Solution Chemistry: Minerals and Reagents 1774072564, 9781774072561

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SOLUTION CHEMISTRY: MINERALS AND REAGENTS

SOLUTION CHEMISTRY: MINERALS AND REAGENTS

Edited by: Valeria Severino

ARCLER

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www.arclerpress.com

Solution Chemistry: Minerals and Reagents Valeria Severino

Arcler Press 2010 Winston Park Drive, 2nd Floor Oakville, ON L6H 5R7 Canada www.arclerpress.com Tel: 001-289-291-7705 001-905-616-2116 Fax: 001-289-291-7601 Email: [email protected] e-book Edition 2020 ISBN: 978-1-77407-395-7 (e-book) This book contains information obtained from highly regarded resources. Reprinted material sources are indicated. Copyright for individual articles remains with the authors as indicated and published under Creative Commons License. A Wide variety of references are listed. Reasonable efforts have been made to publish reliable data and views articulated in the chapters are those of the individual contributors, and not necessarily those of the editors or publishers. Editors or publishers are not responsible for the accuracy of the information in the published chapters or consequences of their use. The publisher assumes no responsibility for any damage or grievance to the persons or property arising out of the use of any materials, instructions, methods or thoughts in the book. The editors and the publisher have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission has not been obtained. If any copyright holder has not been acknowledged, please write to us so we may rectify. Notice: Registered trademark of products or corporate names are used only for explanation and identification without intent of infringement. © 2020 Arcler Press ISBN: 978-1-77407-256-1 (Hardcover)

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DECLARATION Some content or chapters in this book are open access copyright free published research work, which is published under Creative Commons License and are indicated with the citation. We are thankful to the publishers and authors of the content and chapters as without them this book wouldn’t have been possible.

ABOUT THE EDITOR

Valeria Severino obtained her PhD in Biological Processes and Biomolecules from the Second University of Naples in 2009. Her scientific interests concern the structural and functional characterization of proteins and peptides by using biochemical approaches. Fields of expertise comprises food chemistry, cellular biology, natural products and related applications. She published more than 40 papers on international peer-reviewed journals.

TABLE OF CONTENTS

List of Contributors .......................................................................................xv List of Abbreviations .................................................................................. xxiii Preface................................................................................................. ....xxvii Chapter 1

Solubility Products and Solubility Concepts .............................................. 1 Abstract ..................................................................................................... 1 Introduction ............................................................................................... 2 Definitions And Formulation Of Solubility Products ................................... 4 Solubility Product(S) For MnO2 .................................................................. 7 Calculation Of Solubility ........................................................................... 9 Nonequilibrium Solid Phases In Aqueous Media...................................... 21 Solubility Of Nickel Dimethylglyoximate ................................................. 28 Calculation Of Solubility In Dynamic Redox Systems .............................. 30 Final Comments....................................................................................... 37 References ............................................................................................... 40

Chapter 2

Role of Surfactants in Mineral Processing: An Overview......................... 49 Abstract ................................................................................................... 49 Introduction ............................................................................................. 50 Fundamentals Of Froth Flotation .............................................................. 52 Flotation Reagents ................................................................................... 56 Flotation Practice ..................................................................................... 65 Conclusions ............................................................................................. 66 References ............................................................................................... 68

Chapter 3

Sorption of Hydrophobic Organic Compounds on Natural Sorbents and Organoclays from Aqueous and Non-Aqueous Solutions: A Mini-Review......................................................................................... 71 Abstract ................................................................................................... 71

Introduction ............................................................................................. 72 Sorption Isotherms And Sorption Coefficient ............................................ 75 Hoc Binding To Soil Components And Sediments .................................... 83 Kaolinite .................................................................................................. 91 Experimental Determination Of Sorption Co-Efficient And Sorption Kinetics ............................................................................ 94 Conclusions ............................................................................................. 97 Acknowledgments ................................................................................... 98 Author Contributions ............................................................................... 98 References ............................................................................................. 100 Chapter 4

Aqueous Solution Surface Chemistry of Carbon Nanotubes .................. 113 Introduction ........................................................................................... 113 Overview of Analytical Techniques: Strengths And Weaknesses ............. 115 Functionalizing Carbon Nanotubes........................................................ 117 Applications Of Functionalized Carbon Nanotubes ............................... 122 Effect Of Functionalization On Colloidal Stability .................................. 125 Conclusions ........................................................................................... 130 Acknowledgments ................................................................................. 131 References ............................................................................................. 132

Chapter 5

Reverse Flotation................................................................................... 137 Abstract ................................................................................................. 137 Introduction ........................................................................................... 138 Process Of Reverse Flotation.................................................................. 140 Acknowledgments ................................................................................. 154 References ............................................................................................. 155

Chapter 6

Pulmonary Surfactant Preserves Viability of Alveolar Type II Cells Exposed to Polymyxin B In Vitro .................................................. 163 Abstract ................................................................................................. 163 Introduction ........................................................................................... 164 Materials And Methods .......................................................................... 165 Results ................................................................................................... 167 Discussion ............................................................................................. 171 Acknowledgments ................................................................................. 172 References ............................................................................................. 173

x

Chapter 7

Quenching of Tryptophan Fluorescence in a Highly Scattering Solution: Insights on Protein Localization in a Lung Surfactant Formulation ......................................................................... 175 Abstract ................................................................................................. 175 Introduction ........................................................................................... 176 Materials And Methods .......................................................................... 179 Results And Discussions......................................................................... 181 Conclusions ........................................................................................... 194 References ............................................................................................. 196

Chapter 8

Recent Advances in Solvents for the Dissolution, Shaping and Derivatization of Cellulose: Quaternary Ammonium Electrolytes and their Solutions in Water and Molecular Solvents............................ 203 Abstract ................................................................................................. 203 Introduction ........................................................................................... 204 General Synthesis Strategies For Quaternary Ammonium Electrolytes (QAES)....................................................................... 207 Mechanism Of Cellulose Dissolution By Neat QAES, Their Solutions In Water And Molecular Solvents ................................................. 208 Applications of QAES For Cellulose Dissolution, Shaping and Derivatization .............................................................................. 219 Salts of Superbases................................................................................. 240 Conclusions ........................................................................................... 244 Acknowledgments ................................................................................. 245 References ............................................................................................. 246

Chapter 9

Increased Solubility and Bioavailability of Hydroxy-Cr(III) Precipitates in the Presence of Hydroxamate Siderophores .................. 271 Abstract ................................................................................................. 271 Materials And Methods .......................................................................... 273 Results And Discussion .......................................................................... 276 Acknowledgements ............................................................................... 282 References ............................................................................................. 283

Chapter 10 Solubility of Cyclodextrins and Drug/Cyclodextrin Complexes ............. 287 Introduction ........................................................................................... 288 Physiochemical Properties Of Cyclodextrins .......................................... 292 How Much Solubilization Is Needed? .................................................... 295

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The Effect Of The Guest Molecule On The Cyclodextrin Solubility ......... 298 Excipients And Cyclodextrin Solubility................................................... 301 Conclusions And Directions................................................................... 303 References ............................................................................................. 305 Chapter 11 Prediction of Solubility of Active Pharmaceutical Ingredients in Single Solvents and Their Mixtures — Solvent Screening ...................... 313 Abstract ................................................................................................. 313 Introduction ........................................................................................... 314 Ideal Solutions ....................................................................................... 319 Nonideal Solutions ................................................................................ 323 Application Of Solution Thermodynamics In Industry ............................ 331 Conclusion ............................................................................................ 336 References ............................................................................................. 337 Chapter 12 Bismuth Telluride Solubility Limit and Dopant Effects on the Electronic Properties of Lead Telluride ................................................. 341 Abstract ................................................................................................. 341 Introduction ........................................................................................... 342 Experimental.......................................................................................... 344 Results And Discussion .......................................................................... 345 Conclusions ........................................................................................... 352 Acknowledgments ................................................................................. 352 References ............................................................................................. 353 Chapter 13 Decomposition and Mineralization of Dimethyl Phthalate in an Aqueous Solution by Wet Oxidation ............. 355 Abstract ................................................................................................. 356 Introduction ........................................................................................... 356 Experimental Materials And Methods ..................................................... 357 Results And Discussion .......................................................................... 360 Conclusions ........................................................................................... 369 Acknowledgment ................................................................................... 370 References ............................................................................................. 371 Chapter 14 Aqueous Solution Chemistry of Ammonium Cation in the Auger Time Window .................................... 375 Abstract ................................................................................................. 376 xii

Introduction ........................................................................................... 376 Methods ................................................................................................ 379 Results And Discussion .......................................................................... 382 Conclusion ............................................................................................ 390 Acknowledgements ............................................................................... 392 Author Contributions ............................................................................. 392 References ............................................................................................. 393 Chapter 15 Efficient Visible Light Photocatalysis of Benzene, Toluene, Ethylbenzene and Xylene (BTEX) in Aqueous Solutions using Supported Zinc Oxide Nanorods ................................................. 399 Abstract ................................................................................................. 400 Introduction ........................................................................................... 400 Materials And Methods .......................................................................... 402 Results And Discussion .......................................................................... 406 Conclusions ........................................................................................... 413 Acknowledgments ................................................................................. 414 References ............................................................................................. 415 Chapter 16 Desorption of 1,3,5-Trichlorobenzene from Multi-Walled Carbon Nanotubes: Impact of Solution Chemistry and Surface Chemistry ................................................................................. 423 Abstract ................................................................................................. 423 Introduction ........................................................................................... 424 Results And Discussion .......................................................................... 427 Experimental Section ............................................................................. 433 Conclusions ........................................................................................... 436 Acknowledgements ............................................................................... 437 References ............................................................................................. 438 Index ..................................................................................................... 443

xiii

LIST OF CONTRIBUTORS Anna Maria Michałowska-Kaczmarczyk Department of Oncology, The University Hospital in Cracow, Cracow, Poland Aneta Spórna-Kucab Faculty of Chemical Engineering and Technology, Cracow University of Technology, Cracow, Poland Tadeusz Michałowski Faculty of Chemical Engineering and Technology, Cracow University of Technology, Cracow, Poland Abhyarthana Pattanaik Department of Fuel and Mineral Engineering, Indian School of Mines, Dhanbad, India Rayasam Venugopal Department of Fuel and Mineral Engineering, Indian School of Mines, Dhanbad, India Francis Moyo Division of Pharmaceutical Chemistry, Faculty of Pharmacy, Rhodes University, Grahamstown 6140, South Africa Roman Tandlich Division of Pharmaceutical Chemistry, Faculty of Pharmacy, Rhodes University, Grahamstown 6140, South Africa Brendan S. Wilhelmi Department of Biochemistry, Microbiology and Biotechnology, Rhodes University, Grahamstown 6140, South Africa Stefan Balaz Department of Pharmaceutical Sciences, Albany College of Pharmacy and xv

Health Sciences Vermont Campus, 261 Mountain View Drive, Colchester, VT 05446, USA Anup K. Deb Chemistry Department, Middle Tennessee State University, Murfreesboro, Tennessee, USA Charles C. Chusuei Chemistry Department, Middle Tennessee State University, Murfreesboro, Tennessee, USA Fatma Deniz Öztürk Dicle University of Mining Engineering Department, Diyarbakır, Turkey Guido Stichtenoth Department of Pediatrics, University of Luebeck, Luebeck, Germany Egbert Herting Department of Pediatrics, University of Luebeck, Luebeck, Germany Mario Ru¨diger Department of Pediatric Intensive Care and Neonatology, Technical University Dresden, Dresden, Germany Andreas Wemho¨ner Department of Pediatric Intensive Care and Neonatology, Technical University Dresden, Dresden, Germany Luca Ronda Department of Medicine and Surgery, University of Parma, Parma, Italy Biopharmanet-TEC, University of Parma, Parma, Italy Barbara Pioselli Chiesi Farmaceutici, R & D Department, Parma, Italy Silvia Catinella Chiesi Farmaceutici, R & D Department, Parma, Italy Fabrizio Salomone Chiesi Farmaceutici, R & D Department, Parma, Italy xvi

Marialaura Marchetti Biopharmanet-TEC, University of Parma, Parma, Italy Stefano Bettati Department of Medicine and Surgery, University of Parma, Parma, Italy Biopharmanet-TEC, University of Parma, Parma, Italy Italian National Institute of Biostructures and Biosystems, Rome, Italy Marc Kostag Institute of Chemistry, University of São Paulo, Av. Prof. Lineu Prestes 748, 05508-000 São Paulo, SP, Brazil Kerstin Jedvert Bio-based Fibres, Swerea IVF, SE-431 22 Mölndal, Sweden Christian Achtel Centre of Excellence for Polysaccharide Research, Institute of Organic Chemistry and Macromolecular Chemistry, Friedrich Schiller University of Jena, Humboldtstraße 10, 07743 Jena, Germany Thomas Heinze Centre of Excellence for Polysaccharide Research, Institute of Organic Chemistry and Macromolecular Chemistry, Friedrich Schiller University of Jena, Humboldtstraße 10, 07743 Jena, Germany Omar A. El Seoud Institute of Chemistry, University of São Paulo, Av. Prof. Lineu Prestes 748, 05508-000 São Paulo, SP, Brazil William E. Dubbin Department of Earth Science, The Natural History Museum, London SW7 5BD, UK Tee Boon Goh Department of Soil Science, University of Manitoba, Winnipeg, MB R3T 2N2, Canada Phennapha Saokham Faculty of Pharmacy, Rangsit University, Pathum Thani 12000, Thailand xvii

Chutimon Muankaew Faculty of Pharmacy, Siam University, 38 Petchkasem Road, Phasi Charoen District, Bangkok 10160, Thailand Phatsawee Jansook Faculty of Pharmaceutical Sciences, Chulalongkorn University, 254 Phyathai Road, Pathumwan, Bangkok 10330, Thailand Thorsteinn Loftsson Faculty of Pharmaceutical Sciences, University of Iceland, Hofsvallagata 53, 107 Reykjavik, Iceland Ehsan Sheikholeslamzadeh Department of Chemical and Biochemical Engineering, Western University, Canada Sohrab Rohani Department of Chemical and Biochemical Engineering, Western University, Canada Dana Ben-Ayoun Department of Materials Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel Yaniv Gelbstein Department of Materials Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel Dar-Ren Ji Graduate Institute of Environmental Engineering, National Taiwan University, Taipei 106, Taiwan Chia-Chi Chang Graduate Institute of Environmental Engineering, National Taiwan University, Taipei 106, Taiwan Shih-Yun Chen Graduate Institute of Environmental Engineering, National Taiwan University, Taipei 106, Taiwan

xviii

Chun-Yu Chiu Department of Cosmetic Science and Application, Lan Yang Institute of Technology, Yilan 261, Taiwan Jyi-Yeong Tseng Graduate Institute of Environmental Engineering, National Taiwan University, Taipei 106, Taiwan Ching-Yuan Chang Graduate Institute of Environmental Engineering, National Taiwan University, Taipei 106, Taiwan Department of Chemical Engineering, National Taiwan University, Taipei 106, Taiwan Chiung-Fen Chang Department of Environmental Science and Engineering, Tunghai University, Taichung 407, Taiwan Sheng-Wei Chiang Chemical Engineering Division, Institute of Nuclear Energy Research, Atomic Energy Council, Lungtan, Taoyuan 325, Taiwan Zang-Sie Hung Graduate Institute of Environmental Engineering, National Taiwan University, Taipei 106, Taiwan Je-Lueng Shie Department of Environmental Engineering, National Ilan University, Yilan 260, Taiwan Yi-Hung Chen Department of Chemical Engineering and Biotechnology, National Taipei University of Technology, Taipei 106, Taiwan Min-Hao Yuan Graduate Institute of Environmental Engineering, National Taiwan University, Taipei 106, Taiwan Department of Chemical Engineering and Biotechnology, National Taipei University of Technology, Taipei 106, Taiwan xix

Daniel Hollas Department of Physical Chemistry, University of Chemistry and Technology, Prague, Technická 5, 16628, Prague, Czech Republic Marvin N. Pohl Helmholtz-Zentrum Berlin für Materialien und Energie, Methods for Material Development, AlbertEinstein-Straße 15, D-12489, Berlin, Germany Department of Physics, Freie Universität Berlin, Arnimallee 14, D-141595, Berlin, Germany Robert Seidel Helmholtz-Zentrum Berlin für Materialien und Energie, Methods for Material Development, AlbertEinstein-Straße 15, D-12489, Berlin, Germany Emad F. Aziz Helmholtz-Zentrum Berlin für Materialien und Energie, Methods for Material Development, AlbertEinstein-Straße 15, D-12489, Berlin, Germany School of Chemistry, Monash University, 3800 Clayton, Victoria, Australia Petr Slavíček Department of Physical Chemistry, University of Chemistry and Technology, Prague, Technická 5, 16628, Prague, Czech Republic J. Heyrovský Institute of Physical Chemistry, Dolejškova 3, 18223, Prague 8, Czech Republic Bernd Winter Helmholtz-Zentrum Berlin für Materialien und Energie, Methods for Material Development, AlbertEinstein-Straße 15, D-12489, Berlin, Germany Present address: Fritz-HaberInstitut der Max-Planck-Gesellschaft, Faradayweg 4-6, D-14195, Berlin, Germany Jamal Al-Sabahi Department of Petroleum and Chemical Engineering, College of Engineering, Sultan Qaboos University, AlKhoudh, Oman Chair in Nanotechnology for Water Desalination, Water Research Center, Sultan Qaboos University, Al-Khoudh, Oman Tanujjal Bora Center of Excellence in Nanotechnology, Asian Institute of Technology, Klong Luang, Pathumthani, Thailand xx

Mohammed Al-Abri Department of Petroleum and Chemical Engineering, College of Engineering, Sultan Qaboos University, AlKhoudh, Oman Chair in Nanotechnology for Water Desalination, Water Research Center, Sultan Qaboos University, Al-Khoudh, Oman Joydeep Dutta Functional Materials, Department of Applied Physics, School of Engineering Sciences, KTH Royal Institute of Technology, Kista, Stockholm, Sweden Xingmao Ma Department of Civil and Environmental Engineering, Southern Illinois University Carbondale, Carbondale, IL 62901, USA Sheikh Uddin Department of Civil and Environmental Engineering, Southern Illinois University Carbondale, Carbondale, IL 62901, USA

xxi

LIST OF ABBREVIATIONS AcO

Acetate

AGU

Anhydroglucose unit

Al

Allyl group

AlMeImCl

1-Allyl-3-methylimidazolium chloride

BuMeImCl

1-Butyl-3-methylimidazolium chloride

Bz

Benzyl group

CDI

N,N′-Carbonyldiimidazole

Cel

Cellulose

ChCl

Choline chloride

CMC

Carboxymethyl cellulose

DBN

1,5-Diazabicyclo[[4.3.0]non-5-ene

DBU

1,8-Diazabicyclo[[5.4.0]undec-7-ene

DFT

Density functional theory

DMAc

N,N-Dimethylacetamide

DMF

N,N-Dimethylformamide

DMPh

Dimethylphosphate

DMSO

Dimethyl sulfoxide

DP

Average degree of polymerization

DS

Average degree of substitution

DSC

Differential scanning calorimetry

EtMeImAcO

1-Ethyl-3-methylimidazolium acetate

Fo

Formate group

IL

Ionic liquid

MCC

Microcrystalline cellulose

MD

Molecular dynamics simulations

Me(OEt)

Methoxyethyl

MS

Molecular solvent

NMMO

N-Methylmorpholine N-oxide

NMP

N-Methyl-2-pyrrolidone

PHK

Prehydrolysis kraft

PrO

Proprionate group

QACl

Quaternary ammonium chloride

QAF

Quaternary ammonium fluoride

SA

Solvent acidity as determined by solvatochromic probes (also designated as α)

SB

Solvent basicity as determined by solvatochromic probes (also designated as β)

SEC

Size exclusion chromatography

SEM

Scanning electron microscopy

TBA

Tetra-(n-butyl)ammonium

TBAAcO

Tetra-(n-butyl)ammonium acetate

TBACN

Tetra-(n-butyl)ammonium cyanide

TBAF

Tetra-(n-butyl)ammonium fluoride

TBAOH

Tetra-(n-butyl)ammonium hydroxide

TBPOH

Tetra-(n-butyl)phosphonium hydroxide

TMG

Tetramethylguanidine, Tetramethylguanidinium

χ

Mole fraction

W

Mass fraction

CD

Cyclodextrin

CE

Complexation efficiency

CMβCD

Carboxymethyl-βCD

DMβCD

Dimethyl-βCD

DMαCD

Dimethyl-αCD

DMγCD

Dimethyl-γCD

DS

Degree of substitution

G1βCD

Glucosyl-βCD

G2βCD

Maltosyl-βCD

GUGβCD

Glucoronyl-glucosyl-βCD

HEβCD

Hydroxyethyl-βCD

HPMC

Hydroxypropyl methylcellulose

HPαCD

2-hydroxypropyl-αCD

HPγCD

Hydroxypropyl-γCD

Na CMC

Sodium carboxymethylcellulose

xxiv

PVA

Polyvinyl alcohol

PVP

Polyvinyl pyrrolidone

SBEγCD

Sulfobutylether-γCD

SUG

Sugammadex

TMβCD

Trimethyl-βCD

TMαCD

Trimethyl-αCD

TMγCD

Trimethyl-γCD

αCD

α-Cyclodextrin

βCD

β-Cyclodextrin

γCD

γ-Cyclodextrin

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PREFACE

“Solution Chemistry: Minerals and Reagents” offers a powerful tool for researches on the chemistry of liquid solutions covering several different fields as physical chemistry, molecular biology, biophysics, technology innovation and others. In solution chemistry, solvent plays an important role along with reagents, affecting many aspects including the dielectric, thermodynamic, or transport properties of electrolytes and nonelectrolytes in liquid solutions. Another crucial research field in solution chemistry is related to surfactants, which are compounds able to lower the surface or interfacial tension between two liquids, between a gas and a liquid, or between a solid and a liquid. Surfactants are widely used with different application fields and for many industrial processes such as flotation, enhanced oil recovery, soil remediation, and cleansing. They may act as detergents, wetting agents, emulsifiers, foaming agents, or dispersants. In particular, flotation technology has been used in industry since the end of the 1800s, still representing an important method for mineral processing. This book reports a unique collection of papers focused on solution chemistry, paying attention to minerals and reagents, thus exploring different processes such as solubility of various molecules, sorption, floating, desorption. Starting from a review on solubility products and solubility concepts, “Solution Chemistry: Minerals and Reagents” analyzes the role of surfactants in mineral processing, with a particular look to the sorption of hydrophobic organic compounds from aqueous and non-aqueous solutions, and to the aqueous solution surface chemistry of carbon nanotubes. In addition, the research field of nanotubes id detailed proposing a study on the desorption of 1,3,5-trichlorobenzene from multi-walled carbon nanotubes, analyzing the impact of solution chemistry and surface chemistry on this field. A biological point of view is also included, proposing a paper on pulmonary surfactants able to preserve the viability of alveolar type II cells exposed to polymyxin b. Moreover, an interesting topic in solution chemistry is related to the prediction of the solubility of active pharmaceutical ingredients in single solvents and their mixtures.

Finally, few works focused on minerals and mineralization in solution chemistry are presented here, including a paper about the decomposition and mineralization of dimethyl phthalate in an aqueous solution by wet oxidation. Overall, the information reported in this book will provide interesting and recent clues for upcoming trends in treating concepts, applications and research fields on solution chemistry, minerals and reagents.

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1 Solubility Products and Solubility Concepts

Anna Maria Michałowska-Kaczmarczyk1 , Aneta Spórna-Kucab2 , and Tadeusz Michałowski2 1

Department of Oncology, The University Hospital in Cracow, Cracow, Poland

Faculty of Chemical Engineering and Technology, Cracow University of Technology, Cracow, Poland

2

ABSTRACT The chapter refers to a general concept of solubility product Ksp of sparingly soluble hydroxides and different salts and calculation of solubility of some hydroxides, oxides, and different salts in aqueous media. A (criticized) conventional approach, based on stoichiometry of a reaction notation and the solubility product of a precipitate, is compared with the unconventional/ Citation: Anna Maria Michałowska-Kaczmarczyk, Aneta Spórna-Kucab and Tadeusz Michałowski (August 23rd 2017). Solubility Products and Solubility Concepts, Descriptive Inorganic Chemistry Researches of Metal Compounds, Takashiro Akitsu, IntechOpen, DOI: 10.5772/67840. Copyright: © 2017 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Solution Chemistry: Minerals and Reagents

correct approach based on charge and concentration balances and a detailed physicochemical knowledge on the system considered, and calculations realized according to generalized approach to electrolytic systems (GATES) principles. An indisputable advantage of the latter approach is proved in simulation of static or dynamic, two-phase nonredox or redox systems. Keywords: electrolytic two-phase systems, solubility, dissolution, static systems, dynamic systems, computer simulation, GATES, GEB

INTRODUCTION The problem of solubility of various chemical compounds occupies a prominent place in the scientific literature. This stems from the fact that among various properties determining the use of these compounds, the solubility is of the paramount importance. Among others, this issue has been the subject of intense activities initiated in 1979 by the Solubility Data Commission V.8 of the IUPAC Analytical Chemistry Division established and headed by S. Kertes [1], who conceived the IUPAC-NIST Solubility Data Series (SDS) project [2, 3]. Within 1979–2009, the series of 87 volumes, concerning the solubility of gases, liquids, and solids in liquids or solids, were issued [3]; one of the volumes concerns the solubility of various oxides and hydroxides [4]. An extensive compilation of aqueous solubility data provides the Handbook of Aqueous Solubility Data [5]. A remark. Precipitates are marked in bold letters; soluble species/ complexes are marked in normal letters. The distinguishing feature of a chemical compound sparingly soluble in a particular medium is the solubility product Ksp value. In practice, the known Ksp values are referred only to aqueous media. One should note, however, that the expression for the solubility product and then the Ksp value of a precipitate depend on the notation of a reaction in which this precipitate is involved. From this it follows the apparent multiplicity of Ksp’s values referred to a particular precipitate. Moreover, as will be stated below, the expression for Kspmust not necessarily contain ionic species. On the other hand, factual or seeming lack of Ksp’s value for some precipitates is perceived; the latter issue be addressed here to MnO2, taken as an example. Solubility products refer to a large group of sparingly soluble salts and hydroxides and some oxides, e.g., Ag2O, considered overall as hydroxides. Incidentally, other oxides, such as MnO2, ZrO2, do not belong to this group,

Solubility Products and Solubility Concepts

3

in principle. For ZrO2, the solubility measurements showed quite low values even under a strongly acidic condition [6]. The solubility depends on the prior history of these oxides, e.g., prior roasting virtually eliminates the solubility of some oxides. Moderately soluble iodine (I2) dissolves due to reduction or oxidation, or disproportionation in alkaline media [7–12]; for I2, minimal solubility in water is a reference state. For 8-hydroxyquinoline, the solubility of the neutral molecule HL is a reference state; a growth in solubility is caused here by the formation of ionic species: H2L+1 in acidic and L−1 in alkaline media. The Ksp is the main but not the only parameter used for calculation of solubility s of a precipitate. The simplifications [13] practiced in this respect are unacceptable and lead to incorrect/false results, as stated in [14–18]; more equilibrium constants are also involved with two-phase systems. These objections, formulated in the light of the generalized approach to electrolytic systems (GATES) [8], where s is the “weighed” sum of concentrations of all soluble species formed by the precipitate, are presented also in this chapter, related to nonredox and redox systems. Calculation of s gives an information of great importance, e.g., from the viewpoint of gravimetry, where the primary step of the analysis is the quantitative transformation of a proper analyte into a sparingly soluble precipitate (salt, hydroxide). Although the precipitation and further analytical operations are usually carried out at temperatures far greater than the room temperature, at which the equilibrium constants were determined, the values of s obtained from the calculations made on the basis of equilibrium data related to room temperature are helpful in the choice of optimal a prioriconditions of the analysis, ensuring the minimal, summary concentration of all soluble forms of the analyte, remaining in the solution, in equilibrium with the precipitate obtained after addition of an excess of the precipitating agent; this excess is referred to as relative to the stoichiometric composition of the precipitate. The ability to perform appropriate calculations, based on all available physicochemical knowledge, in accordance with the basic laws of matter conservation, deepens our knowledge of the relevant systems. At the same time, it produces the ability to acquire relevant knowledge in an organized manner—not just imitative, but focused on heuristics. This viewpoint is in accordance with constructivist teaching, based on the belief that learning occurs, as learners are actively involved in a process of meaning and knowledge construction, as opposed to passively receiving information [19].

4

Solution Chemistry: Minerals and Reagents

DEFINITIONS AND FORMULATION OF SOLUBILITY PRODUCTS The Ksp value refers to a two-phase system where the equilibrium solid phase is a sparingly soluble precipitate, whose Ksp value is measured/ calculated according to defined expression for the solubility product. This assumption means that the solution with defined species is saturated against this precipitate, at given temperature and composition of the solution. However, often a precipitate, when introduced into aqueous media, is not the equilibrium solid phase, and then this fundamental requirement is not complied, as indicated in examples of the physicochemical analyses of the systems with struvite MgNH4PO4 [20, 21], dolomite CaMg(CO3)2 [22, 23], and Ag2Cr2O7. The values of solubility products Ksp (usually represented by solubility constant pKsp = −logKsp value) are known for stoichiometric precipitates of AaBb or AaBbCc type, related to dissociation reactions: (1) (2) where A and B or A, B, and C are the species forming the related precipitate; charges are omitted here, for simplicity of notation. The solubility products for more complex precipitates are unknown in the literature. The precipitates AaBbCc are known as ternary salts [24], e.g., struvite, dolomite, and hydroxyapatite Ca5(PO4)3OH.

The solubility products for precipitates of AaBb type are most frequently met in the literature. In these cases, for A are usually put simple cations of metals, or oxycations [25]; e.g., BiO+1 and UO2+2 form the precipitates: BiOCl and (UO2)2(OH)2. As B, simple or more complex anions are considered, e.g., Cl−1, S−2, PO4−3, Fe(CN)6−4, in AgCl, HgS, Zn3(PO4)2, and Zn2Fe(CN)6. In different textbooks, the solubility products are usually formulated for dissociation reactions, with ions as products, also for HgS (3)

although polar covalent bond exists between its constituent atoms [26]. Very low solubility product value (pKsp = 52.4) for HgS makes the dissociation according to the scheme presented by Eq. (3) impossible, and even verbal formulation of the solubility product is unreasonable. Namely, the ionic product x = [Hg+2][S–2] calculated at [Hg+2] = [S–2] = 1/NA exceeds Ksp, 1/

Solubility Products and Solubility Concepts

5

NA2> Ksp (NA – Avogadro’s number); the concentration 1/NA = 1.66∙10–23 mol/L corresponds to 1 ion in 1 L of the solution. The scheme of dissociation into elemental species [14] (4) is far more favored from thermodynamic viewpoint; nonetheless, the solubility product (Ksp) for HgS is commonly formulated on the basis of reaction (3). We obtain pKsp1 = pKsp – 2A(E01−E02), where E01 = 0.850 V for Hg+2 + 2e–1 = Hg, E02 = –0.48 V for S + 2e–1 = S–2, 1/A = RT/F⋅ln10, A = 16.92 for 298 K; then pKsp1 = 7.4. Equilibrium constants are usually formulated for the simplest reaction notations. However, in this respect, Eq. (4) is simpler than Eq. (3). Moreover, we are “accustomed” to apply solubility products with ions (cations and anions) involved, but this custom can easily be overthrown. A similar remark may concern the notation referred to elementary dissociation of mercuric iodide precipitate where I2 denotes a soluble form of iodine in a system. From

(5) (6)

we obtain pKsp1 = pKsp – 2A(E01–E03), where

The species in the expression for solubility products do not predominate in real chemical systems, as a rule. However, the precipitation of HgS from acidified (HCl) solution of mercury salt with H2S solution can be presented in terms of predominating species; we have (7) Eq. (7) can be applied to formulate the related solubility product, Ksp2, for HgS. To be online with customary requirements put on the solubility product formulation, Eq. (7) should be rewritten into the form (7a)

Applying the law of mass action to Eq. (7a), we have

(8) where [HgCl4 ] = 10 [Hg ][Cl ] , [H2S] = 10 [H ] [S ], Ksp (Eq. (3)). The solubility product for MgNH4PO4 can be formulated on the basis of reactions: –2

15.07

+2

–1 4

20.0

+1 2

–2

6

Solution Chemistry: Minerals and Reagents

(9) (10) (11) where K1N = [H+1][NH3]/[NH4+1], K2P = [H+1][HPO4–2]/[H2PO4–1], K3P = [H+1] [PO4–3]/[HPO4–2], [MgOH+1] = K1OH[Mg+2][OH–1], KW = [H+1][OH–1].

Note that only uncharged (elemental) species are involved in Eqs. (4) and (5); H2S enters Eq. (8), and NH3 enters Eqs. (10) and (11). This is an extension of the definition/formulation commonly met in the literature, where only charged species were involved in expression for the solubility product. Note also that small/dispersed mercury drops are neutralized with powdered sulfur, according to thermodynamically favored reaction [27]

reverse to Eq. (4). Some precipitates can be optionally considered as the species of AaBb or AaBbCc type. For example, the solubility product for MgHPO4 can be written as Ksp = [Mg+2][HPO4–2] or Ksp1 = [Mg+2][H+1][PO4– 3 ] = KspK3P.

The ferrocyanide ion Fe(CN)6–4 (with evaluated stability constant K6 ca. 1037) can be considered as practically undissociated, i.e., Fe(CN)6–4 is kinetically inert [28], and then it does not give Fe+2 and CN–1 ions. The solubility product of Zn2Fe(CN)6 is Ksp = [Zn+2]2[Fe(CN)6–4]. Therefore, consideration of Zn2Fe(CN)6 as a ternary salt with Ksp1 = [Zn+2]2[Fe2+][CN–1]6 = Ksp/K6 is not acceptable. In principle, the solubility product values are formulated for stoichiometric compounds, and specified as such in the related tables. However, some precipitates obtained in laboratory have nonstoichiometric composition, e.g., dolomite Ca1+xMg1-x(CO3)2 [22, 23], FexS [29]. In particular, FexS can be rewritten as Fe+2pFe+3qS; from the relations: 2p + 3q − 2 = 0 and p + q = x, we get q/p = 2(1 − x)/(3x − 2). In this context, some remark needs a formulation of Ksp for some hydroxyoxides (e.g., FeOOH) and oxides (e.g., Ag2O). The related solubility products are formulated after completion of the corresponding reactions with water, e.g., FeOOH + H2O = Fe(OH)3, Fe2O3∙xH2O + (3 − x)H2O = 2Fe(OH)3⇒ Fe(OH)3 = Fe+3 + 3OH–1 ⇒ Ksp = [Fe+3][OH–1]3; Ag2O + H2O = 2AgOH ⇒ AgOH = Ag+1 + OH–1 ⇒ Ksp = [Ag+1][OH–1], see it in the context with gcd(a,b) = 1.

Solubility Products and Solubility Concepts

7

The solubility product can be involved not only with dissociation reaction. For example, the dissolution reaction Ca(OH)2 + 2H+1 = Ca+2 + 2H2O [30], characterized by Ksp1 = [Ca+2]/[H+1]2, is involved with Ksp = [Ca+2][OH–1]2 in the relation Ksp1 = Ksp/Kw2. In Ref. [31], the solubility product is associated with formation (not dissociation) of a precipitate.

SOLUBILITY PRODUCT(S) FOR MNO2

The scheme presented above cannot be extended to all oxides. For example, one cannot recommend the formulation of this sequence for MnO2, i.e., MnO2+ 2H2O = Mn(OH)4 ⇒ Mn(OH)4 = Mn+4 + 4OH–1 ⇒ Ksp0 = [Mn+4] [OH–1]4; Mn+4 ions do not exist in aqueous media, and MnO2 is the sole Mn(+4) species present in such systems. In effect, Ksp0 for MnO2 is not known in the literature, compare with Ref. [32]. However, the Ksp for MnO2 can be formally calculated according to an unconventional approach, based on the disproportionation reaction (12) reverse to the symproportionation reaction 2MnO4 + 3Mn+2 + H2O = 5MnO2+ 4H+1. The Ksp = Ksp1 value can be found there on the basis of E01 and E02values [33], specified for reactions: −1

(13) (14) Eqs. (13) and (14) are characterized by the equilibrium constants: (15) defined on the basis of mass action law (MAL) [14], where logKe1 = 3⋅A⋅E01, logKe2 = 2⋅A⋅E02, A = 16.92. From Eqs. (13) and (14), we get (16) Assuming [MnO2] = 1 and [H2O] = 1 on the stage of the Ksp1 formulation for reaction (16), equivalent to reaction (12), we have

and then

(17)

Solution Chemistry: Minerals and Reagents

8

(18) (19) The solubility products with MnO2 involved can be formulated on the basis of other reactions. For example, addition of (20)

to Eq. (14) gives Multiplication of Eq. (21) by 3, and then addition to Eq. (13a)

(21)

(reverse to Eq. (13)) gives the equation

and its equivalent form, obtained after simplifications,

(22)

(22a) Eq. (22) and then Eq. (22a) is characterized by the solubility product (23)

where

(24) for Mn + e = Mn (E03 = 1.509 V) (reverse to Eq. (20)), logKe3 = A⋅E03. Then +3

−1

+2

(25) Formulation of Kspi for other combinations of redox and/or nonredox reactions is also possible. This way, some derivative solubility products are obtained. The choice between the “output” and derivative solubility product values is a matter of choice. Nevertheless, one can choose the Ksp3 value related to the simplest expression for the solubility product Ksp3 = [Mn+2] [MnO4−2] involved with reaction 2MnO2 = Mn+2 + MnO4−2. As results from calculations, the low Kspi (i = 1,2,3) values obtained from the calculations should be crossed, even in acidified solution with the related

Solubility Products and Solubility Concepts

9

manganese species presented in Figure 1. In the real conditions of analysis, at Ca = 1.0 mol/L, the system is homogeneous during the titration, also after crossing the equivalence point, at Φ = Φeq > 0.2; this indicates that the corresponding manganese species form a metastable system [34], unable for the symproportionation reactions. 0 MnSO 4

-4

Mn(OH) +2

Mn +2

MnO 4- 1

log[Xi]

-8

-12 Mn(OH) +1

-16 Mn(OH) +2

-20 0.0

MnO 4- 1

MnO 4- 2

Mn +3

0.1

0.2

0.3

0.4

F Figure 1. The log[Xi] versus Φ relationships for different manganese species Xi, plotted for titration of V0 = 100 mL Figure The log[Xi] versus Φ relationships for different manganese species solution of FeSO1: 4 (C0 = 0.01 mol/L) + H2SO4 (Ca = 1.0 mol/L) with V mL of C = 0.02 mol/L KMnO4; Φ = CV/(C0V0). The species are indicated the corresponding lines. Xi,Xi plotted forat titration of V0 = 100 mL solution of FeSO4 (C0 = 0.01 mol/L)

+ H2SO4 (Ca = 1.0 mol/L) with V mL of C = 0.02 mol/L KMnO4; Φ = C·V/ (C0∙V0). The species Xi are indicated at the corresponding lines.

4. Calculation of solubility

CALCULATION OF SOLUBILITY In this section, we compare two options applied to the subject in question. The first/criticized option, met commonly in different textbooks, is based on the considerations, In this section, we compare two options applied to stoichiometric the subject in question. resulting from dissociation of a precipitate, characterized by the solubility product Ksp value, The first/criticized option, met commonly in different textbooks, is andbased considered a priori as an equilibrium solid phase in the system in question; the solubility on the stoichiometric considerations, resulting from dissociation value obtained this way will be denoted by s* [mol/L]. The second option, considered as a of a precipitate, characterized by the solubility product Ksp value, and correct resolution of the problem, is based on full physicochemical knowledge of the system, considered a priori as an equilibrium solid phase in the system in question; not limited only to Ksp value (as in the option 1); the solubility value thus obtained is denoted solubility value obtained this way will expressed be denoted by s*and [mol/L]. The as sthe [mol/L]. The second option fulfills all requirements in GATES involved with second option, considered as a correct resolution of the problem, is based basic laws of conservation in the systems considered. Within this option, we check, among on whether full physicochemical of the system, notThe limited to Ksp others, the precipitate is knowledge really the equilibrium solid phase. results only (s*, s) obtained according to both options (1 and 2) are compared for the systems of different degree of complexity. The unquestionable advantages of GATES will be stressed this way. 4.1. Formulation of the solubility s* *

o

o

10

Solution Chemistry: Minerals and Reagents

value (as in the option 1); the solubility value thus obtained is denoted as s [mol/L]. The second option fulfills all requirements expressed in GATES and involved with basic laws of conservation in the systems considered. Within this option, we check, among others, whether the precipitate is really the equilibrium solid phase. The results (s*, s) obtained according to both options (1 and 2) are compared for the systems of different degree of complexity. The unquestionable advantages of GATES will be stressed this way.

Formulation of the Solubility s* The solubility s* will be calculated for a pure precipitate of: (1o) AaBb or (2o) AaBbCc type, when introduced into pure water. Assuming [A] = a∙s* and [B] = b∙s*, from Eq. (1), we have

(26) and assuming [A] = a∙s , [B] = b∙s , [C] = c∙s , from Eq. (2), we have *

*

*

(27) As a rule, the formulas (26) and (27) are invalid for different reasons, indicated in this chapter. This invalidity results, among others, from inclusion of the simplest/minor species in Eq. (26) or (27) and omission of hydroxo-complexes + other soluble complexes formed by A, and protocomplexes + other soluble complexes, formed by B. In other words, not only the species entering the expression for the related solubility product are present in the solution considered. Then the concentrations: [A], [B] or [A], [B], and [C] are usually minor species relative to the other species included in the respective balances, considered from the viewpoint of GATES [8].

Dissolution of Hydroxides We refer first to the simplest two-phase systems, with insoluble hydroxides as the solid phases. In all instances, s* denotes the solubility obtained from stoichiometric considerations, whereas s relates to the solubility calculated on the basis of full/attainable physicochemical knowledge related to the system in question where, except the solubility product (Ksp), other physicochemical data are also involved. Applying formula (26) to hydroxides (B = OH−1): Ca(OH)2 (pKsp1 = 5.03)

Solubility Products and Solubility Concepts

11

and Fe(OH)3 (pKsp2 = 38.6), we have [35] (28) (29) respectively. However, Ca+2 and Fe+3 form the related hydroxo-complexes: [CaOH+1] = 101.3∙[Ca+2][OH−1] and: [FeOH+2] = 1011.0∙[Fe+3][OH−1], [Fe(OH)2+1] = 1021.7∙[Fe+3][OH−1]2; [Fe2(OH)2+4] = 1025.1∙[Fe+3]2[OH−1]2 [31]. The corrected expression for the solubility of Ca(OH)2 is as follows (30) Inserting [Ca ] = Ksp1/[OH ] and [OH ] = KW/[H ], [H ] = 10 14.0 for ionic product of water, KW) into the charge balance +2

−1 2

−1

+1

+1

−pH

(pKW= (31)

we get, by turns,

(32) where pH=−log[H+1]pH=−log[H+1]. Applying the zeroing procedure to Eq. (30), we get pH0 = 12.453 (Table 1), where: [Ca+2] = 0.0116, [CaOH+1] = 0.00656, s = 0.0182 mol/L (Eq. (28)). As we see, [CaOH+1] is comparable with [Ca+2], and there are none reasons to omit [CaOH+1] in Eq. (28). Table 1: Zeroing the function (30) for the system with Ca(OH)2 precipitate introduced into pure water (copy of a fragment of display) pH 12.451 12.452 12.453 12.454 12.455

y(pH) 0.000377 0.000193 8.30E-06 −0.000176 −0.000359

[OH−1] 0.02825 0.02831 0.02838 0.02844 0.02851

[Ca+2] 0.01169 0.01164 0.01159 0.01153 0.01148

[CaOH+1] 0.006592 0.006577 0.006561 0.006546 0.006531

The alkaline reaction in the system with Ca(OH)2 results immediately from Eq. (29): [OH−1] – [H+1]

.

Analogously, for the system with Fe(OH)3, we have the charge balance (33)

12

Solution Chemistry: Minerals and Reagents

and then Eq. (32) zeroes at pH0 = 7.0003 (Table 2), where the value

(34)

Table 2: Zeroing the function (32) for the system with Fe(OH)3 precipitate introduced into pure water (copy of a fragment of display) pH

y(pH)

[Fe+3]

[FeOH+2]

[Fe(OH)2+1]

[Fe2(OH)2+4]

7.0001

7.99E-11

2.510E-18

2.511E-14

1.259E-10

7.936E-25

7.0002

3.38E-11

2.508E-18

2.510E-14

1.258E-10

7.929E-25

7.0003

−1.23E-11

2.507E-18

2.508E-14

1.258E-10

7.921E-25

7.0004

−5.84E-11

2.505E-18

2.507E-14

1.258E-10

7.914E-25

7.0005

−1.04E-10

2.503E-18

2.506E-14

1.257E-10

7.907E-25

(35) is close to s ≅ [Fe(OH)2 ] = 10 . Alkaline reaction for this system, i.e., [OH−1] > [H+1], results immediately from Eq. (30), and pH0 = 7.0003 (>7). +1

–9.9

At pH = 7, Fe(OH)2+1 (not Fe+3) is the predominating species in the system, [Fe(OH)2+1]/[Fe+3] = 1021.7–14 = 5∙107, i.e., the equality/assumption s* = [Fe+3] is extremely invalid. Moreover, the value [OH−1] = 3∙s* = 2.94∙10–10 = 10–9.532, i.e., pH = 4.468; this pH-value is contradictory with the inequality [OH−1] > [H+1] resulting from Eq. (31). Similarly, extremely invalid result was obtained in Ref. [36], where the strong hydroxo-complexes were totally omitted, and weak chloride complexes of Fe+3 ions were included into considerations. Taking only the main dissociating species formed in the solution saturated with respect to Fe(OH)3, we check whether the reaction Fe(OH)3 = Fe(OH)2+1+ OH−1 with Ksp1 = [Fe(OH)2+1][OH−1] = 1021.7∙10–38.6 = 10–16.9 can be used for calculation of solubility s›=(Ksp1)1/2s›=(Ksp1)1/2 for Fe(OH)3; the answer is also negative. Simply, the main part of OH−1 ions originates here from dissociation of water, where the precipitate has been introduced, and then Fe(OH)2+1 and OH−1 differ significantly. As we see, the diversity in Ksp value related to a precipitate depends on its dissociation reaction notation, which disqualifies the calculation of s* based solely on the Ksp value. This fact was not stressed in the literature issued hitherto. Concluding, the application of the option 1, based on the stoichiometry of the reaction (29), leads not only to completely inadmissible results for s+, but also to a conflict with one of the fundamental rules of conservation obligatory in electrolytic systems, namely the law of charge conservation.

