OCH3 Si

CH2

CHCONH2

CHCONH2 CH2 CH2

(CH2)3CO2C CH3 CH2 CHCONH2

Figure 11.7 Preparation of capillaries with polyamide coated inner walls (I). Silylation of the capillary walls with (g-methacryloxypropyl)trimethoxysilane and consecutive polymerization with acrylamide to form covalent bonding via Si–O–Si–C link (according to Hjerteń [51]). TEMED, N,N,N0 ,N0 -tetramethylethylenediamine

246


Si OH

SOCl2

Si Cl

CH2

CHMgBr

(NH4)2S2O8 CH2 TEMED

Si CH CH2

CHCONH2

CHCONH2 CH2 CH2 Si

CH CH2 CHCONH2

Figure 11.8 Preparation of capillaries with polyamide coated inner walls (II). Treatment of the capillary walls with Grignard reagent in the first step followed by polymerization with acrylamide in the second step to form direct Si–C bonds, which are stable against hydrolysis (according to Cobb et al. [52])

More stable coated capillaries can be prepared by treating the capillary walls with a vinyl group-containing grignard reagent (vinylmagnesium bromide) in the first step before the polymerization with acrylamide, thus providing coatings linked to the capillary walls via Si–C bonds (Figure 11.8) [52,53]. This method is more time consuming, but gives coated capillaries with almost completely suppressed electroosmotic flow and excellent stability against hydrolysis over a broad pH range (from pH ¼ 2 to pH ¼ 10.5). Bruin et al. reported a method for capillary coating with polyethyleneglycol via Si–O–Si–C linkage (Figure 11.9) [54,55]. Capillary coating Si OH

(CH3O)3Si (CH2)3 O CH2 CH CH2 O

in toluene

Si

OH

Si

O

O

Si (CH2)3 O CH2 CH CH2 O

CH2 CH2 O CH2 CH2 OH n

Si (CH2)3 O CH2 CH OH

BF 3 Et2O in dioxane

CH2 O

CH2 CH2 O

n

CH2 CH2 OH

Figure 11.9 Preparation of capillaries with polyethyleneglycol coated inner walls. Initial treatment of the capillary walls with (g-glycidoxypropyl)trimethoxysilane and consecutive reaction of the bonded epoxy group with polyethyleneglycol (according to Bruin et al. [54])


247

with bonded acrylamido-2-methylpropanesulphonic acid yields controlled, pHindependent electroosmotic flow, which increases the separation reproducibility and allows the application of reversed migration of micelles over a broad pH range [56].

11.4 High Voltage Power Sources To exploit fully the separation potential of capillary electrophoresis and electrokinetic chromatography, an electric field as high as 100 kV m1 is required to obtain optimum separation efficiency and short analysis time. However, taking into account practical restrictions imposed by the capillary internal diameter, background electrolyte ionic strength and possibilities of efficient capillary cooling, the maximum voltage in commercially supplied instruments does not exceed 30 kV and the driving electric current is limited to 200 mA (see Table 11.1). Some automated instruments allow continuous monitoring of current and voltage during the analysis, which helps to detect and solve accidental problems with instability of separation conditions during the analysis. The ripple of the applied voltage should not exceed 0.1 %. Electrophoretic instruments are equipped with a high voltage interlock for maximum operation safety. The high-voltage sources are built in compact electrophoretic instruments, but selfstanding HV units for in-house made instruments are available, too [57–60]. The use of a high voltage power supply with reversible polarity is very useful, as it increases the instrument versatility. Usually, the high voltage (HV) is applied on the injection end (‘hot end’) of the separation capillary and the detector end is grounded (‘cold end’) [Figure 11.10(a) and (b)]. This arrangement avoids possible increase of the signal noise and damage of the detector due to a high electric potential difference between the detector cell and the ‘hot-end’ of the capillary and is absolutely necessary when conductivity or electrochemical detection, or coupling with a mass spectrometer, are used. Therefore, if the voltage polarity across the capillary is reversed, it should

Figure 11.10 Possible set-ups of high voltage power supply in capillary electrophoresis and electrokinetic chromatography. (a), (b) ‘hot end’ of the capillary at the injector position with grounded detector end of the capillary; (c). ‘hot end’ of the separation capillary at the detector end with grounded injector. Arrows indicate the direction of the electroosmotic flow under usual conditions (neutral and basic pH, noncoated capillary)

248


be performed by changing the polarity of the applied voltage at the HV source [Figure 11.10(b)]. With some instruments, the polarity of the HV source must be changed manually. For these reasons, high voltage is only rarely applied at the detector end [Figure 11.10(c)]. 11.4.1

Joule Heat and Capillary Temperature

The electric current I in the capillary filled with an electrolyte of conductivity k produces Joule heat, i.e. the thermal energy, P, which is directly proportional both to the current and to the applied electric field strength, E, and indirectly proportional to the capillary cross section, S: I2 ð11:3Þ P ¼ EI ¼ kS Here, the thermal energy, P, is defined as the electric power per unit length converted into heat. A part of the thermal energy is dissipated to the environment, but another part heats the liquid inside the capillary. The rise in the capillary temperature causes a change in the physicochemical properties of the background electrolyte, namely chemical equilibria shift, decrease in viscosity and increase in conductivity, which cause further increase in the electric current and consequently may further increase the capillary temperature. If the heat transfer from the capillary to the surrounding environment by convection is insufficient, the temperature may rise uncontrollably, until eventually the liquid in the capillary starts boiling and the gas bubbles form, which inhibit the passage of the current. The increase in the electric current with increasing electric field strength can be described by linear Equation (11.4) only at a constant temperature (constant k): I ¼ kSE ð11:4Þ A nonlinear increase in the electric current in the capillary at increasing voltage in a higher current region is a strong indicator of significant Joule heat formation. The thermal energy dissipated per volume unit in the capillary Pvol depends on the equivalent molar conductivity LT and rises up to hundreds of W cm3 as the background electrolyte molar concentration c increases: ð11:5Þ Pvol ¼ E2 T c Because the Joule heat is generated in the whole capillary volume, but can be dissipated to the environment only by convection through the capillary walls, the temperature of the electrolyte inside the separation capillary is not homogenous and a radial temperature gradient is formed with the maximum in the capillary center. The resulting temperature profile is shown in Figure 11.11. Under typical operating conditions, the difference between the temperature in the core of the capillary and the capillary inner wall is less than 1 K, a small difference compared with the temperature gradient between the capillary outer wall and surrounding environment [61]. The heat loss by heat conduction through the capillary walls is not sufficient for efficient capillary cooling when a high electric field strength (>200 V cm1) is applied across the capillary and forced capillary cooling is necessary. Cooling with strong


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Figure 11.11 Temperature gradient outside and inside the separation capillary and relevant thermal conductivities lT of the media. (Reproduced from Ref. [62] with permission of Vieweg-Publishing)

circulating air stream can reduce the temperature rise in the capillary up to five times [62]. More efficient cooling is accomplished when the capillary is immersed in a circulating liquid cooling medium, because of a better heat transfer to the liquid as compared with the circulating air, but the construction of the electrophoretic instrument with liquid cooling is more complicated than that having a circulated air thermostat. At a higher temperature inside the capillary, the mobilities of the background electrolyte ions and of the analytes increase by approximately 2 % per K, mainly due to a decrease in viscosity. The temperature rise accelerates the migration, but on the other hand, the resolution may decrease due to the parabolic temperature profile inside the capillary. Temperature fluctuations during the analysis may cause poor reproducibility in the migration times. Thus effective capillary thermostating is essential for reproducible results. Time-dependent fluctuations of the capillary temperature and viscosity also explain lower reproducibility of the peak areas than of the migration times: the peak areas depend mainly on the actual conditions during the injection (especially when electrokinetic injection is used) and during the migration of the analyte zones through the detector cell, whereas the migration times reflect the average conditions during the whole analysis run, where the instantaneous fluctuations partially compensate each other over a longer time interval. The effects of the thermal nonhomogeneity in the capillary also contribute to band broadening and decrease the separation efficiency, which can be described by Equation (11.6): s2T ¼ 2 D T t

ð11:6Þ

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sT and DT are the variance and the dispersion coefficient contributions, respectively, due to the Joule heat. The temperature effects on the separation efficiency are only marginal if the temperature difference between the center of the capillary and its inner walls is less than 1.5 K [63]. The loss of efficiency due to the thermal contribution limits the capillary diameter to 50 mm at maximum, when concentrated buffers ( 100 mmol l1) with high conductivities are used. In practice, the capillary diameter is usually selected as a compromise between the detection path length dictated by the sensitivity (when spectrophotometric detectors are used), the allowable sample concentration and the temperature effects on the efficiency of separation and reproducibility of results.

11.5 Sample Introduction To obtain high resolution in capillary electromigration techniques, the volume of the sample controlling the zone length inside the capillary must be much smaller than the dispersion generated by the diffusion during the analysis and in the detection window. Table 11.2 shows that the total volume of a typical separation capillary (30–70 cm long, 50–75 mm i.d.) is a few microliters or even less. Hence, only nanoliter or even smaller sample volumes can be introduced directly into a capillary. Ideally, an infinitely narrow zone of concentrated sample should be introduced to limit the dispersion only to the contribution by the longitudinal (axial) diffusion. (Band broadening due to various flow velocities of liquid segments resulting from the pressure-driven laminar (Poisseuille) flow profile is not present due to a flat plug flow profile in electrically driven capillary separations, where the liquid segments move with identical velocity over more than 90–95% of the capillary cross section.) In practice, a rectangular sample plug with a finite injection length, linj, is injected, which contributes to the peak dispersion (expressed as sample variance in length units), s2inj : l2inj ð11:7Þ s2inj ¼ 12 According to Grushka and McCormick [64], the relationship between the length of the injected sample zone, linj, and the relative decrease in the efficiency in the terms of theoretical plate number caused by the finite injection zone length can be described by Equation (11.8): ð11:8Þ x inj ¼ l inj =Ld ¼ ð24Dd=mVd Þ1=2 Ld is the length of the capillary from the injector to the detection window, xinj is the normalized injection length, D is the sample diffusion coefficient, d is the maximum tolerable loss of efficiency, m is the apparent mobility and Vd is the voltage applied to the capillary up to the detection window position. For example, assuming D ¼ 5 1010 m2 s1 , m ¼ 3 108 m2 V1 s1 , Vd ¼ 20 kV and a 10 % efficiency loss (d ¼ 0:1), the normalized zone length is xinj ¼ 0:0014, which represents the sample zone length of 0.7 mm and volume 1.3 nl for a capillary with Ld ¼ 50 cm and i.d. ¼ 50 mm. Various mechanical techniques for the introduction of nanoliter volumes into separation capillaries have been attempted with limited success, including miniaturized


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sampling valves [28], rotary type injector valves [65], microsyringe injection [66], or a combination of microsyringe injection with a capillary flow splitter [67]. These techniques can be successfully applied only with large capillary diameters of more than 200 mm i.d., which are of little practical use in capillary electrophoresis and electrokinetic chromatography because of the large Joule heat generation in broad capillaries (see Section 11.4.1). Two techniques are typically used for introduction of nanoliter and subnanoliter volumes in capillaries of less than 100 mm i.d.: electrokinetic injection and overpressure (or hydrodynamic) sample introduction. 11.5.1

Electrokinetic Sample Introduction

For electrokinetic sample introduction, the inlet end of the separation capillary and the electrode are removed from the vial of background electrolyte (BGE) and are immersed into another vial containing the sample. Then, a high voltage is applied for a short time, which causes sample ions to migrate from the sample vial into the separation capillary [Figure 11.12(a)]. As the migration direction of the ions depends on their charge, the applied voltage should be selected so that the combination of the electroosmotic and electrophoretic migration velocities direct the sample ions from the HV source end to the detector end of the separation capillary. Finally, the voltage is switched off and the capillary, together with the injection-end electrode, is immersed again into the vial with the background electrolyte and the separation is started by switching on the potential. Assuming a uniform electric field strength in both sample zone and in running buffer and a short injection time, the amount of substance of analyte introduced into the separation capillary, Qinj , is directly proportional to the injection time, tinj , to the molar concentration of the analyte in the sample component, ci , and to the voltage Vinj applied during the sample introduction: Qinj ¼ ðmEO þ mi Þ

ptinj ci dc2 Vinj 4 L

ð11:9Þ

where L is the total length of the separation capillary with internal diameter dc, and mEO and mi are the electroosmotic mobilities in the buffer used and the electrophoretic mobility of the analyte, respectively. Because the mobilities mi of the sample components differ from one another, the relative injected amounts of faster moving ions are higher compared to the ions with lower mobilities. In spite of the sample discrimination potentially leading to some systematic errors in quantification, electrokinetic sample introduction is popular in capillary electrophoresis, because of simple instrumentation and the very low sample volumes that can be injected in comparison with hydrodynamic injection [68]. 11.5.2

Hydrodynamic Sample Introduction

Hydrodynamic injection is based on the pressure difference between the capillary inlet and outlet ends. The pressure difference can be achieved by different methods like siphoning, pneumatically generated overpressure, or vacuum [Figure 11.12(b)–(d)]. The amount of substance of analyte introduced into the separation capillary, Qinj , at a

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Figure 11.12 Techniques of sample introduction in capillary electromigration methods. (a) electrokinetic injection; (b),(c),(d) hydrodynamic modes: (b) siphoning effect based on the difference between the levels h of the sample vial and the vial with the background electrolyte (BGE) on the detector end of the capillary; (c) pneumatic overpressure in the sample vial; (d) vacuum in the vial with the electrolyte on the detector end of the capillary

constant pressure difference, P, between the inlet and outlet capillary ends, is directly proportional to the injection time, tinj , and to the molar concentration of the analyte in the sample, ci , as with electrokinetic sample introduction: Qinj ¼ P

ptinj ci dc4 128ZL

ð11:10Þ

Here, L is the total length of the separation capillary with internal diameter dc and Z is the sample solution viscosity. During the siphoning injection [Figure 11.12(b)], the sample vial is raised vertically from the separation position to a predetermined height over the buffer vial at the detector end of the capillary for a fixed time interval. The pressure difference is proportional to the difference between the liquid levels at the two capillary ends. Some instruments allow the use of compressed air to apply a controlled pneumatic overpressure in a closed sample vial for a predetermined time interval [Figure 11.12(c)]. Principally, vacuum can be applied at the detector end of the capillary to draw the sample into the capillary [Figure 11.12(d)], but this technique is rarely used because of poor reproducibility and a risk of bubble formation inside the capillary during the sample suction. The pneumatic sample introduction technique has better reproducibility and allows more accurate control of the injected sample amount than do other injection techniques.


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Hydrodynamic sample introduction techniques are universally applicable in electrokinetic separation methods, and do not discriminate between components with different electrophoretic mobilities so that the injected sample plug has the same composition as the sample in the injection vial. However, some practical limitations should be considered, especially when the siphoning technique is used. In large-diameter capillaries (>100 mm), the linear velocity is too high for the practical use of hydrodynamic injection. At a constant pressure difference between the capillary ends, the mean linear velocity of a pressuredriven flow decreases with decreasing capillary diameter [Equation (11.10)], so that it can be too low in the capillaries with an internal diameter of less than 20 mm (see Table 11.2). Further, pressure-driven laminar flow in an open capillary has a Poiseuille (parabolic) profile across the capillary cross section, which may cause a contribution to band broadening that does not occur with an electrically driven flat plug flow profile. Finally, spontaneous injection may affect the accuracy of results in electrophoresis and in electrokinetic chromatography, because during the insertion and withdrawal of the capillary from the sample vial, the liquid can penetrate into the capillary from the drop hanging on the capillary end [64]. 11.5.3

Sample Stacking and Sweeping On-line Enrichment

Unfortunately, direct sample injection techniques allow the introduction of only limited sample amounts into the separation capillary. To increase sample loading and to minimize the impact of the sample zone length on the band broadening and detection sensitivity, sample stacking and sample sweeping techniques have been developed for online sample concentration enrichment and sensitivity enhancement in capillary zone electrophoresis [69–72] and in electrokinetic chromatography [73–75]. The sample stacking technique utilizes differences in the migration velocities of ionic sample compounds (or neutral compounds partitioning into a charged pseudostationary phase) in a high electric-field strength (low-conductivity) sample region and in a low electric-field strength (high-conductivity) separation region. The principle of the technique is based on fast migration of sample compounds in a high electric-field strength sample region to the stacking boundary between the sample and the background electrolyte regions. The stacking boundary is pseudostationary and moves with the electroosmotic flow. As soon as the charged pseudostationary phase (micelles, microemulsions or charged cyclodextrin) containing analytes reaches the boundary, the migration slows down. Hence, the molecules contained in the rear part of the sample plug zone migrate faster than the molecules in the front part of the zone, which results in the formation of a thin sample zone. After hydrodynamic or electrokinetic injection of a sample solution, which contains a pseudostationary phase, but has a conductivity considerably lower than that of the background electrolyte, the stacking sample enrichment process can be performed either in normal or reversed electrode polarity modes. Stacking in the normal mode without voltage polarity switching is suitable for slightly hydrophobic compounds, but the length of the sample zone that can be injected is limited [76]. In MEKC with SDS micelles in a low pH buffer (low EOF), only one (negative) polarity is needed to focus, separate and detect the analytes. Using reversed electrode polarity mode stacking, a negative polarity is needed to focus the analyte bands and a positive polarity is necessary to separate the

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focused bands. In the first step, after the sample introduction the analyte molecules accumulate at the injection end of the capillary and sample matrix can be removed before the separation of sample compounds starts after reversal of the polarity of applied voltage [77]. The enhancement factor of the stacking sample enrichment technique (30–300 times) depends on the analyte hydrophobicity: highly hydrophobic compounds are much more stacked than the polar ones, which may be even partially flushed out from the capillary during the stacking process. Other methods, such as field-enhanced sample injection or reverse migrating micelles mode [78,79], have also been used for stacking of neutral compounds (see Chapter 10). The sweeping sample preconcentration method is based on picking and accumulating of analyte molecules by the pseudostationary phase, which enters and fills the sample zone upon application of voltage. It occurs when the sample matrix does not contain a carrier pseudostationary phase and is mainly used with low EOF velocity. Thus it is usually constrained to separations performed at low pH. E.g. after hydrodynamic sample introduction into the capillary, the sample vial is replaced by the vial containing a micellar background electrolyte, and a negative polarity voltage is applied on the sample capillary end to accomplish sample preconcentration. The negatively charged SDS surfactant micelles migrate towards the detector end of the capillary, ‘sweeping’ on their way neutral analyte molecules resulting in sample zone compression (see Chapter 10). In most cases, switching of the voltage polarity is not necessary between the sweeping and the separation steps. The sweeping enrichment technique is well suited to the preconcentration of hydrophobic compounds under acidic conditions. In some applications, impressive results were achieved, such as a UV spectrophotometric detection sensitivity increase of six orders of magnitude for the MEKC separation of aromatic amines, using a background electrolyte with SDS micelles [80].