Solubility Products and Solubility Concepts

13

Similarly, critical/disqualifying remarks can be related to the series of formulas considered in the chapter [37], e.g., Ksp = 27(s*)4 for precipitates of A3B and AB3 type, and Ksp = 108(s*)5 for A2B3 and A3B2. For Ca5(PO4)3OH, the formula Ksp = 84375(s*)9 (!) was applied [38]. As a third example let us take a system, where an excess of Zn(OH)2precipitate is introduced into pure water. It is usually stated that Zn(OH)2dissociates according to the reaction applied to formulate the expression for the solubility product

(36)

(37) The soluble hydroxo-complexes Zn(OH)i+2−i (i=1,…,4), with the stability constants, KiOH, expressed by the values logKiOH = 4.4, 11.3, 13.14, 14.66, are also formed in the system in question. The charge balance (ChB) has the form i.e., 2∙10−15/[OH−1]2 + 2∙1014.66∙10−15∙[OH−1]2 = 0

104.4∙10−15/[OH−1]

–

(38) 1013.14∙10−15∙[OH−1]

–

(39) The function (39) zeroes at pH0 = 9.121 (see Table 3). The basic reaction of this system is not immediately stated from Eq. (38) (there are positive and negative terms in expression for [OH−1] − [H+1]). The solubility s value Table 3: Zeroing the function (39) for the system with Zn(OH)2 precipitate introduced into water; pKW = 14 pH

[OH−1]

[Zn+2]

[ZnOH+1]

[Zn(OH)2]

[Zn(OH)3−1]

[Zn(OH)4−2]

y(pH)

s [mol/L]

9.118

1.3122E-05

5.8076E-06

1.9143E-06

0.0002

1.8113E-07

7.8705E-11

2.2702E-07

0.00020743

9.119

1.3152E-05

5.7810E-06

1.9099E-06

0.0002

1.8155E-07

7.9068E-11

1.3858E-07

0.00020740

9.120

1.3183E-05

5.7544E-06

1.9055E-06

0.0002

1.8197E-07

7.9433E-11

5.0322E-08

0.00020737

9.121

1.3213E-05

5.7280E-06

1.9011E-06

0.0002

1.8239E-07

7.9800E-11

−3.7750E-08

0.00020734

9.122

1.3243E-05

5.7016E-06

1.8967E-06

0.0002

1.8281E-07

8.0168E-11

−1.2564E-07

0.00020731

9.123

1.3274E-05

5.6755E-06

1.8923E-06

0.0002

1.8323E-07

8.0538E-11

−2.1335E-07

0.00020728

calculated at this point is different from s* = (Kso3/4)1/3 = 6.3⋅10−6, and [OH−1]/ [Zn+2] ≠ 2; such incompatibilities contradict application of this formula.

Dissolution of MeL2-type Salts Let us refer now to dissolution of precipitates MeL2 formed by cations

Solution Chemistry: Minerals and Reagents

14

Me+2and anions L−1 of a strong acid HL, as presented in Table 4. When an excess of MeL2 is introduced into pure water, the concentration balances and charge balance in two-phase system thus formed are as follows: Table 4: logKiOH and logKi values for the stability constants Ki and Kj of soluble complexes Me(OH)i+2-iand MeLj+2-j and pKsp values for the precipitates MeL2; [MeLi+2-i] = Ki[Me+2][L−1]i, Ksp = [Me+2][L−1]2 Me+2

MeOH+1

Me(OH)2

Me(OH)3−1

logK1OH

logK2OH

logK3OH

Hg+2

10.3

21.7

21.2

Pb+2

6.9

10.8

13.3

L−1

MeL+1

MeL2

MeL3−1

MeL4−2

logK1

logK2

logK3

logK4

MeL2 pKsp

I−1

12.87

23.82

27.60

29.83

28.54

I−1

1.26

2.80

3.42

3.92

8.98

Cl−1

1.62

2.44

2.04

1.0

4.79

(40) (41) (42) where [MeL2] denotes the concentration of the precipitate MeL2. At CL = 2CMe, we have (43) From Eqs. (40) and (41) (44) i.e., reaction of the solution is acidic, [H+1] > [OH−1]. Applying the relations for the equilibrium constants: [Me+2][L−1]2 = Ksp, [Me(OH)i+2−i] = KiOH[Me+2][OH−1]i (i = 1,…, I), [MeLj+2−j] = Kj[Me+2][L−1]j (j = 1,…, J) from Eqs. (43) and (44) we have (45) where

Solubility Products and Solubility Concepts

15

In particular, for I = 3, J = 4 (Table 4), we have (46) Applying the zeroing procedure to Eq. (46) gives the pH = pH0 of the solution at equilibrium. At this pH0 value, we calculate the concentrations of all species and solubility of this precipitate recalculated on sMe and sL. When zeroing Eq. (46), we calculate pH = pH0 of the solution in equilibrium with the related precipitate. The solubilities are as follows: (47) (48) The calculations of sMe and sL for the precipitates specified in Table 4 can be realized with use of Excel spreadsheet, according to zeroing procedure, as suggested above (Table 1).

0.010749606

0.010744657

0.01073971

0.010734765

0.010729823

4.5343

4.5344

4.5345

4.5346

4.5347

2.91939E-05

2.92007E-05

2.92074E-05

2.92141E-05

2.92208E-05

[PbOH+1]

7.94315E-11

7.94315E-11

7.94315E-11

7.94315E-11

7.94315E-11

[Pb(OH)2]

8.60384E-18

8.60186E-18

8.59988E-18

8.5979E-18

8.59592E-18

[Pb(OH)3-1]

0.017389867

0.017393872

0.017397878

0.017401884

0.017405892

[PbCl+1]

0.004466836

0.004466836

0.004466836

0.004466836

0.004466836

[PbCl2]

6.91359E-05

6.912E-05

6.91041E-05

6.90882E-05

6.90723E-05

[PbCl3−1]

2.45136E-07

2.45023E-07

2.44911E-07

2.44798E-07

2.44685E-07

[PbCl4−2]

0.038877983

0.038869032

0.038860083

0.038851136

0.038842191

[Cl−1]

-0.000105799

-4.48848E-05

1.60945E-05

7.7139E-05

0.000138249

y

0.000630817

0.000630527

0.000630236

0.000629946

0.000629656

5.15

5.1501

5.1502

5.1503

5.1504

7.07137E-06

7.073E-06

7.07463E-06

7.07626E-06

7.07789E-06

[PbOH+1]

7.94152E-11

7.94152E-11

7.94152E-11

7.94152E-11

7.94152E-11

[Pb(OH)2]

3.55061E-17

3.5498E-17

3.54898E-17

3.54816E-17

3.54735E-17

[Pb(OH)3−1]

1.47758E-05

1.47792E-05

1.47826E-05

1.4786E-05

1.47894E-05

[PbI+1]

6.60693E-07

6.60693E-07

6.60693E-07

6.60693E-07

6.60693E-07

[PbI2]

3.5518E-09

3.55098E-09

3.55016E-09

3.54935E-09

3.54853E-09

[PbI3−1]

1.44843E-11

1.44776E-11

1.44709E-11

1.44643E-11

1.44576E-11

[PbI4−2]

0.00128958

0.001289283

0.001288986

0.001288689

0.001288393

[I−1]

-0.000105799

-4.48848E-05

1.60945E-05

7.7139E-05

0.000138249

y

For HgI2: pH0 = 6.7769, sHg = 1.91217∙10−5, sI = 3.82435∙10−5, see Table 7. The difference between sI and 2sHg = 3.82434∙10−5 results from rounding the pH-value. The concentration [HgI2] = K2Ksp = 1.90546∙10−5 is close to the sHgvalue. For comparison, 4(s*)3 = Ksp ⟹ s* = 1.93∙10−10, i.e., s*/s ≈ 10−5.

[Pb+2]

pH

Table 6: Fragment of display for PbI2

For PbI2: pH0 = 5.1502, sPb = 6.5276∙10−4, sI = 1.3051∙10−3, see Table 6. The difference between sI and 2sPb = 1.3055∙10−3 results from rounding the pH0-value.

[Pb+2]

pH

Table 5: Fragment of display for PbCl2

16 Solution Chemistry: Minerals and Reagents

[Hg+2]

2.99681E-15

2.99398E-15

2.99114E-15

2.98831E-15

2.98548E-15

pH

6.7767

6.7768

6.7769

6.777

6.7771

3.56544E-12

3.568E-12

3.57056E-12

3.57313E-12

3.57569E-12

[HgOH+1]

5.3606E-08

5.36322E-08

5.36583E-08

5.36844E-08

5.37106E-08

[Hg(OH)2]

Table 7: Fragment of display for HgI2 [Hg(OH)3−1]

1.01464E-15

1.0149E-15

1.01517E-15

1.01543E-15

1.01569E-15

[HgI+1]

2.17524E-09

2.17627E-09

2.1773E-09

2.17833E-09

2.17936E-09

[HgI2]

1.90546E-05

1.90546E-05

1.90546E-05

1.90546E-05

1.90546E-05

1.12848E-08

1.12794E-08

1.12741E-08

1.12688E-08

1.12634E-08

[HgI3−1]

[HgI4−2]

1.88359E-13

1.88181E-13

1.88002E-13

1.87824E-13

1.87646E-13

[I−1]

9.82863E-08

9.82398E-08

9.81932E-08

9.81467E-08

9.81003E-08

-9.84182E-11

-3.99731E-11

1.8567E-11

7.72021E-11

1.35932E-10

y

Solubility Products and Solubility Concepts

17

Solution Chemistry: Minerals and Reagents

18

Dissolution of CaCO3 in the Presence of CO2 The portions 0.1 g of calcite CaCO3 (M = 100.0869 g/mol, d = 2.711 g/ cm3) are inserted into 100 mL of: pure water (task A) or aqueous solutions of CO2specified in the tasks: B1, B2, B3, and equilibrated. Denoting the starting (t = 0) concentrations [mol/L]: Co for CaCO3 and CCO2CCO2 for CO2 in the related systems, on the basis of equilibrium data collected in Table 8: (A) we calculate pH = pH01 and solubility s = s(pH01) of CaCO3 at equilibrium in the system; (B1) we calculate pH = pH02 and solubility s = s(pH02) of CaCO3 in the system, where CCO2CCO2 refers to saturated (at 25 oC) solution of CO2, where 1.45 g CO2 dissolves in 1 L of water [39]. (B2) we calculate minimal CCO2CCO2 in the starting solution needed for complete dissolution of CaCO3 in the system and the related pH = pH03 value, where s = s(pH03) = Co; (B3) we plot the logsCa versus V, pH versus V and logsCa versus pH relationships for the system obtained after addition of V mL of a strong base MOH (Cb = 0.1) into V0 = 100 mL of the system with CaCO3 presented in (B1). The quasistatic course of the titration is assumed.

• •

•

•

Table 8: Equilibrium data No.

Reaction

Expression for the equilibrium constant

Equilibrium data

1

CaCO3 = Ca+2 + CO3−2

[Ca+2][CO3−2] = Ksp

pKsp = 8.48

2

Ca+2 + OH−1 = CaOH+1

[CaOH+1] = K10[Ca+2][OH−1]

logK10 = 1.3

3

H2CO3 = H+1 + HCO3−1

[H+1][HCO3−1] = K1[H2CO3]

pK1 = 6.38

4

HCO3−1 = H+1 + CO3−2

[H+1][CO3−2] = K2[HCO3-1]

pK2 = 10.33

5

Ca+2 + HCO3−1 = CaHCO3+1

[CaHCO3+1] = K11[Ca+2][HCO3−1]

logK11 = 1.11

6

Ca+2 + CO3−2 = CaCO3

[CaCO3] = K12[Ca ][CO3 ]

logK12 = 3.22

7

Ca(OH)2 = Ca+2 + 2OH−1

[Ca+2][OH−1]2 = Ksp1

pKsp1 = 5.03

8

H2O = H+1 + OH−1

[H+1][OH−1] = KW

pKW = 14.0

+2

−2

The volume 0.1/2.711 = 0.037 cm3 of introduced CaCO3 is negligible when compared with V0 at the start (t = 0) of the dissolution. Starting concentration of CaCO3 in the systems: A, B1, B2, B3 is Co = (0.1/100)/0.1 = 10−2 mol/L. At t > 0, concentration of CaCO3 is co mol/L. The balances are as follows: (49)

Solubility Products and Solubility Concepts

19

(50) (51) (52) (52a)

where [M ] = CbV/(V0+V). • For (A) From Eqs. (49) and (50), we have +1

(53) Considering the solution saturated with respect to CaCO3 and denoting: f1= 1016.71−2pH + 1010.33−pH + 1, f2 = 1 + 10pH−12.7, from Eq. (53) and Table 1, we have the relations:

Inserting them into the charge balance (52), rewritten into the form (54) and applying the zeroing procedure to the function (54), we find pH01 = 9.904, at z = z(pH01) = 0. The solubility s = s(pH) of CaCO3, resulting from Eq. (49), is (55) We have s = s(pH = pH01) = 1.159⋅10 mol/L. • For (B1) Subtraction of Eq. (49) from Eq. (51) gives −4

(55a)

In this case,

(56) where CCO2CCO2 = 1.45/44 = 0.0329 mol/L. Eq. (55) has the form

Solution Chemistry: Minerals and Reagents

20

(57) and the charge balance is transformed into the zeroing function (58) where [CO3−2] = 10-8.48/[Ca+2], and [Ca+2] is given by Eq. (56). Eq. (58) zeroes at pH = pH02 = 6.031. Then from Eq. (57) we calculate s = s(pH02) = 6.393∙10−3 mol/L, at pH = pH02 = 6.031. • For (B2) At pH = pH03, where co = 0, i.e., s = Co, the solution (a monophase system) is saturated toward CaCO3, i.e., the relation [Ca+2][CO3−2] = Ksp is still valid. Applying Eqs. (56) and (57), we find pH values zeroing Eq. (58) at different, preassumed CCO2 values. Applying these pH-values in Eq. (57), we calculate the related s = s(pH, CCO2) values (Eq. (57), Table 9). Graphically, CCO2 = 0.100 is found at pH03 = 5.683, as the abscissa of the point of intersection of the lines: s = s(pH) and s = Co = 0.01. Table 9 shows other, preassumed s = Co values. • For (B3) We apply again the formulas used in (B1) and (B2), and the charge balance (Eq. (52a)), which is transformed there into the function (59) applied for zeroing purposes, at different V values. The data thus obtained are presented graphically in Figures 2a–c. The data presented in the dynamic solubility diagram (Figure 2b), illustrating the solubility changes affected by pH changes (Figure 2a) resulting from addition of a base, MOH; Figure 2c shows a synthesis of these changes. Solubility product of Ca(OH)2 is not crossed in this system. Table 9: The set of points used for searching the CCO2 value at s = Co = 0.01; at this point, we have pH03 = 5.683 CCO2

0.090

0.091

0.092

0.093

0.094

0.095

0.096

0.097

0.098

0.099

0.100

0.101

0.102

pH

5.716

5.712

5.709

5.706

5.702

5.699

5.696

5.693

5.690

5.687

5.683

5.680

5.577

s

9.58E3

9.64E3

9.67E3

9.70E3

9.77E3

9.80E3

9.84E-3

9.87E-3

9.91E3

9.94E3

10.01E3

10.06E-3

10.10E-3

Solubility Products and Solubility Concepts

21

Figure 2: Graphical presentation of the data considered in (b3): (a) pH versus V, (b) log sCa versus V, (c) log sCa versus pH relationships.

NONEQUILIBRIUM SOLID PHASES IN AQUEOUS MEDIA Some solids when introduced into aqueous media (e.g., pure water) may appear to be nonequilibrium phases in these media.

Silver Dichromate (Ag2Cr2O7) The equilibrium data related to the system, where Ag2Cr2O7 is introduced into pure water, were taken from Refs. [33, 40, 41], and presented in Table 10. A large discrepancy between pKsp2 values (6.7 and 10) in the cited literature is taken here into account. We prove that Ag2Cr2O7 changes into Ag2CrO4. Table 10: Physicochemical equilibrium data relevant to the Ag2Cr2O7 + H2O system (pK = −logK), at “room” temperatures Reaction

Equilibrium data

H2O = H + OH H2CrO4=H++HCrO−14H2CrO4=H++HCrO4−1 +1

-1

HCrO−14= H++CrO−24HCrO4−1= H++CrO4−2 HCr2O−17=H+1+Cr2O−27HCr2O7−1=H+1+Cr2O7−2 2HCrO−14=Cr2O−27+H2O2HCrO4−1=Cr2O7−2+H2O Ag+1 + OH−1 = AgOH Ag+1+2OH−1=Ag(OH)−12Ag+1+2OH−1=Ag(OH)2−1 Ag+1+3OH−1=Ag(OH)−23Ag+1+3OH−1=Ag(OH)3−2

= 14.0 pK1 = 0.8 pK2 = 6.5 logK3 = 0.07 logK4 = 1.52 logK1OH = 2.3 logK2OH = 3.6 logK3OH = 4.8 pKw

22

Solution Chemistry: Minerals and Reagents

Ag2CrO4=2Ag+1+CrO−24Ag2CrO4=2Ag+1+CrO4−2

pKsp1 Ag2Cr2O7=2Ag+1+Cr2O−27Ag2Cr2O7=2Ag+1+Cr pKsp2 2O7−2 AgOH=Ag+1+OH−1AgOH=Ag+1+OH−1 pKsp3

= 11.9 = 6.7 = 7.84

On the dissociation step, each dissolving molecule of Ag2Cr2O7 gives two ions Ag+1 and 1 ion Cr2O7−2, where two atoms of Cr are involved; in the contact with water, these ions are hydrolyzed, to varying degrees. In the initial step of the dissolution, before the saturation of the solution with respect to an equilibrium solid phase (not specified at this moment), we can write the concentration balances (60) (61) where 2C0 is the total concentration of the solid phase in the system, at the moment (t = 0) of introducing this phase into water, [Ag2Cr2O7] is the concentration of this phase at a given moment of the intermediary step. As previously, we assume that addition of the solid phase (here: Ag2Cr2O7) does not change the volume of the system in a significant degree, and that Ag2Cr2O7 is added in a due excess, securing the formation of a solid (that is not specified at this moment), as an equilibrium solid phase. The balances in Eqs. (60) and (61) are completed by the charge balance (62) used, as previously, to formulation of the zeroing function, y = y(pH), and the set of relations for equilibrium data specified in Table 10. From these relations, we get (63) (63A) Denoting by 2c0 (< 2C0) the total concentration of dissolved Ag and Cr species formed, in a transition stage, from Ag2Cr2O7, we can write (64) (65)

Solubility Products and Solubility Concepts

23

From Table 10 and formulas (63)–(65) we get the relations: (66) where g0 = 1 + 10pH−11.7 + 102pH−24.4 + 103pH−37.2; g1 = 107.3−2pH + 106.5−pH + 1; g2 = 1014.59−3pH + 1014.52−2pH. Applying them in Eq. (62), we get the zeroing function (67) where g3 = 1 – 10 – 2∙10 ; g4 = 10 + 2; g5 = 10 + 2∙1014.52−2pH, and [Ag+1] and [CrO4−2] are defied above, as functions of pH. The calculation procedure, realizable with use of Excel spreadsheet, is as follows. We assume a sequence of growing numerical values for 2c0. At particular 2c0 values, we calculate pH = pH(2c0) value zeroing the function (67), and then calculate the values of the products: q1 = [Ag+1]2[CrO4−2]/ Ksp1and q2 = [Ag+1]2[Cr2O7−2]/Ksp2, where: [Ag+1], [CrO4−2], and [Cr2O7−2] are presented above (Eqs. (66a), (66b) and (63a), resp.), pKsp1 = 11.9, pKsp2 = 6.7. 2pH−24.4

3pH−37.2

6.5−pH

14.59−3pH

Figure 3: The convergence of logq1 and logq2 to 0 value; Ksp1 is attained at lower 2c0 value.

As results from Figure 3, where logq1 and logq2 are plotted as functions of 2c0; logq1 = 0 ⇔ q1 = 1 ⇔ [Ag+1]2[CrO4−2] = Ksp1 at lower 2c0 value, whereas logq2< 0 ⇔ q2 < 1 ⇔ [Ag+1]2[Cr2O7−2] < Ksp2, both for pK2 = 6.7 and 10, cited

24

Solution Chemistry: Minerals and Reagents

in the literature. The x1=1 value is attained at 2c0 = 3.5∙10−4 ⟹ c0 = 1.75∙10−4; then Ag2CrO4 precipitates as the new solid phase, i.e., total depletion of Ag2Cr2O7occurs. It means that Ag2Cr2O7 is not the equilibrium solid phase in this system. This fact was confirmed experimentally, as stated in [42], i.e., Ag2Cr2O7 is transformed into Ag2CrO4 upon boiling with H2O; at higher temperatures, this transformation proceeds more effectively. Concluding, the formula s* = (Ksp2/4)1/3 applied for Ksp2 = [Ag+1]2[Cr2O7−2] is not “the best answer,” as stated in Ref. [43]. The system involved with Ag2CrO4 was also considered in context with the Mohr’s method of Cl−1 determination [44–46]. As were stated there, the systematic error in Cl−1 determining according to this method, expressed by the difference between the equivalence (eq) volume (Veq = C0V0/C) and the volume Vend corresponding to the end point where the Ksp1 for Ag2CrO4 is crossed, equals to

where Ksp = [Ag+1][Cl−1] (pKsp = 9.75), V0 is the volume of titrant with NaCl (C0) + K2CrO4 (C01) titrated with AgNO3 (C) solution; Vend = Veq at C01 = (1 + Vend/V0)∙Ksp1/Ksp. All calculations presented above were realized using Excel spreadsheets. For more complex nonequilibrium two-phase systems, the use of iterative computer programs, e.g., ones offered by MATLAB [8, 47], is required. This way, the quasistatic course of the relevant processes under isothermal conditions can be tested [48].

Dissolution of Struvite The fact that NH3 evolves from the system obtained after leaving pure struvite pr1 in contact with pure water, e.g., on the stage of washing this precipitate, has already been known at the end of nineteenth century [49]. It was noted that the system obtained after mixing magnesium, ammonium, and phosphate salts at the molar ratio 1:1:1 gives a system containing an excess of ammonium species remaining in the solution and the precipitate that “was not struvite, but was probably composed of magnesium phosphates” [50]. This effect can be explained by the reaction [20] (68) Such inferences were formulated on the basis of X-ray diffraction analysis, the crystallographic structure of the solid phase thus obtained. It was also

Solubility Products and Solubility Concepts

25

Struvite is not the the equilibrium solid phase when requires introducedainto aqueous solution CO2 stated that precipitation of also struvite significant excessofof (CCOammonium , mol/L), modified (or not) by free strong acid HB (C , mol/L) or strong base MOH a 2 species, e.g., Mg:N:P = 1:1.6:1. Struvite (pr1) is the equilibrium(Cb, mol/L).

solid phase only at a due excess of one or two of the precipitating reagents. The This case ofremark struviteisrequires moreindetailed The reaction (68) was theoretiimportant contextcomments. with gravimetric analysis of proved magnesium callyas [20], on the basis of simulated calculations iterative computer programs, pyrophosphate. Nonetheless, also performed in recentbytimes, the solubility of withstruvite use of allisattainable physicochemical knowledge about the *system in1/3question. For this calculated from the approximate formula s = (Ksp1) based on an purpose, the fractions assumption that it is the equilibrium solid phase in such a system.

q1 ¼ �½PO4phase �=Ksp1also , q2 ¼when ½Mg introduced � ½PO4 � =Ksp2 , q3aqueous ½Mg �½NH4 solid Struvite is not the equilibrium into ð69Þ �2 �1 2 þ2 þ2 ¼CO2 ½Mg �½HPO4modified �=Ksp3 , q4 ½Mg �½OHby �free =Ksp4strong acid HB (Ca, solution of CO2 (C , mol/L), (or not) mol/L) or strong base MOH (Cb, mol/L). þ2

þ1

�3

þ2 3

�3 2

were calculated for: pr1 = MgNH4PO4 (pKsp1 = 12.6), pr2 = Mg3(PO4)2 (pKsp2 = 24.38), pr3 = The case of struvite requires more detailed comments. The reaction (68) was MgHPO4 (pKsp3 = 5.5), pr4 = Mg(OH)2 (pKsp4 = 10.74) and are presented in Figure 4, at an 0 the basis of�3simulated 0calculations performed proved theoretically [20], Con initial concentration of pr1, equal = [pr1]t=0 = 10 mol/L (pC = (ppr1)t=0 = 3); ppr1 = �log programs, all attainable physicochemical [pr1].byAsiterative we see, computer the precipitation of pr2with (Eq. use (68))ofstarts at ppr1 = 3.088; other solubility knowledge theThe system in question. For thisofpurpose, the fractions products are not about crossed. changes in concentrations some species, resulting from dissolution of pr1, are indicated in Figure 5, where s is defined by equation [20]

(69) �1 s ¼ sMg ¼ ½Mgþ2 � þ ½MgOHþ1 � þ ½MgH2 POþ1 4 � þ ½MgHPO4 � þ ½MgPO4 � þ2 þ2 þ2 MgNH PO (pK calculated for: pr1 = = 12.6), pr2 = Mg3(PO4)ð70Þ þ½MgNH 4 3 Þ42 � þ ½MgðNH sp1 2 3 Þ3 � 3 � þ ½MgðNH

were (pKsp2= 24.38), pr3 = MgHPO4 (pKsp3 = 5.5), pr4 = Mg(OH)2 (pKsp4 = 10.74) 0 = and are presented in Figure 4, atare an identical initial concentration of pr1, equal involving all soluble magnesium species in its form, irrespective of the C equilib−3 0 rium[pr1] solid phase(s) present in this = system. Moreover, it is stated that pH in the solution equals = 10 mol/L (pC (ppr1) = 3); ppr1 = −log[pr1]. t=0 t=0

Figure 4. Plots of logqi versus ppr1 = �log[pr1] relationships, at (ppr1)t=0 = 3; i = 1,2,3,4 refer to pr1, pr2, pr3 and pr4, Figure 4: Plots of logqi versus ppr1 = −log[pr1] relationships, at (ppr1)t=0 = 3; respectively.

i = 1,2,3,4 refer to pr1, pr2, pr3 and pr4, respectively.

26

Solution Chemistry: Minerals and Reagents

As we see, the precipitation of pr2 (Eq. (68)) starts at ppr1 = 3.088; other solubility products are not crossed. The changes in concentrations of some species, resulting from dissolution of pr1, are indicated in Figure 5, where s is defined by equation [20]

Figure 5: The speciation curves for indicated species resulting from dissolution of pr1 at (ppr1)t=0 = 3.

Figure 5. The speciation curves for indicated species resulting from dissolution of pr1 at (ppr1)t=0 = 3.

ca. 9–9.5 (Figure 6); this pH can be affected by the presence of CO2 from air. Under such conditions, NH4+1 and NH3 occur there at comparable concentrations [NH4+1] ≈ [NH3], but [HPO4�2]/[PO4�3] = 1012.36�pH ≈ 103. This way, the scheme (10) would be more advantageous, provided that struvite is the equilibrium solid phase; but it is not the case, see Eq. (70) (68). The involving all soluble magnesium identical in its form, irrespective reaction (68) occurs also in the presence ofspecies CO2 in are water where struvite was introduced.

of the equilibrium solid phase(s) present in this system. Moreover, it is stated that pH in the solution equals ca. 9–9.5 (Figure 6); this pH can be affected by the presence of CO2 from air. Under such conditions, NH4+1 and NH3 occur there at comparable concentrations [NH4+1] ≈ [NH3], but [HPO4−2]/[PO4−3] = 1012.36−pH ≈ 103. This way, the scheme (10) would be more advantageous, provided that struvite is the equilibrium solid phase; but it is not the case, see Eq. (68). The reaction (68) occurs also in the presence of CO2 in water where struvite was introduced.

Figure 6. The pH versus log[pr2] relationship; pr2 = Mg3(PO4)2, at [ppr1]t=0 = 3. The numbers at the corresponding lines indicate pCO2 ¼ �logCCO2 values; pCO2 ¼ ∞ ⇔ CCO2 = 0.

Solubility Products and Solubility Concepts

27

Figure 6: The pH versus log[pr2] relationship; pr2 = Mg3(PO4)2, at [ppr1]t=0 = 3. The numbers at the corresponding lines indicate pCO2=−logCCO2 values; pCO2=∞ ⇔ CCO2= 0.

After introducing struvite pr1 (at pC0 = [ppr1]t=0 = 2) into alkaline (Cb = 10−2mol/L KOH, pCb = 2) solution of CO2 (pCO2 = 4), the dissolution is more complicated and proceeds in three steps, see Figure 7.

Figure The speciation curves for species Xizi, disFigure 7. The 7: speciation curves for indicated species Xi ziindicated , resulting from dissolution of pr1resulting = MgNH4POfrom 4, at (pC0, pCO2, 0 pCbsolution ) = (2, 4, 2); sof is defined Eq. (71). PO , at (pC0, p , pCb) = (2, 4, 2); s′ is defined by pr1 =byMgNH Eq. (71).

4

4

CO2

After introducing struvite pr1 (at pC0 = [ppr1]t=0 = 2) into alkaline (Cb = 10�2 mol/L KOH, pCb = 2) solution of CO2 (pCO2 = 4), the dissolution is more complicated and proceeds in three steps, see Figure 7. In step 1, pr4 precipitates first, pr1 + 2OH�1 = pr4 + NH3 + HPO4�2, nearly from the very start of pr1 dissolution, up to ppr1 = 2.151, where Ksp2 is attained. Within step 2, the solution is saturated toward pr2 and pr4. In this step, the reaction expressed by the notation 2pr1 + pr4 =

28

Solution Chemistry: Minerals and Reagents

In step 1, pr4 precipitates first, pr1 + 2OH−1 = pr4 + NH3 + HPO4−2, nearly from the very start of pr1 dissolution, up to ppr1 = 2.151, where Ksp2 is attained. Within step 2, the solution is saturated toward pr2 and pr4. In this step, the reaction expressed by the notation 2pr1 + pr4 = pr2 + 2NH3 + 2H2O occurs up to total depletion of pr4 (at ppr1 = 2.896). In this step, the reaction 3pr1 + 2OH−1 = pr2 + 3NH3 + HPO4−1 + 2H2O occurs up to total depletion of pr1, i.e., the solubility product Ksp1 for pr1 is not crossed. The curve s′ (Figure 7) is related to the function (71) where s is expressed by Eq. (70).

SOLUBILITY OF NICKEL DIMETHYLGLYOXIMATE The precipitate of nickel dimethylglyoximate, NiL2, has soluble counterpart with the same formula, i.e., NiL2, in aqueous media. If NiL2 is in equilibrium with the solution, concentration of the soluble complex NiL2 assumes constant value: [NiL2] = K2∙[Ni2+][L−]2 = K2∙Ksp, where K2 = 1017.24, Ksp = [Ni2+][L−]2 = 10−23.66 [14, 17, 18], and then [NiL2] = 10−6.42 (i.e., log[NiL2] = −6.42). The concentration [NiL2] is the constant, limiting component in expression for solubility s = sNi of nickel dimethylglyoximate, NiL2. Moreover, it is a predominant component in expression for s in alkaline media, see Figure 8. This pH range involves pH of ammonia buffer solutions, where NiL2 is precipitated from NiSO4 solution during the gravimetric analysis of nickel; the expression for solubility

Figure 8: Solubility curves for nickel dimethylglyoximate NiL2 in (a) ammonia, (b) acetate+ammonia, and (c) citrate+acetate+ ammonia media at total con-

Solubility Products and Solubility Concepts

29

centrations [mol/L]: CNi = 0.001, CL = 0.003, CN = 0.5, CAc = 0.3, CCit = 0.1 [14].

(72) The effect of other, e.g., citrate (Cit) and acetate (Ac) species as complexing agents can also be considered for calculation purposes, see the lines b and c in Figure 8. The presence of citrate does not affect significantly the solubility of NiL2 in ammonia buffer media, i.e., at pH ≈ 9, where sNi ≅ [NiL2].

Calculations of s = sNi were made at CNi = 0.001 mol/L and CL = 0.003 mol/L HL, i.e., at the excessive HL concentration equal CL – 2CNi = 0.001 mol/L. Solubility of HL in water, equal 0.063 g HL/100 mL H2O (25oC) [51], corresponds to concentration 0.63/116.12 = 0.0054 mol/L of the saturated HL solution, 0.003 < 0.0054. Applying higher CL values needs the HL solution in ethanol, where HL is fairly soluble. However, the aqueous-ethanolic medium is thus formed, where equilibrium constants are unknown. To avoid it, lower CNiand CL values were applied in calculations. The equilibrium data were taken from Ref. [31]. The soluble complex having the formula identical to the formula of the precipitate occurs also in other, two-phase systems. In some pH range, concentration of this soluble form is the dominant component of the expression for the solubility s. As stated above, such a case occurs for NiL2. Then one can assume the approximation (73) Similar relationship exists also for other precipitates. By differentiation of Eq. (73) with respect to temperature T at p = const, and application of van’t Hoff’s isobar equation for K2 and Ksp, we obtain

where

(74)

Because, as a rule,

then

, and Eq. (74) can be rewritten into the form

30

Solution Chemistry: Minerals and Reagents

(75) If within the temperature range (T0, T), the value of s is approximately constant. Let T0 denote the room temperature (at which,as a rule— all the equilibrium constants are determined) and T ≠ T0 is the temperature at which the precipitate is filtered and washed. In this case, the solubility s and then theoretical accuracy of gravimetric analysis does not change with temperature.

CALCULATION OF SOLUBILITY IN DYNAMIC REDOX SYSTEMS Preliminary Information The redox system presented in this section is resolvable according to generalized approach to redox systems (GATES), formulated by Michałowski (1992) [8]. According to GATES principles, the algebraic balancing of any electrolytic system is based on the rules of conservation of particular elements/cores Yg (g = 1,…, G), and on charge balance (ChB), expressing the rule of electroneutrality of this system; the terms element and core are then distinguished. The core is a cluster of elements with defined composition (expressed by its chemical formula) and external charge that remains unchanged during the chemical process considered, e.g., titration. For ordering purposes, we assume: Y1 = H, Y2 = O,…. For modeling purposes, the closed systems, composed of condensed phases separated from its environment by diathermal (freely permeable by heat) walls, are considered; it enables the heat exchange between the system and its environment. Any chemical process, such as titration, is carried out under isothermal conditions, in a quasistatic manner; constant temperature is one of the conditions securing constancy of equilibrium constants values. An exchange of the matter (H2O, CO2, O2,…) between the system and its environment is thus forbidden, for modeling purposes. The elemental/core balance F(Yg) for the g-th element/core (Yg) (g = 1,…, G) is expressed by an equation interrelating the numbers of Yg-atoms or cores in components of the system with the numbers of Yg-atoms/cores in the species of the system thus formed; we have F(H) for Y1 = H, F(O) for Y2 = O, etc. The key role in redox systems is due to generalized electron balance (GEB) concept, discovered by Michałowski as the Approach I (1992) and

Solubility Products and Solubility Concepts

31

Approach II (2006) to GEB; both approaches are equivalent: (76) GEB is fully compatible with charge balance (ChB) and concentration balances F(Yg), formulated for different elements and cores. The primary form of GEB, pr-GEB, obtained according to Approach II to GEB is the linear combination (77) Both approaches (I and II) to GEB were widely discussed in the literature [7–12, 14, 15, 17, 18, 34, 52–74], and in three other chapters in textbooks [75–79] issued in 2017 within InTech. The GEB is perceived as a law of nature [9, 10, 17, 67, 71, 73, 74], as the hidden connection of physicochemical laws, as a breakthrough in the theory of electrolytic redox systems. The GATES refers to mono- and polyphase, redox, and nonredox, equilibrium and metastable [20, 21–23, 78, 79] static and dynamic systems, in aqueous, nonaqueous, and mixed-solvent media [69, 72], and in liquid-liquid extraction systems [53]. Summarizing, Approach II to GEB needs none prior information on oxidation numbers of all elements in components forming a redox system and in the species in the system thus formed. The Approach I to GEB, considered as the “short” version of GEB, is useful if all the oxidation numbers are known beforehand; such a case is obligatory in the system considered below. The terms “oxidant” and “reductant” are not used within both approaches. In redox systems, 2∙F(O) – F(H) is linearly independent on CHB and F(Yg) (g ≥ 3,…, G); in nonredox systems, 2∙F(O) – F(H) is dependent on those balances. This property distinguishes redox and nonredox systems of any degree of complexity. Within GATES, and GATES/GEB in particular, the terms: “stoichiometry,” “oxidation number,” “oxidant,” “reductant,” “equivalent mass” are considered as redundant, old-fashioned terms. The term “mass action law” (MAL) was also replaced by the equilibrium law (EL), fully compatible with the GATES principles. Within GATES, the law of charge conservation and law of conservation of all elements of the system tested have adequate importance/significance. A detailed consideration of complex electrolytic systems requires a collection and an arrangement of qualitative (particular species) and quantitative data; the latter ones are expressed by interrelations between concentrations of the species. The interrelations consist of material balances and a complete set of expressions for equilibrium constants. Our further considerations will be referred to a titration, as a most common example of dynamic systems. The redox and nonredox systems, of any degree of

32

Solution Chemistry: Minerals and Reagents

complexity, can be resolved in analogous manner, without any simplifications done, with the possibility to apply all (prior, preselected) physicochemical knowledge involved in equilibrium constants related to a system in question. This way, one can simulate (imitate) the analytical prescription to any process that may be realized under isothermal conditions, in mono- and twophase systems, with liquid-liquid extraction systems included.

Solubility of CuI in a Dynamic Redox System The system considered in this section is related to iodometric, indirect analysis of an acidified (H2SO4) solution of CuSO4 [14, 64]. It is a very interesting system, both from analytical and physicochemical viewpoints. Because the standard potential E0 = 0.621 V for (I2, I−1) exceeds E0 = 0.153 V for (Cu+2, Cu+1), one could expect (at a first sight) the oxidation of Cu+1 by I2. However, such a reaction does not occur, due to the formation of sparingly soluble CuIprecipitate (pKsp = 11.96).

This method consists of four steps. In the preparatory step (step 1), an excess of H2SO4 is neutralized with NH3 (step 1) until a blue color appears, which is derived from Cu(NH3)i+2 complexes. Then the excess of CH3COOH is added (step 2), to attain a pH ca. 3.6. After subsequent introduction of an excess of KI solution (step 3), the mixture with CuI precipitate and dissolved iodine formed in the reactions: 2Cu+2 + 4I−1 = 2CuI + I2, 2Cu+2 + 5I−1 = 2CuI + I3−1 is titrated with Na2S2O3 solution (step 4), until the reduction of iodine: I2 + 2S2O3−2 = 2I−1 + S4O6−2, I3−1 + 2S2O3−2 = 3I−1 + S4O6−2 is completed; the reactions proceed quantitatively in mildly acidic solutions (acetate buffer), where the thiosulfate species are in a metastable state. In strongly acidic media, thiosulfuric acid disproportionates according to the scheme H2S2O3 = H2SO3 + S [80].

Formulation of the System We assume that V mL of C mol/L Na2S2O3 solution is added into the mixture obtained after successive addition of: VN mL of NH3 (C1) (step 1), VAc mL of CH3COOH (C2) (step 2), VKI mL of KI (C3) (step 3), and V mL of Na2S2O3 (C) (step 4) into V0 mL of titrand D composed of CuSO4 (C0) + H2SO4 (C01). To follow the changes occurring in particular steps of this analysis, we assume that the corresponding reagents in particular steps are added according to the titrimetric mode, and the assumption of the volumes additivity is valid. In this system, three electron-active elements are involved: Cu (atomic number ZCu = 29), I (ZI = 53), S (ZS = 16). Note that sulfur in the core

Solubility Products and Solubility Concepts

33

SO4−2 is not involved here in electron-transfer equilibria between S2O3−2 and S4O6−2; then the concentration balance for sulfate species can be considered separately. The balances written according to Approach I to GEB, in terms of molar concentrations, are as follows: •

•

•

Generalized electron balance (GEB)

CHB

F(Cu)

•

F(SO4)

•

F(NH3)

•

F(CH3COO)

•

F(K)

•

F(I)

•

F(S)

(78)

(79)

(80) (81)

(82)

(83) (84) (85)

Solution Chemistry: Minerals and Reagents

34

•

F(Na)

(86)

(87) The GEB is presented here in terms of the Approach I to GEB, based on the “card game” principle, with Cu (Eq. (80)), I (Eq. (85)) as S (Eq. (86)) as “players,” and H, O, S (Eq. (81)), C (from Eq. (83)), N (from Eq. (82)), K, Na as “fans.” There are together 47 species involved in 2 + 6 = 8, Eqs. (78)–(83), (85), (86) and two equalities; [K+1] (Eq. (84)) and [Na+1] (Eq. (87)) are not involved in expressions for equilibrium constants, and then are perceived as numbers (not variables), at a particular V-value. Concentrations of the species in the equations are interrelated in 35 independent equilibrium constants:

Applying A = 16.92 [16], we have

In the calculations made in this system according to the computer programs attached to Ref. [64], it was assumed that V0 = 100, C0 = 0.01, C01 = 0.01,

Solubility Products and Solubility Concepts

35

C1 = 0.25, C2 = 0.75, C3 = 2.0, C4 = C = 0.1; VN = 20, VAc = 40, VK = 20. At each stage, the variable V is considered as a volume of the solution added, consecutively: NH3, CH3COOH, KI, and Na2S2O3, although the true/factual titrant in this method is the Na2S2O3 solution, added in stage 4. The solubility s [mol/L] of CuI in this system (Figures 8a and b) is put in context with the speciation diagrams presented in Figure 9. This precipitate appears in the initial part of titration with KI (C3) solution (Figure 8a) and further it accompanies the titration, also in stage 4 (Figure 8b). Within stage 3, at V ≥ C0V0/C3, we have

Figure 9: The speciation plots for indicated Cu-species within the successive stages. The V-values on the abscissas correspond to successive addition of V mL of: 0.25 mol/L NH3 (stage 1); 0.75 mol/L CH3COOH (stage 2); 2.0 mol/L KI (stage 3); and 0.1 mol/L Na2S2O3 (stage 4). For more details see text.

(88) and in stage 4 (89) The small concentration of Cu+1 (Figure 9, stage 3) occurs at a relatively high total concentration of Cu+2 species, determining the potential ca. 0.53–0.58 V, [Cu+2]/[Cu+1] = 10A(E – 0.153), see Figure 10a. Therefore, the concentration of Cu+2 species determine a relatively high solubility s in the initial part of stage 3. The decrease in the s value in further parts of stage 3 is continued in

36

Solution Chemistry: Minerals and Reagents

stage 4, at V < Veq = C0V0/C = 0.01∙100/0.1 = 10 mL. Next, a growth in the solubility s4at V > Veq is involved with formation of thiosulfate complexes, mainly CuS2O3−1 (Figure 9, stage 4). The species I3−1 and I2 are consumed during the titration in stage 4 (Figure 9d). A sharp drop of E value at Veq = 10 mL (Figure 10b) corresponds to the fraction titrated Φeq = 1.

Figure 10: Plots of E versus V for (a) stage 3 and (b) stage 4.

The course of the E versus V relationship within the stage 3 is worth mentioning (Figure 10a). The corresponding curve initially decreases and reaches a “sharp” minimum at the point corresponding to crossing the solubility product for CuI. Precipitation of CuI starts after addition of 0.795 mL of 2.0 mol/L KI (Figure 11a).

Figure 11: Solubility s of CuI within stage 3 (a) and stage 4 (b).

Solubility Products and Solubility Concepts

37

Subsequently, the curve in Figure 10a increases, reaches a maximum and then decreases. At a due excess of the KI (C3) added on the stage 3 (VK = 20 mL), solid iodine (I2(s), of solubility 0.00133 mol/L at 25oC) is not precipitated.

FINAL COMMENTS The solubility and dissolution of sparingly soluble salts in aqueous media are among the main educational topics realized within general chemistry and analytical chemistry courses. The principles of solubility calculations were formulated at a time when knowledge of the two-phase electrolytic systems was still rudimentary. However, the earlier arrangements persisted in subsequent generations [81], and little has changed in the meantime [82]. About 20 years ago, Hawkes put in the title of his article [83] a dramatic question, corresponding to his statement presented therein that “the simple algorithms in introductory texts usually produce dramatic and often catastrophic errors”; it is hard not to agree with this opinion. In the meantime, Meites et al. [84] stated that “It would be better to confine illustrations of the solubility product principle to 1:1 salts, like silver bromide (…), in which the (…) calculations will yield results close enough to the truth.” The unwarranted simplifications cause confusion in teaching of chemistry. Students will trust us enough to believe that a calculation we have taught must be generally useful. The theory of electrolytic systems, perceived as the main problem in the physicochemical studies for many decades, is now put on the side. It can be argued that the gaining of quantitative chemical knowledge in the education process is essentially based on the stoichiometry and proportions. Overview of the literature indicates that the problems of dissolution and solubility calculation are not usually resolved in a proper manner; positive (and sole) exceptions are the studies and practice made by the authors of this chapter. Other authors, e.g., [13, 85], rely on the simplified schemes (readyto-use formulas), which usually lead to erroneous results, expressed by dissolution denoted as s* [mol/L]; the values for s* are based on stoichiometric reaction notations and expressions for the solubility product values, specified by Eqs. (1) and (2). The calculation of s* contradicts the common sense principle; this was clearly stated in the example with Fe(OH)3 precipitate. Equation (27) was applied to struvite [50] and dolomite [86], although these precipitates are nonequilibrium solid phases when introduced into pure

38

Solution Chemistry: Minerals and Reagents

water, as were proved in Refs. [20–23]. The fact of the struvite instability was known at the end of nineteenth century [49]; nevertheless, the formula s* = (Ksp)1/3for struvite may be still encountered in almost all textbooks and learning materials; this problem was raised in Ref. [15]. In this chapter, we identified typical errors involved with s* calculations, and indicated the proper manner of resolution of the problem in question. The calculations of solubility s*, based on stoichiometric notation and Eq. (3), contradict the calculations of s, based on the matter and charge preservation. In calculations of s, all the species formed by defined element are involved, not only the species from the related reaction notation. A simple zeroing method, based on charge balance equation, can be applied for the calculation of pH = pH0 value, and then for calculation of concentrations for all species involved in expression for solubility value. The solubility of a precipitate and the pH-interval where it exists as an equilibrium-solid phase in two-phase system can be accurately determined from calculations based on charge and concentration balances, and complete set of equilibrium constant values referred to the system in question. In the calculations performed here we assumed a priori that the Ksp values in the relevant tables were obtained in a manner worthy of the recognition, i.e., these values are true. However, one should be aware that the equilibrium constants collected in the relevant tables come from the period of time covering many decades; it results from an overview of dates of references contained in some textbooks [31, 85] relating to the equilibrium constants. In the early literature were generally presented the results obtained in the simplest manner, based on Ksp calculation from the experimentally determined s* value, where all soluble species formed in solution by these ions were included on account of simple cations and anions forming the expression for Ksp. In many instances, the Ksp* values should be then perceived as conditional equilibrium constants [87]. Moreover, the differences between the equilibrium constants obtained under different physicochemical conditions in the solution tested were credited on account of activity coefficients, as an antidote to any discrepancies between theory and experiment. First dissociation constants for acids were published in 1889. Most of the stability constants of metal complexes were determined after the announcement 1941 of Bjerrum’s works, see Ref. [88], about amminecomplexes of metals, and research studies on metal complexes were carried out intermittently in the twentieth century [89]. The studies of complexes

Solubility Products and Solubility Concepts

39

formed by simple ions started only from the 1940s; these studies were related both to mono- and two-phase systems. It should also be noted that the first mathematical models used for determination of equilibrium constants were adapted to the current computing capabilities. Critical comments in this regard can be found, among others, in the Beck [90] monograph; the variation between the values obtained by different authors for some equilibrium constants was startling, and reaching 20 orders of magnitude. It should be noted, however, that the determination of a set of stability constants of complexes as parameters of a set of suitable algebraic equations requires complex mathematical models, solvable only with use of an iterative computer program [91–93]. The difficulties associated with the resolution of electrolytic systems and two-phase systems, in particular, can be perceived today in the context of calculations using (1o) spreadsheets (2o) iterative calculation methods. In (1o), a calculation is made by the zeroing method applied to the function with one variable; both options are presented in this chapter. The expression for solubility products, as well as the expression of other equilibrium constants, is formulated on the basis of mass action law (MAL). It should be noted, however, that the underlying mathematical formalism contained in MAL does not inspire trust, to put it mildly. For this purpose, the equilibrium law (EL) based on the Gibbs function [94] and the Lagrange multipliers method [95–97] with laws of charge and elements conservation was suggested lately by Michałowski. From semantic viewpoint, the term “solubility product” is not adequate, e.g., in relation to Eq. (8). Moreover, Ksp is not necessarily the product of ion concentrations, as indicated in formulas (4), (5), and (11). In some (numerous) instances of sparingly soluble species, e.g., sulfur, solid iodine, 8-hydroxyquinoline, dimethylglyoxime, the term solubility product is not applied. In some instances, e.g., for MnO2, this term is doubtful. One of the main purposes of the present chapter is to familiarize GEB within GATES as GATES/GEB to a wider community of analysts engaged in electrolytic systems, also in aspect of solubility problems.

In this context, owing to large advantages and versatile capabilities offered by GATES/GEB, it deserves a due attention and promotion. The GATES is perceived as a step toward reductionism [19, 71] of chemistry in the area of electrolytic systems and the GEB is considered as a general law of nature; it provides the real proof of the world harmony, harmony of nature.

40

Solution Chemistry: Minerals and Reagents

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the Gran methods. A comparative study. Analytica Chimica Acta. 2008;606(2):172-183. http://www.sciencedirect. com/science/article/ pii/S0003267007018673 Ponikvar M, Michałowski T, Kupiec K, Wybraniec S, Rymanowski M. Experimental verification of the modified Gran methods applicable to redox systems. Analytica Chimica Acta. 2008;628(2):181-189. http:// pl.scribd.com/doc/173699262/ACA-2008-2 Michałowski T, Pietrzyk A. The generalized electron balance concept. Derivation based on elementary rules of the matter conservation. In: Zuba D, Parczewski A, editors. Chemometrics: Methods and Applications. Institute of Forensic Research, Kraków; 2006. pp. 415422. https://pbn.nauka.gov.pl/sedno-webapp/works/210292 Michałowski T. Electron Balance as the Basis of Calculations in Redox Systems (in Polish). In: Use of Information Technology in Academic Teaching of Chemistry (Maciejowska I, Ruszak M, Witkowski S, eds.), Jagiellonian University, Cracow, 2007. pp. 162-169. http:// www. chemia.uj.edu.pl/~ictchem/book.html Michałowski T, Pietrzyk A. Complementarity of physical and chemical laws of preservation in aspect of electrolytic systems (in Polish). Wiadomości Chemiczne. 2007;61:625-640 Michałowska-Kaczmarczyk AM, Asuero AG, Toporek M, Michałowski T. “Why not stoichiometry” versus “Stoichiometry – why not?” Part II. GATES in context with redox systems. Critical Reviews in Analytical Chemistry. 2015;45(3):240-268. http://www. tandfonline.com/doi/full/ 10.1080/10408347.2014.937853 Michałowska-Kaczmarczyk AM, Michałowski T, Toporek M, Asuero AG. “Why not stoichiometry” versus “Stoichiometry – why not?” Part III. Extension of GATES/GEB on Complex Dynamic Redox Systems. Critical Reviews in Analytical Chemistry. 2015;45 (4):348366. DOI: 10.1080/10408347.2014.953673. http://www.researchgate. net/publication/274401037_Why_Not_Stoichiometry_Versus_ Stoichiometry_-_Why_Not_Part_III_ Extension_of_GatesGeb_on_ Complex_Dynamic_Redox_Systems Michałowska-Kaczmarczyk AM, Michałowski T, Toporek M. Formulation of dynamic redox systems according to GATES/ GEB principles. International Journal of Electrochemical Science. 2016;11:2560-2578. DOI:10.20964/e110340 Michałowski T, Ponikvar-Svet M, Asuero AG, Kupiec K.

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Thermodynamic and kinetic effects involved with pH titration of As(III) with iodine in a buffered malonate system. Journal of Solution Chemistry. 2012;41(3):436-446. http://www.springerlink.com/content/ p2m73068h2q5u174/. DOI: 10.1007/s10953-012-9815-6 Michałowska-Kaczmarczyk AM, Michałowski T. Comparative balancing of non-redox and redox electrolytic systems and its consequences. American Journal of Analytical Chemistry. 2013;4(10):46-53. http://www.scirp.org/journal/PaperInformation. aspx?PaperID=38569 Toporek M, Michałowska-Kaczmarczyk AM, Michałowski T. Disproportionation reactions of HIO and NaIO in static and dynamic systems. American Journal of Analytical Chemistry. 2014;5:10461056. http://www.scirp.org/journal/PaperInformation.aspx?Paper ID=51637#.VHXKcWfpt74 Michałowska-Kaczmarczyk AM, Michałowski T. Generalized electron balance for dynamic redox systems in mixed-solvent media. Journal of Analytical Sciences, Methods and Instrumentation. 2014;4(4):102-109. http://www.scirp.org/Journal/PaperInformation. aspx?PaperID=52018#.VH1N5Gfpt74 Michałowska-Kaczmarczyk AM, Michałowski T. Compact formulation of redox systems according to GATES/GEB principles. Journal of Analytical Sciences, Methods and Instrumentation. 2014;4(2):39-45. http://www.scirp.org/journal/PaperInformation.aspx?PaperID=46335 Michałowska-Kaczmarczyk AM, Michałowski T. GATES as the unique tool for simulation of electrolytic redox and non-redox systems. Journal of Analytical & Bioanalytical Techniques. http://omicsonline.org/ open-access/gates-as-the-unique-tool-for-simulationof-electrolyticredox-and-non-redox-systems-2155-9872.1000204.pdf Michałowski T, Pilarski B, Asuero AG, Michałowska-Kaczmarczyk AM. Modelling of acid-base properties in binary-solvent systems. In: Wypych G, editor. Handbook of Solvents, Vol. 1. Properties. Toronto: ChemTec Publishing; 2014. pp. 623-648. Chapter 9.4 Michałowski T, Michałowska-Kaczmarczyk AM, Toporek M. Formulation of general criterion distinguishing between non-redox and redox systems. Electrochimica Acta. 2013;112:199-211. http://www. sciencedirect.com/science/article/pii/S0013468613016836 Toporek M, Michałowska-Kaczmarczyk AM, Michałowski T. Symproportionation versus disproportionation in bromine redox

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systems. Electrochimica Acta. 2015;171:176-187. http://www. sciencedirect.com/science/article/pii/S0013468615011238 Michałowska-Kaczmarczyk AM, Spórna-Kucab A, Michałowski T. A Distinguishing Feature of the Balance 2f(O) – f(H) in Electrolytic Systems. The Reference to Titrimetric Methods of Analysis, in: “Titration”, InTech 2017 Michałowska-Kaczmarczyk AM, Spórna-Kucab A, Michałowski T. Principles of Titrimetric Analyses According to Generalized Approach to Electrolytic systems (GATES), in: “Titration”, InTech 2017 AM, Spórna-Kucab A, Michałowski T. Generalized Electron Balance (GEB) as the Law of Nature in Electrolytic Redox Systems, in: “Redox: Principles and Advanced Applications”, InTech 2017. Pietrzyk A, Michałowski T. Computer simulation of the process of struvite MgNH4PO4∙6H2O dissolution in aqueous solutions, (in Polish). Use of Information Technology in Academic Teaching of Chemistry. Kraków: UJ; 2007. pp.137-146. http://www. chemia.uj.edu. pl/~ictchem/book.html Pietrzyk A, Michałowski T, Conditions of struvite formation in aqueous systems. In: Zuba D, Parczewski A, editors. Chemometrics: Methods and Applications. Kraków; 2006. pp. 423-427. https://pbn.nauka.gov. pl/works/210292 Steudel R, editor. Elemental Sulfur and Sulfur-Rich Compounds. II. Topics in Current Chemistry. Berlin, Heidelberg: Springer-Verlag; 2003 Clark RW, Bonicamp JM. The Ksp-solubility conundrum. Journal of Chemical Education. 1998;75(9):1182-1185. DOI: 10.1021/ ed075p1182 Umland JB, Bellama JM. General Chemistry. 2nd ed. Minneapolis, MN: West; 1996. pp. 621-622 Hawkes SJ. What should we teach beginners about solubility and solubility products? Journal of Chemical Education. 1998;75(9):11791181. DOI: 10.1021/ed075p1179 Meites L, Pode JSF, Thomas HC. Are solubilities and solubility products related? Journal of Chemical Education. 1966;43:667-672 Šůcha L, Kotrlý S. Solution Equilibrium in Analytical Chemistry. London: Van Nostrand Reinhold Comp.; 1975 Chen G, Tao D. Effect of solution chemistry on flotability of magnesite

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2 Role of Surfactants in Mineral Processing: An Overview

Abhyarthana Pattanaik and Rayasam Venugopal Department of Fuel and Mineral Engineering, Indian School of Mines, Dhanbad, India

ABSTRACT Depletion of high-grade resources has necessitated the use of low-grade fines, which contain good amount of mineral values and also liberate in finer sizes. Froth flotation, a physico-chemical surface-based process, is the most established solution, both technologically and economically, compared to other alternatives for fines beneficiation. For a successful and effective flotation performance, an understanding of the mineral surface and proper selection of the surfactant/reagent regimes along with their molecular chemistry and their specific adsorption mechanism are mandated. This chapter focuses on the complexity of the flotation process along with Citation: Abhyarthana Pattanaik and Rayasam Venugopal (June 24th 2019). Role of Surfactants in Mineral Processing: An Overview [Online First], IntechOpen, DOI: 10.5772/intechopen.85947. Copyright: © 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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adsorption and interaction mechanism of different surfactants in accordance to mineral surface characteristics and their dependency on many microevents. To further strengthen mineral flotation chemistry and advancement of mineral engineering, research gears at investigating new surfactants, specific for particular mineral surface. The selection of reagents/surfactants with appropriate chemical composition and their administration are of critical importance in view of varied mineralogy, chemical complexity and size consist of feed material. Cost- effective and lower cost flotation reagents can be synthesized through insertion of new functional groups, molecular modelling of reagents for more environment-friendly nature, modifying the structure of other chelating agents and novel green chemicals from renewable resources, adding aliphatic alcohol and carboxylic acid to biobased collectors and adding chaotropic anions to alkyl and aryl surfactants and organic and inorganic salts having strong orientation with more proton donor and acceptor; addition of another cationic group to known cationic surfactants can be tried for enhanced flotation performance. The study also provides an idea on the effect of other parameters like pH, composition of pulp, zeta potential, electrostatic potential, etc. For envisagement of a successful flotation performance, proper selection of the reagent system according to the specific surface and understanding of the mineral surfacespecific adsorption mechanism are mandated. Keywords: Flotation, ore fines, reagents, reagent system for specific objective

INTRODUCTION The most innovative and ingenious process development of the century is the emergence of the froth flotation process for the treatment of low-grade ores. Froth flotation process, which uses the difference in hydrophobicity of minerals, is employed in several industries (mineral processing and others) for fines processing. It is a process of upgradation of minerals by taking advantage of differences in physico-chemical surface properties between valuable and gangue minerals of two different minerals. Froth flotation process can be effectively applied to the system where more amount of fine liberated valuable and gangue mineral grains are present rather than of interlocked forms [1]. Froth flotation, being an established method, has been known in a century’s practice across the globe for its efficiency to eliminate impurities from different ores to produce good grade concentrate.

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Froth Flotation The grade of mined ore is depleting day by day where as demand for metal and steel is increasing steeply. Improving the resource base and exploitation of iron ore resources through the processing and upgradation is the most important challenging task. A nation’s socio-economic development completely depends on effective and judicious utilization of its mineral resources. Proper utilization of wastes is achieved through balance between natural resource management and sustainable growth process to minimize the burden on ecological pyramid due to enormous growth of industrialization. With regard to the tailings management, reduction of tailing volume is feasible, if the maximum metallic content is extracted or recovered by a suitable technology [2]. The conventional ore processing and mining operations generate fines and slimes of huge quantities to the tune of 10–15% of run of mine which are generally of poorer grade and being discarded. These discarded tailing stockpiles occupy a huge space, which contain good metallic values, cause pollution to ground and surface water, and are having a negative impact to the environment. They need to be processed to recover metallic values for resource augmentation and to meet environmental stipulation. These fines and slimes cannot be utilized directly as feed to metallurgical plants due to size specification; besides these occupy a huge space and cause environmental and ecological problems, which need to be clearly assessed. The scarcity of high-grade ore is compelling the mineral processing industries to look for low-grade ore fines. Hence it is essential to beneficiate and to recover the additional mineral values from these fines, not only to earn additional revenue to the mineral industries but also from the point of view of conservation of mineral wealth. These low-grade slimes can be considered as national resource rather than a waste of nuisance. In the present days, the minerals liberated at extremely fine sizes, and in addition the ore typically consists of valuable mineral intergrowth with unwanted/gangue minerals making the mineral surface quite complex. This nature of particle characteristic compels to be separated by the technique that relies on surface properties. So the flotation technique is being developed to treat these low-grade ore and waste slimes. Low-grade ores imply finer liberation size and cannot be upgraded by conventional gravity concentration techniques. Wet and dry low-intensity magnetic separation (LIMS) techniques are used to process ores that

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contain minerals with strong magnetic properties, such as magnetite and titanomagnetite. Wet high-gradient magnetic separators (WHGMS) and wet high-intensity magnetic separators (WHIMS) are used to separate the minerals having weak magnetic properties such as hematite, goethite and limonite from gangue minerals [3, 4]. Synchronically Xiong et al. [5] explained major problems about the WHIMS and WHGMS that when metallic ores are treated in these separators, matrix dogging and mechanical entrainment of nonmagnetic particles occur, because hematite ore contains a large amount of weakly magnetic particles along with it. The change from gravity-based separation to magnetic-based separation improved the iron grade by approximately 13%. Concurrently, Pradip [6] examined that multigravity separation is the most effective technique for processing low-grade Indian iron ore slimes to decrease alumina content. However according to Roy and Das [7], this beneficiation method is not commercially successful due to its low capacity. Later on people combined two methods, i.e. magnetic separation and selective flocculation, and found good results. The gravity and magnetic methods, i.e. physical separation techniques, are restricted to coarse-grained sizes. So, when the size is extremely fine, in case of slimes, the physicochemical properties start dominating over physical properties; hence these methods are unable to give satisfactory results. Hence, froth flotation is the single most important unit operation, which is the root solution to all these problems and used for the recovery and upgradation of valuable mineral, especially below 150. Froth flotation which uses the difference in physico-chemical surface properties of minerals is employed in several industries for fines processing. This chapter addresses how flotation has been and can be helpful in recovering the metallic values from the tailings, through a review of basics and fundamentals, efforts made earlier and future directions for research.

FUNDAMENTALS OF FROTH FLOTATION The most important factor in froth flotation process is the selectivity, which means the choice of a suitable reagent to selectively modify the surface of desired mineral to enhance its hydrophobicity. This implies a thorough knowledge of the particle surface property, the mechanism of particle surface-reagent interaction and the correct type and quantity of the reagent

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to create the best selectivity conditions. Surfactants play the most important role for a successful operation of flotation process. To make the mineral float, the surface of such minerals has to be modified by adsorption of suitable surfactants in order to reduce the Gibbs’ energy. Ensuring maximum floatability of desired minerals through maximum selectivity with the aid of reagents is the key element of flotation research and the driving force of flotation research efforts [8, 9]. From an early modest beginning to treat base metal sulphides, it has been established itself as the most versatile process for the treatment of oxide ores, carbonate ores, industrial minerals and fine coal. It is not an exaggeration to state that there is not a single mineral or ore system which cannot be treated by froth flotation (Figure 1).

Figure 1: (a) Schematic representation of flotation process and (b) flotation mechanism and role of contact angle [10].

In flotation of minerals, contact angle plays a major role in hydrophobicity as it is directly proportional to hydrophobicity. The more the contact angle, the greater is the hydrophobicity and the more is the floatability. Despite numerous years of research and development work since 1900, flotation is still not fully interpretable and remains a challenge, as there is involvement of the major phases (macroprocesses) and the number of interrelated events (microprocesses) (Figure 2).

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Figure 2: Process and phases in flotation [11].

Ensuring maximum floatability of desired minerals (with good grade and high recovery) through maximum selectivity with the aid of reagents/ surfactants is the key element and driving force of a successful flotation research. Flotation of different minerals is broadly divided into three main types: • • •

Salt-type flotation Sulphide flotation Oxide flotation o Salt-type minerals include carbonate, phosphate, sulphate, tungstate and some halide compounds. They are known for their ionic bonding and moderate solubility in water. Salttype minerals are difficult to float because they contain common cations; hence modifying agents, e.g. ammonium phosphate, calcium sulphate, sodium sulphate, nickel chloride, zinc chloride, sodium chromate, barite, celestite, gypsum, etc., are used to obtain the selectivity. o Sulphide minerals are less electronegative than oxide minerals; hence it forms fewer ionic bonds than oxygen. Sulphur has greater tendency to form covalent bonds, especially S-S linkages, e.g. chalcopyrite, cuprite, pyrite, sphalerite, galena, etc. o Oxide minerals include metal oxides, carbonates, silicates

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and fatty acids having saturated and unsaturated hydrocarbon chains that are used to float it, e.g. hematite, magnetite, goethite, quartz, malachite, etc. Generally flotation is practised in two different ways around the globe: •

•

Direct flotation—The flotation in which surfactants are added to selectively float the value minerals while the gangue minerals are collected in the tailing launder Reverse flotation—The flotation in which surfactants are selectively added to float the gangue minerals while the value minerals remained depressed with specific reagents as pulp product

Origin of Surface Charge and Zeta Potential When mineral is suspended in water, charged species/ions (potential determining ions) are transferred upon the surface which develops an electric charge or electric double layer. In the case of oxide minerals, H+ and OH− ions are the principal potential determining ions, and they interact with water and produce surface hydroxyls [12]: (1) Due to the charge inequality, a double layer around the particle’s surface is created. The potential difference between the stern layer and diffused layer is known as zeta potential. At certain pH, an equal number of positive and negative surface sites are created, where the surface is having no specific charge, termed as point of zero charge (PZC). These two terms have great influence on the flotation performance of mineral at specific pH. Zeta potential denotes charge properties of particles and in turn implies adsorption, penetration and adherence of certain substances. Processes such as adsorption, particularly surfactants or macromolecules, can alter the interfacial behaviour of the solids markedly. Adsorption and desorption of potential determining ions (H+ and OH− ions) play an important role in accounting the surface charge:

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(2) In Eqs. (1) and (2), M denotes the metal. In the case of iron ores, the isoelectric point of natural hematite varies in between 5.98 and 7.01, depending upon the association of gangues. If the hematite particles are not liberated completely, then isoelectric point will be closer to quartz. The zeta potential of quartz depends on the hydroxylation of quartz surface at different pH values and the interaction of amine species. The pHPZC and pHiep values for various oxides and hydroxides of alumina vary widely (pH 5–9.6) depending upon the association of other minerals [11]. The pHiep of quartz is at pH = 2.5, below which it acquires a positive charge, and above this pH, the quartz surface acquires negative charge (Table 1). Table 1: Represents the pHPZC and pHIEP of some minerals, which has been modified from the data of Parks [13] and Kosmulski [14] Minerals Quartz, SiO2 Cassiterite, SnO2 Sulphides, MeS Diamond, C Rutile, TiO2 Ilmenite, FeTiO3 Hematite, Fe2O3 Barite, BaSO4 Tenorite, CuO Dolomite, (Ca, Mg)CO3 Alumina, Al2O3 Magnesite, MgCO3 Periclase, MgO

pHPZC quartz > kaolinite > montmorillonite > goethite [66]. This pesticide can form diastereoisomers which follow linear sorption isotherms on quartz, corundum and goethite [66]. The isotherms became non-linear for the cis A and trans C isomers on kaolinite and montmorillonite. Kaolinite proved to have the highest sorption affinity towards cis B and trans D isomers [66]. This supports the above conclusion about the possibility of applying kaolinite in remedial operations for the removal of aromatic hydrocarbons, their chlorinated derivatives and pesticides.

The Linear Isotherm In linear isotherms, sorption of HOCs onto soils and clay minerals occurs due to partitioning and is described by the soil/water sorption partition coefficient for the respective sorbate, i.e., Kd (units mL/g or mmol/g) [67,68]. Mathematically, Kd can be defined using Equation (4) as shown below: qe = Kd × Ce

(4)

All terms in Equation (4) have the same meaning as in Section 2.1 and Section 2.2 and the unit of the linear sorption partition coefficient Kd is mL/g or L/kg. The linear sorption partition coefficient is the slope of the linear sorption isotherm [26]. Linear sorption isotherms have been reported by Tandlich and Balaz for

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biphenyl on the illite-rich soil from North Dakota and a commercial sodium bentonite sample [26]. On the illite-rich soil, the Kd value for biphenyl was equal to 42.7 ± 1.8 mL/g after 6 days and this value increased to 120 ± 8 mL/g after 21 days of the sorbate/sorbent contact time [26]. With the commercial sodium bentonite (montmorillonite), the Kdvalue was virtually independent of the contact time, as the respective Kd value was equal to 20.3 ± 0.3 mL/g after 6 days and to 23.0 ± 1.1 mL/g after 21 days of sorbentsorbate contact [26]. After normalisation to the solid/liquid ratios for both sorbents, the six-day contact time, most likely resulted in the sorption onto the internal surface of the clay mineral crystal lattice, while the 21 day period indicated when the soil organic carbon become the dominant sorption site for aromatic HOCs [26]. For other HOCs besides biphenyl, such sorption behaviour could be described a combination of linear and Freundlich isotherms can be observed at low organic carbon concentrations [69]. Mathematical of the resulting isotherm is similar to Equation (2). Wang et al. [70] found that nonylphenol, if sorbed onto the surface of kaolinite at concentrations of 1.0 mg/L, inhibited successive sorption of phenanthrene which is a polyaromatic hydrocarbon. If the dissolved concentration of nonylphenol in the aqueous phase reached 10 mg/L and this solution was in contact with kaolinite prior to phenanthrene sorption, then the apparent Kd values for phenanthrene increased in comparison to the 1.0 mg/L conditioning [70]. The most likely explanation for this observation is that at the initial nonylphenol concentration of 1.0 mg/L, the surfactant and phenanthrene were sorption antagonists. On the other hand, if the initial nonylphenol concentration increased to 10 mg/L, then enough surfactant was likely sorbed onto the kaolinite surface to form nonylphenol hemimicelles or micelles there. If this was the case, then micellial nonylphenol structures would have formed a hydrophobic phase at the kaolinite surface, i.e., thus facilitating increased sorption partitioning of the phenanthrene molecules onto the kaolinite surface. The presence of microbial cells on the surface of the soil mineral phase has been shown to influence phenanthrene sorption [71]. Thus, the combination of the kaolinite with surfactants could provide a viable remediation technology for HOC elimination from the environment.

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HOC BINDING TO SOIL COMPONENTS AND SEDIMENTS HOC Binding to Soil Organic Matter/Carbon Soils are mixtures containing soil micro- and macrobiota, organic components (humin, humic acids and fulvic acids) and minerals [21]. Sorption of HOCs onto soils is dependent on the amount and type of the soil organic matter (SOM) in a given sorbent [47,67], the nature and composition of the soil mineral phase, the water/moisture content of particular soil(s) and the liquid medium that the soil in question is in contact with and that the HOCs are sorbing from onto the given soil [35]. The structure of a SOM will depend on the geographical location of the soil biotope, geological history, bedrock material and the origin of the soil in question [67]. All these factors will have a significant influence on the HOC sorption onto the studied soils [67]. The main compounds and polymers contained in the SOM including the following chemicals [27,43,72]: lignin, proteins, polysaccharides, black carbon, humic acid, humin and fulvic acids. These fractions form the SOM and each of them is a potential sorbent for HOCs and organic chemical compounds/pollutants in general [73]. Particulate organic matter (POM) is part of the SOM and it contains among other things organic debris with particle diameters up to 0.05 mm [43]. POM has been shown to play an important role in the HOC sorption to soils [43]. As with other SOM components, the HOC sorption onto POM will be related to the sorbent’s chemical composition which in turn is a function of the soil’s origin and humification history [43]. As a result of this, sorption of HOCs on POM will differ between individual soils and the type of debris of organic origin found in particular soils [43]. Guo et al. [43] studied the sorption of naphthalene, phenanthrene, and pyrene onto POM. They compared the sorption of these polycyclic aromatic hydrocarbons onto four soils from different origins to illustrate the effect of the different compositions of POM of these soils. The Freundlich isotherm (Equation (3)) was used to analyse the data and the intensity of the HOC sorption was evaluated based on the n values derived from experimental data using non-linear regression [43]. This is based on the fact that the n values describe the site energy distribution on the soil surface [43]. Therefore the smaller the n value, the more heterogeneous the sorption site energy distribution. In the experiments of Guo et al. [43], the POM content did not vary significantly in the four soils examined, with

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n varying from 0.86 to 1.00 [43]. POM 1 contained mobile aliphatic carbon atoms and alkyl groups and the respective nvalues were closer to 1.0, i.e., the sorption onto this type of POM was closest to the partitioning mechanism than was the case for POMs 2–4 [43]. Freundlich exponent values ranged from 0.83 for naphthalene to 0.97 for phenanthrene, while the respective value for pyrene was equal to 1.00 [43]. These results indicate that the number of aromatic rings in a polyaromatic hydrocarbon and the molecular volume likely influence the sorption of polyaromatic hydrocarbons onto soils. Sorption of cypermethrin to POM was also influenced by the nature and origin of POM; and the extent increased with the increasing coating of the clay mineral montmorillonite by the humic material [74]. The affinity of the HOC is influenced by the composition of the NOM, the NOM-chemical contact time and the solute properties [75]. Comparison of the significance of clay minerals and SOM are indicated by studies such as that by Tandlich and Balaz [26]. The authors found that the soil organic carbon became the dominant sorption sites for biphenyl after 21 days of sorption. Up to 6 days of the contaminant soil contact, the external surfaces of the kaolinite provided a temporary sorption site for biphenyl, with the internal surfaces of illite and bentonite becoming more important between 6 and 21 days [26]. Soil organic carbon contains various sub-components with varying affinity for HOCs’ sorption [76]. One such component is soot/black carbon [77]. The HOC soil sorption is affected by the total concentration of SOM, if the concentrations of soil organic carbon (SOC) exceeds 0.01%–0.2% [27,78,79]. Differences in sorption are based on factors such as hydration which is described more in the next Section(s).

Effect of Hydration of the Sorbent and Medium of Sorption Hydration can affect the SOM structure and thus the HOC sorption and any sorption antagonism of any HOC mixtures binding to the SOM. Graber et al. [80] studied the effect of Pahokee peat hydration on sorption of phenol, pyridine and atrazine to this mineral-free SOM. The sorbates were dissolved in water, n-hexadecane and n-hexane [80]. Sorption from aqueous solutions followed the linear sorption isotherms, while Langmuir sorption isotherms were observed in the hydrocarbon media for all three pollutants [80]. For the Langmuir isotherms, the respective qm values were determined to be equal to 1397 ± 137 mmol/kg for phenol, 1082 ± 131 mmol/kg for pyridine and 448 ± 55 mmol/kg for atrazine [80]. The molecular volume of atrazine is higher

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than the corresponding values for phenol and pyridine, and it was quoted as the reason for the lowest qm value out of the three pollutants studied [80]. This is likely caused by the fact that the majority of the atrazine sorption takes place on the outside of the peat particles [80], in contrast to the other two pollutants where the molecular volume likely allowed for pollutant diffusion into the inside of the Pahokee peat particles [80]. N-hexadecane and n-hexane are inert and saturated hydrocarbons and cannot participate in non-covalent interactions such as hydrogen bonding or as Lewis acids and bases in reactions [68]. If sorption from these solvents onto soil particles takes place, non-covalent interactions responsible for sorption will be predominantly determined by the covalent structure of the sorbate(s) and the molecular composition of the sorbent. The type of interactions that are responsible for the sorption of a given HOC onto NOM can thus be deduced by studying its sorption onto the (hydrated) sorbent from an inert solvent. As hydration can stimulate the occurrence of non-covalent interactions such as hydrogen bonds, their significance in sorption can be deduced from sorption of HOCs with varying structures onto Pahokee peat from n-hexadecane [68,71]. Use of this solvent eliminates the influence of polarizability of the tested HOCs on their sorption onto Pahokee peat [68,71]. Under the same conditions, the effect of the compound’s structure on its sorption onto the NOM can be elucidated, along with the structural features in the NOM structure being characterised [68,71]. Using the study of Graber et al. [80], the abovementioned concept was applied to phenol (a hydrogen-donating compound in hydrogen bonding) and pyridine which is a hydrogen acceptor in hydrogen bonds [80]. Graber et al. [80] concluded for the sorption data that the sorption of HOCs from the water system was much higher than the sorption from the hydrocarbon system due to an increased number of sorption sites in the Pahokee peat upon hydration [80]. The hydrated peat structure contains more water molecules than the air-dried matrix. This leads to more hydrogen-bonding potential and thus provides for the increased sorbate mass transfer through/into the Pahokee peat structure based on hydrogen bonds [80]. Such hydration is facilitated by the presence of hydrogen-bonding groups, such as COOH in the structure of the peat. This in turn increases the number of available sorption sites upon hydration of Pahokee peat more, than upon its solvation with organic solvent. More sorption sites lead to higher sorption capacities, i.e., likely resulting in the linear sorption isotherms under conditions of hydration of Pahokee peat in aqueous environments [80]. Similar solvation does not take place in the n-hexadecane, thus lowering sorption uptake for phenol and

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pyridine [80]. These conclusions about the role of hydration in the sorption of HOCs onto the soil organic carbon/matter are supported by the findings of Borisover et al. [73]. They examined the sorption of m-nitrophenol from n-hexadecane, m-nitrophenol from hexane, nitrobenzene from hexadecane and acetophenone from n-hexadecane, benzyl alcohol from n-hexadecane onto NOM [73]. Sorption from water was also studied for all solutes [73]. N-Hexadecane and n-hexane are hydrophobic and were considered the dry inert systems [73]. It was found that the sorption of organic compounds from hydrocarbon solutions on dried NOM was much slower as compared to sorption of organic compounds by the NOM sorbent from water. This is demonstrated by the observation that the apparent sorption equilibrium for m-nitrophenol was reached at about 50 h from the aqueous phase as compared to between 300 and 600 hours in n-hexane and 700 hours in n-hexadecane [73]. They attributed this to the poor solvation of the sorbent in the hydrocarbon phase resulting in the “rigidity” of the sorbent, i.e., formation of new sorption sites for hydrogen-bonding compounds in the hydrated Pahokee peat as compared to peat exposed to the dry peat matrix [73]. Borisover et al. [81] examined twelve systems with the following combination of sorbate/ sorbent/ solvent: m-nitrophenol/humic acid/water, m-nitrophenol/humic acid/n-hexadecane, m-nitrophenol/ humin/water, m-nitrophenol/humin/nhexadecane, nitrobenzene/humic acid/water, nitrobenzene/ humic acid/nhexadecane, nitrobenzene/humin/water, nitrobenzene/humin/n-hexadecane, acetophenone/humin/water, acetophenone/humin/n-hexadecane, benzyl alcohol/humin/water, and benzyl alcohol/humin/n-hexadecane. From their study, the authors concluded that hydration of the NOM may cause up to 2–3 orders of higher sorption of organic compounds in comparison to wetting by hydrocarbon solvents [81]. Acetophenone and benzyl alcohol sorption was higher in the aqueous conditions as compared to n-hexadecane [81]. Lower polarity of the HOCs resulted in stronger sorption to dry humin, as demonstrated by the strength of sorption to dry humin decreased in the following order [81]: nitrobenzene > m-nitrophenol > acetophenone > benzyl alcohol. Sorption of compounds with strong specific interactions, such as H-bonding (benzyl alcohol, m-nitrophenol), is significantly influenced by hydration [81]. For acetophenone and nitrobenzene there was a decrease in sorption upon hydration, whereas the opposite was recorded for benzyl alcohol and m-nitrophenol [73,81]. Thus, hydration of NOM or SOM leads to formation of new sorption sites, but access to them is controlled by the sorbate’s molecular volume and its functional groups.

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Effects of Temperature, Ionic Strength and pH on the HOCs’ Sorption In a study to determine the effects of temperature on sorption by Zhang et al. [60], the Freundlich isotherm best described the sorption data of naphthalene and phenanthrene onto soils between 15 to 35 °C [60]. It was noted that n was directly proportional to the incubation temperature as it increased from 0.713 to 0.893 for naphthalene and from 0.550 to 0.756 for phenanthrene, respectively [60]. Kf for naphthalene decreased from 106.8 to 42.8 in the respective units, while the Kf value for phenanthrene decreased from and 932.7 to 568.9 (mL/g)0.55–0.893 [60]. According to Equation (3), Kf and n are isotherm constants for a given sorbate and sorbent; and they indicate the capacity and intensity of the sorption at a given and constant temperature. Zhang et al. [60] also reported that as temperature increases n increases, i.e., the solute-solvent interaction strength increases which in turn leads to a decrease in Kf. Similarly, an inverse correlation between the temperature and the sorption partition coefficient normalized to the soil organic carbon content (Koc) was reported [60].. The most common explanation is the increase I n the solute’s relative affinity for liquid phase in comparison of the solid phase. The effect of pH has been studied mainly in the soil/aqueous systems. The effects pH on the sorption of 4-phthalic acid ester, dimethyl phthalate (DMP), diethyl phthalate (DEP), diallyl phthalate (DAP) and din-butyl phthalate (DBP), on three soils have been studied [82]. The aqueous phase pH was set to 4.0, 5.5, 7.0, 8.5 and 10.0. An increase in pH leads to the decrease in the Kf as shown in Table 1. At pH 4.0, the maximum Kf values were observed, and thus the sorption capacity of the soils for phthalic esters, was indirectly proportional to the aqueous phase pH [82]. This was attributed to the increase in the dissociation/ionisation of the functional groups on SOM which leads to the increase in the charge in the SOM structure [82]. This resulted in the decreased sorption of phthalic esters to the soils studied as these are non-ionised HOCs. Similar observations were reported in other studies [46,83,84]. Table 1: The Kf values of the phthalic acid ester in relationship to pH (adapted from reference [82] Compound pH 4.0 pH 5.5

DMP Kf 5.31 4.64

DEP Kf 9.87 8.59

DAP Kf 33.1 28.3

DBP Kf 161 147

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3.18 2.70 2.54

6.38 5.85 5.85

21.7 19.6 18.3

128 97.2 91.3

Salting out effect, i.e., the increase in the apparent sorption of non-ionic HOCs into kaolinite in the case increased aqueous phase ionic strength was observed for endrin by Peng et al. [85]. The sorption isotherm was linear and troughs were observed at pH = 5.4 [85]. Hydrophobic and ion-dipole interactions were found to the main non-covalent interactions involved in the endrin sorption to kaolinite [85]. Finocchiaro et al. [86] examined the relationship between the following soil properties: pH, the organic carbon concentration, the content of amorphous iron oxides and the content of clays, and the soil sorption uptake of molinate, terbuthylazine, bensulfuron methyl and cinosulfuron. Extent of sorption of molinate and terbuthylazine was directly proportional to the concentration of organic carbon and the content of amorphous iron oxides [87]. On the other hand, sorption of bensulfuronmethyl to be a function of the soil pH, the organic carbon concentration and the clay content [86]. Finally, the cinosulfuron sorption was positively correlated with the soil pH [86]. Thus all these variables together with the covalent structure of the HOCs must be taken into account when conducting a sorption experiment Behra et al. [87] showed that tributyltin sorbed onto mineral surfaces via cation exchange of the monovalent cation of the tin complex for H+ and Na+, if the pH of the aqueous phase was equal to 6.0 or less. Sorption capacities of mineral surface for cationic version of tributyltin decreased from pure quartz > treated sand > natural sand >> kaolinite [87]. The XPS results indicated that tributyltin sorbs first by creating a monolayer on the mineral surface which thus becomes hydrophobic if the sorbate concentrations reach 100 μM or more [87]. Further sorption past this point occur via dissolution of the tributyltin molecules in the hydrophobic phase formed by the butyl side-chains of the organometallic species, i.e., the mechanism of sorption is likely surface condensation [87].

Interaction of HOC with Soil Mineral Phase Major Soil Mineral Components The mineral particulate nature of soils is based on diameter and consists of sand (50 µm–2 mm), silt (2 µm–50 µm) and clay, with diameters below 2 µm [42]. The dominant mineral structures in clay soils are silicates and

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aluminosilicate mineral structures [88]. Butachlor (CAS number: 2318466-9) belongs to the acetanilide class of herbicides and its sorption onto montmorillonite, kaolinite, the calcium montmorillonite, calcium kaolinite amorphous hydrated aluminium and iron oxides have been reported [89]. The most important clay mineral with respect to butachlor sorption was montmorillonite [89]. This indicates the important role of expanding minerals in butachlor sorption onto soil particles. Structure of the sorbate and the concentration of the soil organic carbon have a strong influence on the sorption of the HOCs onto clay minerals as demonstrated for trichloroethylene [90]. The sorption isotherm can be linear, as shown for trichloroethylene [15,90], or non-linear as reported in selected cases for perchloroethylene [15]. The details of the non-covalent interactions between organic sorbates and clay minerals with specific focus on kaolinite are described below.

Hydrophobicity of Siloxane Groups in Clay Soils in the Sorption of HOC Siloxane groups are composed of alternating silicon and oxygen atoms connected by a covalent bond [-Si-O-Si-] [42,91]. As summarised by Tandlich and Balaz [26], it has been shown by some studies that siloxane surfaces inside the crystal lattice of expandable clays can be without net charge [92]. Theoretical calculations also suggest that the O atoms that are located in the interlayer spaces in the clay crystal lattices are hydrophobic in nature [52]. These findings provide possible sites for sorption of aromatic hydrocarbons [93]. On the other hand, siloxane groups in clay soils can also be hydrophobic in nature, if they do not contain isomorphous substitution [42,91]. In the study done by Su et al. [91] on the adsorption of poly(ethylene oxide) on smectite, they concluded that an interaction between the siloxane groups of the smectites with the -CH2-CH2- of the poly(ethylene oxide) occurred while the poly(ethyleneoxide) hydrophilic ether group formed a hydrogen bond with the OH structures on the smectite. This showed that the hydrophobic part of poly(ethyleneoxide) had a higher affinity for the siloxane groups in the smectite soils [91]. Jaynes and Boyd [93] studied the nature of siloxane in the modified smectite soils by converting them to organo-soils by replacing the hydrophilic, inorganic exchange cations of a series of smectites with the small, hydrophobic organic cation, trimethylphenyl ammonium (TMPA). This limited the adsorption sites to the TMPA cations and the siloxane

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oxygen surfaces. Sorption of benzene, toluene, ethylbenzene, propylbenzene butylbenzene and naphthalene were studied on Wyoming montmorillonite (SAC), an Arizona montmorillonite (SAz) and Washington nontronite (SWa) [93]. The results of their experiments showed that aromatic hydrocarbons can effectively adsorb the siloxane surfaces of the smectites if hydrophilic, inorganic exchange cations are replaced with small, hydrophobic organic cations [93]. The Langmuir isotherm parameters for benzene and propylbenzene obtained suggested that adsorption occurred on the clay surface, and not on the organic phase derived from the TMPA cations. It was discovered that adsorption was inversely proportional to the TMPA from the sorption isotherms. This was because as TMPA content decreased, sorption increased as layer charge increased. They concluded that the organic compounds adsorbed to the siloxane surfaces and this demonstrated the hydrophobicity of the siloxane surfaces in smectites [26,93]. For organic cations, the results of flow-through analysis indicate that sorption isotherms are linear at sorbate concentrations lower than 10% of the cation-exchange capacity for illite and kaolinite, and up to just below 1% of the cation exchange capacity for bentonite [94]. A significant influence of the liquid phase used to leach the solid/clay matrix on the cation sorption by clay matrices was observed [94]. The extent of this effect required the use of correction factors which were based on empirical measurements [94]. The variability in sorption affinities among kaolinite, illite and bentonite could be eliminated by normalisation of the cation sorption to the cation exchange capacity of the given clay mineral [94]. After such normalisation, the importance of organic matter and soil minerals in organic cation sorption was comparable, with the exception of quaternary ammonium salts [91]. This observation stresses the potential significance of clay minerals in pollutant retention as indicated by the results of Tandlich and Balaz [26]. TMPA is a small organic cation. It forms monolayers between the inter layers of the smectite soil. This occurs in both high charge and low charge smectites. The TMPA cations are physically more isolated in low charge smectites than in high charge smectites, hence this leads to more of the inter layer clays surface being available for adsorption. The interlayer of the smectite is composed of the siloxane layers hence the adsorption was attributed to the siloxane bonds. The reduced-charge montmorillonites were prepared from the SAz using Li-saturated and Na-saturated clay suspensions in the ratios 0.3 Li/0.7 Na, 0.6 Li/0.4 Na, 0.8 Li/0.2 Na, and 1.0 Li/0.0 Na. The soils were respectively coded as 0.3 Li-250, 0.6 Li-250, 0.8 Li-250, and 1.0 Li-250. From the adsorption isotherms of benzene, toluene, ethylbenzene,

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propylbenzene, butylbenzene, and naphthalene onto SAz-TMPA, 0.3Li250 SAz-TMPA and 0.6Li-250 SAz-TMPA, it was concluded that the more reduced the SAz the higher the sorption of the organic compound [93].