11.6 Detection Techniques The right choice of detection technique in CZE and EKC depends on the type and concentration of analytes, on the complexity of the sample and on potential interferences from the sample matrix and – last but not least – on the constraints imposed by the electromigration separation method used. Commercial availability of the detector, and the cost and ease of operation should also be considered. The detection can be performed either off-line (off-capillary) or in an on-line (oncapillary, end-capillary, and entire capillary) arrangement. In the off-capillary arrangement, the detector is not connected directly to the separation capillary and the separation does not affect the detection as significantly as with on-line detection, so that the separation conditions can be optimized fairly independently of the detection requirements. An example is off-line connection of capillary electromigration techniques with MALDI–TOF–MS [81]. However, the detection process is discontinuous. On-line detection can be accomplished either directly on the separation capillary (typically with UV-spectrophotometric or laser-induced fluorescence detection), or using a detector connected to the end of the capillary or a microchip separation channel, such as with ESI–MS detection or electrochemical detection [82,83]. This type of detector should be carefully designed to suppress contributions to band broadening.


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Direct on-capillary detection can employ a detection window (see discussion in Section 11.3), or the entire separation capillary length can be continuously monitored by measuring UV absorbance or fluorescence [84] for detection and imaging of the separation process on microchips [16]. Optical detection techniques, including UV spectrophotometric and LIF (laser induced fluorescence) measurements, are widely used in electrophoresis and electrokinetic chromatography. With few exceptions, only UV or LIF detectors are installed in compact commercial instruments (see Table 11.1). Other detection techniques based on the measurement of electrochemical properties of analytes (conductivity, amperometry or potentiometry) are used less often, but their sensitivity is in many cases better than the sensitivity of UV spectrophotometric detectors. Coupling of the separation capillary with a mass spectrometer opened new dimensions in capillary electromigration separation methods, by allowing not only sensitive and universal detection, but moreover the identification and structure elucidation of separated analytes. However, special precautions concern the use of background electrolytes in coupled CZE–MS and related techniques to avoid the contamination of the ion source and of ion optics of the mass spectrometer with solid particles originating from the buffers. For this purpose, special ‘orthogonal’ ion source geometry, or ‘MS-friendly’ volatile buffers are used. At present, EKC–MS techniques are still at a young stage compared to CZE-MS (see Chapter 15). Pseudostationary phases used in electrokinetic chromatography are often incompatible with MS, as they mask the ionization process necessary for detection and contaminate the ion source [85]. One solution of this problem is the partial filling technique [86,87], where only a part of the capillary is filled with an electrolyte solution containing the pseudostationary phase, which allows the separation avoiding the pseudostationary phase to enter the ion source of the mass spectrometer. 11.6.1

UV/VIS Spectrophotometric Detection

UV/VIS spectrophotometric detection is simple to use and relatively inexpensive. Commercial detectors are widely available, including common LC detectors equipped with a CE cell. It is versatile and nondestructive, and therefore can be easily connected in tandem with other detectors such as MS, amperometric, or conductometric detectors. The basic scheme and operating principle of a spectrophotometric UV detector for CZE and EKC is the same as in HPLC. The detector consists of a UV light source, wavelength selector, transferring optics, detector cell, a photodiode or a photomultiplier and necessary electronics for parameter control and signal acquisition and processing. The single-wavelength UV-light sources include atomic (mercury, cadmium or zinc) lamps with discrete emitted wavelengths, and an interference filter is used for wavelength selection. Deuterium arc lamps produce a fairly stable continuous emission spectrum over the interval 190–400 nm, tungsten–halogen lamps are typically used in the higher wavelength range. A grating monochromator is employed for the selection of required wavelengths, or a multiwavelength diode array detector is used for full UV spectra acquisition [88]. A coherent laser UV source [89] or light emitting diodes (LEDs) in the VIS region [90,91] and more recently in the UV region [92] have also been used for spectrophotometric detection in capillary electromigration separation techniques.

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The detection cell is the most critical part in a UV/VIS spectrophotometric detector. Its design is usually a compromise between the desired high sensitivity on one side and the requirement of minimum contribution to band broadening on the other. Because of small internal diameters of the separation capillaries, severe volume restrictions apply for on-line detection cells. The volume of the cell should not exceed one-tenth of the analyte zone volume to avoid significant band broadening. The contribution to the zone dispersion s2det related to the length of the detection zone, ldet , can be estimated as: l2 ð11:11Þ s2det ¼ det 12 Hence, the length of the detection cell should not exceed 1 mm [93]. This usually corresponds to subnanoliter cell volumes. On-column detection windows prepared by removing a section of polyimide coating from the capillary surface (see Section 11.3) in general do not contribute significantly to band broadening, but the capillaries with a circular cross section do not have ideal optical properties. The detection optical path length depends on the internal diameter of the capillary, which does not exceed 100 mm and, due the curved walls of the capillary, the actual path length depends on the position of the light beam with respect to the radial axis of the capillary, so that the effective optical path is not more than 70 % of the capillary internal diameter [94]. Because of the restrictions of the optical path length, low sensitivity is the major problem of on-capillary UV/VIS spectrophotometric detection and the detection limits usually are not lower than 105 –107 mol l1 , depending on the molar absorption coefficients of analytes. The nonideal cell geometry is also the reason for a low linear dynamic range of detection. This problem can be partially solved by focusing the light beam into the capillary using ball or cylindrical lenses and fiber optics [95] to collect and conduct the light to the photosensitive element. A more efficient way to improve the sensitivity and detection limits is to extend the optical path length in the detection cell. Different approaches have been reported, including a multireflection cell [96], a rectangular capillary cell [38], a ‘bubble’ cell [88,97] and a ‘Z-cell’ [88]. Using a rectangular cell illuminated along the longer axis, the optical path length is extended and both the sensitivity and the linear dynamic range are improved, but the fabrication of rectangular capillaries is difficult, hence these cells are not widespread. In a ‘bubble’cell [Figure 11.13(a)], the optical path is extended in an enlarged capillary section with a diameter three to five times larger than the diameter of the rest of the capillary, formed at the appropriate distance from the end of the capillary. Although the volume of the bubble cell is larger than the volume of the nonenlarged capillary, it does not contribute significantly to band broadening because of the zone compression in the bubble cell. However, the size and shape of the light entrance slit should be optimized to maintain narrow detected peaks. A high sensitivity ‘Z-cell’ introduced by Agilent Co. [88] is shown in Figure 11.13(b). The extended optical path length of 1.2 mm is approximately 20-times longer than the effective optical path length of 60 mm in the on-column window of a typical cylindrical capillary with i.d. ¼ 75 mm. The light path with square cross section 100 100 mm through the cell is micromachined in a block of fused silica to minimize stray light, and


257

Figure 11.13 UV spectrometric capillary detector cells with increased optical pathlength. (a) capillary with a ‘bubble’ cell; (b) high sensitivity Z cell: 1, 2, cell windows; 3, black quartz cell body with optical path channel; 4,5, inlet and outlet capillaries with flared ends. (Reproduced with permission of HPST)

the reflective interior works as a light-conducting pipe. In combination with plane parallel cell windows, the linear response range is extended up to 1.4 AU. The cell is tightly connected to the end of exchangeable capillaries, whose ends should be flared to the diameter of 100 mm for maximum separation efficiency without zone distortion or broadening.

11.7 Conclusions This chapter presents a short and basic introduction into the instrumentation used in electroseparation methods, with special attention to electrokinetic chromatography. The basic instrumental set-up in electrokinetic chromatographic methods is the same as in capillary zone electrophoresis, but some differences arise from the presence of the pseudostationary phase in the separation capillary, which may cause problems such as some restrictions in the choice of the detection technique (MS). On the other hand, the presence of the pseudostationary phase in the background electrolyte can be advantageous with regard to sample in-capillary preconcentration. More detailed information on other instrumental aspects, pseudostationary phases, sample introduction techniques and special detection techniques used in electrokinetic chromatographic methods are discussed in other chapters of this book. The instrumentation in capillary electromigration separation techniques has advanced considerably since the pioneering times of Jorgenson and Lukacs and very sophisticated

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commercial instruments are now available. Besides the capillary format of electrokinetic chromatographic methods, chip technologies have emerged in the last decade, triggering new rapid developments in this field.

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12 Laser-induced Fluorescence Detection: A Summary Christophe Bayle, Ve´reńa Poinsot, Clara Fournier-Noe¨l and François Couderc

12.1 Introduction Laser-induced fluorescence (LIF) detection can be regarded as the most sensitive optical detection technique to be commonly used with high performance liquid chromatography (HPLC), capillary electrophoresis (CE), electrokinetic chromatography (EKC) and capillary electrochromatography (CEC). LIF is widely used for the analysis of very complex mixtures where the concentration of the analyte of interest is in the mM range and where superb sensitivity and selectivity are needed. As an example, LIF can be used to detect trace levels of (derivatized) amino acids in biological media using simplified sample preparation. When LIF detection is used with capillary-format separations, it can detect nM or subnanomolar concentrations; this allows for a number of important innovative analyses, such as the simultaneous monitoring of the efflux of neurotransmitters at a frequency of every 10 s in microdialysates from brain tissues [1]. This chapter will discuss some theoretical aspects of LIF, the different optical arrangements that are used, and describe some applications that have been presented in the literature. We note that EKC is closely tied to CE with respect to instrumental developments, i.e. the instrumentation employed (including LIF detectors) is the same, therefore some CE applications have been included in this presentation. The preparation of a short article about a topic as broad as the use of LIF detection in CE and EKC has necessitated the selection of a fairly broad range of applications and omission of discussion of certain important and very timely topics. As an example, we have omitted a discussion of a series of innovative experiments concerning single cell analysis [2–4]


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because these experiments normally use customized CE injectors, and we will not review DNA or RNA detection because these assays are typically run using sieving media or capillary gels.

12.2 Theoretical Aspects Fluorescence detection is generally used in HPLC to detect molecules that possess native fluorescence, or that have been derivatized to generate a fluorophore. Typically, the fluorescent compound is excited using a pseudomonochromatic light source such as a xenon lamp in combination with a monochromator. The source irradiates a detection cell with a volume of a few mL. When EKC or CE is employed, HPLC detection cells cannot be used because their volume is excessively large, which will cause significant band broadening. Therefore the detection cell must be a small portion of the capillary used for the separation. Since the detection window of the capillaries is very small, a laser is used for excitation, with (quasi) continuous emission power in a range of a few tenths of a mW. Laser light is much more easily focused into a capillary than is a lamp, achieving higher light intensity inside the capillary. The increase of sensitivity using a laser compared with the use of a lamp could be in the order of 10 000, provided the wavelength of the laser line is reasonably close to the excitation maximum of the fluorophore. Because the resulting incident light intensity (photons cm2 s1) is much higher, reactions that are not important in conventional fluorescence are observed in LIF. As an example, photodegradation, which induces the bleaching of the fluorescent molecule and converts it in a nonfluorescent molecule, may be very important. Figure 12.1 presents the kinetic scheme of electronic excitation, showing the different electronic states of a molecule and the different reactions that can occur after excitation (without photodegradation). A number of publications have described the theoretical aspects of LIF detection, two especially useful ones are References [5] and [6]. These works demonstrated that the sensitivity of the detection depends on a number of factors, including: the rate of photodegradation kd of the molecule that absorbs at the laser wavelength; the transit time tt of the molecule in the laser beam; the incident light intensity I (photons cm2 s1); fast

ki

S1

T ka

kf °

kn kt

S0

Figure 12.1 Kinetic scheme showing the ground singlet state S0, the first excited singlet state S1, and the triplet state T. ka is the rate of absorption, kf is the natural radiative rate, kn is the radiationless decay rate, ki is the intersystem crossing rate, kt is the overall triplet decay rate. It is assumed that relaxation from the optically pumped vibronic levels to the emitting levels is very rapid compared with the pumping rate ka

LASER-INDUCED FLUORESCENCE DETECTION: A SUMMARY

265

the ratio a of background scattering to fluorescence at very low light levels and short transit time. For a fluorescent molecule, if we call k the ratio of ka (the rate of absorption, ka ¼ saI, sa is the absorption cross section) to kf (the rate of excited state population decay, kf ¼ kf þ kn þ ki, kf being the natural radiative fluorescence rate, ki the intersystem crossing rate, kn the radiationless decay rate) is indicated in Equation (12.1). k¼

ka kf

ð12:1Þ

In this expression we note that k is proportional to I, the incident light intensity. Then we use the steady state equation of the first exited singlet state (Figure 12.1), and calculate the expression for the probability that a molecule is intact after being in the laser beam for a time t, then we integrate the obtained expression following the residence time tt, and if we call the fluorescence quantum yield Qf, and the photodegradation quantum yield Qd, the mean number nf of fluorescence photons emitted by a molecule crossing an illuminated volume is shown in Equation 12.2. Qf kt 1 exp ð12:2Þ nf ¼ Qd ðk þ 1Þ where t ¼ kd tt , kd is the rate of photodegradation of the fluorophore in the laser beam, tt is calculated as the ratio of the velocity of the fluorophore to the light beam length (supposed to be a square beam profile to simplify calculations). The longer is the transit time, the longer is t. The scattering background is: Q nb ð12:3Þ nb ¼ f akt with a ¼ Qd nf tk!0 We note that nb is always proportional to the light intensity [see k in Equation (12.1)] and to the transit time. It should be noted, however, that if nf is proportional to the light intensity and the transit time for low values, then for higher values, ground state depletion and photodegradation are no longer negligible and nf does not increase linearly with k and t [5]. Figure 12.2 presents the variation of the noise (the noise is defined as the average value of the distance between a maximum peak and a minimum peak taken for a period of 1 minute) (&) measured by flushing with a 40 mM boric acid pH ¼ 9.6 buffer (the noise value is magnified ten times), the fluorescence intensity (^), and the calculated signal to noise ratio (*) with respect to the laser intensity for a solution of 0.01 mM fluorescein isothiocyanate (FITC). The FITC solution is buffered to pH ¼ 9.6 using 40 mM boric acid adjusted with 5 M NaOH. A 75 mm fused silica capillary of 75 cm length was used for the rinsing experiments. The buffer and the FITC solution was flushed using a depression of 850 or 400 mbar, respectively. An Arþ ion laser is used for these experiments. An optimum of S/N is observed for each flushing pressure at 10 mW and 6 mW respectively. These data show that the S/N ratio is very sensitive to the residence time; with a short residence time, a higher laser power must be used to optimize the signal-to-noise ratio.

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ELECTROKINETIC CHROMATOGRAPHY 35 Signal intensity (arbitrary units)

(a)

30 25 20 15 10 5 0 0

10

20

30

40

Signal intensity (arbitrary units)

35 (b)

30 25 20 15 10 5 0 0

10

20

30

40

Laser power (mW)

Figure 12.2 Variation of PMT current of a ‘ball lens’ detector using laser power. (a) When flushing a 75 mm ID capillary with water (noise, magnified by 10) &, or with 10-nM fluorescein isothiocyanate solution (signal) using a depression aspiration of 850 mbar; (b) same with a depression of 400 mbar. The signal-to-noise ratio is presented by *, the optimum laser power differs following the pressure, i.e. 10 mW for 850 mbar, 5 mW for 400 mbar, showing the importance of photodegradation in the laser beam

In CE experiments, the optimum laser power will depend on the photodegradation rate of the compound, on the capillary diameter (which determines the number of photons going through the liquid), and the velocity of the sample in the cell. Van den Beld [6] presented another expression for the integrated fluorescence F (photons/s) in a capillary flow cell with the volume V illuminated by a laser beam. This expression considers that the laser beam irradiance may not totally illuminate the inner diameter of the capillary, that photodegradation is important and also the concentration of the sample. The beginning of the mathematical formalism is: ð ð12:4Þ F ¼ 2:3 ef Cðx; y; zÞdV V


267

where e and f are the coefficient of molar extinction and the quantum yield of the fluorescent molecule and Cðx; y; zÞ is its concentration. It should be noted that the concentration of the sample in the laser beam is not homogeneous (because of photodegradation). In a flowing system, molecules of fluorophore have a velocity vz in the z direction (z is along the length of the capillary). When entering the laser beam (which is along the y axis), they will decompose causing a concentration distribution in the z direction. Assuming a plug flow condition (because it is a CE separation), and that the velocity of the electrolyte is uniformly distributed, F can be written as follows: F ¼ 2:3 efCo ðdc2 =2rL Þ½pvz rL =2kd ½1 expðsÞ

ð12:5Þ

(this equation not be true if the electrolyte is pumped in the capillary, keeping a laminar parabolic flow). Where Co is the concentration of the fluorophore injected in the capillary, dc is the internal diameter of the capillary, rL is the radius of the laser at the beam waist (e2 irradiance), s is defined as the reduced laser power, s ¼ 2kd P/p vz rL, where P is the laser light power getting inside the capillary. This expression is helpful for describing the fluorescence intensity (produced by one dissolved compound) dependent on the laser power, or the diameter of a capillary.