KAOLINITE Structure of Kaolinite Kaolinite is a naturally occurring inorganic polymer. It consists of siloxane and gibbsite-like layers. Its chemical formula is Al2[Si2O5](OH)4. It consists of a 1:1 octahedral alumosilicate sheet with aluminium cations bonded to another tetrahedral sheet with silicon cations [95,96]. These sheets are stacked on top of each other and the adjoining layers form van der Waals forces and hydrogen bonds because of the availability of OH groups and oxygen atoms in the two adjacent layers [95]. The hydroxyl functional groups on kaolinite are the most reactive [95,97]. They often take part in various chemical reactions including ion exchange [94,97]. The inability of kaolinite to expand due to hydrogen bonds [26] means that its internal surface area is negligible as compared to the total specific surface area [93], leading to the conclusion that sorption of HOC takes place mostly on the outer surface of kaolinite [26,98]. The crystal lattice of kaolinite is neutral as compared to other clay soils, and its two well-defined layers, alumina surface and silica surfaces provide two different potential surfaces of adsorption because of the hydroxyl groups and the silica-oxygen bridged surfaces [99]. Kaolinite has a high affinity for organic compounds as compared to other clay surfaces especially illite [100,101]. According to van Duin et al. [99] this could be due to the neutrality of the kaolinite lattice and due to the close proximity of charged counter-balancing ions to the illite surfaces rendering it a low affinity for less polar organic compounds. Saada et al. [100] focused on the hydrophilicity and hydrophobicity of illites and kaolinite. They concluded that only 25% of the kaolinite surface is hydrophilic and the remaining part is either neutral or hydrophobic compared to illites which are 40% hydrophilic [100]. They concluded that as the hydrophilicity of asphaltene increases, the adsorption capacities decreases. Wettability by oils was found to be high for kaolinite surface [100]. The infrared bands of kaolinite between 3700 and 3620 cm−1 correspond to the well-crystallized structure of kaolinite [101]. Cheng et al. [102]

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contradicted Suraj et al. [103] where the bands at 937 and 914 cm−1were attributed to OH bending vibrations and bands at 983 and 1035 cm−1 were attributed to the Si-O-Si in-plane vibrations [102]. As described above, the Si-O-Si represents the siloxane bonds which are hydrophobic and will have a bearing on the sorption of HOC. Table 2 below shows the spectral wave lengths of kaolinite as studied by Suraj et al. [103]. Table 2: Band assignments for kaolinite soil [103] Wave Number (cm−1) 3700 3620 1114, 1035, 1010 938, 918 792, 754 692

Assignments Inner surface -OH stretching vibration Inner -OH stretching vibration Si-O bending vibrations AI-OH bending vibration Si-O-Al compounded vibrations Si-0 stretching vibration

Interaction of Kaolinite with Organic Molecules In a limited number of cases, HOCs can interact with kaolinite through intercalation between the kaolinite layers [104]. Examples include the hydrogen-bonding compounds which undergo interactions between hydroxyl groups of a octahedral alumosilicate sheet and the tetrahedral sheet with silicon, i.e., N-methylformamide (NMF) and dimethylsulfoxide (DMSO). The other reason is that the internal surface area of kaolinite is very small [81], hence only smaller molecules can intercalate. Specific surface area of the sorbent is also a factor to consider. Different methods of measuring specific surface area have been adopted. The ethylene glycol monoethyl ether (EGME) method has been used to calculate both the external and internal specific surface area of the soils (interlayer surfaces of soils and clays) [26,105,106]. In different studies done using kaolinite from different locations it was found that the specific surface area of kaolinite was 25.5 m2∙g−1 [107], 5.9 m2∙g−1 [108] and 15 m2∙g−1 [106]. It has been stated in the literature that non-expanding soils like kaolinite have SSA values ranging from 10 m2∙g−1to 40 m2∙g−1 [106]. Intercalation of NMF or DMSO is an intermediate state in the intercalation of other guest species, [109]. The process breaks down the hydrogen bonds linking the gibbsite and the siloxane layers of kaolinite [102], making kaolinite a single layered mineral [95,110,111]. New hydrogen bonds are

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formed between the inserted molecules and the crystal lattice of the clay mineral [104] and the intercalation process has three stages [112]. The intercalation of kaolinite by organic compounds has been studied in recent years [99]. In the study done by Komori et al. [109] on the intercalation of alkyl amines (CnN; n is the carbon number in alkyl chain) in kaolinite they found out that octylamine was bound to the Al2[Si2O5](OH)4 in the ratio of 2.4 moles of octylamine to 1 mole of kaolinite. Intercalation occurred via an intermediate step where kaolinite/methanol was made from kaolinite/NMF and used as the intermediate. Intercalation was done up to alkyl C18N. These intercalation compounds are applicable as other effective intermediates and extend the variation of kaolinite/organic intercalation compounds. Secondary and tertiary amines could not be intercalated in kaolinite because they lack the ability of forming hydrogen bonds with the hydroxyl groups and basal O atoms of kaolinite [109]. Intercalation of alkylamines was also attributed to the Van-der-Waals interactions between alkyl chains. This was concluded because of the quick deintercalation of C6N when exposed to air [108]. Erten et al. [113] showed that residual amounts of NAPL that can’t be removed from clay media by consolidation settlement are on the order of 0.1 g NAPL/1 g soil particulate matter. Clay minerals can be ion-exchanged with long-alkyl cations which leads to the formation of so-called “organophilic clays” [31]. Such matrices have been shown to adsorb up to 0.93 g NAPL/1 g of organophilic clay [114]. This has been reported to have a significant effect on the perturbation of the NAPLs from Soltrol 130 through the kaolinite matrix [114]. Organophilic clays, such as kaolinite modified with cetyltrimethylammonium bromide have been shown to exhibit linear sorption uptake for hydrophobic chemicals, as demonstrated for chlorobenzenes [115]. The apparent soil/ water distribution coefficient has been shown to increase from kaolinite to bentonite (montmorillonite), i.e., the surfactants coat both internal and external surface and provide additional surfaces for chlorobenzene dissolution [115]. For ionic liquids, Mrozik et al. [116] found that sorption on kaolinite surfaces took place via multi-layer formation, analogous to the tributyltin results of Behra et al. [87]. The average free energy of sorption values indicated that the sorption mechanism was overlapping of electrostatic interactions between the sorbate and sorbent; and physical sorption [116]. The chemistry of the kaolinite surface has been shown to determine the extent of dye sorption onto the clay mineral. This can be demonstrated by the increase in the sorption capacity of the kaolinite from the Delta

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State, Nigeria, for aniline blue from 1,666 to 2,000 mg/kg upon surface modification with sodium tetraborate [117].

EXPERIMENTAL DETERMINATION OF SORPTION CO-EFFICIENT AND SORPTION KINETICS Experimental Determination of Sorption Coefficient Batch equilibration (BE) is a common experimental method of determination of sorption coefficients. Important factors to consider in the batch equilibration method are: (i) equilibration time, (ii) sorbent and solute concentration, and (iii) temperature [102]. For reliable results these factors have to be determined for the solute and the sorbent in question. After this Kd can determined in the method outlined below. A soil/sediment is weighed and placed in a vial or container. A known concentration of the solute, normally dissolved in the solvent in question, is added. The vial is not filled to capacity hence leaving room for the volatilization of the solute into the headspace of the vial. The vial is sealed and shaken until equilibration is reached. The vial is then centrifuged and the two phases are separated and examined for the concentration of the solute. The amount of the solute which is sorbed onto the soil/sediment may also be calculated by finding the difference between the initial concentration of the solute and the final concentration of the solute. The Kf and Kd are calculated by manipulating the Freundlich and Langmuir isotherms, respectively [26,35]. The sources of error in the batch equilibration method are the length of the experiment i.e., time to reach equilibration and failure of the complete separation between sorbent and the phase in which the sorbent is dissolved [35]. For experiments where a longer time is required to reach equilibration, measures should be taken to avoid physical losses of the solute for example through volatalisation [26,35]. To avoid degradation of the solute by soil microorganisms autoclaving has been used [118]. This is important to avoid loses of solute through degradation. Sodium azide has also been shown to render effective sterilization without altering the chemical structure of the soil [37]. Soil: solution ratio is also paramount in this method. This ratio can be altered to effect a significant change in the difference between the initial concentration of the solute and the final concentration of the solute hence more reliable results. In the batch method it is important to adjust this ratio to between 20% and 80% [102] and in some cases 15%–70% [39] of

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the solute is removed to minimize errors. However it is important to choose this ratio carefully because of the solids’ effect due to the presence of nonsettling particles.

Sorption Kinetics For sorption measurements equilibrium should be reached [42]. This is because there is a saturation of sorption sites; hence no further sorption is expected to occur. This is where a “steady state” concentration has been established. Equilibrium is reached at different times depending on the characteristics of the sorbent and sorbate. as well as the characteristics of the media from which the solute is dissolved. Equilibrium times range from 1 h to a few hours to days, months and years, depending on the structure of the compound and media/sorbent where the individual equilibration takes place [18,37,38,40]. After apparent equilibrium has been reached the amount of solute removed by the sorbent is calculated.

Relationship between Hydrophobicity of the Solute and Sorption When little or no empirical data are available quantitative structure–activity relationships (QSARs) are reliable tools for the hazard assessment of organic chemicals [2,119]. Organic compounds are characterized as more or less lipophilic. Hydrophobicity is important in the QSAR and therefore it is important to determine the hydrophobicity of an organic compound [120]. Lipophilicity/hydrophobicity can be measured using the thermodynamic distribution ratio of the solute between two immiscible solvents. The distribution ratio is defined as the ratio of equilibrium concentrations of a substance distributed in any binary system consisting of two largely immiscible solvents [121]. The distribution ratio that can be called the partition co-efficient P, which is defined as the ratio of the equilibrium concentration of a chemical in the two adjacent phases, 1-octanol and water [122]. P is a routine measurement of a compound’s hydrophobicity [123]. It is possible to investigate the effects of different compound characteristics such as presence of aliphatic moieties, aromatic moieties, hydrogen bonding potential and 1-octanol-water distribution (logKow) on sorption [69]. The partition in water and organic solvent systems was reported by Colander in 1947. He reported that the relationship between partition coefficients of various organic solvents in a two phase system of water/organic solvent, and the partition coefficients of the same solutes in

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a different organic solvent/water system were linear using the logarithmic scale; he thus derived the Colander equation [124,125,126]. Sorption of organic compounds can be regarded as the partitioning of the hydrophobic chemical between and aqueous and organic phases (hydrophobicity) [35]. Hydrophobicity is often quantified using the logKow term which stands for the decadic logarithm of the 1-octanol/water partition coefficients. Octanol is a model of the hydrophobic phase and the organic matter found in soils and sediments may be equated to that of an organic phase in solvent extraction [35]. The sorption capabilities of kaolinite and montmorillonite to sorb HOCs with different lipophilicities is directly proportional to the lipophilicilty. As the lipophilicity increases, the amount of sorbed HOCs increases. Gianotti et al. [98] studied the sequestration of the organic pollutants 2,4,6-trichloroaniline (2,4,6-TCA) with 1-octanol/water partition coefficients (logKow) of 3.74 and 4-chlorophenol (4-CP) with a logKow of 2.49, using kaolinite and montmorillonite. The amount of 2,4,6-trichloroaniline retained by both soils was higher than that of 4-chlorophenol. It was concluded that the lipophilicity of 2.4.6 TCA (logKow= 3.74) resulted in its greater affinity for the soils as compared to 4-CP (logKow = 2.49) [98]. These results were similar to a reported study by Angio et al. [44] on the sorption of, 3-chloroaniline, 3,4-dichloroaniline and 2,4,6-trichloroaniline. A similar conclusion was reported for the sorption of aniline, atrazine, simazine, diuron and aromatic sulfonates as a function of hydrophilicity [40]. Sanchez-Martin et al. [127] studied the relationship between hydrophobicity (logKow) of the pesticides and desorption of these pesticides from the different clay minerals modified with a cationic surfactant octadecyltrimetyl ammonium bromide (ODTMA). The pesticides used with their are shown in the Table 3below. Table 3: The water solubility and logKow of pesticides [127] Pesticide Penconazole Linuron Atrazine Alachlor Metalaxyl

Water solubility (µg/mL) 73 81 30 240 8400

log Kow 3.72 3.00 2.50 2.63 1.75

Desorption of these pesticides from natural unmodified soils followed a

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Freundlich isotherm with R2 ≥ 0.88, while the ODTMA modified soils had the same type of isotherm and R2 ≥ 0.92. The hysteresis coefficient, H, varied with the nature of the clay mineral and, mainly, with the hydrophobicity of the pesticide. Penconazole has the highest H because it’s the most hydrophobic pesticide and metal-axyl from ODTMA-montmorillonite. In the ODTMAmontmorillonite most of the pesticide was adsorbed in the interlayer space. There was no significant correlation between the organic matter content of soils or Kowvalue of pesticides and the adsorption of pesticides by clay minerals. Significant correlations between Kvalues and organic matter were obtained with the ODTMA modified clays. r2 values ranged between 0.81 and 0.96 for adsorption and the correlation between Kdesorption and organic matter content was also high with r2 values ranging from 0.85 to 0.98. Correlations between K, Kdesorption and Kow were related using Equation (5): Kdes = 86.7 OM + 0.53 Kow − 1.57

(5)

Organic molecules which contain ionisable functional groups may also adsorb significantly onto mineral surfaces on the soils [41,128]. Studies have shown that the sorption of HOC is strongly dependent on organic carbon content. Combustion methods can be used to determine the organic carbon content (OC) [26]. In this study the relationship between Koc of naphthalene and aromaticity (AR) as compared with the predicted Koc from Kow [107]. Predicted Koc using was 1,130 mL/g. From the results above it is evident that Kow, the quality of the SOM and aromacity should be considered in order to accurately measure Koc. Sorption of naphthalene was directly propotional to aromaticity. Increase in aromaticity led to an increase in sorption and sorption increased with decrease in polarity of the SOM in the soil [121]. This was because naphthalene is a non-polar polyaromatic hydrocarbon. The relationship between Koc of naphthalene and effective polarity (PI) of the five soils is shown in equation 21 below [121], where PI is effective polarity.

CONCLUSIONS Results of the review indicate that there is a possibility for the presence of hydrophobic siloxane groups on kaolinite and other clay minerals in soils. Thus soils can retain HOCsm, even if the concentration of the soils organic carbon is low. Data presented in this review provides some evidence about the wettability of clay minerals with nonpolar solvents and sorption of HOCs to the clay mineral can take place from aqueous and nonaqueous solvents alike. Therefore it is expected that clay minerals will sorb

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HOC such as NAPLs. Information presented in this review indicates that inorganic cations and surfactants sorbed onto the soils and clay minerals can alter the rate and extent of HOC sorption to these natural sorbents. In line with previous research papers and reviews, soil organic carbon plays a key role in the HOCs’ sorption to soils, but the extent will be strongly affected by the structure of the NOM, SOM, POM and the presence of soot. It is therefore imperative to characterise the soil organic carbon in a particular soil specimen. Due to the emerging pollutants such as mining extractants and antibiotics, more research is needed into predictive approaches such as QSAR in the context of the HOCs’ sorption onto clay minerals from aqueous and non-aqueous solutions.

ACKNOWLEDGMENTS The authors would like to thank the Water Research Commission of South Africa for supporting the study in part (grant number K5/2011/3). The text of the manuscript was not, however, subjected to this funding agency’s peerreview process and therefore no formal endorsement of the manuscript by the Water Research Commission of the South Africa should be inferred by the readers.

AUTHOR CONTRIBUTIONS Francis Moyo has recently graduated with a Masters of Science in degree from Rhodes University and the review chapter that was compiled by him as part of his studies forms the basis of this paper. Francis Moyo also prepared the majority of the manuscript drafts and completed most of the formatting of the references. The second author, Roman Tandlich, obtained the abovementioned grant and guided the research in the context of the completion of grant research goals. He provided the main inputs in the structure of the manuscript and the role of the clay minerals in the sorption of HOCs in soils, i.e. he took the lead in selection of the research questions and topics that the review had to answer and address. Brendan Wilhelmi has a research background in the sorption as a treatment process and in-depth understanding of the sorption isotherm models. He provided critical feedback and crucial input on the types of sorption isotherms that needed to be covered in this review article. He also guided the author team on the mathematical interpretation of the sorption models. Stefan Balaz has extensive experience in the application of QSARs in pharmaceutical sciences and environmental

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chemistry. He has provided input of fundamental importance on the role of QSARs in the soil sorption and the general aspects of mathematical modelling which needed to be covered in this mini-review article.

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113. Erten M.B., Gilbert R.B., El Mohtar C.S., Reible D.D. Development of a laboratory procedure to evaluate the consolidation potential of soft contaminated sediments. Geotech. Test. J. 2011;34:467–475. 114. Erten M.B., Reible D.D., Gilbert R.B., El Mohtar C.S. Contaminated Sediments: 5th Volume, Restoration of Aquatic Environment. ASTM International; West Conshohocken, PA, USA: 2012. The Performance of Organophilic Clay on Nonaqueous Phase Liquid Contaminated Sediments under Anisotropic Consolidation; pp. 32–44. 115. Shu Y., Li L., Zhang Q., Wu H. Equilibrium, kinetics and thermodynamic studies for sorption of chlorobenzenes on CTMAB modified bentonite and kaolinite. J. Hazard. Mater. 2010;173:47–53. 116. Mrozik W., Jungnickel C., Skup M., Urbaszek P., Stepnowski P. Determination of the adsorption mechanism of imidazolium-type ionic liquids onto kaolinite: Implications for their fate and transport in the soil environment. Environ. Chem. 2008;5:299–306. 117. Unuabonah E.I., Adebowale K.O., Dawodu F.A. Equilibrium, kinetic and sorber design studies on the adsorption of aniline blue dye by sodium tetraborate-modified kaolinite clay adsorbent. J. Hazard. Mater. 2008;157:397–409. 118. Bowman B., Sans W. Partitioning behavior of insecticides in soilwater systems: I. Adsorbent concentration effects. J. Environ. Qual. 1985;14:265–269. 119. Xu X., Li X. Sorption behaviour of benzyl butyl phthalate on marine sediments: Equilibrium assessments, effects of organic carbon content, temperature and salinity. Mar. Chem. 2009;115:66–71. 120. Hansch C., Hoekman D., Leo A., Zhang L., Li P. The expanding role of quantitative structure-activity relationships [QSAR] in toxicology. Toxicol. Lett. 1995;79:45–53. 121. Ruelle P. The n-octanol and n-hexane/water partition coefficient of environmentally relevant chemicals predicted from the mobile order and disorder (MOD) thermodynamics. Chemosphere. 2000;40:457– 512. doi: 10.1016/S0045-6535(99)00268-4. 122. Abraham M.H., Chadha H.S., Whiting G.S., Mitchell R.C. Hydrogen bonding. 32. An analysis of water-octanol and water-alkane partitioning and the Δlog p parameter of seiler. J. Pharm. Sci. 1994;83:1085–1100. 123. Hsieh C., Lin S. Prediction of 1-octanol–water partition coefficient and infinite dilution activity coefficient in water from the PR+COSMOSAC

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4 Aqueous Solution Surface Chemistry of Carbon Nanotubes

Anup K. Deb and Charles C. Chusuei Chemistry Department, Middle Tennessee State University, Murfreesboro, Tennessee, USA

INTRODUCTION Since the rediscovery of carbon nanotubes (CNTs) by Iijima in 1991, a plethora of applications have been developed in the fields of biomolecular science, catalysis, environmental chemistry and medicine. Relevant to the development of these new technologies, it is important to effectively characterize and tune the chemical and electronic structures of these materials for desired properties. Within the last 15 years, an array of surface characterization methods have been developed to assay the surface structures of single- (SWNTs) and multi-walled (MWNTs) carbon nanotubes, in particular as organic moieties and catalytically active metal Citation: Anup K. Deb and Charles C. Chusuei (February 27th 2013). Aqueous Solution Surface Chemistry of Carbon Nanotubes, Physical and Chemical Properties of Carbon Nanotubes, Satoru Suzuki, IntechOpen, DOI: 10.5772/51869. Copyright: © 2013 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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nanoparticles are tethered to them. Distinctive physical, chemical, electrical and high thermal properties of CNTs make these materials suitable for widespread applications, such as fuel cells, semiconducting materials in electronics, atomic force microscopy probes, microelectrodes, adsorbents to remove pollutants from waste water, electrochemical sensing and drug carriers. Aqueous surface chemistry plays a vital role in determining the fate and transport of CNTs. A large fraction of the atoms in CNTs reside at or near the surface (Sayes et al., 2006; Bottini et al., 2006). Pristine carbon nanotubes are barely soluble in liquids. To introduce nanotubes in more easily dispersible forms, they require functionalization. These processes entail attaching various organic moities to the sidewalls, which can be used to tether catalytically reactive nanoparticles. Biomolecules require electron mediators to promote electron transfer needed for effective biosensing (Sampath et al., 1998). Electrochemical metal ion sensors require certain functional groups which show potential affinity towards particular metal ions (Mojica et al., 2007). Surface electrostatic interactions in solution also influence the sorption properties of these materials to entrain environmental contaminants on the CNT sidewalls (Tavallai et al., 2012). Historically, the synthesis, fabrication and characterization of carbon nanomaterials have been carried out in vacuum environments. As these materials proliferate in use, knowledge pertaining to their environmental impact (i.e., involving fate and transport in aqueous systems) becomes increasingly important (Cho et al., 2008). Furthermore, preparation and synthesis of these materials in non-vacuum conditions makes these processes more amenable for industrial scale up. Recent attention has focused on modifying SWNTs and MWNTs in solution media. A review of recent advancements to modify CNT surfaces in aqueous media is described in this chapter. Changes in the material properties are often observed concomitant to alterations in surface structure, such as colloidal dispersion and electrocatalytic activity. In the introductory section, the strengths and weaknesses of various traditional CNT surface chemistry probes are presented. Following this, nanotubes that have been chemically modified via chemical oxidation and organic derivatization are discussed. The technique of electrochemical functionalization using carbon nanotubes as the working electrode surface is presented. The next section describes the applications of derivatized carbon nanotubes as it applies to catalysis (involving noble metal nanoparticles), sensing, and selective cancer cell destruction, in which the nanotube sidewall structure plays a key role. The use of transmission electron microscopy (TEM) in conjunction with point-of-zero

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charge (PZC) measurements for exploring structure-property relationships is shown. The final sections present the effects of CNT functionalization on properties pertaining to colloidal stability and isoelectric points relevant for applications in environmental chemistry, catalyst synthesis, and designing materials for the remediation of contaminated ground water.

OVERVIEW OF ANALYTICAL STRENGTHS AND WEAKNESSES

TECHNIQUES:

Traditional analysis methods of carbon nanotubes include Boehm titrations, settling speed measurements, atomic force microscopy (AFM), and quartz crystal microbalance (QCM) measurements, X-ray photoelectron spectroscopy (XPS), attenuated total reflection infrared spectroscopy (ATR-IR), transmission electron microscopy (TEM), Raman spectroscopy, thermogravimetric analysis (TGA) and temperature programmed desorption (TPD). Each of these techniques has its own advantages in the chemical/ structural information that they can provide as well as drawbacks. Wet chemical characterization methods provide a rapid means of characterizing the CNT surface structure. Settling speed measurements is a crude, but rapid technique for measuring the extent of CNT sidewall oxidation containing protic groups with which the solvent can undergo hydrogen bonding (Xing et al., 2005). In this simple experimental setup, the rate at which CNTs fall in a buret (by gravity) is measured and correlated with the extent of surface functionalization. However, no qualitative information regarding the identity of the surface groups is available using this approach. Boehm titrations can be used to quantify the number of proton-containing functional groups (carboxylic acids, hydroxyl groups, lactones, etc.) on the CNT sidewall surface (Boehm et al., 1964). The titrant typically involves various bases ideal for each protic group, e.g., Na2CO3, NaOH, NaHCO3, etc.), the acidity constants (pKa) of which differ by orders of magnitude, rendering the analysis selective to the functional group of interest. But, this technique is ineffective for characterizing CNTs functionalized with aprotic moieties. ATR-IR, AFM, QCM and Raman spectroscopy can be performed in ambient environments (i.e., not requiring vacuum conditions for analysis). ATR-IR is useful for qualitative identification of CNT surface moieties; however, quantitation is not available and some modes are too small to be observed relative to background (Brundle et al., 1992). AFM offers

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the capability of probing changes in CNT surface morphology, sidewall surface coverage and CNT lengths. However, the technique is not amenable to subnanometric scales as thermal noise becomes a major interference at this lengthscale (Magonov et al., 1996). QCM provides a means of monitoring mass changes during the assembly process as CNTs undergo functionalization, but accurate mass measurements are readily hampered by changes in temperature or cavitation (i.e., during ultrasonication) (Brown and Gallagher, 2007). The “diamond” D and G band shifts observed in Raman spectroscopy at ~1300 and ~1600 cm−1, respectively, is a useful tool for assessing the degree of sidewall surface damage encountered in some functionalization methods (i.e., ultrasonication) as well as CNT purity and composition. D and G bands emanate from disordered and ordered sp2hybridized carbon from the graphene sheets, respectively, and are commonly used markers for elucidating covalent bond formation (Dresselhaus et al., 2001). However, spectral interpretion, involving relative D and G band intensity determinations can be complex (Brundle et al., 1992). Vacuum-based characterization tools (the most cost-prohibitive class of these analytical methods), include electron spectroscopy, microscopy and mass analysis. XPS is an excellent tool for monitoring analyte surface oxidation states, and useful for elemental quantification and qualitative identification of surface functional groups. However, large amounts of sample (~ 5 mg) are needed for analysis and peakfitted interpretation can be complex. TEM offers powerful imaging capabilities of the CNT sidewalls to allow for observation of surface roughening that can result from either functionalization or the creation of surface defects. Material length, diameter and dispersion state can also be readily determined by TEM. In addition, spatial elemental analysis is available via energy dispersive X-ray spectroscopy (EDX), as it is often an available technique built into many TEM instruments. However, CNTs are susceptible to beam damage from TEM electrons. Another caveat is that variation in technique involving dispersing samples onto TEM grids and subsequent drying can skew observed results. TGA and TPD can be used to quantify the concentration of moieties tethered to the CNT sidewalls; but, limiting case assumptions, e.g., all of the mass lost (TGA) and bonding modes remain unchanged (TPD), need to be made for assessments, which may not be accurate if the CNT surface chemistry is complex. In addition, large amounts of sample (> 10 mg) are required for TPD and TGA analysis.

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FUNCTIONALIZING CARBON NANOTUBES Both single- and multiwalled carbon nanotubes have a tendency to aggregate into bundles very efficiently via van der Waals interactions in solution. These bundles can be exfoliated by using ultrasonication in combination with suitable surfactants. Typically, the outer walls of pristine carbon nanotubes are chemically inactive. Two major functionalization routes are used to activate CNT sidewalls: (i) endohedral and (ii) exohedral functionalization.

Figure 1: Functionalization pathways of SWNTs: A) defect-group functionalization, B) covalent sidewall functionalization, C) noncovalent exohedral functionalization with surfactants, D) noncovalent exohedral functionalization with polymers, and E) endohedral functionalization with, for example, C60. (Reprinted with permission from [Hirsch., 2002]. Copyright, WILEY-VCH Verlag).

Endohedral functionalization involves insertion of various nanoparticles into the inner walls (Fig. 1E) (Hirsch, 2002). This task can be achieved either by (i) spontaneous penetration with colloidal nanoparticle suspensions filling the inner walls by evaporation of the carrier solvent; or (ii) by wet chemistry, as compounds are introduced into the inner walls of the nanotubes where they are transformed into nanoparticles while maintaining predetermined thermal/ chemical conditions. Various pathways for exohedral functionalization is summarized in Figs. 1A-D (Hirsch., 2002). These avenues include defect group functionalization (Fig. 1A), covalent sidewall functionalization (Fig.

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1B), and noncovalent exohedral functionalization using surfactants (Fig. 1C) and polymers (Fig. 1D). Covalent functionalization, which typically damages the carbon framework and is an irreversible process, is achieved by attaching functional groups to the nanotube ends or defects (Hirsch, 2002; Banerjee et al., 2005). Noncovalent exohedral functionalization, on the other hand, is achieved by wrapping nanotubes using polymers or surfactants (Hirsch, 2002). They leave the CNT carbon framework intact and, it is usually a reversible process. Hu et al. (2005) exohedrally functionalized SWNTs with DNA (noncovalently) by wrapping the outer surface of dispersed SWNTs with single-stranded DNA (ss-DNA). The functionalized ss-DNA-SWNTs have a strong tendency to attach onto glass substrates, forming a uniform film. These behaviors make it possible for electrochemical analysis and sensing. The material is amenable for use as a working electrode, exhibiting good electrochemical voltammetric properties. The electrode has well-defined quasi-reversible voltammetric responses, showing rapid electron transfer properties for Fe(CN)6 3−/Fe(CN)6 4− redox pair systems, important for biosensing as this redox couple has demonstrated the ability to traverse bilayer lipid membranes (Lu et al., 2008).

Figure 2: Arrangement of SWNT sheet in an electrochemical cell. The freestanding sheet of SWNTs underwent electrochemical oxidation upon reaction in potassium nitrite (KNO2) solution (McPhail et al., 2009).

CNTs can also be functionalized electrochemically. Fig. 2 shows the general arrangement of an electrochemical cell where a SWNT sheet is used as a working electrode. This particular set up has been used to functionalize pristine HiPco SWNTs with nitroso (NO) functional groups in which freestanding SWNT sheets were produced via ultrasonication in 1% Triton X-100 solution surfactant. Prior to use as a working electrode for the electrochemical NO group attachment reaction, the Triton X-100 surfactant

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is removed via thermal decomposition in a tube furnace while flowing inert Ar gas is heated to 800°C. The electrochemical reaction forms a N2O4 dimer, which then dissociates into NO groups that attach to the SWNT sidewalls (Piela and Wrona, 2002; McPhail et al., 2009). The mechanistic scheme for the reaction is as follows:

Nitric oxide (NO) is formed from nitrite (NO2−), in which dimerization occurs and followed by disproportionation. The observed nitrogen dioxide (NO2) gas is liberated from the free standing SWNT working electrode during electrolysis. It should be noted that the fabrication technique for the free-standing sheet is not effective for homogeneously electrografting large quantitites of SWNTs (with a ~2 μm thickness), hampering industrial scaleup. This task can be accomplished by using room-temperature ionic liquid (RTIL) to fabricate a supported three-dimensional network of SWNTs as the working electrode (Zhang et al., 2005). In this design, N-succinimidal acrylate (NSA) serves as a monomer dissolved in the supporting RTIL, 1-butyl-3-methylimidazolium hexafluorophosphate (BMIMPF6), electrografted onto the SWNTs. The resulting linear sweep voltammogram (LSV) for the oxidation of glucose is shown in Fig. 3. Voltage is applied to the three dimensional network SWNT electrode from 0 to −2.4 V before and after the electrografting. The passivation peak due to the chemisorption (grafting) of an insulative polymer film on the cathode surface is observed at about −2.0 V in the first scan. After electrografting, the passivation peak disappears, denoting electrografting saturation.

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Figure 3: Linear sweep voltammograms of electrografting N-succinimidyl acrylate (NSA) at the three-dimensional network SWNT electrode in BMIMPF6 during the first scan (a) and the second scan after conditioning at the passivation potential for a period of 40 min. (b). Scan rate: 20 mV/s. (Reprinted with permission from [Zhang et al., 2005]. Copyright, American Chemical Society).

Figure 4: Normalized Raman spectra (the intensity of the strongest tangential modes) of pristine SWNTs (a) and SWNTs-poly-NSA (b). (Reprinted with permission from [Zhang et al., 2005]. Copyright, American Chemical Society).

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Raman bands (Fig. 4) at 1591 cm-1 (tangential modes) and at 1278 cm(disorder mode) are observed in both pristine SWNTs (Fig. 4a) and the SWNTs tethered to poly-NSA (Fig. 4b), showing direct evidence of covalent electrografting. Raman spectra were collected at several different spots for each of these surfaces; no distinctive differences in spectral features were observed, confirming homogeneous functionalization. Control experiments without NSA addition showed no affect on the structure of pristine SWNTs, as observed by Raman spectroscopy.

1

Ultrasonication has become a standard technique for accelerating surface functionalization, employing the cavitation process from sound waves to facilitate acid oxidation. Defect sites are created during this process to facilitate sidewall functionalization (Fig. 1A). It should be noted that acid oxidized functionalization is more amenable to MWNTs than to SWNTs as robust conditions render the latter more susceptible to material decomposition. A sonochemical treatment method under acidic condition has been carried out to functionalize carbon nanotubes with –C=O, –C-O-C–, –COO–, –C-OH groups, which serve as effective tethering points for attaching catalytically active Pt nanoparticles for improved direct methanol fuel cell performance (Xing et al., 2005; Hull et al., 2006; Chusuei and Wayu, 2011). Raman spectra of the D and G “diamond” bands indicate minimal surface damage of the underlying graphene sheet during the sonication process (applied up to 8 hours). Pt nanoparticles were deposited onto these functionalized surfaces via O-containing moieties resulting in the improved electrocatalytic activity. Hull et al. (2006) demonstrated from ATR-IR data that, specifically, the carboxylate oxygen atoms were responsible for effective tethering of the catalytically active nanoparticles. It should be noted, however, that while sonication improves and facilitates functionalization of the MWNT sidewalls, it is possible to overtreat the MWNT sidewalls using this process. In the study, catalytic activity improved when sonication was performed over a 1-hour period, maximizing after a 2-hour sonication treatment. At a 4-hour sonication treatment, however, performance (for the direct methanol fuel cell reaction) diminished. ATR-IR peaks indicated that carboxylate surface structure was damaged after prolonged treatment. These same surfaces also show signs of roughening in the TEM images (Xing et al., 2005), attributable to defect formation and an increased degree of functionalization. Welldefined MWNT sidewall surface structures of the MWNTs are paramount for effective catalytic performance (vide infra).

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APPLICATIONS OF FUNCTIONALIZED CARBON NANOTUBES Functionalized CNTs have distinctive physicochemical properties, such as ordered structure with high aspect ratio, high mechanical strength, ultra-light weight, high electrical conductivity, high thermal conductivity, metallic or semi-metallic behavior and high surface area, which make them amenable for diverse applications (Ajayan, 1999). For example, Zhang et al. (2006) showed that electrochemically functionalized SWNT with polyaniline (PANI) can be used to fabricate chemical gas sensors. In monitoring ammonia gas with the PANI-SWNT composite, superior sensitivity and detection limits with good reproducibility were observed. Fig. 5 shows gas sensing response to various concentrations of NH3, ranging from 50 ppm to 15 ppm, relative to initial baseline. It is clear from the graph that, after exposure to NH3, the resistance of the PANI-SWNT sensor dramatically increased.

Figure 5: NH3 gas sensing results using polyaniline coated SWNTs. The arrows (↔) show exposure times to NH3. PANI was coated on SWNTs using a two electrode configuration at 0.8 V for 5 minutes. (Reprinted with permission from [Zhang et al., 2006]. Copyright, WILEY-VCH Verlag).

When comparing the performance of the functionalized MWNT surface for the direct methanol fuel cell reaction in the previous section (vide supra), catalysts with the functionalized MWNT support exhibited a 48% increase in electrocatalytic activity compared to Pt nanoparticles tethered to the more commercially used Vulcan XC-72 fibrous carbon black support (Xing, 2004).

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The increased activity was due to the finer dispersion of catalytically active Pt nanoparticles (~3.5 nm in diameter) tethered to the CNT sidewalls (as compared to carbon black) made available by uniform attachment of the Pt nanoparticle precursors to ester-like oxygen atoms (Hull et al., 2006). Hence, sonication in aqueous acid environment has been shown to be effective for creating functional tethering points for practical catalyst synthesis. Overjero et al. (2006), similarly applied acidic (liquid phase) oxidation to MWNTs using nitric acid (HNO3) to tether catalytically active Pt, Cu, and Ru nanoparticles. The sturdy support provided by functionalized MWNTs (with oxygen-containing moieties) was responsible for the observed, enhanced catalytic activity.

Figure 6: XP survey spectra of the MWNTs: (a) as received; (b) treated with nitric acid; (c) treated with oxygen plasma. The N 1s region at around 400 eV in trace (b) is magnified 10 times. (Reprinted with permission from [Xia et al., 2007]. Copyright, Elsevier B.V.).

In fact, aqueous solution acid treatments have been found to be more effective than oxygen plasma treatments to functionalize CNTs with oxygen containing moieties. Xia et al. (2007) showed that nitric acid treatment yielded a 60% higher surface oxygen concentration compared to plasma treatment. Fig. 6shows XPS survey spectra of the intensity of nitric acid-treated and plasma-treated MWNTs were recorded to identify the chemical composition. There was no evidence of metallic impurities (i.e., FeCo used to synthesize the nanotubes) present. In addition, after the nitric acid treatment an N 1s peak was found. It can be clearly seen that the intensity of the O 1s peak increased, whereas the C 1s peak decreased due to the oxidizing treatment with nitric acid and plasma treatments. The

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atomic percent oxygen-to-carbon ratios (taking into account differences in instrumental atomic sensitivity factors in the XPS) for the as-received, nitric acid-treated and oxygen plasma-treated MWNTs were found to be 0.118, 0.214 and 0.0526, respectively. The acid-treated MWNTs clearly yielded the higher density of surface oxygen. Functionalized SWNTs have also received attention for their potential applications in medicine. Carboxylic acid functionalization on SWNTs improves electrocatalytic reactivity towards the oxidation of an array of biomolecules, such as dopamine, ephinephrine and ascorbic acid (Luo et al., 2001). SWNTs functionalized with hydroxyl (−OH) and carboxylic acid (−COOH) exhibit antimicrobial properties, capable of inactivating bacterial pathogens. In a study by Arias et al. (2009), modified SWNTs inactivated both Gram-positive and Gram-negative bacterial cells in deionized water and 0.9% NaCl solution regardless of cell shape. Antimicrobial activity increased with both increasing concentration of the CNTs (in colloidal suspension) and treatment time (Arias et al., 2009). In either deionized water or 0.9% NaCl aqueous solution, 200-250 μg/mL of either OH-SWNTs or COOH-SWNTs have the ability to inactivate ~107 cfu/mL Salmonella cells in 15 minutes. The oxygen-containing moieties attached to the cell surface facilitated inactivation. Functionalized SWNTs have also shown promise as near-infrared agents for selective cancer cell destruction (Kam et al., 2005). Engineering SWNTs for this purpose is achieved by tethering pristine SWNTs with folate groups using sonication and centrifugation, in which the HiPco SWNTs are incorporated into a solution of phospholipids with polyethylene glycol moieties and folic acid terminal groups. These folateSWNTs selectively attach to the inside structures of cancer cells that contain folate receptor tumor markers. Cell death is then triggered using near infrared irradiation that thermally decompose cancer cells without harming normal cells, which are folate receptor-free. Kam et al. (2005) demonstrate that while biological systems are transparent to 700-to-1100-nm near-infrared light, there is a strong absorbance of SWNTs within this wavelength region resulting in selective thermal heating of cancer cells. In applications pertaining to ground water remediation, −OH, −COOH, and carbonyl (−C=O) functionalized MWNTs have been shown to have high sorption capacities. In fact, carboxyl-carbon sites are 20 times more energetic for zinc sorption than unoxidized carbon sites (Cho et al., 2010). Along with Zn(II) and Cd(II) chemically modified MWNTs have also been used as sorbent material (Tavallai et al., 2012) for separation and preconcentration of trace amounts of Co(II) and Cu(II) in the environmental and biological

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samples. In this study, MWNTs were modified with thiosemicarbazide and found to be an easily prepared solid and cost effective sorbent. These MWNT materials can be used several times without marked loss in sorption capacity. In another study by Shamspur and Mostafavi (2009), MWNTs were modified using the reagent, N,N-bis(2-hydroxybenzylidene)2,2(aminophenylthio)ethane for applications in ground water remediation. The resulting composite (incorporated into column material) was found to be a useful sorbent for simultaneous separation and preconcentration trace amounts of Au(III) and Mn(II). The reagent remained in the column and it’s use could be cycled several times. Analytical ions were quantitatively recovered with detection limits and enrichment factors comparable or better than an array of commercially available matrices, such as Mberlite XAD-2000, silica gel/nanometer-sized TiO2, Cu(II)-9-phenyl-3-fluorone, Kaolinite/5-Br-PADAP, and Penicillum italicum/Sepabeads SP 70 systems. Furthermore, MWNTs can be modified using electrolysis. Unger et al. (2002) discovered that halogens, such as chlorine or bromine, can electrochemically be bonded to the nanotube lattice. Halogen gases are evolved from the anode and are attached to free-standing MWNT bucky sheets. These chlorine and bromine carbon nanotubes offer a pathway to a wide spectrum of nanotube derivatives. Oxygen-bearing functional groups, such as −OH and −COOH groups, are formed simultaneously, promoting solvation of the nanotubes in water or alcohol without any surfactant. Impurities and low grade modified nanotubes remain insoluble and can be filtered out. Since the functionalized nanotube structure is maintained, soluble material can readily be applied in aqueous solution to solid surfaces for applications, such as electric circuit patterning.

EFFECT OF FUNCTIONALIZATION ON COLLOIDAL STABILITY Without the use of sonication, pristine CNTs are generally hydrophobic in nature and cannot be dispersed in most solvents. The disparity of functionalized CNTs in colloidal particle depends on the nature of the functional groups and colloidal particles. Smith et al. (2009a; 2009b) found that the difference in the colloidal stability of the O-MWNTs was due to the effects of surface oxygen. Small changes of surface oxygen concentration, by as little as 1-to-5 percent results in drastic changes in the colloidal

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stability of O-MWNTs. The amount of oxygen incorporated onto the surface of nanotubes depends on the oxidizing agent used (HNO3, KMnO4, H2SO4/HNO3, O3,H2O2, etc.). Fig. 7a shows the relation between critical coagulation concentrations (CCC) for each O-MWNT with the surface oxygen concentration. The effect of pH with the above two parameters are also shown in Fig. 7b. These plots confirm that, for the vast majority of the O-MWNTs studied, CCC has a linear dependence on surface oxygen concentration over the pH range of 4-to-8).

Figure 7: (a) Influence of surface oxygen concentration on the critical coagulation of O-MWNTs at pH = 4, 6 and 8; (b) three dimensional plot showing the functional interdependence of surface oxygen concentration, pH, and CCC of O-MWNTs. (Reprinted with permission from [Smith et al., 2009b]. Copyright, American Chemical Society).

Fig. 7 shows that for a given concentration of surface oxygen, the colloidal stability of O-MWNTs increases with increasing pH (Wepasnick et al., 2011). In the study, chemical derivatization was used in conjunction with XPS to quantify the distribution of oxygen containing functional groups (e.g., −OH, −COOH, −C=O) on the differently functionalized O-MWNTs. At high pH, the carboxylic acid group was the most predominant surface oxide present. This same result was observed by other researchers (Blanchard et al., 2007). Of the various MWNTs studied, the CCC correlated best with carboxylic acid group surface concentration. A significantly poorer correlation was found with both hydroxyl and carbonyl group surface concentration. In terms of MWNT electrophoretic mobility, Smith et al. (2009a) observed that surface oxygen concentration had no measurable affect on electrophoretic mobility.

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No correlation was observed between colloidal stability of O-MWNTs and its electrophoretic mobility. However, in terms of environmental impact, it is noteworthy that CCC values fell within the range of salinity conditions in estuaries and other fresh water bodies, indicating that O-MWNTs are likely stable and prone to aggregate and/or settle prior to being transported to oceanic environments. Colloidal stability of oxidized MWNTs also changes with pH and electrolytic composition. Smith et al. (2009a) found that the colloidal stability of O-MWNTs increases with increasing pH, which is consistent with previous UV-vis studies of acid treated CNTs (Shieh et al., 2007). CCC values of O-MWNTs vary with counter ion concentration and valence in a manner consistent with Derjaguin-Landau-Verwey-Overbeek (DLVO) theory (Derjaguin et al., 1941; Verwey and Overbeek, 1948). MWNT surface oxygen density also affected MWNT adsorption properties. For instance, when adsorption of naphthalene onto O-MWNTs were carried out with variable surface oxygen concentrations (Ball et al., 2008), the MWNTs with the most concentrated surface oxygen content had the least adsorption capacity in the series. The selection of acid oxidant can have markedly different effects on MWNT sidewall oxidation, as shown by Wepasnick et al. (2011). In this study, MWNTs were treated with six commonly used wet chemical oxidants (HNO3, KMnO4, H2SO4/HNO3, (NH4)2S2O8, H2O2 and O3). Using XPS and EDX to characterize and quantify the extent of surface oxidation, density of −OH, −COOH, −C=O surface groups, and their distribution, these parameters were found to be independent of reaction conditions, but sensitive to identity the oxidant. As MWNTs were treated with (NH4)2S2O8, H2O2 and O3, higher concentrations of carbonyl and hydroxyl functional groups were found to form on the surface. In contrast, as more aggressive oxidant agents (HNO3, KMnO4) were used, higher fractional concentrations of carboxylic acid groups formed. Fig. 8 shows representative transmission electron micrographs of pristine MWNTs exposed to various oxidants, comparing the effects of equal concentrations of H2O2 and H2SO4/HNO3.