12.3 LIF Detector Design 12.3.1

Commercial Detectors

Several commercial LIF detectors are available for CE. The optical design of three units is illustrated in Figure 12.3(a–c). Figure 12.3(a) shows a Beckman–Coulter LIF detector, which is a dual wavelength detector and is used on the Beckman MDQ instrument. It works with a 488 nm (Arþ laser) and a 633 nm laser (HeNe) and the detection of the fluorescence is orthogonal to the plane of excitation. This plane is defined by the two optical fibers that illuminate the capillary with two laser wavelengths. At the back of the capillary, a mirror reflects the fluorescence to the photomultiplier tube (PMT) through a bandpass filter [Figure 12.3(a)]. In Figure 12.3(b) is shown the Picometrics ZETALIF detector, a single excitation LIF detector, which is modular and can be used with all CE/EKC instruments as it is external to the instrument. This detector is based on a confocal microscope arrangement, where a sapphire ball lens concentrates the laser light into the capillary. The fluorescence is collected by the same ball lens, which has a very high numerical aperture. The emission is passed through a series of filters (notch filters, which remove the laser reflection, a high pass filter that eliminates Raman scattering of water, and a pinhole), and the fluorescence is then measured by a PMT [Figure 12.3(b)]. Figure 12.3(c) shows another commercial detector from Picometrics, which is based on a design by Carlsson [7], and can be used inside a cassette of any CE instrument. An ellipsoid lens is glued to a capillary and the laser excitation is performed in front of the ellipsoid. The fluorescence, which does not escape from the capillary due to the silica–air interface (total reflection, critical angle of reflection), propagates in the capillary and is

268


Figure 12.3 Scheme of the different LIF optical arrangements which are used in the literature: (a) MQD Beckman–Coulter arrangement; (b) ‘ball lens’ Picometrics arrangement; (c) ellipsoid Picometrics arrangement; (d) sheath flow cuvette arrangement

collected by the ellipsoid, which then transmits the fluorescence to a PMT through a set of highpass and notch filters [Figure 12.3(c)]. These two latter detectors can be used with either a continuous or pulsed laser that provides either a UV, visible, or near infrared emission wavelength. Another LIF detector based on light fibre optics is commercially available from J&M Analytische Mess- und Regeltechnik (not shown). 12.3.2

Laboratory-made Detectors

We described a number of different ‘home-made’ LIF detectors in detail in a previous study [8]. In this section, we will summarize the two most used LIF home-made detector designs: the microscope based detector and the sheath-flow cell detector. Hernandez et al. described the use of a confocal microscope wherein the laser excitation beam was passed through a fiber optic to irradiate a capillary at the detection window, with a PMT and a set of filters allowing detection of the fluorescence [9]. This very sensitive detector provides weak reproducibility because the position of the capillary in front of the laser beam has some long-time instability. The sensitivity has been improved using a ball lens [10]. This simple detector is easy to use because every


269

confocal microscope can be employed for on-capillary detection. The most sensitive LIF detector, described by Dovichi et al. [11] and based on a modified commercial flow cytometry apparatus, was able to detect rhodamine 6G at a 89 femtomolar concentration. Figure 12.3(d) presents a diagram of their experimental set-up. In a small volume flow chamber, the sample stream was ensheathed within a larger solvent/stream under laminar flow conditions. A well-focused laser beam intersects the narrow diameter sample stream to provide a very small detection volume that is far from the cuvette windows. A spacial filter makes it possible to minimize the contribution of scatter and fluorescence from the windows to the background signal, and the fluorescence is measured by a PMT after passing through spectral filters. 12.3.3

Lasers

In recent years lasers with sufficient power and lifetime have become available, at a reasonable cost (within the budgetary constraints of the typical analyst), to excite molecules that absorb in the visible and UV regions of the spectrum to exhibit native fluorescence. The following typical examples are provided: Blue and violet diode lasers (400–415 nm): these continuous (cw) lasers have an emission power in the range 5–15 mW. Argon ion laser (488 nm), well-known cw lasers with an emission power in the range 5–60 mW depending on the LIF supplier. HeCd laser (325 nm or 442 nm), 325 nm typically with 15 mW (cw) and 442 nm with 40 mW (cw) emission power. Frequency-multiplied diode-pumped solid-state lasers (NdYAG) (266 nm, 355 nm, 473 nm, and 532 nm). These lasers are typically pulsed lasers having a quasi-cw emission power ranging from 2 to 12 mW at a frequency of 10 kHz.

12.4 LIF Applications In this section we consider experiments that can be performed with a commercial or a home-made instrument, because the sensitivity does not differ greatly. For the sake of practicality, we will only consider the use of laser wavelengths that are readily employed by the practicing analyst, i.e. lasers having a long life time (>5000 hours), and a relatively low price (8) or increasing the borate concentration (25– 400 mmol L1), the surface charge density increases, thus promoting a wider migration window. In situ charged micelles have been applied to the separation of PAH homologues [46], and in the analysis of pesticides of various classes [41–44]. Alternative and more complex aggregation colloids continue to be explored as a resourceful option for EKC separations. Surfactants composed of two ionic groups and two liphophilic chains, such as sodium 5,12-bis(dodecyloxymethyl)-4,7,10,13-(tetraoxa)1,16-hexadecanedisulfonate (DBTD) [47], bilayered aggregates such as vesicles and liposomes [48] and bilayer micelles [49] are a few examples. The separation of naphthalene derivatives was demonstrated in MEKC with double-chain surfactants [50] whereas examples of the use of liposomes as separation carriers in the separation of benzene derivatives and phenols were reported [51]. 21.2.2

Other EKC Modes

Palmer and coworkers proposed the use of 10-undecylenate (SUA) [52] and sodium 10undecylsulfate (SUS) [53] oligomers as secondary phases for EKC. Due to the fact that oligomers present high stability towards organic solvents, EKC with nonaqueous

478


separation buffers becomes available. The separation of sixteen PAH in SUA oligomers electrolytes was reported [54]. Ozaki and collaborators proposed the use of high molecular mass surfactants (amphiphilic copolymers) such as butyl acrylate–butyl methacrylate–methacrylic acid copolymer sodium salts (BBMA) [55]. The selectivity towards naphthalene derivatives was different compared with that of SDS micelles. Starburst dendrimers, poly(amidoamines) [56], and diaminobutane-based poly(propyleneimine) [57] as well as cationic polyelectrolytes (ionenes) [58] were presented as successful secondary phases for the separations of aromatic compounds. The field of oligomeric and polymeric secondary phases has been reviewed recently [17,59,60]. Negatively and positively charged cyclodextrins (e.g. sulfobutyl ether b-CD, sulfated CD, carboxymethylated b-CD and methylamino substituted b-CD) or mixtures of neutral and charged CDs are frequently employed in EKC separations as secondary phases (CD-EKC or CDCD-EKC) [32–35]. In these cases the separation mechanism is defined by host–guest interactions. The enantiomeric separation of polychlorinated biphenyls using mixtures of neutral and charged CD derivatives is a fine example of the impact of EKC with charged CDs in environmental analysis [61]. Microemulsion electrokinetic chromatography (MEEKC) is a relatively new technique that accomplishes electrokinetic separations using buffers containing surfactant coated oil droplets [62,63]. Typically microemulsions consist of a surfactant (usually SDS), an immiscible oil, such as octane or heptane, a cosurfactant, butan-1-ol, and an aqueous buffer. Due to the high surface tension between octane and water, a high SDS concentration is required to allow droplet formation. Alternatively, oils with lower surface tension such as di-n-butyl tartrate or ethyl acetate might be used, thus allowing microemulsions to be formulated with lower SDS contents (ca 0.6 % w/w or lower). There are several advantages of MEEKC over MEKC separations. Because solutes can penetrate the droplet surface more easily than the more rigid micelle, MEEKC can be applied to a wider range of solutes. MEEKC has often provided higher efficiency, probably due to improved mass transfer between the microemulsion droplet and the aqueous phase, mediated by the cosurfactant. Regan and collaborators examined the potential of MEEKC for the separation of priority endocrine disrupting compounds, which are breakdown products of the alkylphenolic detergents, as well as the synthetic estrogens diethylstilbestrol and ethinylestradiol and the plastic monomer bisphenol-A [64]. Calixarenes are conical-shaped macrocyclic oligomers whose inner cavity can accommodate several guest molecules similar to other macrocycles such as cyclodextrins and crown ethers. They have been introduced successfully as secondary phases in the EKC separation of chlorinated phenols, benzenediols and toluidines [65]. Since these macrocycles absorb in the UV region, with maximum at approximately 204 nm, they can also be employed for the indirect detection of various UV transparent compounds. Sulfonated calixarenes have been used with this additional purpose in the separation of aliphatic amines [66]. The use of suspended chromatographic silica-based particles in SDS buffers was first demonstrated in the EKC separations of phenol derivatives (suspension-EKC) [67]. The desirable characteristics for particles to function as secondary phases in EKC include: they should form homogeneous dispersions in any buffer system (including those modified by organic solvents), provide selectivity in the interaction with the solutes, be charged (sulfuric or carboxylic acids or esters are commonly used), have a small mass

ENVIRONMENTAL ANALYSIS

479

transfer resistance, be small to provide a high surface for the interaction and to avoid light scattering. The interaction with the analytes can either take place at the core or with a group bonded to the surface (a long alkyl chain can be used to promote hydrophobic interactions). In a recent compilation, Go¨ ttlicher and Ba¨ chmann reviewed the applications of polymer and silica-based particles to several pollutants [68]. In 1990, Terabe and Isemura proposed a strategy for the separation of analytes with similar electrophoretic mobility, developing ion-exchange EKC with polymeric ionic additives such as poly(diallyldimethylammonium chloride), PDDAC, and (diethylamino)ethyldextran, DEAE-dextran [69]. They successfully applied this concept to isomers of naphthalenesulfonate and naphthalenedisulfonate. Fritz and collaborators reviewed recently the fundamentals and scope of ion-exchange EKC with ionic polymers for the separation of small ions of potential importance in the environmental context [70].

21.3 Sensitivity The inherently trace level amount of pollutants in the environment coupled with the complexity of sample matrices place a strong demand on the EKC detection capabilities. The most often used detection scheme for capillary electromigration separation techniques, which is based on UV absorbance, responds with a poor concentration detectability (limits of detection in the order of 105 –106 mol L1), generally unsuitable for environmental applications. Several approaches have been devised to overcome the sensitivity problem: those based on sample preconcentration strategies and those based on special cell geometries and alternative detectors. Both areas have been subject to intense investigation and have been thoroughly discussed in recent review articles in the literature [7,8,71–76]. The sensitivity enhancing strategies based on sample manipulation are further divided into off-line and on-line sample enrichment. Liquid–liquid extraction with a variety of solvents (LLE) and solid-phase extraction (SPE) with a large assortment of chromatographic stationary phases of distinct chemistries are among the most often performed offline strategies on environmental samples [7,8,71]. A variety of on-line preconcentration strategies has been reported, aiming at decreasing limits of detection by the insertion of a large volume of sample in the capillary without compromising peak efficiency and resolution. In general, preconcentration strategies can be classified into two categories depending upon the physical phenomenon associated to the analyte concentration. One category involves the careful manipulation of the analyte electrophoretic velocity. A collection of strategies grouped by the name of sample stacking and transient isotachophoresis are a few examples of this category [74,75]. The other group of preconcentration strategies exploits the analyte ability to partition into a secondary phase. Sweeping and stacking of micelles [72,73] are representative of this group. Depending on the nature of the analyte, enhancement factors of the order of 100- up to 1000-fold, even approaching a million-fold sensitivity increase, have been reported, making viable the trace analysis of pollutants by capillary electromigration separation techniques. The low concentration sensitivity is associated with the use of capillary columns, due to the micrometer-range optical pathlength represented by the inner diameter, in addition to the small injection plug necessary to preserve the technique’s high efficiency.

480


Alternative cell geometries have been designed to extend the optical pathlength. Sensitivity enhancements of about tenfold have been reported with these devices [9]. The use of alternative detection schemes such as those based on laser-induced fluorescence [77], amperometry, conductivity and mass-spectrometry have been reported [3,15,17,78]. Some pollutants are natively fluorescent such as PAH and have been subject to diverse studies [79–82]. Others must be converted into fluorescing derivatives such as phenoxy- [83,84] and alkylphosphonic [85] acids herbicides. A number of fluorescent labelling techniques has been covered in the literature [86]. Derivatization is sometimes prone to difficulties such as incomplete reactions or the presence of contaminants due to side reactions. It is also time consuming. An interesting approach to speeding up derivatization procedures is the use of in-capillary derivatization reactions, which exploit differences in the electrophoretic mobilities to merge distinct zones of analyte and labelling reagent under the effect of an electric field [87]. In-capillary derivatization offers some relevant advantages over conventional batch procedures, such as: full automation of the derivatization step in an easy way, improvement of the reproducibility of the peak areas, and low consumption of sample and reagents. Molina and Silva explored the possibilities of LIF detection for in-capillary derivatization of amino compounds (herbicides and biogenic amines) [87]. Plugs of analyte and the labelling compound (5-(4,6-dichloro-s-triazin-2-ylamino)fluorescein, DTAF) solutions were injected successively into the inlet of the separation capillary under hydrodynamic conditions. Owing to their different electrophoretic mobilities, electrokinetic mixing of the two zones takes place and then they react for 10 min in the absence of an applied potential. Separation of the derivatives is then performed by MEKC (Brij-35/boric acid pH 9.5 electrolyte), with LIF detection (air-cooled argon-ion laser, 488 nm). Indirect detection schemes, in which a fluorophoric species is added to the electrolyte, are also often employed in environmental analysis. A few examples include: the indirect detection of amino-substituted polycyclic aromatic hydrocarbons using oxazine 750 as visualizing reagent [88] and of high explosives such as TNT, among others, using fluorescein and rhodamine B as fluorophores [89]. Amperometric detection is quite sensitive although not often applied in environmental analysis. Amperometric detection has been applied to the analysis of herbicides in tap water [90], aromatic amines in water samples [91] and phenols and chlorophenols in wastewater [92]. Mass spectrometry is one of the most powerful detection schemes available to environmental screening due to the intrinsic structural information it allows and also due to its high sensitivity. With the advent of effective interfaces and increased affordability of CE–MS instruments, the technique has become quite widespread [93–96]. In CE–MS, the use of nonvolatile buffers is usually avoided. Particularly in MEKC buffers, the presence of high amounts of SDS is detrimental, causing low ionization efficiency [97,98]. Strategies to overcome this shortcoming are discussed in detail in Chapter 15. Several examples of MEKC–ESI–MS applications using the partial filling strategy have been compiled within the pesticide analysis context [99–101]. MEKC– ESI–MS with anodically migrating micelles is an alternative to partial filling [102]. More recently, technological improvements in the ESI interfacing systems were shown to be more tolerant to the usage of nonvolatile buffers as demonstrated by the MEKC separation of triazines and phenols [103,104]. The use of different interfaces has also


481

been demonstrated as in the MEKC–APCI-MS analysis of aromatic amines and alkyl phthalates [105].

21.4 Representative Applications The literature comprises a larger number of methodologies employing EKC mechanisms, diverse preconcentration strategies and a variety of detection schemes with pollutant standards as test mixtures. However, application of these methodologies to real samples is somehow limited. Table 21.1 compiles applications of EKC to the most important pollutant classes in different environmental compartments. This table contains a list of the analytes investigated, the run time needed, characterization of the sample matrices, information on the sample preparation procedures, the optimized composition of the separation electrolyte for each method developed and some information on detection and achieved limits of detection. 21.4.1

Pesticides

‘Pesticide’ is a generic term used to describe a large number of broadly differing organic compounds employed in the control, prevention and elimination of plagues that attack crops and herds as well as vectors of diseases in human beings [106]. The use of pesticides constitutes an important aspect of modern agriculture, with unquestionable impact on crop production. Due to their wide use in agriculture, associated with their persistence and toxicity, these compounds are an important source of environmental contamination. Because pesticides encompass several classes of organic compounds, many of which are positional, geometrical and optical isomers, with differing degrees of ionization, polarity and water solubility, the versatility of EKC has placed the technique in a distinguished position among the separation techniques for the difficult task of assessing trace level concentrations of pesticides and their degradation metabolites in environmental matrices. Several excellent review articles have covered the literature on pesticide analysis by CZE and EKC in the last 10 years [107–114]. Although the intrinsically poor detection limits of EKC methodologies have hindered their application to real environmental samples, where trace level detection capabilities are demanded, the situation was somehow remediated with the advent of on-line and off-line sample preconcentration strategies and sensitive detection schemes as described earlier. The analytical feasibility of EKC methodologies for pesticides has been endorsed by fundamental studies with standards and eventually spiked samples. The standards are either combined in multiresidue mixtures [42,43,100,115–127] or differentiated by classes: pyrethroids [128], s-triazines [27,41,98,102–104,129–132] carbamates [99,133,134], phenoxyacids [44,83,135–137], quaternary ammonium salts [138,139], alkyl- [85] and amino- [87] phosphonic acids and urea-derived pesticides [134,140]. Micellar electrokinetic chromatography methodologies, which include buffered systems with SDS [116,120,124,126,130–132] bile salts [85,119,136], cationic surfactants [27,129,133] nonionic [87] or mixed [123] surfactants and additives such as organic solvents [83,85,115,118,122,123,125,138–140], urea [83,134] and cyclodextrins for chiral separations [115,118,121], are among the most commonly used EKC schemes

Carbendazim, simazine, atrazine, propazine, ametryn, diuron, linuron, carbaryl, propoxur in 6 min Carbendazim, imazalil, methylthiophanate, O-phenylphenol, prochloraz, procimidone, thiabendazole, triadimefon in 25 min Simazine, aziprotryne, hexazinone, diuron in 10 min Fenuron, simazine, atrazine, carbaryl, ametryn, prometryn, terbutryn in 12 min

UV, 215, 240 nm 0.02–0.17 ng L1

[145] UV, 226 nm 0.01 – 0.03 mg mL1

10 mmol L1 phosphate, 60 mmol L1 SDS, 8 % ACN (pH 9.5)

on-line SPE C18 90 – 114 %

Water: river water

[144]

[143]

[142]

20 mmol L1 borate, 8.5 mmol L1 SDS (pH 8.30)

UV, 220 nm 0.1 mg L1

SPE DVN-VP 41 – 109 %

SW, SRMM, SRW SPE C18, NH2

Water: river water well water

Carrots water: drinking water

UV, 210 nm 0.1–1 mg kg-1

[141]

Reference

4 mmol L-1 borate, 75 mmol L1 sodium cholate (pH 9.2)

220, 254, 300 nm, 150 mm extended optical path capillary 0.6–1.9 mg L1

Detection (LOD)

Fruits and vegetables: SPE C8 30 – 105 % grape, orange, tomato, lettuce

Optimal electrolyte

10 mmol L1 tetraborate, 25 mmol L1 SDS, 40 mmol L1 perchlorate, 15 % ACN (pH 9.3) 20 mmol L1 phosphate, 25 mmol L1 SDS, 10 % MeOH (pH 2.5)

Extraction procedure (recovery)

SPE C18 80 – 95 %

Water: well water

Matrix

Selected applications of EKC methods to environmental samples

Pesticides (Multiclass) Atrazine, simazine, paraquat, diquat in 3 min

Pollutant

Table 21.1

Atrazine, simazine, propazine, prometryn, hydroxyatrazine, deisopropylatrazine, deethylatrazine in 7 min

Pyrethroids Pyrethrin esters (pyrethrin, cinerin and jasmolin, I and II) in 25 min Triazines Desethylatrazin2-hydroxy, simazine, prometon, atrazine, simetryn, ametryn, propazine, prometryn, trietazine, terbutylazine, terbutryn in 30 min Atrazine, desethylatrazine, desisopropylatrazine, hydroxyatrazine, chloro-, hydroxydegradation products in 29 min Atrazine in 10 min

SPE C18 52 – 87 %

—

Water: ground water

Humic acid solutions

Fruit juices: grapefruit, SLM-SPE orange, blackcurrant, Fluoroporeapple C18 36.2 – 75.9 %

Water: drinking water well water

UV, 214 nm 0.05 mg L1

UV, 210 nm 2 – 4 mg L1

24 mmol L1 borate, 18 mmol L1 phosphate, 25 mmol L1 SDS, 5 % 1-propanol (pH 9.5) 15 mmol L1 tetraborate, 60 mol L1 SDS, 10 % methanol (pH 9.3)

220 nm, 200 mm extended optical path capillary 0.02–0.30 mg L1

UV, 214 nm 10 mg L1

UV, 254 nm 1.1 – 14.1 mg L1

25 mmol L1 tris, 30 mmol L1 SDS, 25 % ACN ( pH 9)

10 mmol L1 phosphate, 60 mmol L1 SDS, 20 % methanol (pH 9.2) SPE 2 10 mmol L1 borate, PS-DVB 60 mmol L1 disks 73.5 – 102.4 % SDS, 20 % methanol (pH 9.2)

—

Pyrethrum extract

(Continued )

[149]

[148]

[147]

[146]

[128]

[152]

[153]

UV, 202, 214 nm 22–85 ng L1

0.05 mg kg-1

45 mmol L1 borate/phosphate, 40 mmol L1 SDS (pH 8.0)

4 mmol L1 borate, 35 mmol L1 SDS (pH 9)

SPE C8 42 – 118 %

[151]

SPE PS-DVB 82.2 – 104.8 %

UV, 210 nm 0.8 mg L1

[150]

SPE C18 disks 85 %

220, 225, 230, 247 nm 80 %

LLE-SPE cation exchange 72.9–118.5 %

SPE C18 80.2 – 94.9 %

SW, SRMM, SRW SPE C18

Air: greenhouse air

Metsulfuron Grain: wheat, methyl, barley, corn thifensulfuron methyl, chlorsulfuron, rimsulfuron and tribenuron methyl in 20 min Chlorsulfuron, Soil chlorimuron, metsulfuron in 20 min

Water: tap water pond water

Monuron, isoproturon, diuron in 16 min

20 % THF, 0.00625 mol L1 OSUA

NH4Cl/NH3 buffer at 15 mmol L1, 60 mmol L1 SDS (pH 8.5)

30 mmol L1 borate, 80 mmol L1 SDS, 14 % MeOH, 20 % isopropanol (pH 7.0)

50 mmol L1 SDS, 50 mmol L-1 phosphoric acid, 15 mmol L1 g-cyclodextrin 4 mmol L1 tetraborate, 12 mmol L1 phosphate, 30 mmol L1 SDS (pH 7) 25 mmol L1, 50 mmol L1 SDS (pH 6.71)

[54]

UV, 214 nm

(Continued )

[158] UV, 227, 270 nm 0.71–1.18 ng L1

[157]

[156]

UV, 234 nm high-sensitivity optical cell 0.02–0.035 mg L1

UV, 214 nm 10 mg L1

[155]

[154]

UV, 244 nm 0.1 g L1

UV, 244 nm tested z-shaped cell 1 mg L1

10 nitrophenols in 20 min

Phenols 11 priority pollutants in 12 min

5 hydroxyPAH in 20 min

16 homologues in 35 min





Pollutant

Extraction procedure (recovery) 1

Optimal electrolyte

Water: rain water tap water process water

Water: river water sea water

SPE spiked sample 74.2 – 106 % ITP spiked sample

Reference

[206]

LIF Nd-YAG, 266 nm

UV, 214 nm 3–25 ng mL1

UV, 254 nm

[80]

[209]

[208]

UV, 280, 333 nm [207] 1010–109 mol L1

UV, 280 nm 10 mg L1

[205] LIF, bubble cell, 325 nm, 2.5 mW HeCd laser 0.9–21.7 mg L1

Detection (LOD)

50 mmol L1 phosphate, [244] UV, 214 nm 25 mmol L1 28.1 – 215 nmol L1 tetraborate–phosphate, 7.5 mmol L1 DBTH (pH 7) 50 mmol L1 glycine, 0.2 % UV, 254 nm [245] m-HEC, 2.5 % PVP (pH 9.1) 19 – 80 mg L1

25 mmol L SBbCD, SFE CO2 at 400 atm, 400 mL/min, 120 C, 20 mmol L1 MbCD, 20 min; sample 50 mmol L1 borate collected in CH2Cl2 and diluted in MeOH/water Soil: spiked heath sand LLE 8.5 mmol L1 borate, cyclohexane 85 mmol L1 SDS, 50 % ACN (pH 9.9) (48 – 90 %) Water: rain water LLE 0.2 mol L1 PFOS, 50 % DMSO, river water perfluoro 0.1 mol L1 H3PO4 spring water surfactants in THF (99 %) Water: aqueous SPME 50 mmol L1 ammonium standard mixture Silica acetate, 100 mmol L1 THAþ in 100 % methanol extracted by SPME impregnated with polydimethyl-siloxane Air: ambient air Air sample 0.1 mol L1 phosphate, collected on 0.1 mol L1 borate, 50 mmol L1 polyurethane foams STDC, 30 % acetone Isopods: PROTEOLYSIS 30 mmol L1 borate, hepatopancreas protease K 60 mmol L1 SDS, 12.5 mmol L1 g-CD Flatfish: bile in tris buffer pH 9, 37 C, 18 h (pH 9.0)

Soil: wood preserving lot

Matrix


Soil: certified soil reference standard

25 phenols in 20 min

Methylamine, Air: particulate dimethylamine, aerosol diethylamine, dipropylamine, piperidine, pyrrolidine, morpholine in 10 min Aromatic amines 2-Toluidine, 4-toluidine, Water: 1-naphthylamine, wastewater 2-naphthylamine, 2-aminobiphenyl, 4-aminobiphenyl, 2-methoxy-5-methylaniline, 4-methoxy-2methylaniline, 2-chloroaniline, 4-chloroaniline, 2,4,5-trimethylaniline, 2,4,6-trimethylaniline, 2-anisidine, 4-anisidine, 2,4-xylidine, 2,6-xylidine in 50 min

Amines Aliphatic amines Diaminopropane, Water: lake water putrescine, cadaverine, diaminohexane in 7.5 min

12 chloro and Air nitrophenols in 10 min

Water: river water

19 chlorophenols in min

20 mmol L1 borate, 20 % acetone, 5 mmol L1 DM-b-CD

50 mmol L1 phosphate adjusted to pH 8.5 with 100 mmol L1 borate, 300 mmol L1 SDS, 10 mmol L1 cholic acid, 10 mmol L1 Tween 80

SPE/LLE (cation exchange resin; tertiary butyl methyl ether) 78.4 – 94.4 %

10 mmol L1 borate, 100 mmol L1 H2O2, 80 mmol L1 SDS (pH 9.3)

50 mmol L1 phosphate, 1 mmol L1 SB-b-CD (pH 7.5) 25 mmol L1, borate 10 mmol L1 phosphate, 10 mmol L1 SDS (8.86)

50 mmol L1 ACES, 22 mmol L1 SDS (pH 6.1)

FTIC derivatization

ABEI-DSC derivatization 92.8 – 106.8 %

Loopsupported liquid film

—

SPE PSDV 81 – 116 %

[247]

[231]

[246]

(Continued )

UV, 214 nm [270] 0.263 – 9.525 mg mL1

[259] Chemiluminescence, post-column reagents: 3 mmol L1 K3Fe(CN)6, 0.8 mol L1 NaOH.(3.5 – 12) 108 mol L1 [260] LIF, 488 nm Ar laser, 520 nm emission 109 mol L1

UV, 205 nm 3.5 – 17 mg L1

Electrochemical: graphite-epoxy electrode versus Ag/AgC l 0.07 – 0.2 mg L1 UV, 214 nm 0.05 – 0.33 mg L1

Matrix

ðContinued Þ

4-Chloroaniline, Water: tap water 4-bromoaniline, lake water 3,4-dichloroaniline, 3-chloroaniline, 3-chloro-4-methylaniline, 4-isopropylaniline, 3-methylaniline, aniline in 15 min 4-Chloroaniline, Water: lake water 4-bromoaniline, 3,4-dichloroaniline, 3-chloroaniline, 3-chloro-4-methy laniline, 4-isopropy laniline, aniline, 3-methylaniline, acetophenone, propiophenone, butyrophenone, valerophenone, hexanophenone, heptanophenone in 26 min 1,3-Phenylenediamine, Water: surface water 2-methoxy aniline, near textile and 4-ethoxyaniline, leather industries 4,4’-diaminobiphenyl, 2-methylaniline, 2,4dimethylaniline, 2-ethylaniline, 2,6-dimethylaniline in 4 min Carbonyls 4 DNPH derivatives Water: river water in 20 min

Pollutant

Table 21.1

[91] Fluorescence, mercury-xenon lamp, 495 nm emission 1 mg L1

5 mmol L1 tetraborate, 4.5 mmol L1 boric acid, 20 mmol L1 SDS (pH 9)

0.02 mol L1 borate-phosphate, 0.05 mol L1 SDS (pH 9)

Fluorescamine derivatization

Spiked sample 97 – 102 %

UV, 360 nm 0.05 mg L1 (formaldehyde) 0.08 mg L1 (acetaldehyde)

UV, 214 nm LIF, 266 nm solid-state UV laser, 310 nm emission 5.7 108 – 4.9 107 mol L1

35 mmol L1 DOSS, 8 mmol L1 borate, 40 % ACN (pH 8.5)

FMOC derivatization (anilines)

[275]

[272]

[271]

LIF, 488 nm Ar laser, 520 nm emission 1010 mol L1

400 mmol L1 borate, 40 mmol L1 OG (pH 9.0)

FTIC derivatization

Reference

Detection (LOD)

Optimal electrolyte


21 naphthalene sulfonate derivatives in 28 min Dyes Sulfonated azo dyes: acid blue 113, acid red 73, acid red 13, mordant yellow 8, acid red 1, acid red 14, acid red 9, acid yellow 23 in 16 min

Aromatic sulfonates 21 naphthalene sulfonate derivatives in 30 min

5 MBTH derivatives in 10 min

5 DNPH derivatives in 14 min

3 DNPH derivatives in 8 min

SPE

SPE Isolute ENV 54 – 81 %

Water: waste water

Sample was diluted 1/1000 and filtered

Water: river water

Water: industrial effluent

Gas: stack gas from an Impinger 1.56 g organic plant DNPH in 500 mL 2 mol L1 HCl LLE in CS2 Air: vehicular Impinger 0.05 g emission DNPH in 50 mL 2 mol L1HCl LLE in chloroform Air: indoors Impinger 0.05 % MBTH stacking with salt

9.5 mmol L1 ammonium acetate, 0.1 % Brij 35 (pH 9)

UV, 214 nm 19 – 230 mg L1

UV, 230 nm 20 mg L1

UV, 220 nm 0.5 – 3.2 mg L1

(Continued )

[29]

[289]

[288]

[278]

UV, 216 nm 0.54 – 4.0 mg L1

25 mmol L1 tetraborate, 75 mmol L1 Brij 35, 5 mmol L1 octylamine(pH 9.0) 50 mmol L1 borate, 100 mmol L1 SDS (pH 8.7)

[274]

UV, 360 nm 0.2 – 2.0 mg L1

20 mmol L1 borate, 50 mmol L1 SDS, 15 mmol L1 b-cyclodextrin 20 mmol L1 tetraborate, 50 mmol L1 SDS (pH 9.3)

[276]

UV, 214 nm 2.0 mg L1

0.02 mol L1 borate, 0.05 mol L1 SDS (pH 9)

Water: industrial waste water Sewage Sludge

Water: spiked water Soil

Matrix

Estrone, b-estradiol and ethynylestradiol in 10 min

Water: spiked water

and sludges

Endocrine disruptors 17b-Estradiol, Water: river water diethylstilbestrol, ethynylestradiol, octylphenol, nonylphenol, bisphenol A in 15 min Octylphenol, Water: wastewater nonylphenol in 10 min treatment effluents

Surfactants 19 LAS isomers in 45 min

Monosulfonated dyes: cresol red, acid blue, acid orange, tropaeolin, nuclear fast red, orange II, acid red in 27 min

Pollutant


[64]

[305]

[299]

[294]

Reference

[314] UV, 214 nm 0.16 – 0.30 nmol L1

UV, 214 nm 50 mg L1 (tested)

25 mmol L1 phosphate, 200 mmol L1 SDS, 900 mmol L1 butanol, 80 mmol L1 heptane, 20 % propanol (pH 2) 30 mmol L1 phosphoric acid, 80 mmol L1 SDS, 20 % MeOH SPE C18 spiked sample 25.6 – 50.8 % SPE C18; sweeping > 96 %

UV, 214 nm low mg L1 range

100 mmol L1 phosphate, 12.5 % ACN, 25 mmol L1 SDS, 1 mmol L1 HP-b-CD (pH 1.8)

UV, 200 nm 4 mg L1

UV, 214 nm

100 mmol L1 cholate, 10 % acetone (pH 8.35)

10 mmol L1 phosphate, 40 mmol L1 SDS, 30 % acetonitrile (pH 6.8)

Detection (LOD)

Optimal electrolyte

Spiked samplea nalytes solubilized in 10 % ACN:90 % buffer

LLE, MeOH/ NaOH (44.6 – 96.2 %) SPE, C18 and SAX (33.1 – 75.7 %

SPE ion pair (water) C18 (soil) 42.5 – 107 % (water) 17.9 – 105 % (soil)


Spiked sample

20 mmol L1 CAPS, 25 mmol L1 SDS, 15 % acetonitrile (pH 11.5) UV, 200 nm 2.0 – 7.4 mg L1 [306]

Note: SW, sweeping; SRMM, stacking with reverse migrating micelles, SRW, stacking with reverse migrating micelles and a water plug SPE, solid-phase extraction; C8, C18, NH2, octadecyl-, octa-, amino-bonded silica; PS-DVB, poly(styrene-divinylbenzene); DVN-VP, poly(divinylbenzene-N-vinylpyrrolidone); SLM, supported liquid membrane; LLE, liquid–liquid extraction ASE, accelerated solvent extraction; HPGPC, high performance gel permeation chromatography; OSUA, oligomers of sodium undecylenic acid; SFE, supercritical fluid extraction; SDbCD, sulfobutyl ether b-cyclodextrin; MbCD, methyl b-cyclodextrin; PFOS, perfluorooctanic sulfate; DMSO, dimethyl sulfoxide; THAþ, tetrahexylammonium; SPME, solid-phase microextraction; STDC, sodium taurodeoxycholate DBTHP, disodium 5,13-bis(dodecyloxymethyl-4,7,11,14-tetraoxa-1,17-heptadecanedisulfonate; ITP isotachophoresis; m-HEC, methyl-hydroxyethylcellulose; PVP, polyvinylpyrrolidone; PSDVB, polystyrene–divinylbenzene copolymer; SB-b-CD, sulfobutylether-b-cyclodextrin ABEI, N-(4-aminobutyl)-N-ethylisoluminol); DSC, N,N-disuccinimidyl carbonate; FTIC, fluorescein isothiocyanate; OG, n-octylglucopyranoside; FMOC, 9-fluoroenylmethyl chloroformate; DOSS, dioctyl sulfosuccinate Aldehydes LODs refer to each single aldehyde, not the derivative; DNPH, 2,4-dinitrophenylhydrazine; MBTH, 3-methyl-2-benzothiazoline hydrazinone; FASI, field-amplified sample injection;TBAB, tetrabutylammonium bromide; TTAB, tetradecylytrimethylammonium bromide; LAS, linear alkylbenzenesulfonates HP-b-CD, hydroxypropyl-b-cyclodextrin; CAPS, cyclohexylamino-1-propanesulfonic acid