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Figure 8: Representative TEM micrographs (left to right): Pristine MWNTs (0.9%), H2O2-treated MWNTs (4.5% O), and H2SO4/HNO3-treated MWNTs (5.3% O). Amorphous carbon is indicated with arrows, and sidewall defects are highlighted by circles. (Reprinted with permission from [Wepasnick et al., 2011]. Copyright, Elsevier Ltd.).

Noteworthy are the effects of the oxidants on amorphous carbon and sidewall defects. The long and straight outermost wall of MWNT denotes uniform and largely defect-free sidewall structure. The overall level of amorphous carbon was reduced during H2O2 treatment, and few defects were generated on the sidewalls. On the other hand, treatment with H2SO4/ HNO3 produced a distortion in the linearity of the MWNT structure. Following KMNO4treatment, MWNTs exhibited a larger fraction of tethered COOH groups compared to other oxidized MWNTs with a relatively low amount of sidewall damage. The identity of the CNT surface functional group has a large impact on the surface charge of the sidewalls. While using MWNTs as catalyst supports, the point-of-zero charge [PZC, defined as the pH at which the solid-aqueous solution interface is electrostatically neutral, according to the electrical double layer model described by Gouy-Chapman theory (Brown et al., 1999)] is an important parameter to consider when anchoring metal complex precursors to maximize dispersion and loading on the MWNT sidewalls. Lee et al. (2011) showed that the treatment of nitric acid-oxidized MWNTs by ethanol reduction at 20 atm and 180°C was an efficient method for producing a high surface density of −OH groups, which in turn provided effective tethering points for grafting metal acetylacetone metal complexes to the MWNT surface. Since the tethering of cationic/anionic precursors is Coulombic in nature, the PZC can serve as a guide for electrostatic attachment of precursors to engineer the MWNT sidewalls. Similarly, when functionalizing CNT sidewalls with specific moieties, the PZC is an important parameter for depositing finely dispersed metal nanoparticles from precursors in solution. McPhail et al. (2009)

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functionalized HiPco single-walled carbon nanotubes (p-SWNTs) with carboxyl acid (COOH-SWNT), nitroso (NO-SWNT), and maleic anhydride (MA-SWNT) groups. PZC values measured using a method described by Park and Regalbuto (1995) were found to be in the descending order: NO-SWNTs (7.5) > p-SWNTs (3.5) > MA-SWNTs (2.0) > COOH-SWNTs (1.2). The trend in measured PZC values correlated well with the electron withdrawing character of the moieties. Of the functional groups used, those with a greater electron donating character resulted in a higher PZC. By varying only the predetermined selection of the functional groups for sidewall attachment, the PZC of HiPco SWNTs could be tuned within a range of 6.3 pH units. Furthermore, UV-vis-NIR and Raman spectra showed that increasing electron withdrawing character of the functional groups led to greater selectivity for covalent attachment to those SWNTs with greater semiconducting character. The extent of CNT surface oxidation has also been shown to directly impact catalytic reaction rate. Rocha et al. (2011) modified MWNTs using nitric acid at 100°C (boiling temperature), liquid phase urea at 200°C, and gas-phase nitrogen at 600°C in order to produce materials with different textural and chemical properties. In this example, a decrease in sidewall oxidation resulted in increased initial reaction rate for the decomposition of oxalic acid, an important reaction for the clean up of contaminated industrial waste waters. The modified MWNTs were directly applied for catalytic wet air oxidation (CWAO). No impregnated metals were used. This methodology is commonplace among other researchers for preparing Pt-based MWNT catalysts (Yang et al., 2007; Yang et al., 2008; Garcia et al., 2005). The array of functionalized MWNTs studied by Rocha et al. (2011) were as follows. Original, untreated MWNTs (CNT-O) were oxidized in nitric acid and rinsed in distilled water until a neutral pH was attained, followed by drying (CNT-N). The resulting CNT-N was then treated with urea in a high pressure reactor. The MWNTs were then rinsed, dried, and subjected to gas phase thermal treatment under N2 flow at 600°C for 60 minutes to produce CNT-NUT. Excluding CNT-O, which was used as the starting material, the successive treatments resulted in a lowering of the density of oxygen-containing functional groups on the MWNT sidewalls in the descending order: CNT-N > CNT-NU > CNT-NUT. These catalyst surfaces were then examined for their ability to degrade oxalic acid. Fig. 9 shows the relationship between PZC values and initial reaction rate constants, as well as with the basicity (indicated by the decrease in PZC values). The decrease in reaction rates were as follows: CNT-NUT > CNT-O > CNT-NU > CNT-N.

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Accompanying reaction rate increase, the PZC increased with decreasing oxygen-containing moiety density. Noteworthy is the fact that the 1st-order rate constant for oxalic acid decomposition was elevated with increasing PZC while the density of oxygen-containing functional groups decreased. The data indicated that the there were fewer oxygen-containing groups in the CNT-NUT than in the original untreated CNT-Os. The CNT-NUT MWNTs was the least acidic in this series of MWNT catalysts. Catalytic performance for oxalic acid decomposition in CWAO depends mostly on the acid/base nature of MWNTs. Weak activity for CNT-N (having the second largest available surface area in this series of catalysts) can be correlated to the acidic character of the nanotube sidewall surface. The result implies that MWNTs with lower acidic character are more efficient for decomposing oxalic acid.

Figure 9: Apparent first-order initial reaction rate constants (k) (for the decomposition of oxalic acid) vs PZC for the original and treated MWNTs (Rocha et al., 2011).

CONCLUSIONS In summary, the surface chemistry of CNT sidewalls markedly affects its properties relevant to an array of applications. Non-reversible, covalent functionalization often damages the carbon structure and/or creates defects for moiety attachment in order to make these surfaces chemically active. CNT sidewall surface structure, which can be engineered via surface functionalization in solution, can significantly affect heterogeneous catalytic

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properties. More recently, methods for electrochemical functionalization and manipulation of the solid surface isoelectric point have been developed to diversify our ability to engineer CNT sidewall structures. The effects of oxidizing agents on the colloidal stability of these materials and the role of the PZC have become increasingly important for engineering nanomaterials in aqueous solution environments. The direction of future research will undoubtedly involve detailed elucidation of structure-property relationships involving these parameters.

ACKNOWLEDGMENTS AKD and CCC gratefully acknowledge support from the Chemistry Department and the Faculty Research and Creative Activity Committee (FRCAC) of Middle Tennessee State University.

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5 Reverse Flotation

Fatma Deniz Öztürk Dicle University of Mining Engineering Department, Diyarbakır, Turkey

ABSTRACT Reverse flotation of coal can be explained as a process where valuable minerals are depressed, while undesired and unhealthy minerals are floated with the help of some reagents. Nowadays, conventional enrichment method of coal could not achieve removing unhealthy minerals partially from internal structure of coal such as sulfur, Hg, Au, which propagate in air after burning treatment, or heavy metals such as Be, Cr, Ni, As, Cd, Co, Ni, Sb, Se, Pb, Co, Cl, Be, Ba, which involve in water and soil where habitat and human health can directly be influenced from them. In fact, reverse flotation of coal enables to remove these undesired mineral content from Citation: Fatma Deniz Öztürk (September 12th 2018). Reverse Flotation, Energy Systems and Environment, Pavel Tsvetkov, IntechOpen, DOI: 10.5772/intechopen.74082. Copyright: © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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coal structure not only in macro size but also in micro size. On the other hand, like undesired minerals, valuable ones like vanadium, germanium, etc. are also taken from coal particles by using the same procedure. Thus, with all these respect, reverse flotation is considered as an alternative and innovative solution for coal beneficiation especially for low rank coal since low rank coal is more compatible for reverse flotation because of being more hydrophilic which means tendency to float is less. Around the world wide, most of the coal reserves belong to low rank coal, so application of reverse flotation is becoming more inevitably common in future. Keywords: Coal, reverse flotation, mineral matter, collector, depressant, frother

INTRODUCTION Coal is a type of sedimentary rock, which exists in nature in the form of black-dark gray and brown-black color and consumed as fossil fuel. Besides, coal possesses carbonated plants, and its proportions in terms of weight and volume are more than 50 and 70%, respectively [1]. Raw coal is enriched by different beneficiation methods that are mainly gravity-based separation and flotation. In gravity-based separation, undesired substances, which are not compound of coal, might be reduced but it could not be effective on ingredients being in internal structure of coal. It is dangerous to consume raw coal as fossil fuel for environment due to high amount of sulfur ingredients, because impurities like sulfur produces harmful gases after heating process. Therefore, in order to remove these undesired contents, flotation is applied as an enrichment method. Flotation, as the name implies, is expressed like separation of substance in compound form by floating process. Floatability of material is crucial aspect for efficiency of flotation. For coal mineral, some of them have natural floatable properties because of its nature, but some others do not possess an inherent floatability because of its internal structure properties [2, 3, 4]. The surface texture of coal particle may involve both hydrophobic and hydrophilic zones. Thus, domination of this zones is one of the criteria which decides whether coal is floatable or not [5, 6]. Another criterion for defining floatability of coal particle is moisture content. For example, lignite, which involves 70–80% carbon, has high moisture content and extremely less hydrophobic disposition. The chemical structure of lignite is altering due to elimination of polar groups like hydroxyl

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and carboxyl groups, and natural moisture content decreases during the transition from lignite to bituminous coal. As a result, coal comes in position of more hydrophobic. Moreover, the content of carbon is in relation with hydrophobicity of coal, too. In the range of 81–89% of carbon content, polar character loses its influence, and coal becomes more hydrophobic. Hydrophobicity of coal reaches its maximum level in 89% of carbon content, and it decreases slightly when the carbon content climbs up from this level. The flotation is directly related with the floatability of particles, so higher carbon content makes conventional flotation process easier [7, 8]. In addition, flotation efficiency is directly related with the properties of the inorganic and organic mineral impurities existed in coals and amount and dispersion of gangue mineral inclusion. It is not possible to remove these finely dispersed impurities inclusion by applying physical methods [9], so flotation should be taken in consideration inevitably in the manner of protecting environment and recovering valuable minerals. In this respect, flotation is playing significant role in supplying raw materials for various industries. More than 2 billion tons of minerals and fine coals are being processed annually by using flotation in worldwide [10]. For this reason, flotation becomes one of the most important methods for enrichment of minerals and is commonly used in the world [10, 11, 12, 13]. At the same time, flotation is utilized for finely-grain-sized coal upgrading [14, 15, 16, 17, 18], fly ash decarburization [19], and wastewater treatment [20]. Since coals and ore are liberated in fine grain size, tendency to flotation in mineral processing increases [21]. For environment, sulfur and ash content of coal is too important because heating process leads to propagate harmful gases to the environment. Flotation is one of the effective methods for desulfurization and deashing of raw coal having high ash and sulfur content [22]. Flotation properties depend on the surface texture and other features of particle, so to make particle float or depress in pulp, some different reagents are governed. In conventional flotation, oily collector and frother are used, and these reagents are conditioned in a period of time [23, 24]. In flotation of low rank coal, it is difficult to obtain good result using oily collector due to surface of minerals with low surface hydrophobicity [23]. For this reason, collector consumption is much more in flotation of low rank coal compared with high rank ones [25]. In low rank coal flotation, in order to increase performance, parameters like grain size, pulp density, reagents type and dosage, pulp pH, flotation and time conditioning, and air entrainment rate should be investigated, and

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[9, 22, 26, 27] most proper condition should be determined with respect to results of them. In addition to conventional flotation method, reverse flotation is also applied on enrichment of minerals. The reverse flotation was commenced to investigate in 1950s [28, 29]. In following studies after 1950s, different researchers also continued to work on that concept [30, 31, 32, 33, 34] and still have been proceeding [4, 25, 27, 35, 36, 37, 38, 39, 40, 41, 42, 43]. However, researchers have not understood completely how particles inside the pulp interact with each other, yet because there are many uncertain factors that influence the surface of minerals and coal existing in pulp. Foremost among these factors is that coal possesses different type of elements and behavior of these elements has not been identified; thus, theoretical and experimental verification of interaction between elements is difficult. For that reason, more researches should be performed in that regard. Studies until current time are generally associated with reduction of pyrite and ash. However, recovery of valuable elements in coal should also be taken into consideration in the environmental aspect as well, so the objective of this study is to discuss the benefits of reverse flotation of coal for environment on the behalf of past researches.

PROCESS OF REVERSE FLOTATION Ash Reduction Ash content is important for both environment and flotation efficiency. Ash content in coal can be eliminated by both physical methods and flotation process, but the presence of ash in internal structure of coal particle could not be removed by physical methods. To be able to remove impurities inside coal particle, reverse flotation is applied on coal. In reverse flotation, tailing is taken as clean coal, and concentrate is accepted as gangue minerals. Ash content is crucial for coal flotation efficiency. Froth is the key element of determining flotation concentrate, and between concentrate froth and the ash content, there is a strong relation [44]. Ash reduction in reverse flotation of coal subjects have been developed for 30 years by some important researchers. Stonestreet, Pawlik, and Ding have performed intensive studies on ash reduction in reverse coal flotation. Stonestreet and Pawlik prepared their PhD thesis on reverse flotation of coal separately [4, 45] and continued his studies with Franzidis in advance [39, 40, 41]. In their experiment, clean coal with 7% ash and silica were

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mixed as a feed, and quantity of each element was same. From the results of experiments, reverse flotation process, 92% ash reduction was achieved from feed in which ash content was 54%. In depressed coal, ash content was 12%, whereas the recovery of coal is 27%. Results of experiment show that recovery of coal was not good even it was achieved that high ash reduction was obtained [39]. They continued their experiments to increase the recovery of coal by using three stage addition process, and for same substance, a product of 86% coal throughput involving 12% ash was obtained [40]. Within the matter of improving reverse flotation, they extended their studies and compared the laboratory column cell using synthetic feed mixture consisting coal and quartz. Thus, recovery capacity of coal was much better than in normal flotation [41]. Later, Ding and Laskowski took Stonestreet’s studies step further by adding dolomite and calcite as gangue minerals and surveyed the effects of factors on separation. They used dodecyl trimethyl ammonium chloride (DTAC) as a collector whose properties of separation are good when it is used minimum 6 kg/t [2]. After, Ding further continued to study on reverse flotation using DTAC on subbituminous coal, too. DTAC consumption was dramatically descended from 6 to 1.375 kg/t by applying polyacrylamide (PAM) and zero-conditioning time method. Besides, in order to improve selectivity, dextrin was governed, and the addition of tannic acids as a dispersant improved the quality of concentrate. For the feed ash content of 34.6%, the concentrate of 16.7% ash at 50.4% yield was acquired [36]. On the other hand, Patil and Laskowski carried out their studies regarding to enhancing reverse flotation of coal. Patil drew on dodecyl trimethyl ammonium chloride (DTAB) in reverse flotation as collector, but used no depressant, first. Also, zero-conditioning time method was applied in their studies. Zero conditioning was accomplished by adding necessary quantity of DTAB in one step, immediately after system was exposed to the air. The logic behind the zero-conditioning time is that continuity of reverse flotation should not be interrupted in any case. Air bubbles formed from air introducing carried collectors, DTAB, during the flotation process. The entrainment of DTAB carried in air bubble demonstrated that reduction of ash from sub-bituminous coal (LS-26) from 34.7 to 22.9% with gangue yield of 36.8% by using any depressant. In the existence of depressant which was dextrin with 0.5 kg/t, the ash substance of LS-26 was reduced from 34.7 to 16.5% at the clean coal yield 55% [46]. Generally, researchers have been seeking the behavior of ash particles under the participation of different reagents. They mainly focused on low rank coal like lignite due to their

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hydrophilic properties. Vamvuka also studied on lignite and oxidized coals and used dodecyl amine (DDA) with kerosene in flotation. Ash reduction of 18% with coal recovery of 80% was achieved [47]. Ozturk also proceeded their studies on reverse flotation of Turkish lignite samples involving high ash and sulfur content. They used ionic collector (Aero 3477) and obtained clean coal product of 29.04% ash at a combustible yield of 78.14%, while with non-ionic collector [kerosene], these values altered to 27.04 and 81.19%, respectively [27]. On the other hand, Zhang et al. also worked on reverse flotation, but used different reagents, as a collector dodecyl amine chloride (DAH), as a depressant corn starch, and as a further methyl isobutyl carbinol (MIBC), and observed the effect of particle size in the presence of soluble salt. When the highest reverse flotation performance was achieved, concentrate ash content of 11.30% was obtained with a combustible recovery of 65.29% [43]. Finally, Xia et al. applied reverse flotation on taixi oxidized coals. Dextrin was used as depressant, whereas hexadecyl trimethyl ammonium bromide (HTAB) was oriented as collector [42]. Alternatively, Li studied with sub-bituminous coal involving a significant amount of oxygen which causes to decreasing hydrophobicity. Due to being difficult to upgrade fine fraction in normal flotation, reverse flotation method in which minerals was made hydrophobic by adding collector, whereas coal was made hydrophilic by adding depressants. Li commenced experiments preparing mixture from coarse coal with fine quartz and medium size coal with fine silica. Ash content was dropped around 35% while recovering nearly 85% of combustible material by reverse flotation. The obtained results were much better than that acquired from conventional flotation method. However, when same procedure was applied to fine coal and quartz, separation was not as effective as tests prepared with coarse coal due to influence of hydraulic entrainment [48].

Sulfur Removal In the early age of 1960s, Eveson was the first person who took attention on reverse flotation by removing shale from bituminous coal. After, reverse flotation had become popular among other researchers, and they started to focus on desulfurization of coal by using this method [30, 31, 32, 49]. The presence of sulfur in coal might be found in three forms which can be categorized as organic sulfur, metallic sulfur, and sulfatic sulfur [9, 50, 51, 52, 53]. Organic sulfur in coal originates from carbonated plant, while metallic and sulfatic ones’ source is inorganic sulfur which exists among

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mineral compounds. The most common example of metallic sulfur is pyrite and it is called as pyritic sulfur. In addition to pyrite, other minerals may be involved in coal structure such as marcasite, galena, sphalerite, etc. For sulfatic ones, gypsum may be illustrated [54]. The sulfur content is varying by different types of coal, and sulfur content accounts for pyritic and organic sulfur amount in coals. Even coal substances might be extracted from same ore bed, they possess different sulfur content. Pyritic sulfur may represent 20–80% of total sulfur content [38, 50]. Like ash, pyrite particles may also exist in internal structure of coal, so physical methods are becoming nonfunctional in removal of pyrite from coal substance [28]. Flotation was started to be applied to achieve desulfurization as well. Each type of pyrite mineral shows different floatability properties, and the reason of that was investigated by some important researchers. Feurstenau considered that the cause of that variation is related with the formation of elemental sulfur. Because of being naturally hydrophobic [37, 55, 56], elemental sulfur can conduct with the surface of pyrite, and then, it may behave like a collector for pyrite. Oxidation of pyrite under proper condition forms elemental sulfur, and it is frequently observed in weathered coal, not in fresh coal [57]. Two basic reactions are standing below for expressing elemental sulfur formation from pyrite. These are as follows: (1) Eq. (1) accounts for formation of elemental sulfur under microbial oxidation of pyrite, i.e. pyrite oxides in moist. To proceed the process of oxidation, acidic environment is necessary because pyrite-oxidizing bacteria can grow under this circumstance [37, 38]; that means, during the pyrite oxidation, iron sulfates, type of salts, constitutes, and these are known as flotation depressant [55]. These depressants can only be dissolved when acidic conditions are satisfied in pulp. On the other hand, unlike formation of sulfate format, if elemental sulfur formation is obtained at the end of oxidation, it is assumed that reaction of coal pyrite is similar to reaction of mineral pyrites, and flotation can be carried out on neutral pH range [37]. Second oxidation reaction may take place with water [58], and it is expressed in the form of; (2) In both cases, if conditions are suitable, substantial quantity of elemental sulfur formation on pyrite sulfur can be observed even the elemental sulfur

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is normally an intermediate product in a series of reactions that are over with producing sulfate

[37].

Pyrite has small hydrophobic tendency [55, 59, 60, 61] when its surface is unoxidized. With the presence of water, oxidation takes place on surface of pyrite and forms ferric hydroxide, which leads to decreasing hydrophobicity [62, 63, 64]. In pH range of 4.5–6.9, oxidation products of pyrite act like strong depressant [60], as it was mentioned before. In order to enhance hydrophobic tendency of pyrite, it is required to add some collector like xanthate [65] since floatability of pyrite intimately depends on pH, and highest floatability might be obtained in acidic pulp [38]. Kawatra performed experiments on fresh coal and 1-year aged coal for different conditions. Fresh coal substances were exposed to different pH levels, and the percentage of froth weight being in directly proportional with floatability of pyrite were investigated. pH levels were defined as 8.3, 7.5, 2.3,2.2, and 2.0, and froth weights were found as 5, 4, 98, 98, and 99%, respectively. On the other hand, same procedure was applied on 1-year aged coal at -15°C, and lowest weight was attained around 37% when pH was almost equal to 6.8, whereas pH was dropped to 2.0, achieved weight dramatically increased, and equal to 92%. Lastly, 1-year aged coal substances were heated up to 100°C and tested in pH level 6.2 and 2.0, and results were 7% and 82%, respectively. From the results, it can be understood that freshly ground mineral pyrite is not readily floatable at neutral pH despite of being highly floatable in acidic pH. On the other hand, pyrite oxidation concludes with sulfate formation, which is not hydrophobic. If necessary conditions might be satisfied for forming elemental sulfur, pyrite can be floated. Also, it is shown that under certain condition, pyrite can be floated at neutral pH, but that is not a normal case. [37]

Vanadium Recovery Vanadium is strategic metal and has been extensively used in the field of steel and alloy industry. Tensile strength capacity of vanadium is too high, so 80% of vanadium are utilized for alloy steels, whereas remaining portion is applied in chemical industry [66, 67, 68]. Vanadium is another element that might be recovered from coal by using reverse flotation. Coal vanadium element can be found in some coal minerals such as illite, muscovite, roscoelite, and kaolin in the form of isomorphism, whereas tantalite and garnet are appeared in the form of absorption [69]. In

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addition, quartz, calcite, and carbonaceous are found to be main gangues in stone coal [68]. For many studies, flotation has been popular topic for many years, but there are not much more available studies on pre-concentration of vanadium in low-grade coal by the method [70]. Stone coal was exposed to the two stages of flotation processes to recover vanadium microelement. Mineral composition of coal was calcite, barite, quartz, and V-minerals. Reagents were sulfuric acid (pH regulator), oleic acid (Ca minerals collector), sodium silicate (dispersant), sodium fluorosilicate (SFF and depressant), melamine (EA and V minerals collector), dodecyl amine (DDA and V minerals collector), octadecylamine (DC and V minerals collector, terpenic oil (frother)). pH was kept between 7 and 8, and water glass was used as depressant (2000 g/t). Besides, oleic acid was taken 200 g/t as collector [70]. At the end of this study, selective separation of vanadium-bearing minerals can be achieved in pH 3 using melamine (EA). The final vanadium concentrates with V2O5 grade of 1.88% and recovery rate of 76.58% are obtained by desliming-flotation process and 72.51% of the raw ore is rejected as tailings [70]. Also, results of other tests demonstrate that grade and recovery of V2O5 concentrate are 1.32% and 88.38, respectively, and tailing yield is 38.36%. On the other hand, recovery and grade of carbon mineral which may be used as fossil fuels are 75.10 and 30.08%, respectively [71]. Although vanadium recovery from stone coal is exploring recently by researchers, studies have already been demonstrated how well vanadium is recovered and obtained clean coal simultaneously.

Effects of Rank, Mineral, and Maceral Coal quality is determined by many properties, but major factor is coal rank. The rank of coal is identified by the percentage of fixed carbon, moisture (water), volatile matter, and calorific value in British thermal units after sulfur and mineral matter content have been subtracted. Coal types that might be ordered from lowest to the highest rank are lignite, sub-bituminous coal, bituminous coal, and anthracite [72]. Rank directly influences floatability of the coal since chemical structure changes due to elimination of polar groups during coalification process. At the end of this process, carbon content increases, and result in increasing hydrophobicity [73, 74]. Although, rank and floatability are directly proportional, highest hydrophobicity is achieved in bituminous coal, not anthracite, which has highest coal rank, but difference in floatability is not significant between them [75, 76]. Bituminous coals are

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enough hydrophobic to be floated in further without collector, but in order to improve coal recovery, collector oil is governed [77] even it reduces the coal rank [78]. Moreover, degree of the oxidation of the coal surface is essential for hydrophobicity. It leads coal to act like lower rank coal whose hydrophobicity is lower [4, 79, 80]. However, there are some cases that oxidation increases in the floatability of coal like freshly cleaved coal surfaces. Short-time air exposure may increase hydrophobicity due to drying of the coal surfaces which then becomes more difficult to wet [9]. Coal is composed of many different minerals that influence type of beneficiation method and its applications. These materials cannot be removed from coal totally by using conventional method [81]. Coal has heterogeneous structure, but is mainly formed from inorganic materials such as clay, quartz, sulfides, and sulfates [82, 83]. Mineral content determines the coal grade, and its rate should be less than 50% to be accepted as coal [54]. There are more than 120 minerals involved in coal, and primary ones regarding their degree of presence are quartz, kaolinite, illite, montmorillonite, chlorite (may contain Mn), clays (may also contain Be, Ni, and other trace elements), pyrite (may contain As, Cd, Co, Hg, Ni, Sb, and Se), calcite, and siderite (may contain Mn); not common ones are analcime, apatite, barite, chalcopyrite, clausthalite, crandallite, floricide, gorseksit, goyasite, dolomite, feldspar, galena, marcasite (may contain same elements as pyrite), monazite, rutile, sphalerite (may contain Cd), xenotime, and zircon; and rare ones are chromite, gypsum, gold, gibbsite, rock salt, magnetite, and muscovite [72]. Seventy-six elements of periodic table can be found in coal substance. Some of these are trace elements and their ratios are expressed with ppm. Some trace elements may be concentrated in specific coal bed, which make that bed a valuable resource for those elements such as silver, zinc, or germanium [84]. However, some elements have potential to damage environment like cadmium or selenium if their concentrates are more than trace amounts. Trace elements associated with clays or pyrite are removed from coal by flotation process, and it is significant to dispose all trace element with in the manner of environment and recovery of valuable elements. Nevertheless, except for gypsum, the various forms of ash and germanium, recovered minerals have not been used commonly [72]. In addition to rank and mineral matter, maceral also affects the flotation of coal since coal hydrocarbon structure and hydrophobicity are influenced by maceral content [78, 85]. The macerals consist of lithotypes, and their

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proportions vary. The properties of lithotypes also differ from each other. Macerals are classified into groups according to dominant components, which are vitrine, inertinite, or liptinite, and has different hydrophobicity. For example, the lithotype fusain involving inertinite group macerals is generally the least floatable, whereas vitrian involving vitrinite group macerals is the most floatable [75]. Studies associated with maceral recovery proved that it is possible to regain good volume macerals without much loss of combustible value [83]. The studies on floatability of coal macerals were appeared at the beginning of 1950 by Horsley [8] and Sun [86]. According to Burdon, maceral content changed with increasing time flotation [87]. Even in same flotation cell, maceral content could vary when samples were taken from different place of it [3] because the macerals are the basic microscopic, physically distinct, and chemically different constituents of the carbonaceous matter in coal, which originate from material deposited in the primeval swamps [83]. Due to variance in maceral content, it is essential to define coal nature and response each maceral during the flotation. Based on maceral content in clean coal, the use of coal can be optimized. For example, high liptinite content increases the calorific value, whereas high inertinite content in concentrate stimulates increase in fixed carbon [88]. Rank, mineral content and macerals are influencing the flotation performance and type because these are essential parameters for floatability of coal. Reverse flotation can be optimized for low rank coal because low rank coal can be suppressed more easily since hydrophobicity of low rank coals are more less due to its polar structures. In order to recover valuable minerals and remove hazardous minerals at the same time, reverse flotation is again proper way because mineral content of low rank coal is more compared to high rank coal, so minerals might be floated without taking much more effort. Lastly, macerals can be divided into some groups according to compounds content as it was mentioned before. Coal with lowest floatable maceral, fusain, may be upgraded by using reverse flotation, too.

Effects of pH The pH has great importance in flotation because pH of liquid phase influences the surface characteristics and behavior of mineral and induces minerals to absorb all types of reagents on the surface. Response of reagents to the pH is essential for flotation, and there are no standard pH values for particular minerals in flotation. Instead, it is generally expressed with range for flotation of specific minerals, and it may differ according to participating reagents. For this reason, this may become complicated and

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needed to perform sensitive when highly selective products are required. Like coal reverse flotation, effects of hydroxide ions (OH−) and hydrogen ions (H+) ions are not only important for floating mineral matter but also important for suppressing coal [89]. Mineral surface can be altered with adjusting these ions in pulp. Minerals in pulp can be charged positively or negatively by arranging pH regarding the isoelectric point (IEP). When the pH is higher than IEP, minerals charge negatively, on the contrary, opposite actions will take place in mineral charging. Zeta potential is related with absolute changing in pH with respect to IEP, so it increases slowly [90, 91]. The pH plays important role in pyrite removal, which is hazardous mineral for environment. Mineral pyrite and coal pyrite act different. Inherently, mineral pyrite is floatable, and it loses its floatability when pH is greater than 5.0. When the pH range is between 5 and 9, the recovery of mineral pyrite is not noticeable even neutral oil collectors are utilized to render mineral pyrite floatable. Although same fashion is used for coal pyrite, it does not act as mineral pyrites. In the pH range of 2.2–8.8, coal pyrite can be recovered 31–43%, whereas mineral matter pyrite can be achieved to regain 99% over the same pH range. Kawatra carried out microscopic examination of coal pyrite flotation and resulted in floated materials that were coal and locked coal/pyrite particles. Therefore, it is assumed that coal pyrite was floated due to attachment to coal [38]. Chander and Aplan performed studies to prove that pyrite is inherently less floatable due to exposed oxidation during purifying from coal which may result in destroying floatability of pyrite [34]. The studies show that coal pyrite may be floated due to locked or entrained particles [38]. Some experiments were handled by Kawatra to examine the effects of pH with using different reagents. In the first experiment, the pulp pH was arranged lower than 4.0, and fuel oil was used as collector for mineral pyrite. Flotation could be achieved with the range of that pH, but native floatability was entirely lost with higher pH values. In second trial, coal pyrite was tried to be floated. However, coal pyrite may behave like mineral pyrite, and it was not recovered at neutral pH range [38]. The effects of surface and solution chemistry of Fe(II) and Fe (III) ions on the flotation of both mineral and coal pyrite with xanthate were investigated based on flotation output, zeta point measurements, and thermodynamic calculations. The results showed that existence of ferrous and ferric ions induced pyrite depress in pH range 6–9.5. Coal pyrite was recognized nonfloatable above pH 6 due to large number of ferrous ions resulted from pyrite oxidation. Moreover, thermodynamic calculations demonstrated that formation of ferric hydroxyl xanthate leads to reducing floatability of pyrite

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when the pH is greater than 6.0 [92]. On the other hand, some additional experiments have been performed for different types of minerals existing in coal structure. As it is well known that materials vary between each other with respect to their properties. Like pyrite, ash also can be recovered by reverse flotation along the different pH ranges. Stonestreet performed studies on ash reduction by applying reverse flotation method on quartz coal mixtures with same amount. The result of their studies showed that maximum ash reduction was succeeded using talk water whose pH was equal to 7.6 [4]. After, Pawlik also touched upon ash reduction with different coal substances. Sub-bituminous, bituminous, and oxidized bituminous coal were objective of reverse flotation with different pH ranges. At first, bituminous coal were exposed to different pH ranges, and optimal results for normal and oxidized coal differed. For normal bituminous coal, the flotation yield went into decline for higher pH values than 9.5. However, sharp decrease was observed when pH level becomes higher than 4.0 for oxidized bituminous coal sample. Besides, different tests were performed for sub-bituminous coal/silica mixtures, and for these tests, optimum pH range was determined between 8.3 and 8.6 [25]. Moreover, Ozturk mainly focused on ash reduction by reverse flotation of lignite, and they achieved maximum level of reduction at neutral pH range around 8 [27]. Same with Ozturk, Zhang also implemented reverse flotation on lignite sample at neutral pH level [73]. Lastly, sub-bituminous coal/quartz mixture with ratio 7:3 was subjected to the test, and all tests were done at neutral pH level [48]. Some additional examples are given from different pH ranges to represent bad results. For example, the low ash content of concentrate was obtained around 10.5 pH value due to optimum flotation of calcite and dolomite around this pH [93]. As well as ash and pyrite, some other valuable minerals can also be regained by reverse flotation throughout different pH levels. Ding worked on sub-bituminous coal sample with 48.5% ash content and gangue minerals such as calcite dolomite and silica with the ratio of 7:1:1:1, respectively. These gangue minerals were intended to be floated. In first study, when pH was 10.4, these gangue minerals can be floated [35], whereas in second test, zero-time conditioning was also taken into consideration, and maximum yield was achieved at the 7.5–8.4 pH range [36]. Wang also tried to float calcite as well as vanadium, which has great value in industry. For calcite, pH level varied between 7 and 8, while it was 3.0 for vanadium [70]. Therefore, importance of pH is clearly explained by studies, and more research should be carried out to take a step further in reverse flotation.

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Effects of Particle Size The most important criteria of mineral processing is associated to size of liberated mineral particle. The performance of flotation process depends on the degree of liberation of mineral in fine fraction. For this reason, flotation is applied to minerals that are intended to recover or remove from coal. Coal has a complex structure and possesses various minerals. Although the particle size of coal is generally less than 0.5 mm, liberation may not be achieved in that fraction size, so grinding may become inevitably for well separation. Hence, it is compulsory to apply flotation on coal due to liberation in fine fraction phase. However, finer fraction does not always mean that every parameter related with flotation is obtained in well range. There is a trade of between fraction size and performance of flotation. In Table 1, some studies with different coal type associated with various fraction size are demonstrated. Table 1: Particle size of minerals participating into the reverse flotation Coal type

Particle size (micron)

Sub-bituminous coal/quartz

150–200 (coarse coal), 74–120 (medium size coal) −38 (fine coal), −200 (raw coal) −56 (fine silica), −200 (coarse silica) −425, 250–425, 150–250, 150–74, 74–45, −45 100 (86% of material finer mineral than 100 micron) −38, 38–50, 50–74, 74–154, 154–300, +300 −38, 38–50, 50–74, 74–154, 154–600, 600–1500, +1500 250–500, 250–125, 125–74, −74 +300, 300–75, −75

Lignite with 42.34% ash content Lignite Low grade stone coal (mass fraction) Low grade stone coal Taixi oxidized coal Lignite

Floated min- Reference erals Mineral matter [50]

Ash

[43]

Ash

[27]

Carbon, vana- [71] dium Carbon, vana- [70] dium Mineral matter [42] Ash

[47]

Zhang et al. studied on lignite which possessed 42.34% ash content by applying reverse flotation. Recovery amount and flotation performance can differ with respect to particle size. Maximum performance was obtained for

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−74-micron fraction size with the combustible recovery of 65.29% and ash content of 11.30% after 20 minutes flotation. However, maximum flotation rate constant was achieved in 150–250-micron range, and the maximum reverse flotation index efficiency was attained for −425 microns. Hence, combustible recovery increased with increasing size fraction but meanwhile the concentrate ash content also increased particularly for finer particle sizes [73]. For finer fraction, slime problem appears. Because of that reason, there must be performed detailed studies for finer fraction flotation in order to obtain optimum results.

Reagents (Collectors, Depressants, and Frothers) The purpose of using reagents is to change the surface properties of minerals to adjust which material is floated and depressed. In this concept, regulator reagents (pH adjustor, activator, depressants, and dispersants) are entrained into flotation process to improve quality of selectivity and separation. In Table 2, reagents are demonstrated in three groups: depressants, collectors, and frothers. Most of reverse flotation experiments are listed, and for each test, available used reagents are indicated (Table 3). Table 2: Use of reagents in reverse flotation Coal type Depressant Collector Bituminous coal Inorganic oxi- Octylamine, CTAC, dants FAA, CTAB, CDBAC, LPC Subbituminous Not used DTAB coal Bituminous & Dextrin DTAB, PAM sub-bituminous coal Bituminous & Dextrin DTAB sub-bituminous coal Sub-bituminous Dextrin DTAC coal Sub-bituminous Dextrin Lilaflot D817M coal Clean coal and Humic acids DTAB silica mixture (HA)

Frother MIBC

Reference [29]

MIBC*

[45]

DTAB

[94]

MIBC

[46]

not used

[36]

MIBC

[48]

MIBC*

[45]

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Solution Chemistry: Minerals and Reagents

Calcite, dolomite, silica, and raw coal Quartz and clean cooking coal mixture Taixi oxidized coal Quartz and clean cooking coal mixture Lignite coal

Dextrin

DTAC

Not used

Mineral pyrite Pittsburgh coal

Not used Not used

Aero-3477 (anionic collector), kerosene Fuel oil Fuel oil

Mineral pyrite, coal Quartz and clean cooking coal mixture Lignite coal

Not used

Fuel oil

Dextrin

DTAB

Not used

Lignite coal Low grade stone coal Silica and raw coal mixture

Corn starch Sodium silicate Humic acids (HA)

(Cationic; DDA, TTAB) Anionic; SDS, nonionic (2-ethyhexanol)/kerosene DAH oleic acid, EA, DDA, DC, Mixed Alimine DTAB

HTAB, HPYC

Dextrin

[39, 40]

HTAB

–

HPYB

Not used

[35]

[42, 95] [39]

Pine oil

[27]

MIBC Dowfroth 200 Dowfroth 200 MIBC

[37] [37]

MIBC

[47]

MIBC Terpenic oil MIBC*

[43] [70, 71]

[48] [39, 40]

[25]

Table 3: Abbreviations •

• •

MIBC* indicates that it was not used for all experiments TTAB, Myristyl trimethyl ammonium bromide SDS, Sodium dodecyl sulfate

•

DDA, Dodecyl amine

•

HPYC, Hexadecyl pyridinium chloride HPYB, Hexadecyl pyridinium bromide

•

Reverse Flotation •

EA, Melamine

•

•

DAH, Dodecylamine hydrochloride DC, Octadecyl amine

•

•

FAA, Fatty amine acetates

•

•

LPC, Lauryl pyridinium chloride

•

•

153

CTAC, Cetyltrimethylammonium chloride CTAB, Cetyltrimethylammonium bromide CDBAC, Cetyl dimethyl benzyl ammonium chloride Dowfroth 200, A polypropylene glycol methyl ether

Collectors are the reagents, which cause to arranging hydrophobicity of material. Collectors can be observed into two main topics that are ionic and non-ionic collectors. Non-ionic collectors are organic compounds formed from hydrocarbon chains having no neutral and polar groups, whereas ionic collectors are divided into two groups, anionic and cationic. The surface properties of minerals determine the reagents selections, and after necessary conditioning is done, flotation process starts. Some of the preferred collectors in reverse flotation are DTAB, HTAB, DTAC, and so on. On the other hand, PAM and ferric silicate were governed besides collector in order to increase activation of them. On the other hand, depressants are the reagents which are added to the pulp to make mineral surface more hydrophobic. As depressants, commonly used reagents in coal reverse flotation are dextrin, humic acids, and corn starch. Frothers are utilized for forming small size bubbles and durable forth which can bear floated minerals without getting any damage during transportation process. In reverse flotation, most common reagents are MIBC, and pine oil, terpenic oil, and Dowfroth 200 follows it. On the other hand, the use of frothers is not compulsory for reverse flotation because some collectors possess foaming agents. lternatively, Yi et al., stated that waste cooking oil (WCO) can be converted into a bio-flotation agent (BFA), which can be replaced with diesel improves a new coal flotation agent with Zr-SBA-15 catalyst. Pilot program data demonstrated that WCO to BFA brings saving energy by 13%, and CO2emission by 76% as well as production cost when compared with petro-diesel use [96]. As a new trend, environmental aspects should be considered so that less harmful collectors should be employed within the manner of reducing the damage to environment, and in this respect, more studies should be handled to overcome environmental issues.

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Conclusion Flotation was developing at the end of 1800s, and reverse flotation was first tried in 1960s. Although not much researcher paid attention on reverse flotation issue, they contributed to literature significantly through past 50 years. With respect to these results, it is inevitable to reach success by reverse flotation. SO2 gases are the main triggering factor of acid rains due to propagating toxic gases after burning treatment. Sulfur gases may be found in coal in the form of organic and mineral sulfur (pyrite, marcasite, galena, and sphalerite) and sulfate (Gypsum—CaSO4 ⋅⋅ 2H2O and Barite—BaSO4). In order to restrain environment and habitat from unhealthy gases, before burning treatment of coal, they should be removed from coal. Besides, Hg and U spread to the air by burning treatment. On the other hand, minerals like Be, Cr, Ni, As, Cd, Co, Ni, Sb, Se, Pb, Co, Cl, Be, Ba, etc. may involve in water and vegetation cover and lead to great damage for habitat. These heavy minerals are also dangerous for human body because human body could not get rid of these minerals easily and cause to irreversible damages. Because of that, these minerals should be removed from coal in prior to burning treatment. Another issue about coal is about eliminating the harmful effects of CO2, which causes greenhouse effects. To achieve this, beech trees which has great potential of consuming CO2 gases in photosynthesis process and the habitat of artificial trees should be constituted especially in the area where coal is being consumed as a main energy source.

ACKNOWLEDGMENTS I would like to express my appreciation to Bilal Umut Ayhan (Master of Science student at Middle East Technical University) who provided great help on preparation process of this chapter.

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6 Pulmonary Surfactant Preserves Viability of Alveolar Type II Cells Exposed to Polymyxin B In Vitro

Guido Stichtenoth1, Egbert Herting1 , Mario Ru¨diger2 , and Andreas Wemho¨ner2 1

Department of Pediatrics, University of Luebeck, Luebeck, Germany

Department of Pediatric Intensive Care and Neonatology, Technical University Dresden, Dresden, Germany

2

ABSTRACT Background Exogenous surfactant derived from animal lungs is applied for treatment of surfactant deficiency. By means of its rapid spreading properties, it could transport pharmaceutical agents to the terminal air spaces. The antimicrobial

Citation: Stichtenoth G, Herting E, Rüdiger M, Wemhöner A. Pulmonary surfactant preserves viability of alveolar type II cells exposed to polymyxin B in vitro. PLoS One. 2013;8(4):e62105. Published 2013 Apr 19. doi:10.1371/journal.pone.0062105. Copyright: © 2013 Stichtenoth et al This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.

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peptide Polymyxin B (PxB) is used as a topical antibiotic for inhalation therapy. Whereas it has been shown that PxB mixed with surfactant is not inhibiting surface activity while antimicrobiotic activity is preserved, little is known concerning the effects on synthesis of endogenous surfactant in alveolar type II cells (ATIIC).

Objective To investigate ATIIC viability and surfactant-exocytosis depending on PxB and/or surfactant exposure.

Methods ATIIC were isolated from rat lungs as previously described and were cultivated for 48 h. After incubation for a period of 1–5 h with either PxB (0.05 or 0.1 mg/ml), modified porcine surfactant (5 or 10 mg/ml) or mixtures of both, viability and exocytosis (spontanously and after stimulation) were determined by fluorescence staining of intracellular surfactant.

Results PxB 0.1 mg/ml, but not porcine surfactant or porcine surfactant plus PxB reduces ATIIC-viability. Only PxB alone, but not in combination with porcine surfactant, rapidly reduces fluorescence in ATIIC at maximum within 3 h, indicating stimulation of exocytosis. Subsequent ionomycin-stimulation does not further increase exocytosis of PxB incubated ATIIC. In presence of surfactant, stimulating effects of PxB and ionomycin on exocytosis are reduced.

Conclusion PxB alone shows negative effects on ATIIC, which are counterbalanced in mixtures with surfactant. So far, our studies found no results discouraging the concept of a combined treatment with PxB and surfactant mixtures.

INTRODUCTION Treatment with exogenous surfactant (SF) is mainly applied in primary SF deficiency of the preterm neonate. Occasionally, it is used in conditions of acute lung injury, aspiration of meconium or gastric content and acute respiratory distress syndrome (ARDS), since impairment of endogenous

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SF synthesis in alveolar type II cells (ATIIC) has been described in these diseases. SF shows rapid spreading properties and may be used to re-open atelectatic airways. Thus, it rapidly can reach the majority of terminal airspaces. Based upon this knowledge, several authors have claimed a novel role of SF, which is, to transport pharmaceutical agents to the terminal airspaces. Thus, specific treatment of pulmonary disease could be facilitated. However, this requires exclusion of mutual interaction of SF and the transported agent. The cationic cyclic antimicrobial peptide Polymyxin B (PxB) is an antibiotic isolated from Bacillus polymyxae, mainly used for topical treatment of Gram-negative infections. A recent interest is emerging to use it in the context of multidrug resistant Gram-negative infections [1]. PxB doesn’t affect biophysical activity and, moreover, improves resistance of modified porcine SF to meconium in vitro, while antimicrobial function is maintained [2]. The bactericidal properties of PxB/SF mixtures are preserved in an animal model and reduced translocation of e.g. E.coli from the alveolar compartment to the bloodstream has been described by our group [3]. Thus, PxB is a potential antimicrobiotic additive to SF for treatment or prophylaxis of Gram-negative pulmonary infections. However, concerns exist in regard to systemic or topic adverse effects of PxB. On the basis of past experience originating from the 1970th and 80th, neurotoxic and nephrotoxic properties have been critically re-evaluated recently and may be less than formerly assumed [4]. The objective of this study is to investigate, whether viability or function of ATIIC are impaired by PxB/SF mixtures.