Estriol, phenol, Water: river water trichlorophenol, bisphenol A, pentachlorophenol, butylphenol, estrone, b-estradiol, diethylstilbestrol, ethinylestradiol, nonylphenol in 25 min

492


for pesticides. The use of polySUS for pyrethoids [128], DOSS [117] and in situ charged micelles [41–44] for herbicide mixtures and alkylglycoside chiral surfactants [135] for phenoxy acids has also been reported. The MEKC determination of s-triazines and quats in well water samples was described by Acedo-Valenzuela and collaborators [141]. Buffer pH, type (tetraborate and phosphate) and concentration, surfactant type (SDS and cholate) and concentration, acetonitrile content (0–20 %) and ion pair reagent (perchlorate) concentration were investigated to compose the final electrolyte. A solid-phase extraction procedure with recoveries between 80 and 95 % combined with MEKC (see Table 21.1) allowed the analysis of well water samples spiked with 2 mg L1 of triazines and 5 mg L1 of quats. Detection limits were in the 0.6–1.9 mg L1 range. On-line preconcentration strategies for the multiresidue analysis of pesticides in drinking water and carrots using reduced-flow micellar electrokinetic chromatography (RF-MEKC) were investigated by Tavares and coworkers [142]. Sweeping and stacking with reverse migration of micelles, with and without the insertion of a plug of water before sample injection, were contrasted. Limits of detection in the order of 2–46 mg L1 were obtained using solely the on-line strategies. Enrichment factors of 3–18-fold were achieved. By combining off-line solid-phase extraction and the proposed on-line strategies, the detection of pesticides in drinking water at 0.1 mg L1 level was conceived. A method based on solid-phase extraction and MEKC was developed by Pico´ and collaborators for the simultaneous determination of pesticide residues in fruits and vegetables [143] Selectivity was evaluated by changing the buffer pH and concentration, the type and concentration of surfactant, and the methanol content in the electrolyte. Recoveries of fungicides in spiked fruit and vegetable samples ranged from 30 to 105 % and limits of detection from 0.1 and 1 mg kg1. The multiresidue analysis of s-triazine and phenylurea herbicides was approached by Chicharro and collaborators [144] using solid-phase extraction combined with MEKC. The method reached 0.02–0.17 ng L1 limit of detection levels (spiked well water). Simazine was detected at 1–2 ng L1 concentration in river water samples, which was further confirmed by gas chromatography coupled to mass spectrometry. Valca´ rcel and collaborators developed an automatic, on-line, solid-phase extractor for the multiresidue analysis of pesticides in river water [145]. A few figures of merit of the proposed method include: linearity in the range of 0.05–0.25 mg mL1 achieving LOD from 0.01–0.03 mg mL1 and LOQ from 0.03–0.09 mg mL1 (after preconcentration; a tenfold enrichment). Four river samples were spiked with the test mixture at three different levels presenting recoveries from 90–114 %. The EKC separation of pyrethrin esters in a technical pyrethrum extract, using both SDS and a polymerized surfactant as secondary phase, was investigated by Warner and collaborators [128]. Parameters such as pH, SDS and polymerized sodium N-undecyl sulfate (polySUS) concentration, type and concentration of background electrolyte (borate, borate/phosphate and Tris buffers) and type and ratio of organic modifier (acetonitrile, methanol and isopropanol) were studied. The MEKC results are compared to the HPLC separation of these esters and show an improvement in efficiency and total analysis time. A MEKC method for the determination of triazines in ground water was developed by Rodrı´guez and coworkers [146] (see Figure 21.1). Buffer pH and concentration as well as concentration of SDS were optimized. Different organic solvents were tested


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Figure 21.1 Separation of triazine herbicides. Electrolyte: 24 mmol L1 borate, 18 mmol L1 phosphate, 5 % 1-propanol and 25 mmol L1 SDS (pH 9.5). Peak identification: (1) desethylatrazin-2-hydroxy, (2) simazine, (3) prometon, (4) atrazine, (5) simetryn, (6) ametryn, (7) propazine, (8) prometryn, (9) trietazine, (10) terbutylazine and (11) terbutryn. (From S. Frıás, M.J. Sańchez and M.A. Rodrı´guez, Anal. Chim. Acta, 503, 271–278, copyright 2004, with permission from Elsevier)

as buffer additives (acetonitrile, ethanol, methanol, 1-propanol and 2-propanol). Concentrations of 0.05 mg L1 were found in ground water samples pretreated by solid-phase extraction. A reversed-phase HPLC and a MEKC method were optimized by Prosen and collaborators for the determination of several triazines and their polar degradation products in solutions with humic acid and without a previous sample preparation step [147]. The HPLC method was satisfactory in terms of repeatability (1.7–12.5 % RSD) and limits of detection (0.1–0.5 mg L1). However, the most polar products could not be separated from the humic acid front peak. MEKC presented excellent resolution for both chloro and hydroxy degradation products and parent compounds, and possible interferences of humic acid were successfully avoided by its electrophoretic migration towards the anode. Higher detection limits (2–4 mg L1) and poorer migration time repeatability (20 % RSD) were obtained. The HPLC method was used to monitor degradation of atrazine and its first degradation products in the presence of humic acids whereas the MEKC method was used for confirmatory purposes. Wieczorek and coworkers used MEKC to assist in a critical evaluation of supported liquid membrane (SLM) and solid-phase extraction (SPE) procedures for the determination of atrazine at microgram level in different types of fruit juices [148]. The authors suggested that the application of SLM extraction prior to SPE is an alternative method for atrazine enrichment from complicated liquid matrices and could be used as routine method for the clean-up of such samples.

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An analytical method combining solid-phase extraction in C18-bonded silica and polystyrene–divinylbenzene (PS–DVB) disks with MEKC separation has been developed by Pe´ rez-Conde and collaborators for the determination of four triazines and degradation products of atrazine in drinking and well-water samples [149]. The influence of the buffer pH and concentration, SDS concentration and methanol (5–30 % range) was studied. Using two PS–DVB disks, quantitative recoveries were obtained for all pesticides (better than 93 %, except for diisopropylatrazine with 73 %). The detection limits were within the 0.02–0.06 mg L1 range in drinking water and the 0.06–0.30 mg L1 range in well water. MEKC was applied by Kubilius and Bushway to separate and quantify hexazinone and its metabolites in groundwater collected from US Geological Survey monitoring wells [150]. Water samples were extracted by a solid-phase procedure. Percentage recoveries of 79–100 for hexazinone were obtained at 0.5, 1.0, 2.0 and 5.0 mg L1 levels. Intraassay (n ¼ 10) and interassay (5 days) repeatability studies indicated RSD better than 12 % for hexazinone and 23 % for the metabolites. The performance of the proposed MEKC procedure was further compared with an established HPLC method in the analysis of hexazinone and its most widespread metabolite in ca 45 groundwater samples showing good correlation and no significant bias. He and Lee proposed an analytical method based on the combination of solid-phase extraction and MEKC with field amplified injection for the analysis of organonitrogen pesticides in drainage water [151]. Recoveries of 85 % and limits of detection of 0.8 mg L1 were obtained. Silva and collaborators developed a MEKC method for the simultaneous analysis of N-methylcarbamate pesticides and their respective hydrolytic phenolic metabolites in environmental waters [152]. The electrolyte composition (type, pH and concentration, SDS concentration) as well as instrumental parameters were optimized. SPE procedures were employed for sample enrichment reaching limits of detection of 22–85 ng L1 with precision better than 7.4 % RSD and preconcentration factors between 1700 to 2000. An analytical method based on solid-phase extraction combined with MEKC was developed by Pico´ and collaborators to determine substituted urea pesticides in orange and tomato samples [153]. Several factors such as buffer type (phosphate, borate, glycine, carbonate and ammonia), pH (phosphate buffer at pH 5.75–11.01) and concentration, SDS concentration, as well as methanol addition (10–30 %) were optimized. After an SPE procedure, which provided a tenfold enrichment for oranges and 25-fold increase for tomatoes, a limit of detection of about 0.05 mg kg1 was achieved. Acceptable recoveries (42–118 %) and precision ( 0.99) was established to a concentration of 500-fold the limit of detection. Contaminated soil samples from a wood preserving lot were extracted by CO2 supercritical fluid and reconstituted in mixtures of dichloromethane and methanol prior to analysis. Six components were identified but samples also exhibited fluorescent components other than the inspected 16 PAH. Bru¨ ggemann and Freitag [206] employed an aqueous-organic buffer composed of borate, SDS and ACN to the inspection of PAH in a deliberately contaminated soil sample (heath sand) and spent machine oil. Takagai and Igarashi explored an interesting approach for the inspection of PAH in natural waters by combining homogeneous liquid–liquid extraction and sweeping preconcentration strategy followed by EKC separation [207]. In the homogeneous liquid–liquid extraction, a pH-induced phase separation of a water sample treated with perfluorooctanic acetate (PFOA) surfactant in different water-miscible solvents was studied. Limits of determination in the range 1010 to 109 mol L1 and enrichment factors up to 125 000-fold were obtained. Wheeler and collaborators [208] explored additive complexation to separate and analyze PAHs in a solid-phase microextracted water sample. A series of conventional reverse-phase liquid chromatography ion-pairing agents (tetramethyl-, tetraethyl- tetrabutyl and tetrahexyl-ammonium salts and butane-, heptane- and decanesulfonic acids) was investigated in three nonaqueous electrolyte systems (MeOH and ACN) and the relative role of hydrophobic interaction versus electrostatic association was evaluated. One advantage of selecting nonaqueous electrolyte systems for hydrophobic interaction EKC is the potential for efficient coupling with SPME. Dabek-Zlotorzynska and Lai [209] tested the usefulness of the bile salt taurodeoxycholate as surfactant and organic solvents (methanol, acetone, acetonitrile and tetrahydrofuran) as modifiers in the EKC separation of PAH for further inspection in ambient air sample extracts. Separation of the 16 priority pollutant PAHs was accomplished except the pair indenol[1,2,3-cd]pyrene and benzo[g,h,i]perylene. The separation of phenolic PAH metabolites has been performed by CD-MEKC using a 30 mmol L1 borate buffer (pH 9.0) containing 60 mmol L1 SDS and varying concentrations of g-cyclodextrin [80]. Conventional fluorescence and LIF detection were applied, the latter by using a new, small-size, quadrupled Nd–YAG laser emitting


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at 266 nm. Conjugated pyrene metabolites in hepatopancreas samples from terrestrial isopods (Oniscus asellus and Porcellio scaber) were separated and determined. Finally, flatfish bile samples from individuals exposed to polluted sediment or crude oil were analyzed regarding the content of 1-hydroxypyrene. 21.4.3

Phenols

Phenols and derivatives are polluting substances present in the aquatic environmental as byproducts of the coal and oil industry or as the result of pesticide and drug decay [106]. US EPA and European Union have included phenol and various chlorophenols and nitrophenols in their lists of priority pollutants to be monitored in aquatic environments. Phenols are weak acids (pK a 9), well suitable for assessment by the CZE mode. However, EKC can be a resourceful alternative for inspection of complex environmental samples due to the enhanced resolution achieved by the complementary interaction of the solutes with the secondary phase. The remarkable separation of a mixture of 14 phenols was used in 1984 to introduce MEKC to the scientific community [14]. Later, the separation of 19 isomers of chlorophenols was presented [210]. Since then, phenols have been used as model compounds in a number of theoretical studies, such as those aiming at modeling retention factors [211–214], mobility [215], optimizing selectivity [216] and ultimately resolution [217]. Several phenols have been used to evaluate the impact of different surfactants (SDS [14,30,210,212,215,218,219–222], N-lauroyl-N-methyl-b-alaninate and -taurate [221], DOSS [223], CTAB [224] and hexadimethrine bromide, HDB [225], bile salts [37,204]), nonionic [226,227] and mixed micelles [30,228], and additives (neutral [229,230] and anionic cyclodextrins [137,231,232], tetraalkylammonium salts [233], organic solvents [204,220,223,225] alkyl polyols [219], urea [137]) in EKC separations. In addition, more exotic secondary phases such as SDS modified by bovine serum albumin [234], watersoluble calixarene [235], starburst dendrimers [236], cationic polymeric phases [237,238], ionenes [239], amphiphilic block copolymers [240], polyelectrolye complexes [241] and even liposome-coated capillaries [242] have all been characterized with phenol test mixtures. Crego and Marina specifically reviewed the separation of phenols of environmental interest [243]. The MEKC separation of the 11 phenols in the priority pollutant list was first demonstrated by Ong and coworkers in 1990 [222]. Several other authors selected the priority phenols as test case [219,224,227,231]. It is well established that MEKC separations of phenols present higher selectivity than CZE; for instance, resolution of chlorophenol congeners is only possible under EKC mode (see Figure 21.3). Nevertheless, CZE has by far received more attention concerning real sample applications. Only a few examples of the investigation of phenols by EKC in aquatic systems and soil could be compiled. Harino and coworkers used a double-chain surfactant having two sulphonate groups (disodium 5,13-bis(dodecyloxymethyl-4,7,11,14-tetraoxa-1,17-heptadecanedisulfonate, DBTHP) to assess phenol concentrations in river and sea water [244]. Baseline resolution of the eleven phenols was achieved in 12 minutes. The authors contrasted the proposed method with established GC, HPLC and SFC methods for phenols in terms of detection limits, resolution and ease of implementation. All methods require some sort of sample preconcentration step prior to analysis, or derivatization in the case of GC. The great advantage of the MEKC would be its resolution power and short analysis time. For

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Figure 21.3 Separation of chlorinated phenols by CD-EKC. Electrolyte: 50 mmol L1 phosphate buffer (pH 11) and 4.0 mmol L1 fully methylated b-CD. Other conditions: injection 5 s, 0.5 psi.; 20 C; 25 kV; 220 nm. Peak identification: (1) 2,3,4,5,6-pentachlorophenol, (2) 2,3,5,6-tetrachlorophenol, (3) 2,3,4,6-tetrachlorophenol, (4) 2,3,4,5-tetrachlorophenol, (5) 2,3,6-trichlorophenol, (6) 2,4,6-trichlorophenol, (7) 2,3,5-trichlorophenol, (8) 2,4,5trichlorophenol, (9) 2,3,4-trichlorophenol, (10) 3,4,5-trichlorophenol, (11) 2,6-dichlorophenol, (12) 2,5-dichlorophenol, (13) 2,3-dichlorophenol, (14) 2,4-dichlorophenol, (15) 3,5dichlorophenol, (16) 3,4-dichlorophenol, (17) o-chlorophenol, (18) m-chlorophenol, (19) pchlorophenol, and (20) phenol. (From K.P. Scharwachter, O. Kranz, J. Voss, W.A. Konig, J. Microcolumn Sep., 12, 68–74 (2000) by permission of John Wiley & Sons, Inc.)

comparison, HPLC is not able to separate all 11 phenols and its run time is in the 20 – 30 min frame. Moreover, the dynamic range of MEKC is wider than those of HPLC and SFC. The determination of ten nitrophenols in glycine buffers modified by b-cyclodextrin (0–10 mmol L1) and polyvinylpyrrolidone (PVP, 0.5–2.5 % w/v) was approached by Kaniansky and collaborators [245] Separation was conducted in capillaries made of fluorinated ethylene–propylene copolymer with a larger than usual diameter (300 mm i.d.) to enhance detectability; 100 nL sample volume was introduced allowing detection in the 19–80 mg L1 range. The method presented notable day-to-day migration time repeatability (less than 1 % after weeks) due to the fact it was conducted in a hydrodynamically closed separation compartment. In addition, excellent linearity (r > 0.994, 0.15–9.9 mg L1 range) and good precision (1–5 % at 1–6 mg L1 concentration level) were achieved. Rain, tap and process water served as matrices to assess the applicability of the proposed method. A MEKC method for the determination of 19 chlorophenols in river samples using electrochemical detection was developed by Kok and collaborators [246]. Detection was performed using a graphite-epoxy working electrode at a potential of 800 mV versus Ag/ AgCl. A palladium metal union was used to decouple the electric field from the electrochemical cell and a compensating pressure was applied during analysis. Detection limits from one to three orders of magnitude lower than with UV detection (10 mg L1) and precision better than 6 % (peak area) for 14 compounds (n ¼ 5) were achieved. With a SPE preconcentration procedure, LODs of 0.1 mg L1 in river water were reached.


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A cyclodextrin-mediated EKC method for the separation and analysis of chlorinated and substituted phenolic compounds was developed by Groom and Luong [231]. The procedure used negatively charged sulfobutylether-b-cyclodextrin (SB-b-CD) as secondary phase and 25 phenolic compounds including the 11 priority phenols were separated. A complexation model was used for investigating the effect of pH and cyclodextrin concentrations on the electrophoretic mobility. With this method pentachlorophenol was quantified in contaminated soil samples. An interesting device for the direct measurement of phenolic substances in the gas phase at levels relevant to occupational health was proposed by Kar and Dasgupta [247]. A small circular 100 mm Pt-wire loop was formed at the end of a fused-silica capillary. A thin film of 0.50 mmol L1 NaOH was inserted on the loop by immersion and withdrawal. Gas sampling was performed by transferring the film-bearing loop into a chamber through which air was aspirated. A part of the film content was then introduced into the capillary by gravity injection and then MEKC analysis was performed. A total of twelve chloro- and nitrophenols were selected for this study. Under the above sampling conditions, limits of detection for various phenols were in the low mg L1 range. 21.4.4

Amines

Amines are organic bases usually present in biological materials (biogenic amines), processed foods and beverages (of concern are the nitrosamines in fried bacon, smoked/ cured meat and fish, canned sausage, etc.) as well as environmental samples [106]. Several amines are strongly toxic and suspected carcinogens. Major sources of amines in the environment include several chemical industry sectors such as oil refining, synthetic polymers, adhesives, rubber tire manufacturing, leather tanning, pharmaceuticals, pesticide production and explosives [248]. Electrophoretic methods for biogenic and aromatic amines have been reviewed recently by Oguri [249]. The EKC analysis of aliphatic amines presents a few challenges: the hydrophilicity and polar character of certain small aliphatic amines impair strong interaction with commonly used micellized surfactants. In addition, the lack of chromophore in aliphatic amines hinders direct UV detection unless derivatizing schemes are devised. Derivatization, in general, will make the amines much more hydrophobic. The EKC separations of aliphatic amines include electrolyte systems comprising several surfactants (SDS [134,250– 252], cholate [253,254], Brij-35 [87]) modified by certain additives (urea [134,251,252] neutral cyclodextrins [251], organic solvents [251–254], mixed cyclodextrins [255]) and more unusual secondary phases (resorcarene-octacarboxylic acid [256], calixarene [66], poly(sodium 4-styrenesulfonate), PSSS [257]). Derivatization is performed when UV (pnitrobenzoyl chloride [134], o-phthaldialdehyde, OPA [251,255,256], dansyl chloride [252] as derivatizing agents), or LIF detection (3-(2-furoyl)quinoline-2-carboxaldehyde [253], 5-(4,6-dichloro-s-triazin-2-ylamino)fluorescein, DTAF [87], 1-pyrenebutanoic acid succinimidyl ester, PSE [254] as labelling agents) are designed. Alternatively, conductivity [257] and amperometric [250] detections have also been reported. Matchett and Brumley explored preconcentration methodologies based on ionexchange and ion-pairing solid-phase extraction for enriching aliphatic amines and alkanolamines in water [258]. Increased selectivity for resolving closely related amines was explored using nonionic surfactants (Tween 20) and pH adjustment. The indirect

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detection mode was shown to be particularly interesting in detecting primary through quarternary amines without derivatization. In this case, imidazole, N-ethylbenzylamine and benzyltriethylammonium chloride were used as electrolytes. The MEKC separation of biogenic amines was reported by Liu and Cheng using borate/SDS buffers [259]. The amines were labelled with N-(4-aminobutyl)-N-ethylisoluminol), ABEI, in the presence of N,N-disuccinimidyl carbonate, DSC, in methanolic medium for on-line chemiluminescence detection. Detection limits in the 1.2 1010 3.5 108 mol L1 range were obtained. A small amount of putrescine (2.98 mmol L1) and cadaverine (2.25 mmol L1) was found in a lake water sample, which was attributed to fish and shrimp corpse. The determination of dimethylamine (DMA) and other low-molecular-mass amines in atmospheric aerosol samples was investigated by Dabek-Zlotorzynska and Maruszak [260]. The method involved a precolumn derivatization with fluorescein isothiocyanate (FITC). Different variables that affect the derivatization (pH, FITC concentration, reaction time and temperature) and the separation (buffer concentration, addition of various organic modifiers, cyclodextrins) were studied. The estimated instrumental detection limit was 50 pg mL1 (109 mol L1), using LIF detection (Arþ laser) with excitation and emission wavelengths of 488 nm and 520 nm, respectively. The proposed CE method was shown to be one to two orders of magnitude more sensitive than available literature methods for derivatized amines (GC–MS and HPLC with fluorescence and chemiluminescence detection). Separation of aromatic amines has been approached by EKC methodologies using SDS [105,213,261–263], mixtures of SDS and nonionic surfactants [264,265], bile salts [204] with electrolyte modifiers (tetraalkylammonium salts [263], urea [264], organic solvents [105,204,213,261,264,265]). In addition, mixed-mode EKC separations where combinations of anionic soluble polymers [266] or crown ether [267,268] and cyclodextrins have also been reported. Since aromatic amines are chromophoric, detection is usually conducted by absorbance in the UV region although alternative detectors have been employed (CE–ESI–MS [105], electrochemical [91,269] and fluorescence [91] detection). With on-line enrichment techniques [262], LODs in the ng L1 range are attainable (see Figure 21.4). Mixed micellar systems constituting of three surfactant components, namely SDS, cholate, and Tween 80, were employed by Radhakrishnan and coworkers in the evaluation of 16 arylamine isomers in samples collected from a lake near an industrial area with several dyeing and chemical industries [270]. Wall and El Rassi described a precolumn derivatization procedure for anilines using fluorescein isothiocyanate (FITC) and their subsequent separation in the presence of glycosidic surfactants complexed with borate at high pH (in situ charged micelles) followed by LIF detection (LOD of 1010 mol L1) [271]. FITC precolumn derivatization of the anilines was performed in real water (e.g. tap and lake water) spiked with anilines at the LOD level. In later work, Wall, Chan and El Rassi described a surfactantmediated electrokinetic capillary chromatography (SM-EKC) system for the separation of 9-fluoroenylmethyl chloroformate (FMOC)-derivatized anilines [272]. Under these conditions, the FMOC-anilines were readily detected at the 106 mol L1 level by UV at 214 nm and at the 108 mol L1 level by laser-induced fluorescence (LIF) using a solidstate UV laser operating at 266 nm line as the excitation wavelength. FMOC precolumn


503

Figure 21.4 Sweeping-MEKC analysis of aromatic amines. Electrolyte: 50 mmol L1 phosphoric acid, 5 mmol L1 triethanolamine, 50 mmol L1 SDS, 50 mmol L1 urea and 20 % acetonitrile (pH 2). Other conditions: sample in phosphoric acid at the same conductivity as running electrolyte; injection length, 24 cm; 20 kV; 214 nm. Peak identification: (1) N-1-naphthylethylenediamine, (2) 3,4-dichloroaniline, (3) 3,5-dimethylaniline, (4) 2,4-dichloroaniline, (5) 2,3-dichloroaniline, (6) 2,5-dichloroaniline, (7) 3-chloroaniline, (8) 1-phenylethylamine, (9) N-ethylaniline, (10) 2-methylaniline, (11) 4-methoxyaniline, (12) 2-nitroaniline, and (13) 4-nitroaniline. (From J.P. Quirino, Y. Iwai, K. Otsuka and S. Terabe, Electrophoresis, 21, 2899–2903 (2000) by permission of Wiley-VCH Verlag)

derivatization was also performed in lake water spiked with anilines at a concentration near the LOD level. Kok and collaborators proposed two procedures for the determination of aniline derivatives in environmental water samples [91]. In the first procedure, anilines were separated as cations by CZE at low pH and detected by amperometry. The alternative procedure involved the derivatization of the anilines with fluorescamine and separation of the derivatives by MEKC. For fluorescence detection, a lamp-based fiber optics instrument was used. Detection limits were similar in both methods (ca 1 mg L1). However, the MEKC method presented a higher separation efficiency, shorter analysis time (4 min), higher reliability and ease-of-handling. Preliminary experiments with water samples

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collected in areas where pollution with anilines was expected showed that the method is highly specific. 21.4.5

Carbonyls

Low molecular-mass carbonyls are among the most abundant and ubiquitous volatile organic compounds in the atmosphere. They are produced from many sources such as industrial activity, incomplete combustion of fossil fuels and biomass [106]. A number of aldehydes is also emitted indoors (plastic, foam insulation, lacquers, etc.). As a source of free radicals, aldehydes play an important role in ozone formation, in urban smog events as well as in the photochemistry of the unpolluted troposphere. Aldehydes are recognized irritants of the eye and respiratory tract, and often, carcinogenic and mutagenic characteristics are attributed to them. The analysis of low-molecular mass carbonyls by capillary electromigration separation techniques has been challenging due to structural features: the molecules are essentially neutral and present no chromophoric groups for UV detection. Two methodological approaches are envisioned: in one of them, the generation of charged adducts is performed. The CZE separation of anionic bissulfite–aldehyde adducts is a fine example of this approach [273,274]. The second approach comprises the derivatization of the molecules to generate either neutral or charged UV-absorbing or fluorescing derivatives, usually assessed by EKC methods. Several derivatizing agents have been listed for that task, the most commonly used being 2,4-dinitrophenylhydrazine (DNPH) [274–277], 3-methyl-2-benzothiazoline hydrazine (MBTH) [278], 5-(dimethylamino)naphthalene1-sulfohydrazide (dansylhydrazine, DNSH) [279–281] and 4-hydrazinobenzoic acid (HBA) [282]. Strict EKC separations of aldehydes with real sample applications comprise the analysis of DNPH derivatives of four aldehydes in river water as reported by Takeda and collaborators [275]. The effects of pH (6 < pH < 9) and acetonitrile (5–15 %) in SDS electrolytes were studied. Recovery values for spiked tap and river water were in the range of 97–102 %. Detection limits for formaldehyde and acetaldehyde were 0.05 mg L1 and 0.08 mg L1, respectively. The authors demonstrated that the typical duplication of peaks during MEKC analysis of the DNPH-derivatized aldehydes results from isomerization of the hydrazones, forming the syn- and anti-derivative. DNPH derivatization of three aldehydes in stack gas of an organic chemical plant for further MEKC determination was reported by Wei and collaborators [276]. Gas samples were collected by two impingers arranged in series, containing the derivatizing agent. After extraction with carbon disulfide, and successive washing steps, the extracts were dried and resuspended in methanol prior to analysis. Detection limits in the order of 2 mg L1 were obtained for all derivatives. The analysis of five DNPH derivatives in vehicular emission samples was demonstrated by Tavares and collaborators using a neutral CD-MEKC electrolyte [274]. The method included a laborious sample preparation in which the exhaust gases were collected in two impingers arranged in series containing the prepurified DNPH reagent dissolved in acid. After sample collection, the content of the impingers undergoes several procedures until precipitation of the derivatives and resuspension in acetonitrile prior to analysis. Detection limits of 0.5–2 mg L1 with respect to the single aldehyde were


505

R

40

1

mAU

30 20 23 10 0

54 2

4

6

8

10

Time, (min) Figure 21.5 Separation of aldehyde-MBTH derivatives by MEKC. Electrolyte: 20 mmol L1 tetraborate buffer (pH 9.3), 50 mmol L1 SDS. Other conditions: derivatized sample was dissolved in tetraborate electrolyte to give a 30 mmol L1 solution (stacking); injection 12 s, 25 mbar; þ20 kV; 216 nm. Peak identification: (1) formaldehyde, (2) acrolein, (3) acetaldehyde, (4) propionaldehyde and (5) acetone; R, excess reagent

obtained. In a further study, MBTH derivatives of five aldehydes were determined indoors [278]. Air samples were collected in an impinger flask containing 0.05 % MBTH solution. The method had several advantages over established methods for aldehydes. It is worth mentioning that MBTH is available in high degree of purity, thus dispensing laborious reagent purification procedures needed with DNPH. The limits of detection with respect to each single aldehyde were in the range of 0.54–4.0 mg L1 and 11 mg L1 for acetone (see Figure 21.5). 21.4.6

Aromatic Sulfonates

Aromatic sulfonates and their amino- and hydroxy-derivatives are produced on a large scale in the chemical industry. Although the acute toxicity and the risk of bioaccumulation appears to be small, due to their high mobility in the aquatic compartments and limited biodegradability, aromatic sulfonates are reported to be persistent and widespread environmental pollutants. An overview of the electrophoretic methods for determination of benzene- and naphthalenesulfonates in water samples has been presented by Cugat, Borrul and Calull [283]. Due to the ionic character of sulfonates within the entire practical pH range of CZE and EKC separations, improved selectivity and resolution of positional isomers has been sought by means of interactions with cyclodextrins [284], nonionic [285,286] and cationic [286] surfactants and mixed micelles [287]. By using a fractional factorial design approach, an ion-pair chromatographic procedure was optimized and contrasted with a MEKC procedure for the separation of aromatic sulfonates as reported by Gennaro and collaborators [288]. During MEKC optimization, ten electrolyte compositions were investigated with low and high pH buffers containing SDS, Brij-35 and octylamine. Twenty-one compounds could be separated (see Figure 21.6). Both methods performed satisfactorily in terms of efficiency, resolution, precision,

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Figure 21.6 Separation of benzene- and naphthalenesulfonates by MEKC. Electrolyte: 25 mmol L1 tetraborate buffer (pH 9.0), 75 mmol L1 Brij-35 and 5 mmol L1 octylamine. Other conditions: injection 4 s, negative pressure; þ20 kV; 220 nm. Peak identification: (1) 2naphthalenesulfonic acid, (2) 8-amino-2-naphthalenesulfonic acid, (3) 2-amino-1-naphthalenesulfonic acid, (4) 1-naphthalenesulfonic acid, (5) 5-amino-2-naphthalenesulfonic acid, (6) 4-amino-1-naphthalenesulfonic acid, (7) 6-hydroxy-2-naphthalenesulfonic acid, (8) 1-amino5-naphthalenesulfonic acid, (9) 6-amino-1-hydroxy-3-naphthalenesulfonic acid, (10) 6amino-4-hydroxy-2-naphthalenesulfonic acid, (11) 2,6-anthraquinonedisulfonic acid, (12) 3-nitrobenzenesulfonic acid, (13) 4-hydroxy-1-naphthalenesulfonic acid, (14) 3-amino-2, 7-naphthalenedisulfonic acid, (15) 2-hydroxy-3,6-naphthalenedisulfonic acid, (16) 7-amino-1,3-naphthalenedisulfonic acid, (17) 2-amino-1,5-naphthalenedisulfonic acid, (18) 4-phenolsulfonic acid, (19) 1-hydroxy-3,6-naphthalenedisulfonic acid, (20) 4-hydroxy-3nitrobenzenesulfonic acid and (21) 1,2-benzenedisulfonic acid. (From S. Angelino, A.B. Prevot, M.C. Gennaro and E. Pramauro, J. Chromatogr. A., 845, 257–271 (1999), copyright 1999, with permission from Elsevier)

linearity and sensitivity. The contents of aromatic sulfonates in an industrial effluent were determined. Gooijer and collaborators reported the analysis of mono- and dinaphthalenesulfonates as well as hydroxy- and amino-derivatives in river water [289]. A complete separation of 23 naphthalenesulfonates was achieved.


21.4.7

507

Dyes

Synthetic dyes, including azo compounds, are a very important group of synthetic chemicals widely used as coloring agents in a variety of products, such as textiles, paper, leather, gasoline and foodstuffs. Due to their hydrophilic character and high solubility (they usually bear carboxylic or sulfonic acid groups in their structure), synthetic dyes persist after conventional water treatment procedures and can thus be distributed in the environment from urban and industrial wastewater [248]. When the simultaneous separation of a large number of synthetic dyes is attempted, EKC methodologies are usually preferred due to enhanced selectivity. Synthetic dye separation has been approached by buffered SDS [290,291], Brij 35 [292], and polymeric electrolytes [293], modified by cyclodextrins [291] and organic solvents [290,292]. MEKC and HPLC were compared for the analysis of eight environmentally significant azo dyes, mono-, and disulfonated compounds in the work of Cunha and Alpendurada [29]. The LOD was 19–230 mg L1 employing MEKC and 22–280 mg L1 employing HPLC regarding the assay of 500 mL of SPE preconcentrated water samples. Brumley and collaborators reported separations using capillary LC and MEKC for the analysis of synthetic dyes in environmental matrices [294]. Recovery data for spiked water and soil matrices were obtained for four dyes using SPE cartridges and disks followed by determination by MEKC. Capillary LC detection was performed by continuous-flow liquid secondary ion mass spectrometry (CF–LSI–MS) whereas MEKC used UV detection (214 nm). MEKC presented itself as a powerful screening and determinative technique, whereas capillary LC–MS provided a confirmatory tool. 21.4.8

Surfactants

Anionic surfactants, such as alkanesulfonates, alkyl sulfates and linear alkylbenzenesulfonates (LAS) are water soluble, surface-active materials, which are consumed in large quantities in industrial and commercial formulations. LAS surfactants used commercially are complex mixtures of homologues and positional isomers. In environmental studies, to trace up origin, and because degradation rates and toxicity are dependent on the alkyl chain length and the position of the phenyl ring, it is important to know the total content of LAS in addition to the homologues and isomeric distribution (see Figure 21.7). In a series of articles, Ramis-Ramos’s group explored the use of carboxylic and dicarboxylic acids, SDS, bile salts, organic solvents and association with alkylammonium ions to study the separation of LAS homologues and positional isomers [295,296], as well as alkyl ether sulfate oligomers [297]. The MEKC separation of mixtures of the surfactant classes coconut diethanolamide, cocamido propyl betaine and alkylbenzene sulfonate was studied [298]. Full resolution, assistance in peak assignment and improvement of the signal-to-noise ratio was achieved by multivariate data analysis. The procedure was successfully applied to the identification and quantification of the surfactants in household cleaners. Vogt and collaborators demonstrated the use of capillary electromigration separation techniques (CZE and MEKC modes) in the determination of LAS homologues and isomers in household products and waste-water samples [299]. The determination of homologue distribution was achieved in borate or phosphate buffers containing acetonitrile. This condition was applied to the analysis of sewage sludge for LAS after

508

ELECTROKINETIC CHROMATOGRAPHY C11

mAU 6 C12

5

C10

4 3

C13

2 1 0 1

2

3

4

5

min

Figure 21.7 Analysis of linear alkylsulfonates (LAS) by MEKC in a wastewater sample from an industrialized area. Electrolyte: 30 mmol L1 tris, 15 mmol L1 HIBA (pH 8), 40 % ACN and 15 mmol L1 Brij-35. Other conditions: injection 3 s, 50 mbar; þ30 kV; 200 nm. Peak identification: C10 – C13 LAS homologues

methanolic extraction, with an average recovery of 75.5 % and a limit of detection of 4 mg L1. Isomeric separation was only possible using electrolytes with high contents of SDS and acetonitrile as organic modifier. The identification of isomeric distribution in household products was possible. In an attempt to optimize the separation of complex mixtures of industrial surfactants, Desbe`ne and Rony studied the conditions for resolution of model mixtures of alkylbenzenes (precursor compounds), including benzene and a series of homologous compounds with alkyl chain lengths of C1–C16 [300]. The method developed allowed the separation of the alkylated compounds used as bases for the preparation of industrial alkylbenzenesulfonates and the surfactants produced from these precursors. 21.4.9

Endocrine Disruptors

Recently, it has been established that certain synthetic organic chemicals affect the reproductive health of higher organisms by contributing to infertility in various ways and even increasing the rate of cancer in reproductive organs. These chemicals have been termed environmental estrogens due to their disrupting effects on the endocrine system of hormone production and transmission [106]. In addition to organochlorine insecticides, PCBs and dioxins (covered in the previous sections), phenolic compounds such as bisphenol A and nonylphenol, plasticizers, such as phthalic acid esters, as well as pharmaceuticals such as synthetic estrogens, belong to the list of chemicals suspected to have endocrine disrupting effects. MEKC separation and on-line concentration of bisphenol A and alkyl phenols was attempted by Takeda and collaborators in a series of experiments using SDS and other alkyl chain anionic surfactants, bile salts and TTAB in organic solvent and cyclodextrin modified buffers [301–303]. After sweeping was performed, detection limits in the range of 7 to 159 mg L1 were achieved. By employing sulfated b-cyclodextrin binding constants were also determined [304].