MATERIALS AND METHODS Ethical Statement Studies were approved by the local ethical committee of the Technical University Dresden (reference: 24-9168.24-1/2009-13).

Test Samples Curosurf (Chiesi farmaceutici S.p.A., Parma, Italy; 80 mg/ml) is a modified natural SF produced from minced porcine lungs. It is in clinical use for treatment of surfactant deficiency and contains about 80 mg/ml

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phospholipids and 1–2% SF proteins B and C. PxB (Polymyxin B sulphate salt, 8100 units/mg, Sigma-Aldrich, Schnelldorf, Germany) is diluted in saline to a stock solution (10 mg/ml). The following concentrations were used for subsequent testing: SF (5 and 10 mg/ml), PxB (0.05 and 0.1 mg/ml), SF/PxB (5 mg/ml/0.05 mg/ml; 10 mg/ml/0.05 mg/ml or 10 mg/ml/0.1 mg/ ml).

Preparation of ATIIC ATIIC are isolated from adult Sprague-Dawley rat-lungs as previously described [5]–[7]. In short, lungs of anaesthesized animals are prepared exsanguinous by perfusion and removed from the thorax. After instillation with elastase plus trypsin and stopping the reaction with fetal calf serum, the lungs are minced in DNAse-solution (Deoxyribonuclease I from bovine pancreas, 150KU, Sigma Aldrich, Schnelldorf, Germany) and ATIIC are harvested after serial filtration and centrifugation steps. Macrophages are removed by panning the cells on IgG-coated dishes at 37°C. ATIIC are seeded in 96 well microplates at a concentration of 500,000/well, cultured in Dulbecco’s modified Eagle’s medium (DMEM) plus 10% fetal calf serum, 100 U/L penicillin, 100 µg/ml streptomycin and 24 mM NaHCO3 and cultured in 95% humidified air, 5% CO2 at 37°C for 48 h. The prepared cells from 3 animals are equally distributed to the experiments defined by test samples and incubation period. Within an identical experiment, 9 wells with cells originating from 3 animals are investigated. After 48 h, the plates are washed twice with DMEM to remove non-adherent cells and then incubated with test samples 1, 3 or 5 h before staining for viability or exocytosis. Only serum free DMEM-incubated cells are used as controls. Finally, the cells are washed to remove test samples.

Viability Viability is measured by a previously described fluorescent dye assay [8]; [9]. Cells are incubated with the blue dye resazurin, which is reduced by viable cells to the fluorescent dye resofurin. Fluorescence is measured at 560 nm (excitation) and 590 (emission) in a fluorescence reader (Infinite M200; Tecan; Grödig, Austria).

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SF Exocytosis After incubation with test samples and washout, cells are stained using lyso tracker green (LTG). Since the fluorescent dye is specifically staining the lipophilic compartments of the ATIIC which is achieved by an active transport into an acidophilic compartment, this process is only performable by vital ATIIC. After 30 min, the dye is removed by a further washout. SF exocytosis is measured indirectly, by determination of the remaining fluorescence of the adhered ATIIC at the bottom of the wells using the fluorescence reader. This method has been described in detail [10]. First, the initial fluorescence is determined and subsequently half of the wells are allocated to stimulation experiments by addition of ionomycin (Sigma Aldrich, Schnelldorf, Germany) at a concentration of 15 µM/well during a period of 30 min at 37°C. Following ionomycin washout, kinetics of exocytosis is followed during 45 min sampling fluorescence during 15 cycles at 3 min each. Thus, spontaneous exocytosis can be compared to ionomycin-stimulated exocytosis.

Data Analysis Raw data of fluorescent reader were back-ground corrected, i.e. readings from wells containing non-stained cells were subtracted from raw data. Corresponding raw data of 8–9 wells incubated with identical samples and periods are statistically compared with regard to incubation period or sample. DMEM controls are used as reference. Graph Pad Prism 4.1 software (LaJolla, CA, USA) was used for statistical calculations.

RESULTS ATIIC Viability Resofurin-fluorescence of ATIIC is significantly decreased by PxB (0.1 mg/ ml) after 5 h of incubation, indicating PxB-reduced viability. The effect of PxB is prevented in the presence of surfactant. No significant difference in viability is found in cells exposed to DMEM, SF or PxB (0.05 mg/ml) (Table 1).

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Table 1: Viability of alveolar type II cells exposed to surfactant and/or Polymyxin B Sample

Fluorescence [U] 1h 5h

DMEM SF 5 mg/ml SF 10 mg/ml PxB 0.05 mg/ml PxB 0.1 mg/ml SF 5 mg/ml PxB 0.05 mg/ml SF 10 mg/ml PxB 0.1 mg/ml SF 10 mg/ml PxB 0.05 mg/ml

8342±2811 8703±3403 8977±4003 8375±2574 7890±2743 8623±3466 9271±3245 9505±3003

7271±3423 8627±3809 8172±3725 8056±2848 6162±2206** 8737±3547 8305±2750 8933±2755

Viability of alveolar type II cells (ATIIC) incubated for 1 h or 5 h with modified porcine surfactant (SF) and/or Polymyxin B (PxB) or DMEM control expressed by resofurin-fluorescence, in which viability is decreased in non-proliferating ATIIC (mean±SD; n = 9). A significant reduction in viability is found in ATIIC incubated with PxB (0.1 mg/ml), but not in cells incubated with SF or a mixture of SF plus PxB. No significant reduction of fluorescence is found in any sample comparing 1 h vs. 3 h. p CH3CO2− > (C2H5)2PO4− > Cl− > SCN− > Br− > I− > C2H5SO4−. These results bear on cellulose dissolution in QAEs/DMSO; the biopolymer is easily soluble in TBAF∙3H2O/DMSO but not in other TBAX/DMSO with less basic anions (X = Cl−, Br−, I−) [86]. The extensive use of TBAF∙3H2O/DMSO as solvent for cellulose dissolution and derivatization merits additional comments. At room temperature, anhydrous TBAF is the only R4NX that is liquid; it shares with ILs the property of negative energy of fusion [74]. However, obtaining anhydrous TBAF by dehydration of TBAF∙3H2O without extensive Hofmann degradation is laborious [86]; its preparation in situ from the reaction between tetra-(n-butyl)ammonium cyanide (TBACN) and C6F6 is expensive, [92] and the resulting TBAF/DMSO is relatively unstable [93]. Consequently, the use of commercially available, solid (m.p. 58–60 °C) TBAF∙3H2O/DMSO is convenient. At first glance, the efficiency of TBAF·3H2O/DMSO as solvent for cellulose may seem surprising because the free energies of transfer of the (F−) from water to virtually all dipolar aprotic solvents are positive, i.e., unfavorable due to the strong solvation of this anion by hydrogen bonding to water [94]. However TBAF∙3H2O is still a reasonably powerful nucleophile and base, although both properties are dramatically attenuated as a function of increasing the water content of this QAE [95,96]. The potential problem with the use of this electrolyte, however, is the effect of

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its (uncontrolled) water content on the results, e.g., the reproducibility of the degree of substitution (DS) when different electrolyte batches are employed, or when the same electrolyte sample is employed over a relatively long period. In contact with air, solution of TBAF∙3H2O/DMSO absorbs water continuously for hours [97]. Additionally, the water of hydration present in this QAE leads to hydrolysis of the acylating agent. This undesirable side reaction is general-base catalyzed by (F−). The deleterious effect of this water absorption was neatly shown by measuring the dependence of the chemical shifts and bandwidths of the water protons and (F−) as a function of the water content in cellulose TBAF/DMSO solutions. The results suggest the formation of strong Cel-OH∙∙∙F− bonds, leading to the breakdown of the cellulose-cellulose hydrogen bonds, hence biopolymer dissolution. The latter is favored by electrostatic repulsion between the negatively charged Cel-OH∙∙∙F− chains [82]. Each negative chain is most certainly surrounded by a sheath of the TBA+ cation. The synergism between electrostatic repulsion of Cel-OH∙∙∙anion, and steric repulsionof Cel-OH∙∙∙anion/cation complexes appear to prevent association between cellulose chains and favor a molecularly dissolved state as shown for QAEs [83], and, e.g., for the ILs BuMeIm [26,84,98,99,100,101,102,103] or EtMeIm cation [104,105,106,107,108]. Small concentrations of water strongly solvate the fluoride ions, inhibiting them from association with the cellulose chains. This allows the reformation of the cellulose-cellulose hydrogen bonds, which leads to highly viscous solutions or gel formation. These changes in the physical state of the solution are schematically depicted in Figure 3. Part (a) of Figure 3 shows the cellulose in dry TBAF/DMSO solution; part (b) shows preferential solvation of (F−) by the added water and its removal from cellulose. This lead, finally, to solution gelation due to reestablishing strong hydrogen bonding and hydrophobic interactions between the cellulose chains (c) [82]. Quaternary ammonium fluorides of much less water content were prepared by a simple protocol, e.g., NAl4F∙H2O/DMSO and N11Bz2F∙0.1 H2O/DMSO (Al and Bz refer to allyl and benzyl group, respectively). Both QAE∙xH2O/ DMSO dissolve cellulose and the biopolymer was efficiently acylated in these solvents (see Section 4.3 Ammonium fluorides) [109,110]. Interestingly, tolerance for water as a non-solvent for cellulose dissolution in tetra-(nbutyl)ammonium acetate (TBAAcO)/DMSO is twice as high as tolerance for ethanol (calculated on a molar basis). Based on theoretical calculations, it was suggested that the higher tolerance to water is due to its more efficient hydrogen bond interactions that improve solvation of cellulose and, thereby,

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marginally favor dissolution [111]. The higher tolerance toward water may be traced to the fact that water-DMSO interactions are stronger than waterwater interactions [112,113]. The influence of water and other non-solvents in imidazole-based IL solutions on the cellulose solubility is reported as well, e.g. in [102,114] but is outside the scope of the present review.

Figure 3: NMR-based illustration of the mechanism of water-induced gelation of cellulose dissolved in TBAF/DMSO. The symbols are: red dots = water molecules, green squares = F− (associated with cellulose in (a), solvated by water in (b), partially exposed cellulose chains, which leads to reaggregation (c), black lines = cellulose chains; yellow circles = hydrogen bond regions between cellulose chains; reprinted with permission from [82], Copyright (2009) American Chemical Society.

In summary, the hygroscopic nature of solutions of these QAEs/MS should never be underestimated because uncontrolled water contents have deleterious effects on their efficiency as cellulose solvents, and the economy of the process due to hydrolysis of the acylating agent. Additionally, effort should be made to control the purity, including water contents of these solutions as stressed repeatedly for ILs and QAEs [17,115,116,117,118]. In case of QAEs, the presence of small concentrations of KBr in the commercial aqueous tetra-(n-butyl)ammonium hydroxide (TBAOH) and TBAAcO/ LiCl/DMSO decreased the solubility of cellulose, presumably due to the formation of (K+)-mediated complexes between cellulose chains. Addition of (K+)-complexing crown ether 18-crown-6 resulted in clear biopolymer solutions in both cases and increased the concentration of dissolved cellulose, although this represents an expensive solution to the QAE purity problem (see also Section 4.2 Ammonium carboxylates) [119,120]. The carboxylate group is also a hard base. Therefore, QAEs bearing the carboxylate moiety were successfully tested as solvents for cellulose, with emphasis on TBAAcO/DMSO. Indeed, cellulose fibers from this solvent were obtained without noticeable degradation or (slow) formation of cellulose acetate during dissolution (see Section 4.2 Ammonium carboxylates) [121].

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The latter (acetylation) side reaction occurs during acylation of cellulose in pure EtMeImAcO [122].

Different types of cellulose (MCC, cotton, regenerated cellulose) dissolve in TBAAcO/DMSO at 25 °C [85]. The dependence of wt% dissolved cellulose and dissolution time on the electrolyte mass ratio WT[mass of TBAAcO/(mass of TBAAcO + mass of DMSO)] was BAAcO studied. All results showed increases in cellulose dissolution until WT= 0.15, then a decrease at higher WTBAAcO. The dependence of solBAAcO vent efficiency on QAE is schematically represented in Figure 4, where the degree of dissociation of the QAE is larger at WTBAAcO < 0.15 than at WTBAAcO > 0.15 because of the association of QAE ions with cellulose. The authors corroborated this conclusion by the following pieces of evidence: (i) Dependence of solution conductivity (cellulose/TBAAcO/ DMSO) on WTBAAcO that showed a rapid increase until WTBAAcO ~ 0.15 followed by subsequent slower increase; (ii) dependence of 1H and 13CNMR chemical shifts of the cation and anion on WTBAAcO in DMSO-d6, with a “inflection point” at WTBAAcO ~ 0.15; (iii) dependence of the 1Hand 13C-NMR chemical shifts of the cation and anion of TBAAcO on [cellobiose], showing large changes until WTBAAcO ~ 0.15, followed by small changes at WTBAAcO > 0.15; (iv) dependence of (νS=O) of DMSO on [cellobiose] (decrease in (νS=O) as a function of increasing [cellobiose]. Thus, the balance between ion concentration and mobility is crucial to cellulose dissolution.

Figure 4: Schematic representation of the association of cellulose with the ions of TBAAcO as a function of the mass ratio WTBAAcO of the QAE with DMSO; reprinted with permission from [85], Copyright (2016) American Chemical Society.

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This balance is largely controlled by hydrogen bonding and solvophobic interactions. The favorable effect of DMSO is due to viscosity reduction and stabilization of the cellulose-QAE complex [85]. Similar dependence of viscosity and conductivity of cellulose/IL/MS mixtures and the wt% of maximum dissolved cellulose on IL concentration were also observed for AlMeImCl in DMSO [87]. The rheological properties of cellulose/IL/MS mixtures (mostly DMSO as MS) were studied extensively and data regarding viscosity of these solutions are readily available in the literature [123,124,125,126,127,128,129,130,13 1,132,133,134,135]. The comparison and evaluation of the results is not straightforward because there is no common experimental “protocol” for cellulose dissolution (cellulose type, temperature, IL/MS ratio). The effect of MS on the viscosity of cellulose/IL solution have been reviewed as well [136]. It is noteworthy that the viscosity of QAE/MS solution is important but not a controlling factor because at comparable concentration, the same IL is more efficient in DMSO than in (less viscous) DMAc [88]. Dissolution of cellulose in TBAAcO/DMSO was determined at 60 °C by microscopy and turbidity measurements. The results for three QAEs suggested maximum solubilization at molar ratio QAE/AGU of unity. This conclusion was further corroborated from NMR data. This included 1HNMR chemical shifts of the anion and cation of QAE; diffusion coefficients of the ions of QAE and the MS as a function of the molar ratio QAE/AGU, and the results of molecular dynamics (MD) simulations of the system. The latter calculations indicated binding of the acetate ion to more than one hydroxyl group of the AGU. The calculated contact time between the acetate ion and cellulose is at least an order of magnitude longer than the contact time between any other pair of species in the system (cation-cellulose, cation-DMSO, DMSO-DMSO), a clear indication of the strength of anion∙∙∙HO-Cel hydrogen bonding [83]. The simultaneous binding of the anion to more than one hydroxyl group in the same AGU was also advanced to explain the efficiency as cellulose solvents of R4NF∙xH2O/DMSO and AlMeImCl/DMSO. For both solvents, the halide ion binds simultaneously to C2-OH and C3-OH of the AGU [88,110]. We now address the effects of the volume and charge density of the cation because these variables affect the association anion-cation of the QAE and its (solvophobic) interactions with cellulose, thus bear on its efficiency of as solvent.

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Acidity and Volume of the Cation The quaternary ammonium ions are soft acids [137]. Their volumes are important in determining anion-cation interactions whose strength are determinant to cellulose dissolution, as also shown for IL cations [101,138,139]. This was shown by the fact that TBAF∙3H2O/DMSO dissolves cellulose easily, whereas the biopolymer is insoluble in N1111F/ DMSO and only marginally soluble in N111BzF/DMSO. This was explained on the bases of solubility of these QAEs in DMSO at room temperature: 0.94, 0.025 mol/L and negligible, respectively [93]. As shown above, electrolyte solubility and dissociation into free ions in the MS are required for efficient ion/AGU interactions, leading to cellulose dissolution. This idea was corroborated by (DFT) theoretical calculations. Due to the weak interaction of (F−) with the voluminous (TBA+) cation of TBAF, the anion transfers significant amount of charge into the antibonding orbital of the CelOH groups leading to the disruption of the hydrogen bonding and cellulose dissolution. Due to the smaller volume of (N1111+) of N1111F, the (F−) transfers more negative charge into the positively charged cation, hence cannot disrupt the hydrogen bonding of cellulose; the biopolymer is insoluble [89]. In a systematic study on the effect of QAE cation volume on cellulose dissolution, neat N222RAcO, N222RPrO, N333RAcO, N333RPrO and their solutions in DMSO were studied (N222R and N333R refer to derivatives of triethylamine and tri-(n-propyl)amine, respectively; R = n-alkyl, from butyl to dodecyl). Neat QAE with (R = n-butyl) did not dissolve cellulose, independent of the structure of the parent tertiary amine (N222 or N333). In general, addition of DMSO increased cellulose solubility. The efficient QAEs are those with R longer than n-hexyl, as illustrated in Figure 5. For the most efficient QAE N2228AcO at 80 °C the calculated molar ratio QAE/AGU is 4.8 (neat QAE) and 2.1 (20 wt% DMSO) [73]. The latter (electrolyte/AGU) ratio is smaller than that observed for TBAAcO/DMSO [83], and may reflect the effect of the cation steric hindrance in both QAEs.

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Figure 5: Comparison of the temperature of dissolution of 10 wt % microcrystalline cellulose in pure N222RAcO (top) and in mixtures of N222RAcO/DMSO (80/20 wt%, bottom); reprinted (adapted) with permission from [73], Copyright (2017) Wiley-VCH Verlag.

Regarding the molecular structures formed in solutions of cellulose/ QAE/DMSO quantum chemistry calculations were performed on cellobiose, methylated at the positions O-4 and O-1 as model for cellulose, and QAEs (N1111F, NAl4F, N11Bz2F, and TBAF)/DMSO. We present the corresponding structures in Figure 6 (see reference [90] for details of these calculations).

Figure 6: Schematic representations of the structures of interest, including, the starting geometries of the aggregates (A–C), and (A’) an optimized geometry of A [140,141]; redrawn from [90].

In Figure 6, (A) is cyclic whose structure is similar to that indicated elsewhere [140], whereas (B) and (C) are linear with the (F−) bridging the

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sulfur atom of DMSO either to the quaternary nitrogen of the electrolyte, or to one of the OH groups of the cellulose model. Structure (A´) is the theoretically optimized version of (A). Interestingly, during geometry optimization of (A), the initial cyclic aggregates changed to an F−-centered structure, with change in connectivity, as shown in structure (A´). Based on the results of these calculations, we suggested that the aggregates formed in the system cellulose model/R4NF/DMSO are best represented by (C). This structure is corroborated by the above-mentioned NMR and FTIR data [82,89].

Salts of Super Bases A new class of QAEs based on salts of super bases was recently introduced as potential solvents for cellulose [36,142,143,144,145,146]. These QAEs are prepared by neutralizing superbases, e.g., 1,1,3,3-tetramethylguanidine (TMG), 1,5-diazabicyclo-[[4.3.0]non-5-ene (DBN), 1,8-diazabicyclo[[5.4.0]undec-7-ene (DBU) with carboxylic acids, such as acetic or propionic acid. The mechanism of cellulose dissolution is mainly connected to the basic moieties of the electrolytes, which can disrupt the strong intraand intermolecular interactions within the cellulose structure, as shown in Figure 7. The role of solvent descriptors for regeneration of cellulose from EtMeImAcO, TMG PrO and TMG AcO was also compared with other cellulose solvents, e.g., NMMO and LiCl/DMAc [147]. It was found that solvent basicity (SB) was the property that changed most (almost a linear decrease) upon addition of water. However, the ability of the mixtures to dissolve cellulose was best explained by the net basicity, i.e. (SB-SA), rather than SBalone. A window for regeneration of cellulose was suggested (SB < 0.8 and SB-SA < 0.35). Cellulose regeneration was divided into four stages: gelation, particle formation, biopolymer regeneration with adsorbed IL, removal of the latter by washing. It was also shown that there TMG-based solvents were more sensitive towards water during cellulose dissolution than its regeneration. [86]

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Figure 7: Model for the dissolution of cellulose in protic QAEs on the basis of super bases; redrawn from [143].

Aqueous Solvents for Cellulose Dissolution and Regeneration Because the above-mentioned QAEs solutions are alkali-free, they are suitable for cellulose dissolution, regeneration and derivatization with reagents that are subject to hydrolysis, e.g., carboxylic acid anhydrides and acyl chlorides. We comment now on another class of efficient cellulose solvents, quaternary ammonium- and phosphonium hydroxides because their larger capacity of cellulose dissolution at room temperature enhances their potential use in cellulose regeneration. Additionally, dissolution by these systems is clearly linked to the amphiphilic characters of cellulose and the QAE. Unlike ILs, the presence of water in the solvent is not a barrier to cellulose dissolution. Thus tetra-(n-butyl)phosphonium hydroxide TBPOH containing 40 wt% water dissolves 20 wt% cellulose within 5 min at 25 °C under stirring. The interaction of the hydroxide anions with the hydroxyl groups of the AGU of MCC was demonstrated by following the chemical shift and line width of the (OH-/H2O) 1H-NMR peak as a function of increasing MCC concentration, and the crystallinity of regenerated cellulose (type I → amorphous) [148]. Aqueous solutions of Bu4POH also dissolve wood discs (cedar, pine, polar). The dissolution efficiency depends on the water content of the biomass solution; the latter content can be decreased by a slow “autorecovery or “self-dehydration” step, namely by storing the solution for 2–10 days at room temperature under controlled humidity [149].

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The effect of water and cation size on the cellulose dissolution capacity of aqueous R4POH at 25 °C were studied in detail by using aqueous solutions of the following QAEs: PRRRR OH (R = ethyl, n-butyl, nhexyl) and NRRRROH (R = methyl, ethyl, n-butyl, n-hexyl). The QAEs with the smallest volumes (e.g., N1111OH and N2222OH) did not dissolve 0.5 wt% cellulose. The biopolymer dissolution capacity and dissolution time (2–20 min) depended on (n), the number of water molecules/cation (fast dissolution at n ≤ 15). As discussed above, cellulose dissolution by these alkaline solutions involves proton removal, e.g., from C6-OH of the AGU, leading to chemical shift change of the attached (primary) carbon atom. The values of δ 13C-NMR signal of this primary carbon of 10 wt% cellobiose decreased as a function of increasing (n); the limit of cellulose dissolution was reached at δ 13C of 64.8 ppm (n ≈ 15). Below this “threshold” chemical shift, cellobiose is insoluble [150]. The results of several publications highlight the importance of the amphiphilic character of cellulose, and the solvophobic interactions in these QAE solvents. The most relevant result is the effect of urea on dissolution of cellulose. The simplest example is where urea-inorganic base is the solvent. Results of DSC, 1H and 13C-NMR chemical shifts showed that urea hydrate plays its positive role in dissolution through van der Waals interactions, by accumulating on the hydrophobic face of the AGU to prevent dissolved cellulose chains from re-aggregation [151,152]. The amphiphilic character of both components of the system - cellulose and the QAE - was nicely exploited in using aqueous TBAOH to dissolve cellulose. As shown below, the idea is to “match” cellulose and QAE solution, akin to matching the HLB (hydrophilic-lipophilic balance) of the aqueous phase to that of the oil phase in order to obtain stable oil/water emulsions [153]. The cellulose dissolving power of the aqueous solvent is dependent on QAE concentration and the corresponding molar ratio water/QAE (nW/QAE) which was divided (based on DSC measurements) into bound and free water, (nbound-W/QAE) and (nfree-W/QAE), respectively. An increase in QAE concentration decreases the amount of (nbound-W/QAE), leading to contact between the partially desolvated TBA+ cations with concomitant increase in the solvophobic QAE-cellulose interactions. At 60 wt% TBAOH, the value of (nbound-W/QAE) is ca. 2 and cellulose is easily dissolved by solvophobic interactions. In other words, cellulose dissolution can be induced by “tuning” the hydrophilic-lipophilic character of the QAE solution. Another interesting approach to control this character at a fixed QAE concentration is to use urea or thiourea as additive. Addition of urea to 55 wt% of TBAOH led to an upfield shift of the 13C-NMR

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peaks of (NH2)2C=O and (C3H7CH2)4NOH, indicating the association ureaQAE with displacement of some of the (nbound-W/QAE) of the QAE. A similar rational can be applied to the hydrophobic region of the AGU, as depicted in Figure 8 [154].

Figure 8: Schematic representation of the mechanism for dissolution of cellulose in TBAOH/urea aqueous solution; reprinted with permission from [154], Copyright (2013) Springer Nature.

This amphiphilic aspect was exploited in synthesis where the reagent is not very sensitive to hydrolysis. Thus, aqueous Bu4POH was used as solvent for the benzylation of cellulose (reaction with benzyl bromide, 10 min, 20– 25 °C, DSBz ≈ 2.5). The surface activity of Bu4POH leads to association with benzyl bromide and with (more hydrophobic) partially benzylated cellulose, leading to products with relatively high DSBz. The above mentioned association (RX-QAE-cellulose ether) results in less hydrolysis of the halide and efficient etherification reaction [155].

APPLICATIONS OF QAES FOR CELLULOSE DISSOLUTION, SHAPING AND DERIVATIZATION In principle, the quaternary nitrogen atom of QAEs can be attached to four different substituents (e.g. alkyl, alkenyl, benzyl), leading to structural flexibility; hence their properties can be “tuned” conveniently. They are stable under common conditions for cellulose processing and derivatization, while are not subjected easily to side elimination reactions,

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unlike 1,3-substituted imidazole-based ILs with their relatively acidic C2-H [156,157,158,159,160,161]. QAEs with various anions were studied, mainly for cellulose dissolution and shaping, and biomass extraction. Cellulose derivatization is reported as well to a lesser extent. In order to give an overview about the QAEs we classified them by their anions.

Quaternary Ammonium Hydroxides Parallel to the development of DMSO/TBAF∙3H2O Tanczos et al. studied commercially available, relatively inexpensive tetraalkylammonium hydroxides as activating agents and solvents for cellulose [162]. The ability to swell or dissolve cellulose better than other bases such as NaOH was attributed to penetration of R4NOH into cellulose, combined with the amphiphilic character and size of the ammonium cation. The good gelation properties of R4NOH were used to obtain fibrous TEMPO oxidized cellulose nano-dispersions in water [163]. An aqueous solution of commercial TBAOH (40 wt%) was found to dissolve 10 wt % cellulose within 24 h at room temperature [119]. As discussed above in Section 3.1.1, 18-crown-6 was added to eliminate the undesirable effect of KBr (a side product in commercial base solutions). Without addition of crown ether, aqueous TBAOH solutions were used to extract cellulose from wheat straw at 60 °C within less than 1 h [164], and dissolve 10 wt % MCC within 2 min at room temperature ([TBAOH] = 50 and 55 wt%, respectively). Analysis of the regenerated polymer confirmed that no degradation or chemical modification occurred. The same group found that TMAOH solutions dissolve 25 wt % MCC in 2 min [165], and extract cellulose from sugarcane bagasse. The latter was achieved by adding 17 to 29 wt % urea to a 40 wt % aqueous solution of TBAOH [154]. An alternative approach was employed to dissolve cellulose using lower concentrations or R4NOH [166]. Dissolving grade pulp, 6 wt % was dissolved in a solution containing 70 wt % DMSO, 12 wt % TBAOH, and 18 wt % water. The DMSO concentration could be increased to 90 wt % without cellulose precipitation. After complete solubilization of cellulose, β-cyclodextrin was added to the solution to obtain elastic but robust gels. By varying the cellulose and β-cyclodextrin contents the porosity and mean pore size of the cellulose network was adjusted. These cellulose-based hydrogels could potentially find applications in areas such as removal of heavy metal ions from water, or in controlled drug delivery systems [167]. Examples of the solubility of cellulose in the solvent mixtures mentioned in

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this section are listed in Table 1, where the dissolved cellulose is given in wt%. Because of the differences in the molar masses of the components (AGU, QAE, MS) the use of the mole fraction scale is, to our view, preferable to wt % because it is unambiguous. Table 1: Examples of the solubility of cellulose in tetra-(n-alkyl) ammonium hydroxide aqueous solutions Cellulose Solvent

Dissolved Cellulose [wt%]

Dissolution Conditions

Cellulose Type (DP) 2

Reference

(30 wt%) TMAOHaq (25 wt%) TBAOHaq (40 wt%) TBAOHaq (40 wt%) + 18-crown-6 (2.0 M) TBAOHaq (55 wt%)

swelling

RT

-1

[162]

10

RT, 2 min

MCC

[165]

TMAOHaq

10

RT, 24 h

MCC

[119]

10

RT, 10 min

MCC

[119]

10

RT, 2 min

MCC

[164]

TBAOH/urea/H2O (33/17/50 wt%)

7

RT, 1 h

Softwood kraft pulp (660), MCC

[154]

TBAOH/DMSO/H2O (12/70/18 wt%)

6

-1

PHK pulp (630)

[166]

- No data given, 2 DP - average degree of polymerization in brackets, where available

1

Quaternary Ammonium Carboxylates QAE carboxylates are, by far, the most studied compounds regarding cellulose dissolution, derivatization and shaping. They have the advantage over hydroxides, that they can be used in non-aqueous solvents. This is an essential prerequisite to perform some cellulose derivatization, e.g., into carboxylic esters. They are also considered to be “greener” solvents compared to their corresponding (corrosive) halides (Cl−, F−). Molten tetraalkylammonium carboxylates were studied regarding their ability to dissolve and chemically modify cellulose [168]. They were obtained by quaternization of triethylamine or tributylamine with dimethylcarbonate and subsequent conversion with the corresponding carboxylic acid (Scheme 1). Triethylmethyl- and tributylmethylammonium formate (N1222Fo, N1444Fo) dissolve MCC. A mixture of 8 wt % dilute formic acid (25 wt % aqueous solution) in N1222Fo dissolved 10 wt % MCC. The 13C-NMR spectrum of

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this solution revealed the formation of cellulose formate intermadiate during MCC dissolution. As expected, this ester is not stable because pure cellulose was obtained after regeneration of the solution in water. Etherification was performed in these solutions as well. Carboxymethyl cellulose (CMC) with a DS value of 1.55 and a block like distribution of substituents along the polymer backbone was isolated. Hydroxypropylation of MCC, cotton, and spruce sulfite pulp in N1222Fo yielded products with a rather low DS (0.22– 1.27) in spite of the large excess of molar ratio propylene oxide/cellulose employed (40/1) [169]. The biorefinery concept is an expanding research field and a driving force in the development of new solvents for renewable resources, especially cellulose. Thus, QAEs are studied to selectively extract cellulosic material or lignin from biomass. The enzyme catalyzed transformation of cellulose dissolved in IL, e.g., transesterification or hydrolysis, was carried out in bisand tris(2-methoxyethyl)triethylammonium acetates (N222 Me(OEt)2AcO, N222 AcO) [170]. Many ILs inhibit these reactions because the employed Me(OEt)3 enzymes are readily denatured. Here, the cation structure combined with the basic acetate anion enhances cellulose dissolution (up to 10 wt % MCC) while the low anion concentration stabilizes the enzyme. A screening of various cations with carboxylate anions as cellulose solvents was conducted by Zhao et al. [118]. Of the QAEs tested only diethyldimethylammonium acetate (N1122AcO) dissolved 2 wt % cellulose, the formates, propionates and butyrates did not dissolve cellulose. On the other hand, dialkoxydimethylammonium acetates dissolved up to 18 wt % cellulose (MCC) at 80 °C [171], which underlines the discussion in item 3 above, namely that size, structure, and/or molecular weight of the cation influences the solubilization process to a considerable extent. Additionally, the viscosity of the solutions is significantly lower compared to other IL cellulose solutions, due to the higher flexibility of the alkoxy side-chains. TBAAcO dissolved in various MS (28/72 by weight), such as DMSO, DMAc, DMF, pyridine, or NMP was reported to dissolve up to 9 wt % MCC within a few minutes at 60 °C [172]. In TBAAcO/DMSO the dissolution occurred faster than in the other mixtures. The cellulose containing solutions were also used to produce fibers and membranes. Cellulose acetate and butyrate with DS values of around 3 and 2, respectively, were obtained by acylation in this solvent. Miao et al. used TBAAcO and mixtures thereof as cellulose solvents as well [120]. Based on the results of DMSO/TBAF∙3H2O [173] and

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TBAOH [119] the introduction of the acetate anion was expected to yield a promising cellulose solvent. However, neat TBAAcO did not dissolve cellulose, addition of DMSO was required [120]. The dissolution optimum for cellulose was found when the binary mixture of DMSO contained 15–20 wt % TBAAcO, vide Figure 4 [85]. Here cellulose (8 wt%) was dissolved at room temperature within 2 min. Increasing the temperature to 40 °C resulted in a noticeable increase of cellulose solvent efficiency. Thus 11, 22, 33 wt % TBAAcO in DMSO dissolved 6, 22, and 33 wt % MCC. These QAE concentrations correspond to 1 mol acetate anion/AGU due to hydrogen bonding of the acetate to more than one hydroxyl group of the AGU, vide 3.1.1. [83]. At 40 °C, up to 20 wt % MCC dissolved in the TBAAcO/DMSO/18-crown-6 mixture (2/7/1 by weight). Additionally, high molecular weight celluloses (DP = 830) and lignin were also soluble in the same mixture. The clear and viscous solutions of cellulose in TBAAcO/ DMSO/18-crown-6 proved to be suitable for wet-spinning and the cellulose fibers were regenerated in ethanol at room temperature. The fibers showed more amorphous than crystalline cellulose structure based on MAS-NMR and XRD analyses, and they were homogeneous with smooth surfaces and diameters around 40 μm (Figure 9) [120].

Figure 9: Scanning electron microscope images of cellulose fibers prepared from TBAAcO/DMSO/18-crown-6: (a) side surface section, (b) magnified side

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surface section, (c) cross-section with diameter, (d) magnified cross-section; reproduced from [120] with permission of The Royal Society of Chemistry.

In a subsequent study, the same group regenerated cellulose fibers from TBAAcO and DMSO without 18-crown-6. They used a softwood cellulose (DP = 1050) and prepared solutions of 4–10 wt % at 40 °C. The resulting fibers had circular cross-sections and smooth surfaces. Analyses of DP after regeneration indicated no detectable degradation of the regenerated cellulose. The fibers showed tenacities between 2–3 cN/dtex and elongation values between 9.7–11.8% [121]. Thus, the dry strength values are similar to those of viscose (20–25 cN/tex, 18–23% elongation) or cotton (24–36 cN/ tex, 7–9% elongation) [174]. The use of a recycled TBAAcO/DMSO solvent for the dissolution and regeneration of cellulose was recently investigated [175]. It was shown that the TBAAcO/DMSO solvent system tolerates addition of some non-solvents, such as water or ethanol, without cellulose precipitation. Mechanical properties of spun filaments were not altered when prepared from a simulated recycled solvent containing 2 wt % (cellulose) non-solvent. The ability of the system to tolerate non-solvents was dependent on the concentration of both cellulose and TBAAcO. By increasing the concentration of TBAAcO, more water can be tolerated for the same cellulose content [111]. Carbon nanotubes were added to a solution of cellulose in TBAAcO/ DMSO, and were then formed into composite fibers, spun at room temperature and then coagulated in a water bath. Characterization of the fibers using SEM showed that the fibers were smooth and did not contain micro pores, which indicated that the carbon nanotubes were well-dispersed in the cellulose matrix. It was also shown that the mechanical and thermal properties of the composite fibers (5 wt % carbon nanotubes) compared to neat cellulose fibers were improved: increased tensile strength (approx. 20%), elongation at break (approx. 20% increase), and thermal stability (decomposition temperature increased by ca 20 °C) [176]. The TBAAcO/DMSO system was used for the homogeneous esterification of cellulose without catalysts. After 5 h at 60 °C using a 5 molar excess of acetic anhydride per AGU an organo-soluble cellulose acetate with a DSAc of 2.91 was reached. Under the same conditions, cellulose propionate with a DSPr of 1.83 was obtained. Cellulose acetate/propionate and acetate/butyrate mixed esters with almost full functionalization were obtained [177,178]. The conversion of cellulose with succinic anhydride under catalyst free conditions yielded products with DSSuccinate between 0.3 and 1.2 after 1 h at

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60 °C. As known, these products successfully absorb heavy metal ions such as copper(II) and cadmium(II) from aqueous solutions. The concentration of absorbed metal ions increased as a function of increasing DSSuccinate [179].

Abinary mixture of tetrabutylammonium propionate with methylimidazole (2.5/7.5 by weight) dissolves 15.7 wt % MCC at 25 °C. The main driving force of the dissolution was attributed to the propionate anion, while methylimidazole was mainly acting as solvent, promoting dissociation of the ions. The authors also claim that the architecture of regenerated cellulose films can be adjusted in dependence of the processing strategy [180]. A set of 20 tetra-(n-alkyl)ammonium acetates and propionates was synthesized and studied regarding the influence of the cation on cellulose dissolution, vide 3.1.2. The majority of these QAE were able to dissolve cellulose with and without the addition of DMSO, and triethylhexylammonium acetate was the best QAE in the set studied; 22 wt % cellulose at 90 °C [73]. Neat N,N-allylmethylmorpholinium acetate was shown to be an efficient cellulose solvent. Thus 17, 28, and 30 wt % MCC were soluble in this QAE at 80, 100, and 120 °C, respectively, even in the presence of some water. Also 25 wt % of high molecular weight samples (DP = 2082) was dissolved without noticeable degradation, as confirmed by SEC analysis. SEM micrographs of native and regenerated cellulose indicated that upon regeneration, the surface of cellulose fibers became smoother, and uniform, as compared to rough and scattered surface of untreated cellulosic fibers. This was attributed to re-aggregation of strongly bonded crystalline cellulose fibers into more homogeneous macromolecular assembly upon dissolution [181].

The following QAEs for cellulose dissolution and processing are based partially on naturally occurring compounds. Ohira et al. prepared QAEs with amino acid moieties as anions. N,N-Diethyl-N-(2-methoxyethyl)-Nmethylammonium alaninate (N122 Me(OEt)) was the best cellulose solvent for MCC, dissolving 6 wt % at 60 °C and 12 wt % at 100 °C within 10 minutes. The corresponding acetate and chloride dissolved 7 and 10 wt % MCC, respectively, although much more slowly, ca. 48 h for complete dissolution. The fact that the amino acid anions are better than the corresponding carboxylates may be due to the extra amino moiety present in the former anion. Tryptophanate, lysinate, and threoninate were tested as well; they dissolve MCC between 1 and 11 wt%. When DMSO was added to N,Ndiethyl-N-(2-methoxyethyl)-N-methylammonium alaninate (1:1 mixture by volume, which equals a molar fraction of DMSO χDMSO = 0.75) 11 wt % MCC

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were soluble at 25 °C after 10 min, and 22 wt % after 6 h, or after 10 minutes at 100 °C [182,183]. The dissolution of cellulose in these solvents seems to be more suitable for fiber spinning compared to commonly used IL [22]. Cholinium cation-based QAEs with 28 amino acid and carboxylate anions were used for dissolution of biomass [184]. The solubility of cellulose in these QAEs was poor ( 2000) and a minimum polydispersity index of 3.4 [244]. Using the Ioncell-F process for textile applications was further investigated [11]. Ioncell fibers were compared with commercial viscose fibers and converted into two-ply yarn using ring spinning technology. The yarns made using DBN AcO were stronger but more brittle and had higher irregularities than the viscose yarns. However, the Ioncell yarns showed good behavior during the knitting and weaving processes and were produced into garment demonstrators, such as a knitted scarf and a dress. The Ioncell yarn could be dyed in a batch process with reactive dyes that are commonly used on industrial scale. Detailed studies on reasons to spinning failure, such as a breach in the coagulation bath, has also been covered [245]. It was found that NMMO∙2H2O and DBN AcO were good spinning solvents, while EtMeImAcO and TMG AcO were poor spinning solvents. The extent of stretching of the forming filaments was simulated by calculating the diffusion dynamics. Thus a good solvent for spinning must also be a solvent that solidifies the structure of the fiber during regeneration, thus permitting increased and retained orientation. Gelatinous dopes that already have a gel network before regeneration or dopes that weaken upon the addition of water (water progressing towards the center of the fiber and leading to fiber breach) were instead poor spinning solvents. Moreover, the Ioncell-F process has been investigated with cellulose from other types of feedstock. The use of cotton waste to produce virgin fibers of higher quality compared to mechanically recycled material has been reported [246]. However, it was necessary to use a pretreatment to adjust the DP of the cellulose. The material was dissolved and regenerated, and fibers with tenacities as high as 58 cN/tex (870 MPa) were obtained. Another approach the use cellulosic waste, e.g., paper and cardboard, and

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solubilize all biopolymers in the material (i.e. also hemicelluloses and lignin) in the DBN AcO solvent to prepare a spin dope [247]. Also in this case, a series of refining steps (mechanical, chemical, enzymatic) of the raw material and an adjustment of the DP of the cellulose were required to achieve dissolution. The fibers showed again high tenacities and prototype textiles were produced to evaluate the fiber quality and the possibility to use lignin as a natural (beige/brown) dye. A challenge to reach commercial success for the Ioncell-F process, and in general for ILs and QAEs, is the development of a viable and efficient solvent recovery system. Initial laboratory scale recycling trials were conducted and the results showed that DBN AcO can be recycled from aqueous media with an average recovery rate of 95.6 wt % using rotary evaporators [248]. The recycling of the solvent did not affect the chemical composition or DP of the recovered cellulose, however the color of the regenerated material became gradually darker with each regeneration cycle. Additionally, DBN AcO itself underwent detectable hydrolysis (6.0–13.6 mol% per cycle) yielding 3-(aminopropyl)-2-pyrrolidonium acetate. With increasing amount of this byproduct solubility of cellulose decreased and ceased at 30.6–45.6 wt % hydrolysis product. Water evaporation using a thin film short evaporation path; stability and toxicity tests of DBN AcO, and tests to remove oligosaccharides from the coagulation bath are being conducted [247]. Switchable ILs are another class of electrolytes worth a short mentioning in the frame of this review [226]. They are formed by mixing equimolar amounts of an alcohol with a strong organic base, e.g. amidines such as DBU, with gaseous CO2 at ambient pressure and room temperature. By combining these three components, an exothermic transformation takes place, converting the mixture to an ionic fluid by formation of the alkyl carbonate, between CO2 and the alcohol to subsequently form the amine salt (Figure 16). Addition of N2 or other gases leads to a shift of the CO2, and the system is surprisingly found to be fully reversible, resulting once more in the starting materials [249]. Suitable applications for such QAEs are supposedly in biomass processing [250,251,252] or for CO2 capture [253]. The switchable IL that is produced from DBU, methanol and CO2 was also shown to be able to dissolve cellulose. It could be used as reaction media for acylation of cellulose and yielded DSAc values of up to 2.94 depending on reaction conditions [254].

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Figure 16: Illustration of the concept and mechanism of switchable ILs; reprinted with permission from [226], Copyright (2013) Society of Chemical Industry.

CONCLUSIONS Solutions of QAEs in MSs are exciting solvents for cellulose because of their structural versatility, and easy recycling. Cellulose dissolution is favored if the QAE is composed of a small, hard anion and a voluminous cation. The dissolution proceeds by a cooperative mechanism. The anion interacts with the hydroxyl groups of the AGU, leading to hydrogen bond disruption; the polymer chain thus acquires a negative charge. The repulsion between the negatively charged cellulose-anion complex is enhanced by: (i) steric crowding due to the attached sheath of the corresponding cation of the QAE; (ii) solvophobic interactions of the latter with the hydrophobic face of the AGU. Thus, the hardness of the anion and the hydrophobic character of the cation are important for cellulose dissolution. The most employed QAEs are the halides, in particular TBAF∙3H2O, the carboxylates, hydroxides and dialkyl phosphates. Solutions of cellulose/ QAE/MS were successfully employed for derivatization of cellulose under homogeneous conditions into esters and mixed esters. Cellulose ethers were also obtained under homogeneous and heterogeneous conditions with difference in the distribution of the ether group along the biopolymer backbone, leading to different solubility, e.g., in water. Solutions of QAhydroxides are suitable for cellulose dissolution, shaping and derivatization if the reagent is not particularly sensitive to hydrolysis. The use of QAEs for regeneration and shaping as well as chemical modification of cellulose was reported to a limited extent in the literature. However, initial results from cellulose dissolved in QAEs, dominantly TBAAcO and TBAOH, showed high potential and their use in processing of cellulose is an active field of investigation. QA halides, such as TBAF

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and N2228Cl, proved to be excellent media for various acylation reactions. Some unconventional products are reported as well. Dissolution of cellulose in salts of super bases revealed promising results, and there are currently intensive research on shaping cellulose from such solvents. The formed fibers (Ioncell-F) showed favorable mechanical properties. However, the recovery of the solvent from such processes needs to be developed further. A common protocol for cellulose dissolution is needed to provide more consistency in data reporting, as already mentioned by Wang et al. [138] and Pinkert et al. [18,255]. The intended application of each cellulose solution, e.g., fiber spinning or chemical modification is a decisive factor for the choice of the right solvent system. From the sustainability point of view, the solvent should be stable under processing conditions and easily to recycle in a continuous process. The importance of other properties such as viscosity of the biopolymer solution and toxicity of QAE and MS should be taken into consideration.

Scheme 1: Synthesis of quaternary ammonium electrolytes by quaternization of tertiary amines with organic halides (I, II) or dialkyl carbonates (III).