509

Figure 21.8 Separation of endocrine disruptor compounds by MEKC. Electrolyte: 20 mmol L1 CAPS (pH 11.5), 25 mmol L1 SDS and 15 % acetonitrile. Other conditions: injection 5 s, 20 psi; þ20 kV; 200 nm. Peak identification: (1) estriol, (2) phenol, (3) 2,4,5-trichlorophenol, (4) bisphenol A, (5) pentachlorophenol, (6) butylphenol, (7) estrone, (8) 17b-estradiol, (9) diethylstilbestrol, (10) ethynylestradiol and (11) nonylphenol. (From B. Fogarty, F. Regan and E. Dempsey, J. Chromatogr. A., 895, 237–246, copyright 2000, with permission from Elsevier)

The inspection of several target endocrine disruptors in spiked river water [305,306] and in biosolids (sewage sludge and treated sludge) [307] was attempted by Regan and collaborators using MEKC electrolytes. A 25-min separation of 11 endocrine disruptors including chlorophenols, alkylphenols and estrogens was achieved in acetonitrile modified CAPS/SDS electrolytes [306] (see Figure 21.8). With low pH electrolytes, further modified by cyclodextrins, the migration of alkylphenols is reduced, and key compounds can be analyzed in less than 15 min, establishing the applicability of the technique for the routine environmental monitoring of these pollutants [305]. The potential of microemulsion electrokinetic chromatography (MEEKC) for the separation of priority endocrine disrupting compounds in wastewater samples was explored in later work [64]. Using a reverse migrating microemulsion, i.e. negative polarity at the electrode inlet and a pH 2.8 phosphate buffer containing octane, butanol and SDS, further modified by propanol, the separation of the breakdown products of alkylphenolic detergents, a few synthetic estrogens and the plastic monomer bisphenol A was demonstrated. Excessive use of phthalate esters in industrial applications, mainly as plasticizers, has given rise to their persistent presence in consumer goods and in the environment. Go´ mezHens and Aguilar-Caballos discussed the economic and social interest in the control of phthalate esters and the availability of analytical methodologies for areas such as environmental and food analyses [308]. MEKC separations of alkyl phthalate esters include the report of Isoo et al. (three compounds) with MEKC–APCI-MS detection

510


[105] and the reports of Ong et al. [309] (six compounds) and Takeda et al. [310] (ten compounds) with UV detection. In the latter, the use of SDS in buffered solutions modified by methanol seemed inappropriate for resolution of the highly hydrophobic analytes: separation was too long, ca 60 min, and resolution of the last two components (di-n-octyl and bis(2-ethylhexyl) phthalate esters) was not achieved as these compounds have extremely high retention factors. Long chain alkyl phthalate esters clearly demand methodologies in which a better selectivity with hydrophobic compounds is attained, such as those performed by MEEKC, or those using alternative surfactant systems. The occurrence and fate of pharmaceutically active compounds in aquatic environments as well as their removal is one of the emerging issues in environmental chemistry [311]. More than 80 pharmaceuticals from various prescription classes and related metabolites as well as medicinal products for veterinary use have been detected in aquatic environmental samples (sewage influent and effluent samples, surface and groundwater and even drinking water) as reported by studies carried out in several European countries, USA, Canada and Brazil [311]. Due to the polar character of pharmaceutical prescription drugs, many have been addressed advantageously by capillary electromigration separation techniques [4], although environmental applications are rare [312]. Among the apolar pharmaceuticals, estrogens have been receiving increased attention due to the already mentioned possible interference with the reproductive system of man and animals. Quirino and coworkers demonstrated the separation of seven clinically relevant steroids using MEEKC with low pH buffer and heptane/SDS/butanol microemulsion system [137]. Several on-line preconcentration strategies were tested. Peak-height based enhancement factors of 138 to 278 were attained when sweeping was applied. Furthermore, Kim and coworkers used flow-suppressed MEKC with cationic micelles and coated capillaries to separate three steroids [313]. At least 60-fold and about 600-fold increase in detection sensitivity were obtained in terms of peak heights by sample stacking and sweeping, respectively, reaching ca 3 108 mol L1 LOD levels (sweeping). Harino and collaborators assessed three estrogen related compounds in spiked water at the nanomolar level using off-line (SPE in C18 cartridges) combined with on-line (sweeping) preconcentration strategies [314].

21.5 Concluding Remarks Throughout the years, EKC capabilities have proven useful for the separation of compounds of environmental importance and various compounds were used as model analytes in theoretical studies. However, in the environmental analysis scenario, the major challenge has always been the inspection of real samples, where matrix effects and sensitivity issues come to play. Based on the diversity of applications presented in this current compilation, it becomes clear that EKC has attained a solid position among the separation techniques for environmental analysis by fulfilling its needs. Future directions will likely include refinement of preconcentration strategies and possibly continuing coupling of on-line and off-line procedures, as well as consolidation of detection schemes to achieve the desirable low concentration levels. In addition, with the advent of innovative approaches to hyphenate EKC and MS instruments,


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more robust methods are likely to emerge with enhanced sensitivity and superior selectivity, improving further the acceptance of EKC in the routine determination of pollutants.

Acknowledgements The authors wish to acknowledge the Conselho Nacional de Desenvolvimento Cientı´fico e Tecnolo´ gico (CNPq) and the Fundaç a˜ o de Amparo a` Pesquisa do Estado de Sa˜ o Paulo (Fapesp) of Brazil for financial support (Fapesp 04/08503-2; 04/08931-4) and fellowships (CNPq 306068/2003-6; Fapesp 02/10197-1).

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Index

Note: the following abbreviations have been used in this index. EKC – electrokinetic chromatography MEKC – micellar electrokinetic chromatography MEEKC – microemulsion electrokinetic chromatography acrylamide polymers 142–3, 144 acrylate polymers 142–3 additives, charged 160–1 alkaloids 359, 360 alkyl sulfonates 160 amines 272–3, 317 aromatic 502–3 biogenic 273, 431–5, 501, 502 environmental analysis 501–4 food analysis 431–5 tabulated list 487–8 amino acids 199, 272–3, 298–9 body fluid analysis 375 food and beverages 466, 467 photothermal detection 298–9 amperometric (electrochemical) detection applications 285 catecholamines 286 herbicides 480 purine bases 286 end-column detection and decoupling 284–5 microdisk electrodes 283–4 microfluidic devices 282, 365–6 overview 281–2 pharmaceutical analysis 355 amphetamines 315–16 anionic polymers 141–2, 143, 163, 166, 167 anionic surfactants 64, 66, 67 anions, inorganic 156–7, 159, 162–3, 165, 170–2

antibiotics 412 aromatic compounds 169–70 amines 328, 502–3 nitrobenzene and nitrotoluene derivatives 338–9 sulfonates 157, 160, 161, 170 environmental analysis 489, 505–8 artificial neural networks 107–8, 110, 118 atrazine 493, 494 avidin 322 band broadening and efficiency 18–19 beer and hop acids 445, 447, 448 beverages see food and beverages bile salts 86, 119, 314 body fluid analysis 411 binaphthyl derivatives 142 bioanalysis 298–9 enantiomeric separation 465–6 see also body fluids biogenic amines 273, 431–5, 501, 502 blood analysis see body fluids body fluids, analysis applications 411, 416 antibiotics 412 nitrogen–oxygen compounds 414–15 peptides, proteins and related compounds 412–14 sulfur-containing compounds 415–16 tabulated list 391–405


530

INDEX

body fluids, analysis ðContinuedÞ capillaries and coatings 406, 407 cyclodextrins 408 detection systems 409 laser-induced fluorescence 409 mass spectrometry 410–11 near-field thermal lens 301, 410 UV/Vis spectrophotometry 409 direct injection 375, 376–7 EKC modes and conditions 389, 406–9 buffer solutions 406–7 organic solvents 407–8 surfactants 389, 406 in-line electrophoretic preconcentration cation- and anion-exhaustive injection 389, 390 field-amplified electrokinetic injection 387 sample stacking techniques 386–7 sweeping 387–9 in-line sample enrichment 386 off-line sample pretreatment affinity chromatography 384, 386 compounds, matrices and procedures tabulated 376–84 filtration and centrifugation 375, 384–5 liquid–liquid extraction 385–6 microdialysis 375 solid phase extraction 385–6 overview 373–4 protein precipitation and ultrafiltration 377–8, 384–5 solubilized 375 sample preparation summarized 374–5, 376–84 bubble cell 256, 257 buffer solutions body fluid analysis 406–9 factors in optimization 96, 101 and mass spectrometry 324 MEEKC 116, 121–3 tabulated 126–9 MEKC 86–7 nonaqueous and enantiomeric separation 192–3 pharmaceutical analysis 358, 363 polymeric pseudostationary phases 138, 139 time-controlled pH gradients 238–9 zwitterionic TRIS buffer 122, 125

caffeine 330 capillaries, separation bare silica 42, 240, 406 borosilcate glass 240 coatings dynamic 244, 362 inner wall 244–7, 406, 407 critical micelle determination 42 detection windows 242, 255, 256–7 electric double layer and electroosmosis 243–7 Joule heat and temperature 248–50, 357–8 PTFE 240 rectangular 242, 256 sample introduction 251–3 surfactant interaction 42 capillary electrophoresis 4–5, 153–4 amperometric (electrochemical) detection 282–5 critical micelle concentration determination 34–51 described 4–5 flow counterbalanced 187–9 frontal analysis (FACCE) 42–3, 46, 47 instrumentation 236 ion-exchange particles 172–3 and laser-induced fluorescence 263–4 and mass spectrometry 307–11, 363–4 pharmaceutical analysis overview 353–6 validation of analytical procedures 356–65 synchronous cyclic technique 189 capillary isoelectric focusing 193–4 carbonyl compounds 488–9, 504–5 carboxylic acids 157, 161 carrier mode separations 189 catechins 436–40 catecholamines 286 cationic polymers 145, 161–3, 164–5 cationic surfactants 66, 68 cavity model of solution 56 cephalosporins 42 cetylammonium chloride 325 cetyltrimethylammonium bromide 83–4, 157, 435 CHARM model 201 chemical microchips see microfluidic devices chemometric models 105, 198–200, 311 chiral selectors combination of 189–92 development and choice 195–6

INDEX chiral separation see enantiomeric separation column availability 14 column length, virtual 15 complex equilibria, secondary 11–12 cosurfactants and MEEKC 116, 119 coumarin dyes 340–1, 342 counter current techniques 187 critical aggregation concentration 39 critical micelle concentration (CMC) determination of comparison of methods 33–4, 36, 45, 48–51 current intensity method 35–6 frontal methods 34, 42–5, 46, 47 zonal methods 34, 36–7 mobility 39–40 operating conditions discussed 41 retention factor 37–8 retention time 38–9 zeta potential 40–1 effect of organic solvents 67, 69 and MEEKC 115 and MEKC 80–1 table of CMC values 48–50, 82 crown ethers 170–1, 191, 194, 321 cryptand-22 170 cyclodextrins amino acids in food 431 anionic 167–9, 195–6 body fluid analysis 408 cationic 169–70, 195–6 and chlorpheniramine enantiomers 183–4 combined for dual chiral recognition 189–92 development and choice for enantiomeric separations 195–6 dienoic acids 117–18 enantiomeric separation on microfluidic device 346–7 mass spectrometry 315–16, 321, 329 microemulsion electrokinetic chromatography 122, 130 optimizing resolution 88–9, 101 polymeric pseudostationary phases 138, 141 as pseudostationary phases 166 zwitterionic 196 dendrimers 137–9, 146, 172 deoxychlolic acid 314 detection techniques

531

body fluid analysis 409–11 choice of 236, 254–5 pharmaceutical analysis 355 UV/Vis 255–7 see also amperometric detection; laserinduced fluorescence detection; mass spectrometry; photothermal detection detection window 242, 256, 257, 264 diazacrown ethers 170–1 dioxins 495–9 dodecyltrimethylammonium bromide 157 dyes 424, 427, 489–90, 507 fluorescent derivatives 271–7, 409–10 efficiency and theoretical plates 18–19 electrochemical detection see amperometric detection electrokinetic chromatography (EKC) overviews 79, 153–5, 235–6, 238–9, 389–409, 476–81 see also theory of EKC electrokinetic phenomena 4–5 electroosmosis 4–5 and electric double layer 243–4 velocity 5, 15, 80 electrophoretic mobility see mobility electrophoretic preconcentration see sample enrichment electrophoretic velocity 5, 80 elution modes normal 9–11, 12, 14 restricted 10, 14 reversed 9–10, 13, 14 enantiomeric separation anionic cyclodextrins 167–9 applications amino acids in food 431 association constants determination 470 bioanalysis 464–6 body fluids 408 enantiomeric excess determination 470 environmental analysis 468–70 food and beverage analysis 466–8 monitoring asymmetric transformation 470 ofloxacin 270 pharmaceutical analysis 355, 462–4 bile salts 86, 314, 411 chiral selectors 195–6 avidin 322 charged and uncharged 181

532

INDEX

enantiomeric separation ðContinuedÞ experimental design and optimization 101–2, 196–7 chemometric approach 198–200 mathematical models 200–2 method development and validation 461–2 univariate approach 197–8 mass spectrometry 315–16, 321, 329 microfluidic device 194–5, 346–7 and MEEKC 125 overview of EKC techniques 459–61 and polymer nanoparticles 146, 147 and polymerized surfactants 140–2 principles of effective mobility 182–3, 185–6 enantioselective and nonenantioselective phenomena 181–2 pressure driven chromatography and EKC compared 182 separation principle in chiral CE 179–81 techniques capillary isoelectric focusing 193–4 carrier mode separations 189 classification of 180 combination of chiral selectors 189–92 microfabricated electrophoretic devices 194–5, 346–7 mobility counterbalanced mode (FCCE) 184, 187–9 nonaqueous media 192–3 partial filling and counter-current techniques 187 synchronous cyclic capillary electrophoresis 189 endocrine disruptors 490–1, 508–10 enrichment, off-line see sample enrichment environmental analysis amines 501–4 aromatic 502, 503 tabulated list 487–8 aromatic sulfonates 505–6 carbonyl compounds 504–5 tabulated list 488–9 chiral compounds 468–70 detection and sensitivity 479 amperometric detection 480 laser-induced fluorescence 480 mass spectrometry 480–1 photothermal 299–301 sample enrichment 479

dyes 507 endocrine disruptors 131, 508–10 tabulated 490–1 herbicides 311, 314, 320, 327, 492–3, 494 MEKC 476–7 PAHs, PCBs and dioxins 469–70, 495–9 pesticides 320, 468–9, 482–6, 492–5 multiresidue analysis 492 tabulated list 482–6 phenols 499–501 tabulated list 486–7 surfactants 507–8 techniques and strategies 476–9 MEEKC 478 ephedrines 168 experimental design and optimization enantiomeric separation 101–2, 197–202, 461–2 experimental work summarized and tabulated 97–100 MEEKC 118–19 modelling 103 artificial neural networks 107–8, 110, 118 empirical models 105–7 enantiomeric separation 200–2 physiochemical 103–5 optimum parameters summarized 109–10 overview 95–6 pharmaceutical analysis 359 and polymeric pseudostationary phases 137–8 validation 108–9 enantiomeric separation 461–2 pharmaceutical analysis 356–66 explosives 338–9 fenoprofen 193 flavonoids 440, 442, 468 flow counterbalanced capillary electrophoresis 187–9 fluorescein reactive dyes 273, 274 fluorescence, theory of 264–5 see also laser-induced fluorescence food and beverages, analysis of 423 amines, biogenic 273, 431–2 tabulated list 433–4 amino acids 427–8, 431, 466–7 tabulated list 429–30 caffeine 448 carbohydrates 551 enantiomeric separation 466–8