ACKNOWLEDGMENTS O.A.El Seoud and M. Kostag thank the FAPESP research foundation for financial support and postdoctoral fellowship (grants 2014/22136-4 and 2016/22869-7, respectively). O. A. El Seoud thanks CNPq for research productivity fellowship (grant 307022/2014-5). K. Jedvert gratefully acknowledges the Swedish Research Council Formas for financial support.

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9 Increased Solubility and Bioavailability of Hydroxy-Cr(III) Precipitates in the Presence of Hydroxamate Siderophores

William E. Dubbin1 and Tee Boon Goh2 1

Department of Earth Science, The Natural History Museum, London SW7 5BD, UK

2

Department of Soil Science, University of Manitoba, Winnipeg, MB R3T 2N2, Canada

ABSTRACT Siderophores are a diverse group of low molecular weight biogenic metallophores with a particular affinity for Fe(III) but they also have potential to complex a number of other polyvalent metal cations, including Cr(III). Here we show that two hydroxamate siderophores, desferrioxamine B and rhodotorulic acid, at environmentally relevant concentrations,

Citation: Dubbin WE, Goh TB. Increased Solubility and Bioavailability of Hydroxy-Cr(III) Precipitates in the Presence of Hydroxamate Siderophores. Bull Environ Contam Toxicol. 2018;100(3):409–415. doi:10.1007/s00128-017-2234-z Copyright: © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/ by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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facilitate the dissolution of hydroxy-Cr(III) precipitates from a common layer silicate. Desferrioxamine B and rhodotorulic acid induced maximum initial Cr dissolution rates of 11.3 ± 1.7 × 10− 4 and 9.03 ± 0.68 × 10− 4 µmol m− 2 h− 1, respectively, yielding maximum solution Cr concentrations of 0.26 ± 0.01 and 0.20 ± 0.02 µmol m− 2, respectively. These data demonstrate that hydroxamate siderophores may play an important role increasing the dispersal of Cr in natural environments, thus facilitating greater bioavailability of this potential toxin. Keywords: Chromium, Hydroxamate siderophore, Montmorillonite, Dissolution Chromium occurs widely in soil and sediment and may serve as either a pollutant or an essential trace nutrient (Adriano 2001). Elevated chromium levels in soil arise through human activities such as the production of chromium waste slag from mining (Dhal et al. 2013) or they may occur naturally during the weathering of Cr-rich ultramafic rocks (Oze et al. 2007; Morrison et al. 2009). At high concentrations Cr can be toxic, posing a risk to both ecosystem health and human well-being (Adriano 2001; Guertin 2004). In Earth-surface environments Cr occurs in either the trivalent or hexavalent state, with the majority present as poorly soluble hydroxy-Cr(III) polymers sorbed to layer silicates or incorporated into Fe(III) hydroxides (Schwertmann et al. 1989; Dubbin et al. 1994; Sileo et al. 2004). Given the low solubility of hydroxy-Cr(III) precipitates at circumneutral pH Cr is generally thought not to be readily bioavailable (Bartlett and Kimble 1976; Duckworth et al. 2014). Organic chelating ligands such as oxalate and citrate are ubiquitous in soil and they can increase the dissolution rates of sparingly soluble Cr(III) hydroxides (Rodenas et al. 1997; Carbonaro et al. 2008). The dissolved Cr(III) can then be transported to various Mn(III,IV) oxides where it is readily oxidized to the more toxic and mobile Cr(VI) (Hausladen and Fendorf 2017). Interestingly, Cr(VI) has been observed to occur naturally alongside Mn(III,IV) oxides in soils and sediments uncontaminated by anthropogenic Cr, but the mechanisms of Cr dissolution and transport in these environments are not entirely clear (Oze et al. 2007; Garnier et al. 2013). Naturally occurring low molecular weight organic ligands may well serve as key agents driving the dissolution and transport of Cr(III), thus facilitating its subsequent oxidation to Cr(VI) at the Mn oxide surface. Elucidation of the myriad pathways through which Cr is dissolved, transported and oxidised is

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therefore fundamental to the development of models predicting Cr cycling in natural systems. Siderophores are a diverse group of low molecular weight biogenic chelating ligands released by plants and microbes in response to Fe stress. Although siderophores have a particular affinity for Fe(III) they also have considerable potential to complex a large number of other polyvalent metal cations, including Cr(III) (Leong and Raymond 1975; Budzikiewicz et al. 2002). Recent studies indicate that siderophores may indeed play a central role in the geochemical cycling of Cr (Duckworth et al. 2014; Stewart et al. 2016). However, despite the potential of siderophores to influence the bioavailability and fate of Cr in soils and sediments, there has to date been only limited effort to elucidate their role in the dissolution of environmentally relevant Cr-containing solids. The present work therefore examines the effect of desferrioxamine B (DFOB) and rhodotorulic acid (RA), trihydroxamate and dihydroxamate siderophores, respectively, on the dissolution of hydroxy-Cr(III) precipitates sorbed to montmorillonite. DFOB is produced by the bacterium Streptomyces pilosus and RA is produced by yeast of the genera Rhodotorula, both of which are common soil inhabitants (Fracchia et al. 2003; Manteca and Sanchez 2009). We choose montmorillonite as the sorbent because it is a common layer silicate in soils and sediments and has a high capacity to sorb hydroxy-Cr(III) polymers (Dubbin et al. 1994). Our objective was to measure, for the first time, the dissolution kinetics of Cr(III) from Cr(III)-montmorillonite in the presence of environmentally relevant concentrations of DFOB and RA. These data will better characterise the pathways through which Cr is mobilized in soils and sediments.

MATERIALS AND METHODS Montmorillonite reacted with short-range ordered hydroxy-Cr polymers was used as the model contaminant. Briefly, 5 g Na-saturated montmorillonite (< 2 μm) (SWy-1; Clay Minerals Society) were suspended in 2 L deionized water. Predetermined quantities of CrCl3∙6H2O (Aldrich) were then introduced to each of four separate montmorillonite suspensions to give four aqueous Cr(III) concentrations (67, 133, 200, 400, cmol kg− 1 clay) which we denote as 67, 133, 200 and 400, respectively. The four Cr(III)montmorillonite suspensions were then titrated with 0.1 M NaOH at 1 mL min− 1 while stirring to achieve a NaOH/Cr3+ molar ratio of 2.5. The partial neutralisation of Cr3+ (aq) solutions gives rise to olation reactions and a series of hydroxy polymers, mainly dimers, trimers and tetramers as described

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by (Drljaca et al. 1992). The population of these oligomers increases with time while the rate of their formation varies with pH, reaching a kinetic minimum at pH 6–7, then increasing at pH > 8 (Spiccia and Marty 1986). All suspensions were diluted to 3 L, transferred to capped bottles and aged for 30 days at 23 ± 0.5°C. Following the aging period the solid was obtained by filtration through 0.02 μm pores (Millipore®) and the filtrate solutions were subsequently analysed for aqueous Cr by ICP-OES (Thermo iCap 6500 Duo). The hydroxy-Cr montmorillonite reaction products were prepared as oriented mounts on sapphire substrates then characterised by X-ray diffraction (XRD) with an Enraf–Nonius PSD 120 diffractometer (Cu Kα1 radiation; 45 mV; 45 kV) equipped with a 120° position sensitive detector. Exchangeable Cr and cation exchange capacity (CEC) of each solid were measured by first washing the clay three times with 0.5 M CaCl2 to displace any loosely held Cr and to saturate the exchange sites with Ca. The excess Ca was then removed by several washings with ultrapure water (18 MΩ-cm) and the residual, bound Ca was subsequently displaced with 0.5 M MgCl2. The extracts were analysed for Cr and Ca by ICP-OES. The specific surface area of each Cr-montmorillonite was measured by multipoint N2-BET analysis (Micrometrics Gemini III 2375) after sample degassing with N2 at 100°C for 24 h (Brunauer et al. 1938). To ensure accuracy of measurement we analysed a reference mineral (kaolinite; 15.9 ± 0.8 m2 g− 1) alongside the Cr-montmorillonite samples. Rates of Cr(III) dissolution from the hydroxy-Cr montmorillonite were measured in the presence and absence of the two hydroxamate siderophores (desferrioxamine B and rhodotorulic acid) (Fig. 1). To minimise proton promoted dissolution the solution pH was maintained at 6.5 throughout the duration of the reaction using a buffer solution consisting of 10 mM NaNO3 (BDH) and 1 mM MOPS [3-(N-morpholino) propanesulfonic acid; VWR]. This buffer has been used previously in comparable dissolution experiments and was found to have no significant effect on siderophorepromoted dissolution rates of metal hydroxides (Stewart et al. 2016). Portions (100 mg) of each of the four Cr(III)-montmorillonite samples were transferred to a series of 250 mL amber HDPE bottles, each containing 100 mL MOPS/NaNO3 buffer. A further bottle contained, as a control, 100 mg montmorillonite unreacted with Cr. To one set of montmorillonite suspensions we added a predetermined quantity of DFOB, obtained as the mesylate salt [C25H46N5O8NH3 +(CH3SO3 −)], and to a second set of montmorillonite suspensions we added RA [C14H24N4O6]. Both siderophores were obtained in

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crystalline form from Sigma-Aldrich and introduced to the clay suspensions as aqueous solutions. All suspensions were prepared in triplicate, brought to final volumes of 150 mL with MOPS/NaNO3 buffer, then left to react at 23°C on an orbital shaker (100 rpm; Orbital Incubator SI50). Each reaction vessel, except the controls, had a siderophore concentration of 120 µM.

Figure 1: Structural representations of: a desferrioxamine B (DFOB) and b rhodotorulic acid (RA) showing the hydroxamate functional groups. The three hydroxamate groups of DFOB have pK a values of 8.32, 8.96 and 9.55 while the two hydroxamate groups of RA give pK a values of 8.71 and 9.88 (Martell et al. 2003).

Ten mL aliquots were removed periodically from the stirred suspensions with a syringe then filtered using a two-step process. The suspensions were first filtered through cellulose acetate filters of pore size 0.2 µm followed immediately by an additional filtration through nitrocellulose membrane filters of pore size 0.025 µm (Millipore®). Filtration of each 10 mL aliquot was completed within 1 min to ensure uniform sampling of all batch reactors and the obtained supernatant solutions were held at 4°C until analysis. Aqueous Cr in filtrate solutions was measured by combining 2 mL aliquots of the filtrate with 4 mL HNO3(2% (v/v); SpA grade, Romil) prior to Cr analysis by ICP-MS (Agilent Technologies, ASX-7700 Series) monitoring isotope 52. To minimise polyatomic interferences from 40ArO+ and 40ArC+, the instrument was operated with 5 mL min−1 He (99.9995% purity) in the collision-reaction octopole cell and tuned to about 0.1% CeO/Ce. We

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calculate initial dissolution rates by performing least-square regression analyses. For each dissolution we chose the first five data points as these represent the most linear portion of the dissolution curve, giving regression coefficients (R 2) > 0.92 for all least square fits.

RESULTS AND DISCUSSION The four prepared Cr-montmorillonite clays hold varying amounts of Cr, from 34.7 to 174 g kg− 1 (Table 1). Most of the added Cr was sorbed by the clay, with only the 400 clay showing significant amounts of supernatant Cr remaining at the end of the 30 day aging period. The control montmorillonite had a CEC of 91.3 cmolc kg− 1. All four Cr-clays showed a reduction in CEC that increased with increasing amount of sorbed Cr, indicating that the hydroxy Cr polymers were bound tightly via inner-sphere complexes at the montmorillonite siloxane surface, thus blocking the exchange sites. The N2BET specific surface of the control clay was 35.3 m2 g− 1 and this increased with increasing sorbed Cr such that the 400 clay gave a specific surface of 114 m2 g− 1. Given the expansion of the interlayer region as revealed by XRD (Table 1), the hydroxy Cr polymers are evidently sorbed to the internal montmorillonite surfaces, thus creating a porous framework permitting entry of the N2 molecule (~ 0.315 nm diameter; Lide 2004). Continued expansion of the gallery space with increasing Cr sorption further facilitates entry of N2 to the high surface area hydroxy Cr framework. Table 1: Physicochemical properties of the montmorillonite reacted with hydroxy-Cr polymers Supernatant Cr (cmol kg− 1clay)

Cr sorbed g kg− 1

Basal spacing (d 001) (nm)

CEC cmolc kg− 1

Exchangeable Cr cmolc kg− 1

Surface areaa m2 g− 1

Initial

Final

0 (Control)

0

0

1.10

91.3

nd

35.3

67

0

34.7

1.36

57.2

nd

47.5

133

0

69.2

1.52

37.5

nd

87.6

200

1

103

1.73

36.0

nd

92.8

400

66

174

1.82

15.9

nd

114

nd Not detected within the limit of error (Cr detection limit ≈ 0.05 µg g− 1) Derived by multipoint N2-BET analysis

a

Figure 2 shows the Cr release kinetics from montmorillonite in the presence of 120 µM DFOB and RA. In the absence of DFOB or RA there was no detectable soluble Cr over the 336 h reaction, whereas DFOB or RA presence

Increased Solubility and Bioavailability of Hydroxy-Cr(III) Precipitates....

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induces significant Cr release from all four Cr-clays at all reaction times to 336 h. Maximum solution Cr concentrations increase with increasing Cr loading on the clay, and also with siderophore type, where the hexadentate DFOB yields more soluble Cr than the tetradentate RA (Table 2). These trends are most apparent for the absolute concentrations of Cr in solution, although they remain somewhat evident when normalised to surface area.

Figure 2: Release of Cr(III) from the four Cr(III)-treated montmorillonite clays in the presence of: a desferrioxamine B and b rhodotorulic acid to 336 h. A reference montmorillonite, untreated with Cr, serves as a control and was analysed alongside the four Cr-clays for comparison. Initial siderophore concentration: 120 µM; Cr-montmorillonite concentration: 0.67 g L− 1; pH 6.5; 23°C.

3.8 ± 0.24

12.1 ± 1.12

15.5 ± 0.29

20.1 ± 2.61

3.0 ± 0.25

9.9 ± 0.62

12.2 ± 11.5

14.3 ± 0.39

DFOB 67

DFOB 133

DFOB 200

DFOB 400

RA 67

RA 133

RA 200

RA 400 y = (0.068 ± 0.004)x + 0.556 ± 0.028

y = (0.055 ± 0.009)x − 0.043 ± 0.049

y = (0.053 ± 0.004)x − 0.263 ± 0.021

y = (0.018 ± 0.002)x + 0.119 ± 0.051

y = (0.081 ± 0.005)x + 0.435 ± 0.078

y = (0.070 ± 0.011)x − 0.405 ± 0.316

y = (0.047 ± 0.002)x − 0.263 ± 0.047

y = (0.019 ± 0.002)x − 0.221 ± 0.086

Regression equation

−4

8.90 ± 0.52 × 10

8.85 ± 1.4 × 10

−4

9.03 ± 0.68 × 10− 4

5.66 ± 0.63 × 10− 4

10.6 ± 0.65 × 10− 4

11.3 ± 1.7 × 10− 4

8.01 ± 0.34 × 10− 4

5.97 ± 0.63 × 10− 4

2.1 ± 0.2 1.2 ± 0.2 1.0 ± 0.1

7.12 ± 1.21 8.55 ± 0.36

2.1 ± 0.2

2.0 ± 0.1

2.9 ± 0.4

2.9 ± 0.1

3.2 ± 0.3

Pseudofirst-order rate coefficient × 10− 4 (h− 1)

4.31 ± 0.29

2.67 ± 0.35

5.26 ± 0.17

3.92 ± 0.43

2.77 ± 0.25

1.87 ± 0.22

Initial dissolution Siderophore rate (µmol m− 2 surface h− 1) excess (µmol m− 2)

Initial siderophore concentration = 120 µM

Siderophore surface excess was calculated by dividing the siderophore lost from solution by the surface area of Crmontmorillonite

Initial dissolution rate was derived by dividing the slope of the regression equation by the Cr-montmorillonite concentration and surface area

0.19 ± 0.05

0.20 ± 0.02

0.17 ± 0.03

0.09 ± 0.01

0.26 ± 0.01

0.25 ± 0.03

0.21 ± 0.02

0.12 ± 0.01

Maximum Cr in solution (µM) (µmol m− 2)

System

Table 2: Linear regression equations, surface area normalised initial dissolution rates, surface excess values for DFOB and RA, and pseudo-first-order rate coefficients for dissolution of Cr(III) from four Cr(III)-treated montmorillonite clays (67, 133, 200, 400) at pH 6.5

278 Solution Chemistry: Minerals and Reagents

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Errors represent 95% confidence interval Cr-montmorillonite concentration = 0.67 g L− 1 y = soluble Cr (µM); x = time (h) At reaction times less than 100 h Cr release approximates zero-order kinetics, where the solution Cr concentration depends linearly on time, which is typical when dissolution reactions are far-from-equilibrium (Fig. 3) (Sposito 1994; Lasaga 1998). The slope of the linear regression equation given in Table 2, column 4 is therefore equal to the zero-order rate coefficient, which increases with Cr loading for both DFOB (0.019–0.081) and RA (0.018–0.068). The slope of the regression line equation, normalised to surface area, therefore yields the initial dissolution rate (Table 2, column 5). In the presence of either DFOB or RA the initial dissolution rates generally increase with Cr loading. Interestingly, the effect of siderophore type becomes significant only for the 400 clay, where the trihydroxamate DFOB yields a significantly greater dissolution rate than the tetradentate RA (i.e. 10.6 ± 0.65 × 10− 4 vs. 8.90 ± 0.52 × 10− 4 µmol m− 2 h− 1). These dissolution rates compare with Cr release rates of 1.98 ± 0.08 × 10− 5 µmol m− 2h− 1 for Crgoethite at pH 6.5 in the presence of 270 µm DFOB (Stewart et al. 2016) and 1.4 ± 0.2 × 10− 3 µmol m− 2 h− 1 for Cr(OH)3(s) at pH 7 in the presence of 100 mM DFOB (Duckworth et al. 2014). Siderophore surface excess generally increases with clay surface area and Cr loading, with RA showing greater surface adsorption than DFOB at all Cr loadings (Table 2). For example, the surface excess for RA varies from 2.67 ± 0.35 to 8.55 ± 0.36 µmol m− 2, while that for DFOB varies from 1.87 ± 0.22 to 5.26 ± 0.17 µmol m− 2. For comparison, these values are approximately ten-fold greater than the surface excess for DFOB on Cr-treated goethite (0.39–0.94 µmol m− 2) at pH 6.5 and an initial DFOB concentration of 270 µM (Stewart et al. 2016). Given the similarly high pKa values for RA and DFOB (Fig. 1), both siderophores occur as cations in solution at pH 6.5 and will show little electrostatic affinity for the Cr(OH)3precipitates whose pKa is estimated to be approximately 8.5 (Kosemulski 2009). However, the release of Cr to solution at pH 6.5 in the presence of DFOB or RA strongly indicates inner-sphere coordination of the hydroxamate groups at the Cr(OH)3 surface by a mechanism similar to that described for the DFOB-lepidocrocite (γ-FeOOH) system (Borer et al. 2009). Therefore, the greater surface excess of RA that we observe may be due in part to its smaller size, allowing access to interlamellar pores too small to admit the larger DFOB molecule.

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Figure 3: Initial dissolution kinetics showing release of Cr(III) from the four Cr(III)-treated montmorillonite clays in the presence of: a desferrioxamine B and b rhodotorulic acid. A reference montmorillonite, untreated with Cr, serves as a control and was analysed alongside the four Cr-clays for comparison. Initial siderophore concentration: 120 µM; Cr-montmorillonite concentration: 0.67 g L− 1; pH 6.5; 23°C.

Far-from-equilibrium ligand-promoted dissolution kinetics may be characterised by a pseudo-first-order rate coefficient that is obtained by dividing the surface normalised initial dissolution rate by the surface excess of the siderophore promoting the dissolution as described by Stewart et al. (2016) (Table 2). This rate coefficient therefore gives a measure of the surface excess-normalised efficacy of DFOB or RA for each Cr-montmorillonite system. The pseudo-first-order rate coefficients we derive are presented in Table 2and decrease for each siderophore with increasing Cr loading, whilst we also observe that DFOB gives a significantly greater rate coefficient than RA for each system. Thus, the DFOB400 system gives the same rate coefficient as that for RA67 within the margin of error. These trends in rate coefficient are due mainly to an increase in siderophore surface excess that is not matched by a corresponding increase in the initial dissolution rate.

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DFOB and RA are evidently more effective ligands when present at lower surface coverages but this observation may also partly reflect the greater proportion of highly reactive Cr, such as monomers, dimers and trimers, at lower Cr loading. Furthermore, at high Cr loadings the montmorillonite interlayer space is populated by more hydroxy Cr precipitates (as indicated by increasing basal spacings) whose presence, while increasing surface area, may also impede movement of the siderophores throughout the interlayer gallery. The smaller pseudo-first-order rate coefficients that we observe for RA can be explained in part by comparing the molecular geometry of the two Cr(III)-siderophore complexes. The hexadentate DFOB forms a 1:1 complex with Cr(III) such that the sixfold coordination of Cr(III) is satisfied. Also, the flexible carbon backbone of DFOB facilitates formation of both cis and trans isomers, although the cis isomers predominate in the chromic DFOB complexes prepared by Muller and Raymond (1984). The estimated Cr(III)DFOB 1:1 formation constant varies from K Cr (III) HDFOB + = 1030.6 (Duckworth et al. 2014) to KCr (III) HDFOB + = 1033.0 (Kruft et al. 2013) for the reaction: Cr3+(aq) + H4DFOB+(aq) = CrHDFOB+ + 3H+(aq)

In contrast, the tetradentate, dihydroxamate RA is unable to form 1:1 octahedral complexes with Cr(III) due to ligand deficiency. Therefore RA forms bimetallic complexes of the stoichiometry Cr(III)2RA3 at circumneutral pH where the Δ-trans isomer dominates (Muller et al. 1985). Although conditional formation constants are not available for Cr(III)2RA3, one can predict the relative stabilities of Cr(III)-DFOB and Cr(III)2RA3 by comparing the formation constants for each ligand with Fe(III), where K Fe (III) + = 1032.0 (Martell et al. 2003) and (K Fe2RA3 = 1031.1) (Boukhalfa et HDFOB al. 2000). As these values are broadly similar, we infer that the formation constants for Cr(III)-DFOB and Cr(III)2RA3 are also broadly comparable. Therefore, the lower pseudo-first-order rate coefficients observed for RA derive not from reduced stability conferred by its hydroxamate groups, but rather from the ligand deficiency of this tetradentate siderophore. Siderophores may serve as dispersive agents in natural environments by enhancing the mobility of contaminant metals such as Cr. This enhanced mobility can be achieved through siderophore-promoted dissolution of poorly soluble Cr containing solids and the subsequent release of dissolved Cr(III)siderophore complexes that may be transported via advection or diffusion (Mishra et al. 2010; Duckworth et al. 2014). The dissolved Cr(III) may then be oxidized at Mn oxide surfaces and subsequently translocated as Cr(VI)

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to groundwaters, whose naturally occurring aqueous Cr(VI) concentrations can approach 1.4 µM, exceeding the World Health Organization’s threshold for drinking water (Oze et al. 2007). By this means Cr(III) mobilized by siderophores in the uppermost, oxic region of the critical zone may ultimately contribute to the pool of Cr(VI) in anaerobic groundwaters, environments in which siderophore production has not been observed. However, the extrapolation of data from model contaminant systems, as described in this study, to natural environments such as soils and sediments is rarely straightforward. We therefore highlight several factors that must be considered when extrapolating siderophore behaviour from model systems to natural environments. First, as the interaction of siderophores with metals is likely competitive, an abundance of Fe(III) oxides may well diminish the siderophore-mediated dissolution of Cr(III). Second, ubiquitous low molecular weight organic acids (e.g. oxalate) act synergistically with siderophores to facilitate dissolution of Fe(III) oxides (Loring et al. 2008). However, the potential role of these organic acids in enhancing the siderophore-mediated dissolution of Cr(III)-containing solids has not yet been examined. Third, the hydroxy-Cr(III) precipitates used in this study are unlikely to be faithful proxies for those occurring in natural environments, which may, for example, complex a variety of organic substances and possess Al(III) for Cr(III) substitutions. Finally, the aqueous concentration of siderophores in soil is generally low (< 10− 7M) (Powell et al. 1980) and may in fact be orders of magnitude lower than that of the many low MW organic acids. Nevertheless, given their ubiquity in soils and sediments and potential to form thermodynamically stable complexes with Cr(III), hydroxamate siderophores may play an important role in dispersal of this metal in natural environments.

ACKNOWLEDGEMENTS We thank S. Strekopytov and E. Humphreys-Williams for assistance with the chemical analysis and J. Najorka for expert advice with the X-ray diffractometry.

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Adriano DC. Trace elements in terrestrial environments. 2. New York: Springer; 2001. 2. Bartlett RJ, Kimble JM. Behavior of chromium in soils: I. Trivalent forms. J Environ Qual. 1976;5:379–383. doi: 10.2134/jeq1976.00472 425000500040009x. 3. Borer P, Hug SJ, Sulzberger B, Kraemer SM, Kretzschmar R. ATRFTIR spectroscopic study of the adsorption of desferrioxamine B and aerobactin to the surface of lepidocrocite (γ-FeOOH) Geochim Cosmochim Acta. 2009;73:4661–4672. doi: 10.1016/j. gca.2009.05.048. 4. Boukhalfa H, Brickman TJ, Armstrong SK, Crumbliss AL. Kinetics and mechanism of iron(III) dissociation from the dihydroxamate siderophores alcaligin and rhodotorulic acid. Inorg Chem. 2000;39:5591–5602. doi: 10.1021/ic000330k. 5. Brunauer S, Emmett PH, Teller E. Adsorption of gases in multimolecular layers. J Am Chem Soc. 1938;60:309–319. doi: 10.1021/ja01269a023. 6. Budzikiewicz H, Georgias H, Taraz K. Diastereomeric pyoverdinchromium(III) complexes. Z Naturforsch C. 2002;57:954–956. doi: 10.1515/znc-2002-9-1034. 7. Carbonaro RF, Gray BN, Whitehead CF, Stone AT. Carboxylatecontaining chelating agent interactions with amorphous chromium hydroxide: adsorption and dissolution. Geochim Cosmochim Acta. 2008;72:3241–3257. doi: 10.1016/j.gca.2008.04.010. 8. Dhal B, Thatoi HN, Das NN, Pandey BD. Chemical and microbial remediation of hexavalent chromium from contaminated soil and mining/metallurgical solid waste: a review. J Hazard Mater. 2013;250– 251:272–291. doi: 10.1016/j.jhazmat.2013.01.048. 9. Drljaca A, Anderson JR, Spiccia L, Turney TW. Intercalation of montmorillonite with individual chromium (III) hydrolytic oligomers. Inorg Chem. 1992;31:4894–4897. doi: 10.1021/ic00049a033. 10. Dubbin WE, Goh TB, Oscarson DW, Hawthorne FC. Properties of hydroxy-Al and -Cr interlayers in montmorillonite. Clays Clay Miner. 1994;42:331–336. doi: 10.1346/CCMN.1994.0420311. 11. Duckworth OW, Akafia MM, Andrews MY, Bargar JR. Siderophorepromoted dissolution of chromium from hydroxide minerals. Environ Sci Process Impacts. 2014;16:1348–1359. doi: 10.1039/C3EM00717K.

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12. Fracchia S, Godeas A, Scervino JM, Sampedro I, Ocampo JA, GarciaRomera I. Interaction between the soil yeast Rhodotorula mucilaginosa and the arbuscular mycorrhizal fungi Glomus mosseae and Gigaspora rosea. Soil Biol Biochem. 2003;35:701–707. doi: 10.1016/S00380717(03)00086-5. 13. Garnier J, Quantin C, Guimarães EM, Vantelon D, Montargès-Pelletier E, Becquer T. Cr(VI) genesis and dynamics in Ferralsols developed from ultramafic rocks: the case of Niquelândia, Brazil. Geoderma. 2013;193–194:256–264. doi: 10.1016/j.geoderma.2012.08.031. 14. Guertin J. Toxicity and health effects of chromium (All oxidation states) In: Guertin J, Avakian CP, Jacobs JA, editors. Chromium(VI) handbook. Boca Raton: CRC Press; 2004. pp. 215–234. 15. Hausladen DM, Fendorf S. Hexavalent chromium generation within naturally structured soils and sediments. Environ Sci Technol. 2017;51(4):2058–2067. doi: 10.1021/acs.est.6b04039. 16. Kosemulski M. Surface charging and points of zero charge. Boca Raton: CRC Press; 2009. 17. Kruft BI, Harrington JM, Duckworth OW, Jarzęcki AA. Quantum mechanical investigation of aqueous desferrioxamine B complexes: trends in structure binding, and infrared spectroscopy. J Inorg Biochem. 2013;129:150–161. doi: 10.1016/j.jinorgbio.2013.08.008. 18. Lasaga AC. Kinetic theory in the earth sciences. Princeton: Princeton University Press; 1998. 19. Leong J, Raymond KN. Coordination isomers of biological iron transport compounds. IV. Geometrical isomers of chromic desferriferrioxamine B. J Am Chem Soc. 1975;97:293–296. doi: 10.1021/ja00835a011. 20. Lide DR. CRC handbook of chemistry and physics. 84. Boca Raton: CRC Press; 2004. 21. Loring JS, Simanova AA, Persson P. Highly mobile iron pool from a dissolution–readsorption process. Langmuir. 2008;24(14):7054–7057. doi: 10.1021/la800785u. 22. Manteca A, Sanchez J. Streptomyces development in colonies and soils. Appl Environ Microb. 2009;75:2920–2924. doi: 10.1128/AEM.0228808. 23. Martell AE, Smith RM, Motekaitis RJ. Database 46 version 8.0. Gaithersburg: National Institute of Standards and Technology; 2003. NIST critically selected stability constants of metal complexes.

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desferrioxamine B and Suwannee River fulvic acid on Fe(III) release and Cr(III) desorption from goethite. Geochim Cosmochim Acta. 2016;178:62–75. doi: 10.1016/j.gca.2015.11.047.

10 Solubility of Cyclodextrins and Drug/Cyclodextrin Complexes

Phennapha Saokham 1, Chutimon Muankaew 2, Phatsawee Jansook 3, and Thorsteinn Loftsson 4 1

Faculty of Pharmacy, Rangsit University, Pathum Thani 12000, Thailand

Faculty of Pharmacy, Siam University, 38 Petchkasem Road, Phasi Charoen District, Bangkok 10160, Thailand

2

Faculty of Pharmaceutical Sciences, Chulalongkorn University, 254 Phyathai Road, Pathumwan, Bangkok 10330, Thailand

3

Faculty of Pharmaceutical Sciences, University of Iceland, Hofsvallagata 53, 107 Reykjavik, Iceland

4

ABSTRACT

Citation: Saokham P, Muankaew C, Jansook P, Loftsson T. Solubility of Cyclodextrins and Drug/Cyclodextrin Complexes. Molecules. 2018;23(5):1161. Published 2018 May 11. doi:10.3390/molecules23051161. Copyright: © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

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Cyclodextrins (CDs), a group of oligosaccharides formed by glucose units bound together in a ring, show a promising ability to form complexes with drug molecules and improve their physicochemical properties without molecular modifications. The stoichiometry of drug/CD complexes is most frequently 1:1. However, natural CDs have a tendency to self-assemble and form aggregates in aqueous media. CD aggregation can limit their solubility. Through derivative formation, it is possible to enhance their solubility and complexation capacity, but this depends on the type of substituent and degree of substitution. Formation of water-soluble drug/CD complexes can increase drug permeation through biological membranes. To maximize drug permeation the amount of added CD into pharmaceutical preparation has to be optimized. However, solubility of CDs, especially that of natural CDs, is affected by the complex formation. The presence of pharmaceutical excipients, such as water-soluble polymers, preservatives, and surfactants, can influence the solubilizing abilities of CDs, but this depends on the excipients’ physicochemical properties. The competitive CD complexation of drugs and excipients has to be considered during formulation studies. Keywords: cyclodextrin, complex, solubility, poorly soluble drug

INTRODUCTION Cyclodextrins (CDs) are cyclic oligosaccharides, formed by α-1,4-linked glucose units, with a hydrophilic outer surface and a lipophilic central cavity [1,2,3,4]. α-Cyclodextrin (αCD), β-cyclodextrin (βCD), and γ-cyclodextrin (γCD) are natural products that can be found in small amounts in various fermented consumer products, such as beer. Although the unsubstituted natural αCD, βCD, and γCD, and their complexes, are hydrophilic their solubility in aqueous solutions is somewhat limited, especially that of βCD. Consequently the more soluble βCD derivatives, such as 2-hydroxypropylβCD (HPβCD) and sulfobutylether βCD sodium salt (SBEβCD), are preferred for use in aqueous pharmaceutical solutions, such as parenteral drug formulations, even though both αCD and γCD can be found at low concentrations in parenteral formulations [5]. Monographs for αCD, βCD, and γCD and two βCD derivatives are in the European Pharmacopoeia and the United States Pharmacopeia/National Formulary (Table 1). CDs are included in over 40 marketed pharmaceutical products worldwide, in addition to numerous food, cosmetic, and toiletry products [2,6,7].

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Table 1: Cyclodextrins with pharmacopoeia monographs

Cyclodextrin

n

α-Cyclodextrin

R = H or

Abbreviation

Synonyms

Pharmacopoeia Monographs 1

0

αCD

alfadex

Ph.Eur., USPNF, JPC

β-Cyclodextrin

1

βCD

betadex

Ph.Eur., USPNF, JPC

2-Hydroxypropyl-βcyclodextrin

1

-CH2CHOHCH3

HPβCD

hydroxypropylbetadex

Ph.Eur., USPNF

Sulfobutylether β-cyclodextrin sodium

1

-(CH2)4SO3−Na+

SBEβCD

betadex sulfobutyl ether sodium

USP-NF

γ-Cyclodextrin

2

γCD

gammadex

Ph.Eur., USPNF, JPC

The European Pharmacopoeia (Ph.Eur.), the United States Pharmacopeia and the National Formulary (USP-NF), and the Japanese Pharmaceutical Codex (JPC).

1

Due to their ability to change physiochemical properties of drugs and other compounds, CDs are frequently referred to as enabling pharmaceutical excipients. CDs enable delivery of poorly water-soluble and chemically-unstable drugs to the body. Hence, CDs are able to convert biologically-active compounds that lack drug-like physiochemical properties into therapeutically-effective drugs. CDs (referred to as host molecules) are able to form inclusion complexes with drugs (referred to as guest molecules) by taking part of a drug molecule into the central CD cavity. This will change the

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physiochemical properties of the included drug. Formation of a drug/CD inclusion complex can, for example, increase the aqueous solubility of the drug, increase its chemical and physical stability, and enhance drug delivery through biological membranes. No covalent bonds are formed or broken during the complex formation and, in aqueous solutions, drug molecules bound within the CD inclusion complex are in dynamic equilibrium with free drug molecules (Figure 1) [8]. Drug molecules are readily released from the complex upon media dilution or by competitive complexation [9,10]. One or more drug molecules can form a complex with one CD molecule and one or more CD molecules can form a complex with one drug molecule. However, most commonly, one drug molecule (D) forms a complex with one CD molecule. The stoichiometry of the drug/CD complex (D/CD) is then 1:1 and the equilibrium constant (K1:1) defined as [11,12]: (1)

Figure 1: Formation of a cyclodextrin inclusion complex in an aqueous solution and self-assembly of cyclodextrin complexes.

The value of K1:1 can be calculated by Equation (2) where S0 is the intrinsic solubility of the drug (i.e., the solubility in the aqueous media when no CD is present), and Slope is the slope of the linear (i.e., AL-type) drug-CD phase solubility diagram (Figure 2): (2)

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Figure 2: Types of phase-solubility diagrams according to Higuchi and Connors [11] showing how the total drug solubility changes with increasing CD concentration. A-type diagrams are formed when the drug/CD complex is soluble in the aqueous complexation media and they are usually associated with the water-soluble CD derivatives. B-type diagrams are observed when the complex has limited solubility in the media and these are usually associated with the natural CDs that have limited solubility in aqueous media. AL: linear diagram; AP: positive deviation from linearity; AN: negative deviation from linearity; BS: the complex has some but limited solubility; BI: the complex is insoluble.

However, the value of K1:1 is highly sensitive towards small changes in S0 and for poorly-soluble drugs it can be complicated to obtain accurate S0 values. Furthermore, self-association of lipophilic drug molecules in aqueous media can lead to erroneous results. Under such conditions, it can be more accurate to determine the complexation efficacy (CE): (3) Drug/CD complexes, especially those of the natural CDs, have tendency to self-assemble in aqueous solutions to form aggregates (Figure 1). At elevated CD concentrations these aggregates can become large and precipitate as solid microparticles [1]. In addition, the natural CDs and their complexes have limited solubility in aqueous solutions. These solubility limitations can give rise to characteristic B-type phase-solubility diagrams displayed in Figure 2 [11].

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The biopharmaceutical classification system (BCS) divides orally-administered drugs into four cases based on their solubility and intestinal permeability [13]. Drugs possessing favorable physiochemical properties are in Class I. They have adequate aqueous solubility and permeability to be well-absorbed from the gastrointestinal tract. In general, they gave good oral bioavailability. Drugs in Class II have inadequate aqueous solubility, but good permeability when in solution. Thus, their absorption from the gastrointestinal tract is slow and dissolution dependent. Drugs in Class III have adequate aqueous solubility but poor permeability, most often due to their very hydrophilic nature. Frequently such drugs are administered via parenteral injection. Finally, drugs in Class IV have both low aqueous solubility and are poorly absorbed from the gastrointestinal tract. Thus, they have very poor oral bioavailability and can be difficult to formulate as parenteral solutions. CDs can improve oral bioavailability of Class II drugs and sometimes also of Class IV drugs while they have negligible effect on Class III drugs and can under certain conditions even hamper absorption of some Class I drugs [10]. The BCS can be adapted to other types of dosage forms intended for non-oral administration [14]. Here the aqueous solubility of CDs and their complexes is reviewed, as well as the effect of CD concentrations on drug permeation through biological membranes.

PHYSIOCHEMICAL PROPERTIES OF CYCLODEXTRINS The secondary hydroxyl groups on the CD molecule are located on the wider rim of the molecule and the primary hydroxyl groups on the narrow rim make them hydrophilic [12,15]. Due to their hydrophilic outer surface and their large number of hydrogen bond donors and acceptors, CDs have very negative LogPo/wvalue (i.e., the logarithmic value of the octanol/ water partition coefficient) (Table 2) [4,16]. In aqueous solutions, CDs are susceptible to acid hydrolysis at low pH resulting in ring opening and formation of various linear oligosaccharides and glucose units, but they are stable under alkaline conditions. The hydroxyl groups attached to the rim start to deprotonate at pH about 12 [17,18]. Depending on the determination method and the location of the hydroxyl groups, the pKa values of the natural CDs have been reported to be between 12.1 and 13.5 [19]. The main difference of the three natural CDs, besides the size of their central cavity, is their aqueous solubility (Table 2). βCD is the least soluble but, at the same time, possesses the most suitable cavity size for

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complex formation with many drugs [20,21]. The poor solubility can be explained in term of molecular rigidity of CD molecule, and the effect caused by the intermolecular hydrogen bonding in the crystal state [22,23]. Particularly, the hydrogen bond formation between neighboring C2-OH and C3-OH in the βCD molecule leads to the so-called complete secondary belt resulting in inflexible structure and reduced ability of the βCD molecule to form intermolecular hydrogen bond with surrounding water molecules [15]. Molecular dynamic simulations have shown high water density and strong ordering of water molecules around the βCD molecule [24,25]. This indicates that water molecules surrounding dissolved βCD molecules have unfavorable enthalpy and low entropy, which can explain the low water solubility of βCD compared to other natural CDs. In contrast, αCD has incomplete belt of hydrogen bonds and γCD has non-coplanar structure. Consequently, both αCD and γCD possess higher solubility in water. Table 2: The cavity size and some important physicochemical properties of natural CDs and some of their derivatives Types

Substituent

DS

1

Inner Cavity Diameter (Å)

Hydrogen Donors

Hydrogen Acceptors

Solubility (mg/ mL, 25 °C)

Log Po/w

Surface Tension (mN/m)

References

Naural CD αCD

H

0

4.7–5.3

18

30

145

−13

71

[1,42]

βCD

H

0

6.0–6.5

21

35

18.5

−14

71

[1]

γCD

H

0

7.5–8.3

24

40

232

−17

71

[1]

HPαCD

-CH2CHOH-CH3

3.6

4.5–5.3

18

36

-

-

-

[43]

CMβCD

-CH2-CO2H

3–5

-

21

49

50

−4.9

-

[32]

DMβCD

-CH3

12–16

5.8–6.5

7

35

570

-

62

[34]

RMβCD

-CH3

9.7– 13.6

-

9

35

>500

−6

57.5– 54.1

Modified CD

TMβCD

-CH3

21

4–7

0

35

310

-

56

[34,46]

HEβCD

-CH2CH2OH

3.6

-

21

42

>2000

-

-

[26,47]

HPβCD

-CH2CHOH-CH3

2.8– 10.5

6.0

25

39

>1200

−11

54.8– 57.5

[1,47]

SBEβCD

(CH2)4SO3Na

6.2– 6.9

-

21

35

>1200

1500

−9

72

[33]

GUGβCD

glucoronylglucosyl

1

-

-

-

>2000

-

73

[33]

DS is defined as the average number of substituents per one CD molecule; DMαCD, dimethyl-αCD; TMαCD, trimethyl-αCD; HPαCD, 2-hydroxypropyl-αCD; CMβCD, carboxymethyl-βCD; DMβCD, dimethylβCD; TMβCD, trimethyl-βCD; HEβCD, hydroxyethyl-βCD; DMγCD, dimethyl-γCD; TMγCD, trimethyl-γCD; HPγCD, hydroxypropyl-γCD, SBEγCD, sulfobutylether-γCD sodium salt; SUG, sugammadex; G1βCD, glucosyl-βCD; G2βCD, maltosyl-βCD; GUGβCD, glucoronyl-glucosylβCD. 1

To enhance solubilizing potential of the natural CDs, including their complexation capacity, CD derivatives have been prepared by reacting the secondary and/or primary OH groups of the molecule with a wide variety of substituents [26,27]. Randomly methylated and hydroxypropylated CDs and sulfobutylether CDs are manufactured on an industrial scale and often used in pharmaceutical products, whereas other CD derivatives are utilized for specific purposes, such as the removal of pollutants from the environment and reagents for drug analysis [28,29]. Attachment of these substituents disrupts the regular hydrogen bonding network within native CD molecule increasing their ability to interact with the surrounding water molecules [30]. The result can be over 100-fold increase in their aqueous solubility [31,32,33,34]. For example, the sulfobutylether βCD anionic alkyl chains form an extremely hydrophilic exterior surface. These anionic chains provide for electrostatic repulsion resulting in extension of the hydrophobic central cavity and thereby intensifying its solubilizing potential [35]. Most frequently, modified natural CDs exist in amorphous isomeric mixtures of various degree of substitution (DS). The DS has a great influence on the physicochemical properties of CDs and their ability to form complexes. For instance, randomly-methylated βCD (RMβCD) has the highest solubility in water when the degree of substitution is about 14, that is, when two-thirds of the OH-groups have been replaced by methoxy groups [36]. Increasing the

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295

DS above 14 decreases the RMβCD solubility. The cavity diameter of CD derivatives is similar to their parent CDs. However, an effect of substituent location on the cavity volume has been observed [37]. It has been observed that the hydroxypropylation of OH groups at the O-2 position results in a more spread out configuration, whereas the substitution of OH groups at the O-6 position reduces the water density inside the CD cavity [30,38,39]. Unlike native CDs that have negligible surface activity, some CD derivatives manifest such behavior. It is reported that methylated and hydroxyalkylated CD molecules reduce the surface tension of water [40,41]. The increase in surface activity is proportional to the increased degree of substitution. On the other hand, derivatives with polar ionic groups, such as carboxylate ion and sulfobutyl groups, have no influence on surface activity [35]. Table 2 lists dimensional structures and physicochemical properties of the three most common natural CDs and some of their more common derivatives.