INDEX

533

ethanol in wine 447 food additives 423 antioxidants 424, 427, 428 dyes and pigments 424, 427 preservatives 301, 427, 428 sweeteners 427, 428 tabulated list 425–6 fungicides in fruit juice 451 heterocyclic aromatic amines 435 hop and beer acids 8, 445, 447 long chain fatty acids 448, 451, 467 mycotoxins in milk 451 miscellaneous analytes 447 tabulated list 449–50 nitrosamines 434, 435 phenolic compounds 435 catechins in tea 436–40 flavonoids 440, 442, 468 phenolic acids and related compounds 440, 441 polyphenols 442, 444 procyanidins 440, 441, 444 vitamins 444–5, 446, 468 forensic analysis see body fluids frontal analysis continuous capillary electrophoresis (FACCE) 42–3, 46, 47

temperature 248–50, 357 commercial instruments 237–8 detection techniques 236, 254–5 UV/Vis spectrophotometric 255–7, 355 high voltage power supplies 247–8 Joule heat and capillary temperature 248–50, 357 overview 235–6 sample injection 250–1 electrokinetic 251, 357 hydrodynamic 251–3, 357 sample stacking 253–4 sample sweeping 253–4 see also amperometric detection; laserinduced fluorescence detection; mass spectrometry; microfluidic devices; photothermal detection ion separation, theory of 24–5 ion-exchange particles 172–3 ion-exchange phases see pseudostationary phases ion-pair reagents 89–90, 160–1 ionenes 145 ionization techniques (MS) 310, 328

Helmholtz–Smoluchowski equation 5, 40, 243 herbicides 494, 495 triazines 311, 314, 320, 327, 492–3 hexadecyltrimethyl ammonium bromide 244 high voltage power sources 247–8 homocystein 274 hop and beer acids 445, 447, 448 hydrophobic compounds and MEEKC 117, 121, 122, 124 and polymeric pseudostationary phases 137, 139–40, 141–2, 143, 145 sample stacking 254 hydrophobicity (log POW) 116–17, 125, 129–30

laser-induced fluorescence detection applications amines, amino acids, peptides 272–3 body fluid analysis 409–10 homocystein 274 nucleotides 276–7 ofloxacin 270 porphyrin and benzoporphyrin derivatives 270 riboflavins and flavins 269–70 saccharides 276, 277 serotonin 270–1 thiols 274 detector design 267 commercial detectors 267–8 laboratory made detectors 268–9 fluorescent derivatives and reactive dyes 271–7, 409–10 laser types 269 microfluidic devices 239 native fluorescence 269–71 overview 263–4

ibuprofen 193, 322, 323, 466, 467 injection see sample injection inorganic anions 156–7, 159, 162–3, 165, 170–2 instrumentation basic set-up 236, 238–9 capillaries, separation 240–3, 357 inner surface and electroosmosis 243–7

Joule heat and capillary temperature 248–50, 357

534

INDEX

laser-induced fluorescence detection ðContinuedÞ theoretical aspects electronic excitation 264–5 optimum laser power 266–7 photodegradation 264, 265 signal to noise ratio 265–6 L,L-leucylvalinate polymer 141 lidocaine 365 linear anionic polymers 141–2, 143 linear polymers 141–5 structure 142 lipophilicity 354 log POW 116–17, 125, 129–30 lysergic acid diethylamide 385–6, 390 macrocyclic polyamines 170–1 MALDI-TOF-MS 310, 332–3 markers micelle interacting 41–2, 51 and UV-transparent surfactants 43–5 and velocity determinations 15–16 mass spectrometry, EKC coupling to body fluid analysis 410–11 detection techniques 254, 255 direct introduction of pseudostationary phases 324, 363 atmospheric pressure chemical ionization 310, 328, 363 atmospheric pressure photoionization 310, 328, 363 cyclodextrins 329 high molecular-weight surfactants and nanoparticles 330–3 low sheath liquid flow 327 methods tabulated 325–6 micellar phases 324–9 reversed polarity system 327 semi-volatile fluorinated surfactants 329–30 surfactants and buffers 324 environmental analysis 480–1 interfacing 308–11 ionization techniques 310, 328 mass analyzers 310–11 sheath liquid interface 309, 310 off-line matrix assisted laser desorption ionization 310, 332–3 overview 307–8 partial filling approaches 311 co-polymers and polysurfactants 316–17

cyclodextrins 315–16 methods tabulated 312–13 micellar phases 311, 314–15 polymer nanoparticles 317 pharmaceutical analysis 363–4, 365 phase removal systems 322 voltage-switching with buffer renewal 322–4 polymeric pseudostationary phases 146–7 reverse-migrating phases 317 charged cyclodextrins 321 methods tabulated 318–19 micellar 317, 320–1 miscellaneous 321–2 matrix-assisted laser desorption ionization 310, 332–3 mebeverine 328 metal complexes 157, 160, 162 N-methylcarbamate 320, 494 micellar electrokinetic chromatography (MEKC) additives to aqueous phase cyclodextrins 88–9, 166–70 ion-pair reagents 89–90, 160–1 organic solvents 87–8 urea 90–1 buffer solution choice 86–7, 101 defined 79 instrumental set-up 236–40 micelle choice bile salts 86 ionic surfactants 82–4, 85, 155–9 micelle polymers 86 mixed micelles 66, 68–9, 86 nonionic surfactants 84, 86 zwitterionic surfactants 159–60 modelling 103–8 optimizing resolution 91–2, 101–2 overviews (body fluid analysis) 373–4, 389, 406–9 resolution equation 79–82, 104 temperature choice 87 theoretical background 79–82 micelles choice for MEKC optimization 82–4 formation described 34–5, 82 mixed surfactant 66–9, 86, 157–8 polymers 86 as pseudostationary phase 61–2, 155–61 microchips see microfluidic devices

INDEX microemulsion electrokinetic chromatography (MEEKC) applications body fluid analysis 408, 411 catechins 436, 440 chiral separation 125 environmental analysis 131 hop and beer acids 445, 447, 448 hydrophobicity (log POW) 116–17, 125, 129–30 natural product analysis 130–1 pharmaceutical analysis 130 quantitative analysis 130 tabulated list 126–9 vitamins 445, 446 comparison to other electromigration modes 117–18 cosurfactant 116 dual opposite injection CE 125 high speed analysis 125 method development and optimization 102, 118–19 microemulsions droplet formation 115–16 oil type and concentration 123 solvation parameter model 69–70 water-in-oil 123–4 organic solvents, addition of 121 overview 115–17 pH and buffers 121–3, 126–9 pressure assisted separation 124–5 sample preparation 123 surfactant type and concentration 119–21 temperature 123 microfluidic devices advantages and basic features 239, 337–8, 347–8 amperometric (electrochemical) detection 365–6 applications amino acids 340 coumarin dyes 340–1, 342 food analysis 432 nitrobenzene and nitrotoluene derivatives 338–9 norleucine enantiomers 346–7 peptides 343–6 pharmaceutical analysis 364 urine samples 343 cyclic planar microstruture 341–3

535

enantiomeric separation 194–5, 346–7 gradient elution on microchip 340–1 laser induced fluorescence 239 thermal lens spectrometry 295 two-dimensional separations 343–6 migration acids 19–23 bases 23–4 migration (time) window MEKC 81 resolution 12–15, 17 and temperature 87 mobile phase velocity 15–17 mobility critical micelle concentration determination 39–40 electroosmotic electric double layer 243–4 and enantiomeric separation 181–2 electrophoretic 10, 39–40 acid solutes 20–1, 23 bases 23–4 counterbalancing technique 187–9 and enantiomeric separation 182–3, 185–6 ions 24–5 and MEEKC 116–17 modelling and optimization artificial neural networks 107–8 catecholamines 158–9 empirical models 105–7, 311 enantiomeric separation 200–2 physiochemical models 103–5 molar refraction 57 nanoparticles 146, 317, 330 naphthalene dialdehyde 272 naphthalene disulfonates 157, 160, 161, 170, 506 natural product analysis 130–1 neurotransmitters 272 neutral solutes, separation theory of 12–18 nicotine and derivatives 118 norleucine enantiomers 346–7 nucleotides 276–7 off-line pretreatment see sample pretreatment on-line enrichment see sample enrichment optimizing separation flow chart for MEKC 91 see also experimental design; sample enrichment

536

INDEX

organic solvents 87–8, 121, 238 body fluid analysis 407–9 parabens 121–2 Pareto charts 106 partial-filling techniques 187, 308, 311–17 tabulated list 312–13 peak capacity 15 peptides 102, 160, 270, 272–3 body fluid analysis 412–14 microfluidic device 343–6 pesticides 101, 320, 468–9, 481–495 tabulated list 482–6 pH gradient, time-controlled 238–9 pH junction and sample enrichment 226–8 pharmaceutical analysis applications 354 antipsychotic SLV307 463 deprenyl 465 ibuprofen 466, 467 itraconazole 465 moxifloxacin hydrochloride 462–3 praziquantel 466 ritalin 463–4 thalidomide 466 tricyclic antidepressants 301 enantiomeric separations 355, 462–4 environmental analysis 510 mass spectrometry 363–4 MEEKC 130 overview 353–6 procedures accuracy 361 buffer selection 358 capillary conditioning 357 detection 358 limit of detection and quantitation 360 precision 360 response function and linearity 360 sample preparation and injection 357 specificity 359–60 validation of 356, 358–9 voltage and temperature 357–8 rapid analysis 361 dynamic coating 362 high electric field strength 361–2 multiple-injection procedure 362–3 short-end injection technique 362 phase removal systems 322–4 phase velocity ratio 14

phenols 101, 499–501 food analysis 435–44 tabulated list 486–7 phenylurea 492, 494, 495 photoacoustic techniques 290 photodegradation 264 photothermal detection applications antidepressants 295 bioanalysis 298–9 environmental analysis 299–301 etopside 301 food preservatives 301 nitroaromatic compounds 299–301 phenylthiohydantoin amino acids 298–9 urine samples 301 instrumentation 295–8 chip-based techniques 295 cross-beam techniques 295 far-field thermal lens detector 296, 299 near-field thermal lens detector 297–8 overview 289–91 theory 291–4 measuring principle 292–4 sensitivity and sample solvent 294 thermal lens effect 291–2, 293, 294 phytic acid 161 Placket–Burman design 101, 198, 200 polyallylamines 143–4 poly[amidoamine] dendrimers 146 polyamines 170–1 polybrene 145 polychorinated biphenyls (PCBs) 141, 495–9 poly(diallydimethylammonium bromide) 145 poly(diallyldimethylammonium chloride) 161–3 polyethyleneglycol coated capillaries 246 polyimide coated capillaries 240, 245–6, 256 polymer nanoparticles 146, 317 polymeric pseudostationary phases 71–4 acrylate and acrylamide polymers 142–3, 144 anionic polymers 141–2, 143, 163, 166, 167 cationic polymers 145, 161–3, 164–5 dendrimers 138, 146 and mass spectrometry 146–7 overview 137–8, 147 polyallylamines 143–4 polymer nanoparticles 146

INDEX polymerized surfactants 139–41 practical considerations 138 siloxane polymers 143, 144–5 structure of linear polymers 143 polymerized surfactants 139–41 and mass spectrometry 316 polynuclear aromatic hydrocarbons (PAHs) 139–40, 495–9 polyvinylsulphonate 166, 167 power sources, high voltage 247–8 pressure-assisted electromigration 239 pressure-driven chromatography 182 pretreatment see sample enrichment; sample pretreatment procaine 365 procyanidins 440, 444 protein and body fluid analysis 375, 384–5, 412–14 pseudostationary phases 3, 6–8, 79, 153–5 cationic surfactants 155–8 charged additives 160–1 cyclodextrins 166–70 diazacrown ethers 170–1 ion-exchange particles 172 ion-exchange schematic 155 macrocyclic polyamines 170–1 micelles and surfactants 155–60 see also micellar electrokinetic chromatography microemulsions 69–70, 74, 115–16, 123 see also microemulsion electrokinetic chromatography soluble polymers 161–6 solvation parameter model addition of organic solvents 67, 69 intermolecular interactions and free energy 56–8 polymeric phases 71–4 solute descriptors 58, 60–1 system constants 58 theoretical aspects interaction with ionizable solutes 22 mechanism 6–8 neutral phases 25 velocity determination 15–17 see also dendrimers; polymeric pseudostationary phase; surfactants purine bases 286 quaternary ammonium compounds 160

537

reactive dyes 271–7 resolution equation (MEKC) 12, 14, 79–82 resolution optimization see experimental design retention factors 80, 81 critical micelle concentration determination 37–8 ions 24, 25 neutral solutes 8–11 and organic solvents 87–8 and pharmaceutical analysis 354 and solvation parameter model 58 weak acids 19–20 weak bases 23–4 retention indices 17–18 retention time 38–9 saccharides 276, 277 sample enrichment, on-line applications 228–30 body fluids 286–9 dynamic pH junction 226–8 and environmental analysis 479 field amplified sample injection 226 overview 207–8 sample stacking 208, 253–4, 479 body fluids 386–7 charged analytes 208–10 neutral analytes 210–11 normal migration 211–12 reverse migration 213–16 sample sweeping 216, 253–4, 479 body fluids 387–9 charged analytes 220–1 with field amplified sample injection 226 high conductivity zone 221–2 with increased retention factors 223–6 low conductivity zone 221–2 manipulation of retention factors 221–2 neutral analytes 217–19 with pH junction 226–7 sample injection techniques dual opposite 125 electrokinetic injection 251 field amplified 226 hydrodynamic injection 251–3 multiple injection 362–3, 364 sample size and resolution 250–1 short-end 362

538

INDEX

sample pretreatment, off-line affinity chromatography 384, 386 compounds, matrices and procedures tabulated 376–84 filtration and centrifugation 375, 384–5 liquid–liquid extraction 385–6 microdialysis 375 solid phase extraction 385–6 separation capillaries see capillaries separation carriers (pseudostationary phases) 3, 6–8 neutral 25 velocity determination 15–17 see also pseudostationary phases serotonin 270–1 siloxane polymers 143, 144–5 Smoluchowki equation 5, 40, 243 sodium 11-acrylamidoundecanoate 139, 140 sodium cholate 86, 119, 427 sodium deoxycholate 86 sodium dodecyl sulphate (SDS) body fluid analysis 389 and coated capillaries 244, 246 hydrogen-bond acidity 83 mass spectrometry 324 and MEEKC 116, 119 and MEKC 80, 158 sodium N-undecenoxy carbonyl-L-isoleucinate 141 sodium N-undecenoxy carbonyl-L-leucinate 139, 141 sodium taurocholate 86 sodium taurodeoxycholate 86 sodium undecenyl sulfate 139 sodium undecylenate 139 solute descriptors 57–8, 60–1 solvation parameter model anionic surfactants 64–6, 67 cationic surfactants 66, 68 characteristic molecular volume 56–7 micelles as pseudostationary phases 61–2 microemulsions 68, 69–70, 74 mixed surfactant micelles 66–7, 68 model requirements 58–61 organic solvents, addition of 67, 69 overview 55–8 polymeric pseudostationary phases 71–4 selectivity equivalence of surfactant micelles 74

selectivity optimization and method development 74–5 solute descriptors 57–8, 60–1 system constants dodecyl sulfate micelles 65–6 microemulsions and vesicles 70 mixed micelles 68–9 polymeric pseudostationary phases 72–3 ratios for anionic surfactants 67 ratios for cationic surfactants 68 sodium cholate micelles 63 system properties and selectivity 62–4 vesicles 70, 71 solvents see organic solvents stacking, sample see under sample enrichment StarburstTM dendrimers 172 surfactants aggregation number 82 anionic 64, 66, 67, 120, 158–9 bile salts 86, 119, 314, 411 biosurfactants 86, 120 and body fluid analysis 389, 406 capillary interaction 42 cationic 66, 68, 83–4, 120, 155–8 and conductimetry 36 critical micelle concentration values 48–50 environmental analysis of 507–8 ionic and MEKC optimization 82–4 micelle formation 34–5, 83 mixed 66, 68–9, 86, 406 nonionic and MEEKC optimization 120 and MEKC optimization 84–5 polymerized 139–41, 330–3 selectivity related to polar group 83–4 semi-volatile fluorinated 329–30 type and concentration in MEEKC 82–4, 119–21 UV-transparent 43 zwitterionic 86, 159 see also critical micelle concentration sweeping see under sample enrichment symbols and abbreviations listed 26 synchronous cyclic technique 189 system constants and solvation parameter model 58–9 temperature effect on retention times 18 Joule heating of capillaries 245–50

INDEX and MEEKC 123 and MEKC 87 tetradecyltrimethylammonium bromide 157–8 thalidomide 355, 466 theoretical plates 18–19, 80–1 theory of electrokinetic chromatography electrokinetic phenomena 4–5 neutral solutes, separation of efficiency 18 peak capacity 15 resolution 12–15 retention factor 8–11 retention indices 17–18 secondary complex equilibria 11–12 velocities of mobile phase and separation carrier 15–17 overview 3–4 separation carrier 6–8 symbols and abbreviations listed 26 weak electrolytes, separation of application of neutral separation carriers 25 migration of acids 19–23 migration of bases 23–4 separation of ions 24–5 see also solvation parameter model

539

thermal lens spectrometry 295–8 thiols 274 trialkylammonium salts 90 triazines 311, 314, 320, 327, 492–3, 494 urea 90–1, 122 urine analysis see body fluids UV/Vis spectrophotometry 236, 255–7, 479 bubble and Z-cells 256–7 pharmaceutical analysis 355 validation 108–9 enantiomeric separation 461–2 pharmaceutical analysis 356–66 vesicles 70, 71 vitamins 158 food analysis 444–5, 468 warfarin 190–1, 192, 322 water-in-oil MEEKC 123–4 weak electrolytes, separation of 19–24 xanthones 122 Z-cell 256, 257 zeta potential 40–1

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