HOW MUCH SOLUBILIZATION IS NEEDED? CDs can both enhance and hamper drug permeation through biological membranes. Although active drug transport through biological membranes does exist, drug molecules are mainly transported via passive diffusion through the membranes. In general, the driving force for passive diffusion through an aqueous environment (e.g., mucus) into and through membranes, such as mucosa is not the concentration gradient but the gradient of chemical potential, which is a continuous function across interfaces [50]. Likewise, the partitioning of drug molecules from a membrane exterior into the outermost membrane layer is controlled by the chemical potential. Thus, maximum drug permeation from an aqueous exterior into and through biological membrane is expected to be obtained when the drug is at its highest thermodynamic potential [50]. In other words, maximum drug permeation is obtained when the aqueous membrane exterior is saturated with the drug [51]. However, the amount of drug permeating through a membrane also depends on the concentration of dissolved drug at the membrane exterior. Figure 3 shows the flux of hydrocortisone through hairless mouse skin in vitro. The skin was mounted in a Franz diffusion cell where the donor phase was unstirred (i.e., consisted of an unstirred diffusion layer), but the receptor phase was stirred. The total amount of hydrocortisone (i.e., dissolved and undissolved) in the donor phase was kept constant at 16 mg/mL while the CD concentration was increased from 0 to 20% (w/v). About 8% (w/v) CD was needed to solubilize 16 mg of hydrocortisone in

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Solution Chemistry: Minerals and Reagents

1 mL of the donor phase (i.e., the aqueous medium). Thus, increasing the CD concentration from 0 to 8% (w/v) increases the amount of dissolved drug in the donor phase. At these CD concentrations, the donor phase was always saturated with the drug and, thus, the drug is always at its maximum thermodynamic potential. Under these conditions, the drug molecules have maximum tendency to leave the donor phase and partition into the skin. However, only dissolved drug molecules can partition into the skin and, thus, increasing the concentration of dissolved drug molecules through formation of water-soluble drug/CD complexes increases the number of drug molecules that are able to partition into the skin and then permeate through the skin into the receptor phase. Increasing the CD concentration beyond 8% (w/v) decreases the thermodynamic potential of the drug. The solubility of hydrocortisone in 10% (w/v) CD solution is about 20 mg/mL and about 26 mg/mL at 13% (w/v) CD. The donor phase was no longer saturated with the drug and the drug molecules have decreased tendency to leave the donor phase and partition into the membrane. To ensure maximum drug permeation through biological membranes one should only add just enough CD to the pharmaceutical formulation to solubilize the entire drug dose. Too little or too much CD will result in less than optimum drug flux through the membrane. However, small excess CD has to be included in aqueous drug solutions to prevent drug precipitation during storage and handling.

Figure 3: The effect of maltosyl-β-cyclodextrin concentration on the permeation of hydrocortisone through hairless mouse skin in vitro. The amount of hydrocortisone in the aqueous donor medium was kept constant 16 mg/mL but

Solubility of Cyclodextrins and Drug/Cyclodextrin Complexes

297

the maltosyl-β-cyclodextrin concentration was from 0 to 20% (w/v). Below 8% (w/v) maltosyl-β-cyclodextrin the medium was hydrocortisone suspension in water, but hydrocortisone solution in water at higher concentrations. Based on unpublished results.

In solid dosage forms such as tablets adequate amount of CD should be included to prevent dissolution controlled drug absorption from the gastrointestinal tract [10]. Excess CD can hamper absorption from the gastrointestinal tract and, for example, αCD is used to bind and prevent absorption of dietary fat [52]. The unsubstituted natural αCD, βCD, and γCD frequently form drug/CD complexes that have limited solubility in water. However, their solubility is most often sufficient to prevent dissolution limited absorption, and since natural CDs have lower molecular weight than their more water-soluble derivatives their formulation bulk will be lower. General observations regarding the amount of CD to be included in pharmaceutical formulations are listed in Table 3. Table 3: In general, pharmaceutical formulations should contain sufficient CD to solubilize the entire drug dose. However, how much solubilization is needed will depend on the formulation Formulation

Amount of CD

Comments

Parenteral solutions

Sufficient to solubilize the drug dose in, for example, 10 mL of water.

Significant excess CD (as much as two to three times what is needed to solubilize the drug) is frequently included in parenteral formulations, especially those that are given intravenously. This will not affect the drug pharmacokinetics since the drug is almost instantaneously released from the complex upon dilution in the blood circulation.

Solid oral dosage forms (e.g., tablets and capsules)

Sufficient to increase aqueous solubility the drug dose to prevent dissolution controlled absorption.

The formulation bulk usually limits the amount of CD that can be included in solid dosage forms. For example, if βCD (molecular weight 1135 Da) is used in a solid dosage form containing 100 mg of a drug with molecular weight 250 Da the formulation bulk will be increased by over five-fold.

298

Solution Chemistry: Minerals and Reagents

Oral solutions

Sufficient to dissolve the drug dose in the aqueous vehicle.

Excess of CD (e.g., ≥20) should be used to prevent drug precipitation upon storage and usage of the formulation. Due to formulation dilution in the gastrointestinal tract some excess CD will not hamper the drug release. However, large excess (over 50 to 100) can hamper the drug release.

Topical solutions with limited dilution upon administration (e.g., eye drops)

Sufficient to dissolve the drug dose in the aqueous vehicle.

Only a small excess of CD (e.g., 10 to 20%) should be used to prevent drug precipitation upon storage and usage of the formulation. Excess amounts of CD (e.g., more than 10%) can reduce topical bioavailability of the drug.

THE EFFECT OF THE GUEST MOLECULE ON THE CYCLODEXTRIN SOLUBILITY Not only are aqueous solubilities of drugs affected by the formation of drug/CD complexes, but also that of the CDs themselves. According to the phase-solubility diagram classification system that was introduced by Higuchi and Connors [11], linear AL-type diagrams show that the total drug solubility increases as a function of CD concentration through formation of soluble drug/CD complexes. If one molecule of drug forms a complex with one molecule of CD, the slope of a straight line is less than unity and the value of K1:1 can be calculated by applying Equation (2). AP- or AN-type phase-solubility diagrams (i.e., displaying positive or negative deviation from linearity, respectively) suggest formations of higher-order drug/CD complexes [20,53]. If the slope of a linear diagram is greater than unity, but less than 2, the complex formed is likely to be of second, or higher, order with respect to the drug, but first-order with respect to CD. For example, a K2:1 value of drug/CD complex can be determined by [46]:

(4) The AP-type phase-solubility diagram suggests the formation of higher-order complexes with respect to CD (e.g., formation of 1:2 drug/CD complex). The complex stoichiometry and equilibrium constant (K2:1) can then be determined by fitting the solubility results to a quadratic model [20,54].

Solubility of Cyclodextrins and Drug/Cyclodextrin Complexes

299

The tendency of a given drug and CD to form a complex is expressed by a stability constant for the complex (Km:n), where m and n are the number of molecules of the drug and CD forming the complex, respectively, or the equilibrium binding constant (Ka) defined by the ratio of association (ka) and dissociation (kd) rate constants [55,56]. The Ka values of most drug/CD complexes are less than 105 M−1, indicating that the drug and CD interactions are relatively weak [20,56]. Moreover the forward (ka) and reverse (kd) reactions are very fast and the relaxation time is short (less than 1 s) [55,57], indicating that drug and CD molecules in complex are in rapid equilibrium with free molecules in the solution. Thus, in aqueous solutions drug/CD complexes are in dynamic equilibrium with free drug and CD molecules. Studies of dissolved γCD in aqueous complexation media of indomethacin/ γCD, diclofenac sodium/γCD, and amphotericin B/γCD (all of which display AL-type phase-solubility diagrams) show that the determined concentrations of γCD are almost identical to the initial concentration of dissolved γCD before the addition of the drug [58]. The influence of drug concentration on CD solubility in complexation media is negligible when the phase-solubility diagram of the drug/CD complex presents as A-type (Figure 4a).

300

Solution Chemistry: Minerals and Reagents

Figure 4: The phase-solubility diagram of hydrocortisone/HPγCD (a) [58] and hydrocortisone/γCD (b) [59] complex. Concentrations of the soluble drug (open circle) and CD (filled circle) are plotted against the concentration of total CD.

In general, the water-soluble CD derivatives form A-type phasesolubility diagrams, whereas the B-type diagrams are mainly observed when the natural CDs form complexes with poorly-soluble drugs [20]. The B-type phase-solubility diagrams indicate the formation of complexes with limited solubility in the complexation media. The initial linear region of Bs-type diagrams can be regarded as AL-type diagrams. In this region of the diagrams drug molecules do not affect the CD solubility. In the plateau region of the B-type diagram the drug solubility is constant even when the CD concentration is increased, indicating the formation of drug/CD complexes with limited solubility and that the CD solubility is depressed by the presence of the drug [58,59]. The amount of dissolved CD and drug in aqueous complexation media are constant through the length of plateau region (Figure 4b) [59,60]. However, the amounts of drug and CD in the precipitate can differ. Schönbeck reports that precipitate obtained from phase-solubility studies consists of solid drug (i.e., hydrocortisone in excess) and precipitated drug/γCD complex. The ratio of γCD to drug in precipitate increases as a function of the γCD concentration (i.e., the amount of precipitated drug decreases, whereas the amount of precipitated drug/ γCD complex increases) indicating that the stoichiometry of the drug/CD inclusion complex gradually changes from 1:1 to higher-order drug/CD complexes [61]. Since the solubility of the drug/CD complex is limited,

Solubility of Cyclodextrins and Drug/Cyclodextrin Complexes

301

higher-order drug/CD complexes precipitate resulting in decreased CD solubility in the aqueous complexation media. The descendent region of B-type phase-solubility diagrams show that solubility of the drug decreases when the concentration of CD increases, indicating that CD preferably forms self-assembled aggregates and the solubility of CD gradually increases even in the presence of the drug [60]. The absence of solid pure drug in the precipitate from phase-solubility studies also indicates that only higher-order drug/CD complexes are being formed [61]. In conclusion, the CD solubility, especially that of the natural CDs, can be decreased in the presence of drugs if high-order drug/CD complexes, for example 1:2 or 2:1, are formed and then precipitated from the media.

EXCIPIENTS AND CYCLODEXTRIN SOLUBILITY In pharmaceutical products, not only drugs and CDs are present as drug/CD complexes, but also various excipients, such as antioxidants, antimicrobial agents, surfactants and polymers. These excipients can enhance or hamper the CD solubilization of drugs, as shown in Table 4. Preservatives, such as propyl- and methylparaben, can compete with drug molecules and expel them from the CD cavities and, thus, reduce CD solubilization of the drugs [62,63]. In addition, CD complexation of the preservatives can reduce their antimicrobial efficacy. Therefore, formulation scientists need to adjust the amount of preservative in CD-containing formulations to obtain the desired preservative efficacy and safety [64]. The additive or synergistic effects of excipients on the drug solubility through CD inclusion complexes have been reviewed [20,65]. Various additives that are commonly used in pharmaceutical formulations, such as organic acids or bases, organic salts (counterions), cosolvents, metal ions, and water-soluble polymers, can increase the complexation efficacy (CE) of CDs via stabilization and solubilization of drug/CD nanoparticles. Recently, we have shown that CDs and drug/CD complexes can self-assemble and form complex aggregates in aqueous solutions, which can enhance the drug solubility [54,66,67]. Watersoluble polymers play an important role in the stabilization of aggregates. Formation of ternary drug:CD:polymer complexes can be promoted by heating the media, for example, in an autoclave (121 °C for 15–20 min) or in an ultrasonic bath (e.g., 60–70 °C for 1 h) [68]. It has been shown that the addition of small amounts of water-soluble polymer reduces the formulation bulk, decreasing the manufacturing cost and increasing the possibility of using CDs as solubilizers in various solid dosage forms. For instance, the

302

Solution Chemistry: Minerals and Reagents

amount of βCD or SBEβCD required to solubilize 3.0 mg of glibenclamide were 300 mg and 1200 mg, respectively. Addition of hydroxypropyl methylcellulose (HPMC) to the binary complexes reduced the amount of CD in the formulation to 120 mg and 250 mg, respectively [69]. Table 4: Effects of some pharmaceutical excipients on the cyclodextrin solubilization Excipients

Examples

Acids, bases, hydrochloinorganic/organic ride, citrate, salts aspartate, mesylate, maleate, tartrate, phosphate, acetate

Effect on Complexation Enhancement

Some Brief Observations

References

Increase intrinsic solubility of drugs (S0) and/or the apparent stability constant (K1:1) resulting in increased CE

Salt formation of ziprasidone mesylate enhance the CE of drug up to 100 and 240 times in aqueous HPβCD and SBEβCD solutions when compared with the free base of drug

[71]

Ternary complex of terfenadine/βCD/ inorganic acid (phosphate, citrate) induce the synergistic effect of CD solubilization

[72]

The addition of sodium acetate into the complexing medium containing βCD could increase hydrocortisone solubility up to 220%

[73]

K1:1 of fluasterone/ HPβCD complex decreases with increasing ethanol concentration but the drug solubility increased at high ethanol concentration (>40% v/v)

[74]

Ternary complex of diazepam/PG/βCD increased the diazepam solubility than that of the mixture of PG and water

[75]

Enhance S0 but in most cases decrease K1:1

Cosolvents

ethanol, propylene glycol (PG)

Solubility of Cyclodextrins and Drug/Cyclodextrin Complexes Hamper complexation by the competitive effect

At higher concentrations of PG, the methyltestosterone solubility in presence of HPβCD decreased possibly due to the complex dissociation

303

[76]

Water-soluble polymers

HPMC, Na CMC, PVA, PVP

Formation of ternary complex (drug/CD/polymer) that can increase K1:1

[20,77, Polymers and CDs 78,79] can form water-soluble complexes with poorly water-soluble drugs, for example, acetazolamide, carbamazepine hydrocortisone, naproxen, pregnenolone, tropicamide, etc. have been reviewedSynergistic solubilization effect is possible through micellarlike solubilization or stabilization of self-assembled CD and/or CD complex aggregates

Metal ions

Mg2+

Enhance CE by increasing S0 via formation of drug/ CD/metal ion complexes

Synergistic solubilization of quinolone was obtained when the addition of Mg2+ to the drug/ HPβCD complexes

[80]

Hydroxypropyl methylcellulose (HPMC); sodium carboxymethylcellulose (Na CMC); polyvinyl alcohol (PVA), polyvinyl pyrrolidone (PVP). The excipients in the pharmaceutical formulations containing CD may increase or decrease the ability of CD to solubilize drugs depending on their nature and physicochemical properties. Thus, the exact amount of CD needed in a given formulation should be determined by studies (e.g., phasesolubility studies) in a medium which composition is close to that of the final formulation. The competitive complexation effect of the secondary drug should also be considered [70].

CONCLUSIONS AND DIRECTIONS Various physiochemical properties of drugs can be altered through CD complexation, especially drug solubility in aqueous biological media. In aqueous media, drug molecules of appropriate size and structure will enter into the central cavity of CD molecules to form water-soluble complexes

304

Solution Chemistry: Minerals and Reagents

and, frequently, enhanced total drug solubility is observed. AL-type phase solubility diagrams represent linear relationships between concentrations of dissolved drug and amounts of CD added to an aqueous medium. However, when B-type diagrams are observed, the CD molecules and their complexes self-assemble to form aggregates that possess limited solubility. While drug/ CD complexes are in dynamic equilibrium with free drug and CD molecules in aqueous media, CD aggregates frequently precipitate from the media. The solid CD aggregates decrease CD solubility and this will, again, influence formation of drug/CD complexes. Pharmaceutical excipients, for example water-soluble polymers, are able to hamper this type of CD precipitation via formation of ternary complexes leading to enhanced CD complexation efficacy. Since CD forms complexes with wide variety of guest molecules, including drugs and pharmaceutical excipients, competitive complexation should always be take into account. Therefore, the amount of CD and the type and composition of pharmaceutical excipients used in pharmaceutical formulation needs to be carefully selected.

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soluble cyclodextrin derivative with low hemolytic activity. J. Pharm. Sci. 1999;88:970–975. doi: 10.1021/js990128i. Tongiani S., Ozeki T., Stella V.J. Sulfobutyl ether-alkyl ether mixed cyclodextrin derivatives with enhanced inclusion ability. J. Pharm. Sci. 2009;98:4769–4780. doi: 10.1002/jps.21791. Fenyvesi É., Szemán J., Csabai K., Malanga M., Szente L. Methylbeta-cyclodextrins: The role of number and types of substituents in solubilizing power. J. Pharm. Sci. 2014;103:1443–1452. doi: 10.1002/ jps.23917. Del Valle E.M.M. Cyclodextrins and their uses: A review. Process Biochem. 2004;39:1033–1046. doi: 10.1016/S0032-9592(03)00258-9. Yong C.W., Washington C., Smith W. Structural behaviour of 2-hydroxypropyl-β-cyclodextrin in water: Molecular dynamics simulation studies. Pharm. Res. 2008;25:1092–1099. doi: 10.1007/ s11095-007-9506-y. Terekhova I.V., Kumeev R.S., Al’per G.A. The interaction of caffeine with substituted cyclodextrins in water. Russ. J. Phys. Chem. A. 2007;81:1071–1075. doi: 10.1134/S0036024407070114. Müller B.W., Brauns U. Hydroxypropyl-β cyclodextrin derivatives: Influence of average degree of substitution on complexing ability and surface activity. J. Pharm. Sci. 1986;75:571–572. doi: 10.1002/ jps.2600750609. Leclercq L., Bricout H., Tilloy S., Monflier E. Biphasic aqueous organometallic catalysis promoted by cyclodextrins: Can surface tension measurements explain the efficiency of chemically modified cyclodextrins? J. Colloid Interface Sci. 2007;307:481–487. doi: 10.1016/j.jcis.2006.12.001. Loftsson T., Jarho P., Másson M., Järvinen T. Cyclodextrins in drug delivery. Expert Opin. Drug Deliv. 2005;2:335–351. doi: 10.1517/17425247.2.1.335. Szente L., Fenyvesi É. Cyclodextrin-lipid complexes: Cavity size matters. Struct. Chem. 2017;28:479–492. doi: 10.1007/s11224-0160884-9. Legrand F.-X., Sauthier M., Flahaut C., Hachani J., Elfakir C., Fourmentin S., Tilloy S., Monflier E. Aqueous hydroformylation reaction mediated by randomly methylated β-cyclodextrin: How substitution degree influences catalytic activity and selectivity. J. Mol.

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11 Prediction of Solubility of Active Pharmaceutical Ingredients in Single Solvents and Their Mixtures — Solvent Screening

Ehsan Sheikholeslamzadeh and Sohrab Rohani Department of Chemical and Biochemical Engineering, Western University, Canada

ABSTRACT In this chapter, the applicability of two predictive activity coefficientbased models will be examined. The experimental data from five different types of VLE (vapor-liquid equilibrium) and VLLE (vapor-liquidliquid equilibrium) systems that are common in industry are used for the evaluation. The nonrandom two-liquid segment activity coefficient (NRTLSAC) and universal functional activity coefficient (UNIFAC) were selected Citation: Ehsan Sheikholeslamzadeh and Sohrab Rohani (December 21st 2015). Prediction of Solubility of Active Pharmaceutical Ingredients in Single Solvents and Their Mixtures — Solvent Screening, Recent Advances in Thermo and Fluid Dynamics, Mofid Gorji-Bandpy, IntechOpen, DOI: 10.5772/60982. Copyright: © 2015 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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to model the systems. The various thermodynamic relations existing in the open literature will be discussed and used to predict the solubility of active pharmaceutical ingredients and other small organic molecules in a single or a mixture of solvents. Equations of states, the activity coefficient, and predictive models will be discussed and used for this purpose. We shall also present some of our results on solvent screening using a single and a mixture of solvents. Keywords: Solubility prediction, Pharmaceuticals, NRTL-SAC Thermodynamic model, Activity coefficient, Solvent screening, Single solvent, Solvent mixture

INTRODUCTION The study of solutions and their properties is one of the important branches of thermodynamics. It is important to know the behavior of a mixture of components for a change in temperature, pressure, and composition. Knowledge in this area of thermodynamics helps engineers and scientists to better design, optimize, and operate the process units in the oil, gas, petrochemicals, pharmaceuticals, agricultural, and other chemical-related industries. Knowledge of the thermodynamics is essential to improve process performance and product quality. For example, the use of phase behavior calculations to understand and estimate the production rate of solids from a crystallization process in a pharmaceutical industry is of paramount importance in modeling, optimization, and control of product quality. A solution is called ideal if its mixture property is a linear combination of the properties of each of its constituents at the given temperature and pressure [1]:

(1) where msolution and mi represent the molar property of the mixture and pure component i, respectively, and xi denotes the mole fraction of each constituent i in the solution. Not all solutions can be considered ideal. The interactions between the solute and solvent molecules in the solution renders a solution nonideal. The fundamental relationship which relates the thermodynamic properties is the Gibbs free energy [1]:

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(2) where G, V, P, S, and T are, respectively, Gibbs free energy, volume, pressure, entropy, and temperature of the solution. The represents the change in the Gibbs energy as a result of changes in the concentration of species i while the pressure, temperature, and the molar content of other species are kept constant. This is known as the chemical potential and in some textbooks is shown by μi. For a real solution, the chemical potential for each species is expressed by (3) In which and ai are the chemical potential of species i in its standard conditions and activity of the species i. The activity is defined as (4) where γi is the activity coefficient which is 1 for ideal solutions. Inserting Equation (4) into Equation (3), results in (5) The term RTlnγi accounts for the nonideality of the solution (it is also referred to as the partial molar energy). As it can be seen from Equation (5), the terms on the right side, except Tlnγi, are calculated from the pure properties. However, in order to have an accurate prediction of the chemical potential of any species in the solution, RTlnγi should be known as well. In general, the activity coefficient is a function of temperature and composition and to a much less extent, the pressure. Because the activity coefficient is defined for a liquid solution, the pressure has very little effect on it. However, temperature and mole fractions of the species have significant effects on the activity coefficient of each species in a solution. This chapter provides the reader with different and the most up-to-date thermodynamic models to estimate the activity coefficients of active pharmaceutical ingredients (API) in a solution.

Thermodynamics of the Solutions Containing Dissolved Solids For a solid in equilibrium with itself in a solution, there is a thermodynamic relation [2]:

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(6) denotes fugacity of component i in solid phase and where represents the fugacity in the liquid phase. Equation (7) below correlates the fugacity of a pure component i in solid and liquid state ( , respectively). (7) In order to find the ratio of the two fugacities, we need to consider all the thermodynamic processes that are involved from a solid to the liquid state. The three processes are shown in Figure 1. Path A in this figure shows the transformation from process conditions to the state where the solid starts melting. Path B shows the melting process at constant temperature and pressure. Path C indicates the change from melting to the process state. The sum of the three paths will give us the whole change from solid to liquid state of a pure component. From the fundamental rules in thermodynamics, we have: (8) And the Gibbs energy change is related to change of enthalpy and entropy: (9)

Figure 1: Schematic diagram for finding the fugacity change from solid to liquid state of a pure substance.

From Figure 1, the whole change in enthalpy is:

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(10) . In the same manner, the entropy change from where solid to liquid state can be found from

(11) Also, (9), then:

. If we substitute Equations (10) and (11) into Equation

(12) If we neglect the terms including change in the heat capacity (because of the large value of heat of fusion compared to the heat capacities), then we will get the following important equation: (13) where xs is the equilibrium mole fraction of the solute (dissolved solid) in a solution at temperature TT. Equation (13) is the starting point in every solidliquid equilibrium calculation procedure that relates the three important variables xs, TT, and γs. However, we already know that γs is a function of solution temperature and the mole fraction of the species. Therefore, one can fix all the thermodynamic properties of a solution if the mole fraction of the species and the solution temperature are known. We recall that although the pressure has to be fixed as well, but due to its minimal effect on the activity coefficient and other properties of the system, we don›t need to have it for calculations.

Classification of the Thermodynamic Models for Solutions In order to predict the solubility of solids in pure and mixed solvents, the use of noncorrelative (predictive) thermodynamic models is of high importance. Since several years ago, there have been many thermodynamic models introduced to help scientists and engineers in the prediction of

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phase behaviors of various liquid-liquid and vapor-liquid systems, such as the Margules equation [3], the Wilson equation [4], the Van Laar equation [5], the nonrandom two-liquid (NRTL) equation [6], and the UNIQUAC equation [7]. As these models are applicable in the estimation of activity coefficients, they can also be utilized to predict solid-liquid equilibrium systems. In general, the models which govern the activity coefficients of the species in the solutions are grouped into two categories: •

The models which need experimental data at various temperatures, pressures, and compositions of the mixture, such as UNIQUAC equation. • The models which only need some fundamental properties of the chemical molecule and a very few experimental data to predict the phase behavior of the solids within various solvents, such as the UNIFAC [8] and NRTL-SAC models [9]. As it is apparent from the above two categories, the first one is not useful for the prediction of the phase behavior of mixtures, specifically for mixtures of more than two species. Because of the time-consuming and expensive nature of binary interaction parameter evaluation of various chemical components, the first group of thermodynamic models (above) is not practical. As an example, the activity coefficient from Wilson’s equation of state is found from [4]:

(14) The binary interaction parameter is:

(15) where i and j refer to the compounds present in the solution. From Equation (14), it can be seen that for obtaining the activity coefficient of a component 1 in a pure solvent 2, we need four interaction parameters ( , which are temperature dependent. In addition, from Equation (15), it is evident that for calculating the value of the binary interaction parameters, additional experimental data, such as molar volume is needed. From the predictive category (second group), the universal functional

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activity coefficient (UNIFAC) model is a well-known example. The main application of the UNIFAC model is in systems showing nonelectrolytic and nonideal behaviors. Fredenslund et al. [8] developed the UNIFAC model. The NRTL segment activity coefficient (NRTL-SAC) model was first introduced in 2004 by Chen et al. [9]. This model was proposed in order to compensate for the weakness of the UNIFAC in predicting the solubility of complex chemical molecules with functional groups that had not been studied for the UNIFAC parameters. Also, in some cases, the UNIFAC group addition rule becomes invalid [2]. One of the main advantages of the NRTL-SAC model in comparison to the other predictive methods is its ability to predict organic electrolyte systems. The UNIFAC method identifies the molecule in terms of its functional groups, while the NRTL-SAC model divides the whole surface of the molecule to four segments. These segments’ values are found from their interactions with other molecules in a solution. Based on Chen et al., three purely hydrophilic, hydrophobic, and polar segments have been selected as water, hexane, and acetonitrile, respectively.

IDEAL SOLUTIONS An ideal solution is simply defined as a mixture of chemical components with its thermodynamic property related to the linear sum of each pure species thermodynamic property (Equation (1)). A common example is a solution which obeys Raoult’s law. This law states that the total pressure of a system is a linear combination of the component’s vapors pressure at the system’s temperature, provided that the total pressure is less than 5 atm. In order to derive Raoult’s law, we start from Equation (5) and assume that the liquid solution is ideal: (16) If Equation (16) is written for component i in both the liquid and vapor phases, we have: (17)

(18) where

and PP are the fugacity of species i in the vapor mixture and the

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total pressure, respectively. From the thermodynamic equilibrium criteria, if the two phases of liquid and vapor are in a state of equilibrium, then: (19) After substitution of Equations (17) and (18) into Equation (19), we get: (20) If Equation (19) is written for the case of pure component i in liquid phase at equilibrium with its vapor phase, then: (21) By comparing Equations (20) and (21), it yields:

(22) Equation (22) is simplified to: (23) Now, if the liquid and vapor mixtures are assumed to be ideal, then the fugacity values can be substituted by their corresponding pressure and thus: (24) Pi is called the partial pressure of species i in the vapor mixture and denotes the pure vapor pressure of the component i at the solution temperature.

Ideal Solution Mixtures: VLE Phase Behavior In order to calculate the properties of a system of components that obey Raoult’s law, Equation (24) is written for each of the species present in the solution,

(25)

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and by simplification:

(26) by which the solution equilibrium temperature can be found. As we know, the vapor pressure of each species is temperature-dependent and by having the mole fraction of the components in the liquid phase, one can find the temperature which corresponds to the total pressure of the system. This problem can be solved quickly using a spreadsheet and by changing the solution temperature until Equation (26) is satisfied. Sometimes, the temperature of the solution is known and the total pressure needs to be calculated, which is a straightforward calculation from Equation (26). This way, there is no need to use the nonlinear solvers to find the temperature. There are two examples of the binary systems which exhibit negative deviation from Raoult’s law.

Figure 2: T-x-y diagram for the binary systems of hexane-benzene (left) and ethyl acetate-benzene (right) at a pressure of 101.33 kPa.

In order to better demonstrate whether a system follows Raoult’s law, a diagram of the phase equilibrium called T-x-y should be plotted. This plot (Figure 2) shows the equilibrium temperatures at which either a liquid solution will start bubbling (bubble curve) or a vapor mixture starts condensing (dew curve). The two systems with their experimental data and the calculation curve of the ideal solution is shown in Figure 2. In Figure 2, the system of hexane-benzene at the pressure of 101.33 kPa [10] and the system of ethylacetate-benzene [11] show negative deviations from Raoult’s law.

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If one is interested in finding the bubble and dew curves for an ideal solution at low to moderate pressures, then: • Bubble point From Equation (26), by knowing the mole fraction of each component in the liquid phase, two cases are possible: •

Pressure known. If the total pressure of the system is given, then Equation (26) should be solved for the temperature (if the vapor pressure follows Antoine’s law): (27)

•

• •

Temperature known. For this case, the problem is straightforward. The vapor pressure of each species can be found readily from Antoine’s equation and then inserted into Equation (27) to find the total pressure. Dew point Pressure known. If Raoult’s law is isolated for the mole fraction of the species in the vapor phase, then:

(28) by taking the sum for all the components in the liquid phase and knowing that the sum of the mole fractions in a phase is 1, we get:

(29) If the total pressure is known, then Equation (29) should be solved for the temperature which determines the vapor pressure of each of the species in the mixture. •

Temperature known. In this case, Equation (29) is isolated for the Ptot to find the total pressure of the system:

(30)

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which has a straightforward solution.

Ideal Solution Mixtures: SLE Phase Behavior For a solid-liquid equilibrium behavior, Equation (13) for the ideal solution (in which γs=1) is simplified to:

(31) From Equation (31), one can find the mole fraction (or what is called solubilityin the case of SLE) by inserting the appropriate values for the enthalpy of fusion, ΔHfus, melting temperature, Tm, and the solution temperature, TT. It can be found from this equation that for any solvent, the solubility of a solid will be the same regardless of the nature of the solvent. For very few cases, this assumption might be correct; however, for most of the practical and common applications, the above formula does not work well. Therefore, a term accounting for the nonideality of the system should be added to Equation (31).

NONIDEAL SOLUTIONS Almost all real VLE or SLE systems show nonideality. Equations that predict the behavior of different phase equilibria are divided into two: •

Equations of state (EOS) that are useful to predict the nonideal behavior of the vapor phase • Equations which are applied to the liquid phase to predict the nonideal behavior of the liquid solutions We focus on the thermodynamic models that deal with the liquid mixtures in this chapter. From the two categories of activity coefficient models, the correlative one is not very useful for solubility prediction and solvent screening purposes. The main reason for this is the lack of experimental data for the binary interaction parameters of the solute-solvent, soluteantisolvent, and solvent-antisolvent systems. As an example, the activity coefficient from Wilson’s equation of state is found from Equations (14) and (15). It can be seen that for obtaining the activity coefficient of a component 1 in a pure solvent 2, we need four interaction parameters ( , which are temperature dependent. It is evident that for calculating the value of the binary interaction parameters, additional experimental data, such as

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molar volume is needed. Other models which belong to the first category have the same limitations as Wilson’s method. The Wilson model was used in the prediction of various hydrocarbons in water in pure form and mixed with other solvents by Matsuda et al. [11]. In order to estimate the pure properties of the species, the Tassios method [12] with DECHEMA VLE handbook [13] were used. Matsuda et al. also took some assumptions in the estimation of binary interactions (because of the lack of data) that resulted in some deviations from the experimental data. From the predictive category, we bring some examples of the application of the UNIFAC model. In one study, this model has been used to predict the solubility of naphtalene, anthracene, and phenanthrene in various solvents and their mixtures [8]. They showed the applicability of the UNIFAC model in prediction of the phase behavior of solutes in solvents. There have been efforts to make the UNIFAC model more robust and powerful in the prediction of phase behaviors [14]. In one study, the solubility of buspirone-hydrochloride in isopropyl alcohol was measured and evaluated by the modified UNIFAC model [15]. It was concluded that for highly soluble pharmaceutics, the modified form of the UNIFAC model was not suitable. In another study, the solubility of some chemical species in water and some organic solvents was predicted by the UNIFAC model [16]. For some unknown functional groups, they used other known groups which had chemical structures that were similar to unknown ones. In conclusion, it was stated that the UNIFAC model is not a proper model for use in crystallization and related processes. The UNIFAC model also has been utilized to predict the solubility of some aromatic components as well as long-chain hydrocarbons [17]. The results showed that the predictions for the linear hydrocarbons are not as good as the ones for the aromatics. Chen et al. developed the NRTL-SAC model in 2004 [9]. One of the main reasons for developing this model was to enhance the predicting capability of the solubility of complex chemical molecules with functional groups that were not included in the UNIFAC model. Also, in some cases, the UNIFAC group addition rule becomes invalid [2]. One of the main advantages of the NRTL-SAC model in comparison to the other predictive methods is its ability to predict organic electrolyte systems [18]. The UNIFAC method identifies the molecule in terms of its functional groups, while the NRTLSAC model divides the whole surface of the molecule to four segments. The hydrophobic segment (X) denotes parts of the molecule surface which don’t participate in forming a hydrogen bond, such as hexane. The polar segments (Y- and Y+) do not belong to either hydrophobic or hydrophilic segment. The

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polar attractive segment (Y-) shows attractive interaction with hydrophilic segment, while the polar repulsive segment (Y+) has repulsive characteristic with hydrophilic segment. Hydrophilic segment (Z) contributes to the part of the molecule which tends to form a hydrogen bond, such as water. Based on the interaction forces between the molecule surfaces, the four segments of the NRLT-SAC model have been identified. The three reference solvents mentioned before were used to determine the rest of chemical components’ segment numbers [9]. As an example, the VLE and LLE data containing the component of interest in binary mixtures with hexane, water, and acetonitrile were collected and then used in order to find the segment numbers of the component. Sheikholeslamzadeh et al. have investigated various industrial case studies to show the applicability of the NRTL-SAC in processes consisting of solvent mixtures [19]. The segment numbers for each of the nonreference solvents are found from the nonlinear optimization methods which minimize the deviation from the model output and the experimental data for the whole range of data (VLE and LLE). Most of the solvents have some segment numbers that are high in value compared to other segment numbers. The reason is that it is less probable that a chemical component collects all four segments at the same level of value. Currently, more than a hundred solvent segment numbers have been evaluated and optimized which can be found in some commercial simulation packages. The two important predictive equations of UNIFAC and NRTL-SAC, as representatives of the activity coefficient models, are presented here.

UNIFAC Model In general, the activity coefficient models of the predictive category split the activity coefficients into two segments: •

A part that includes the contribution of the chemical structure and the size of a compound (combinatorial part) • The second part that includes the contribution of the functional sizes and binary interaction between pairs of the functional groups (residual part) With the above definition, the total activity of a component in the solution is the sum of the two parts: (32) In which γi is the activity coefficient of component i in the solution, is the combinatorial part and is the residual part. Up to this point,

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all of the group contribution and activity coefficient methods (i.e. NRTLSAC) have been the same, but the methods in which the activities have been calculated are different. In the UNIFAC model, the combinatorial part for component i is found from the following equation [8]:

where

(33)

(34) z is the coordination number and is taken to be 10. In Equation (33), ϕi is the segment fraction and θi is the area fraction of component i and is related to the mole fraction of species i in the mixture:

(35)

(36) qi and ri are the pure component surface area and volumes (van der Waals), respectively. These parameters are not temperature-dependent and are only functions of the chemical structure of a functional group. In the UNIFAC model, for every functional group, there is a unique value for surface area and volume that can be found in common texts and handbooks [1]. The first step in modeling the UNIFAC for a specific binary or ternary system is to break down the chemical structure of a molecule into the basic functional groups. As it is suggested in thermodynamic textbooks [19], the optimum way of breaking it down is the one which results in the minimum number of subgroups, and with each subgroup having the maximum replicates. The qi and ri can be found from Equations (37) and (38):

(37) (38) is the number of subgroup k in component i. The residual part of the

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UNIFAC is found from the equation below:

(39) In Equation (39), Γk is the residual activity coefficient of subgroup k in the mixture and is that value in a pure solution of the component i. This term is added so when the mole fraction approaches unity, the term tends to . The residual activity coefficient of subgroup k in a solution is zero given by

(40) Equation (40) is also applicable to the case of , in which the parameters of the right-hand side of the equation are written based on the pure component i. θm is the area fraction of the functional group m in the mixture:

(41) Xm is the mole fraction of subgroup m in the mixture. ψnm is the group interaction parameter between groups n and m and is dependent on the temperature:

(42) The group interaction parameter anm is found from the large sets of VLE and LLE data in the literature, which are tabulated for many subgroups. It is worth noting that anm≠amn. There are some modifications to the original UNIFAC equation in order to make the model robust for some complex systems. In the UNIFAC-DM method, the modification is made on the combinatorial part:

(43)

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In which the term

is defined as

(44)

Figure 3: The algorithm of converging to the solubility of a ternary system using the UNIFAC model.

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The algorithm for finding the solute solubility in the mixture of ternary solution (solvent/cosolvent/solute) is shown in Figure 3. The algorithm starts with known values, such as the physical properties of the solute. After making an initial guess for the solubility, the program obtains the activity coefficients and the new solubility is found and is compared with the old value and the calculations are repeated to converge to a unique value for solubility. This procedure is done for all the experimental data points.

Nonrandom Two-liquid Segment Activity Coefficient (NRTLSAC) According to Chen et al. [9], the NRTL-SAC model is based on the derivation of the original NRTL model for polymers. From Equation (32), the activity coefficient is made up of two terms, combinatorial and residual. Like the UNIFAC model, the activity coefficients must be generated in order to obtain solubility. In the NRTL-SAC model, the combinatorial part is calculated by Equation (45):

(45) With the definitions: (46)

(47) where xi is the mole fraction of component i, rm,i is the number of segment m, ri is the total segment number in component i, and ∅i is the segment mole fraction in the mixture. The residual term is defined as

(48) , which are the acIn Equation (48), there are two terms, tivity coefficients of segment m in solution and component i, respectively. The two mentioned terms are found using Equations (49) and (50):

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(49)

(50) In the two above equations, l is referred to as the component and j, k, m, and m′ are referred to the segments in each component. xj,l is the segmentbased mole fraction of segment species j in component l only. The mole fractions of segments in the whole solution and in components are defined as below: (51)

(52) Gi,j and τi,j are the local binary values which can be related to each other based on NRTL nonrandom parameter αijαij, and are shown by their values in Table 1. Gi,j and τi,j have the following relation: (53) Therefore, from fixed values of τi,j and αi,j one can find Gi,j. The segment numbers for the common solvents can be found from the literature [20]. After putting the values of segments for solvents and initial guess values for the solute segments, the written code for NRTL-SAC starts solving for the mole fractions at saturation for all of the species in the solution (see Figure 3).

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Figure 4: Algorithm flowchart for parameter estimation using NRTL-SAC model.

It is worth noting that the main difference in Figures 3 and 4 is the use of parameter estimation method for the calculation of the NRTL-SAC parameters, while for the UNIFAC model, the calculation is straightforward. Once the parameters (here, the segment numbers) are found, then they could be used for validation against other experimental data.

APPLICATION OF SOLUTION THERMODYNAMICS IN INDUSTRY One of the main applications of the thermodynamic models is in the chemical industries which use solvent (or their mixtures) [19-22]. Two cases of the vapor-liquid equilibrium of common industrial solvent systems are discussed here.

VLE Study of Two Binary Azeotropic Systems There are some solvents within the chemical and pharmaceutical industries

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which are of importance to study, such as ethanol, isopropyl alcohol, and water in addition to some aromatic components, such as benzene and toluene. These solvents are sometimes used as additives to other valuable chemicals to maintain some performances or enhance their physical or chemical properties. The systems that form azeotropes make the distillation process calculations complex. As a result, having an accurate knowledge about the phase behaviors of such systems are important (such as tolueneethanol or toluene-isopropyl alcohol). The four case studies of the VLE data for the mentioned azeotropic binary systems were used in a study by Chen et al. [24]. The operating pressures were at four distinct levels for the calculations. They have used three equations of state (from the correlative group) to fit the experimental data with the model outputs and found the necessary binary interaction parameters. Based on their work, the estimated parameters were found; however, they were not used to further validate the models for other operating conditions. In a study by Sheikholeslamzadeh et al., they used the NRTL-SAC and UNIFAC models to predict these azeotropic systems [20]. Table 1 (from their work) shows average relative deviation for the compositions and temperature for the two systems. It is seen from the table that the deviations from the experimental data in the vapor phase mole fractions are almost one-third relative to the NRTL-SAC model. On the other hand, the relative deviation for the saturation temperature is higher using the NRTL-SAC model. Another fact from this finding is that the deviations for both binary systems when the NRTL-SAC model is used are nearly the same. This is not the case when utilizing the UNIFAC model to predict the systems’ behaviors. The final conclusion from Table 1 would be the better predictive capability of the UNIFAC model for light alcohols than the heavier ones. Table 1: The results of the prediction using the NRTL-SAC and UNIFAC models with the experimental values of Chen et al. [20,24] Thermodynamic model

NRTL-SAC UNIFAC

Pressure, (kPa)

%ARD (equilibrium temperature and vapor-phase mole fractions) Temperature, (K)

Ethanol

Toluene

Temperature, (K)

2-Propanol

Toluene

101.3

0.46

5.14

9.81

0.41

4.91

7.19

201.3

0.64

7.63

9.72

0.66

7.76

9.77

101.3

0.10

1.08

3.15

0.22

2.04

3.87

201.3

0.27

2.03

3.47

0.36

3.43

5.40

System 1

System 2

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Figure 5: The results for the systems (A) ethanol-toluene at 101.3 kPa, (B) ethanol-toluene at 201.3 kPa, (c) isopropyl alcohol-toluene at 101.3 kPa, and (D) isopropyl alcohol-toluene at 201.3 kPa [20].

VLE Study of a Ternary System With the increasing prices of fossil fuels, the demand to obtain alternatives has received much attention. One of the candidates for this purpose is ethanol, as it decreases the air pollution when blended to the conventional fossil fuels and thereby, increasing the performance of burning fuels within the vehicle engines. It would also be cost-effective when adding other lowprice additives to the fuel. The higher the purity of the alcohol being used as additive, the better the performance of the fuel. It was found that the addition of glycols to the mixture containing alcohols and water can improve the separation processes and utilize less energy to perform the process [25,26]. The experimental data containing the ternary system of ethylene glycolwater-ethanol and the performance of separation by varying the glycol concentration were performed by Kamihama et al. [27].

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Figure 6: VLE diagrams of the systems (A) ethanol-water, (B) ethanol-ethylene glycol, and (C) water-ethylene glycol at 101.3 kPa [20].

They performed binary system experiments for each of the pairs in the ternary system. It was found that glycol can move the azeotrope point and therefore, enhance the separation process. Sheikholeslamzadeh et al. have used both the NRTL-SAC and UNIFAC models to perform phase calculations and assess the capacity of the mentioned models in the prediction of binary and ternary systems containing glycol and alcohols [20]. From Figure 6, the UNIFAC model has the capability of predicting the system of ethanol-water, perfectly. However, this is not the case for the systems using ethylene glycol-water and ethylene glycol-ethanol. On the other side, the NRTL-SAC model gave satisfactory results for all three binary system, specifically, the systems that contain ethylene glycol. Also from Figures 6B and 6C, it can be seen that for nonazeotropic systems, the NRTL-SAC model could best show capability in prediction comparable to the UNIFAC model. The UNIFAC model could best locate the azeotrope point and the VLE behavior of the ethanol-water system.

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For the ternary system of solvents consisting of ethanol, water, and ethylene glycol, Kamihama et al. [27] conducted the vapor-liquid measurements at a pressure 101.3 kPa. In order to use the correlative models (such as Wilson) for the ternary system, the binary interaction parameters should be known for each pair of components in the mixture at that temperature and pressure. They used this method to find the ternary behavior of the system. Sheikholeslamzadeh et al. used the NRTL-SAC model with the four conceptual segments of each solvent, which were already accessible in the literature [9, 18]. The results showed the high performance of the NRTL-SAC model in the prediction of this ternary system. The bubble point temperature as well as the vapor and liquid compositions could be estimated fairly well with the NRTL-SAC model. The predicted results are shown in Figure 7, giving the vapor phase mole fractions of the three species as well as the mixture temperature. It is apparent that the deviation from the experimental data for the case of water and ethanol in this ternary mixture is almost zero. The UNIFAC model could not match the experimental data as well as the NRTL-SAC model. For the ethylene glycol, as the experimental concentrations of the vapor phase are very small, with the inclusion of errors of the experimentation, the NRTL-SAC model could also give satisfactory results. Finally, for the bubble point temperature, Figure 7 illustrates the perfect predictions of the NRTL-SAC model compared with the UNIFAC model. The average relative deviation for the whole set of experimental data on the saturated temperature from the NRTL-SAC model is one-third that from the UNIFAC model.

Figure 7: Vapor phase mole fractions of ethylene glycol (bottom-left), ethanol (top-left), water (top-right), and the bubble temperature (bottom-right) prediction from the NRTL-SAC model [20].

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CONCLUSION There are several equations of state that describe the phase behavior of chemical components of a system at various temperatures, pressures, and compositions. From these models, the first group which needs various experimental data to predict the system behavior at other conditions is not very attractive. Instead, the second group (predictive models) is based on the activity coefficients that are found from the molecular structures with a few experimental data. In this chapter, the capacity of handling two binary and ternary systems of solvents using those predictive models was assessed. The NRTL-SAC and UNIFAC models were chosen for the modeling of those systems. The NRTL-SAC model showed relative advantage over the UNIFAC model in almost all cases, except for the systems containing light alcohols with water. The preference of using NRTL-SAC is due to its simplicity compared to the UNIFAC. If the four segment parameters of a specific component are known, then they can be set as a unique value for that component irrespective of the mixture conditions. This way, various operating conditions can be defined and the phase behavior of the components can be predicted accurately and rapidly. One of the main advantages of the NRTL-SAC model is that it can be written in various computer programming languages to be used in process simulation analysis. One good example of such work can be found in Sheikholeslamzadeh et al. [19,21]. They used the NRTL-SAC model to find the solid-liquid equilibrium for three pharmaceuticals. Then, the parameters they optimized for the given pharmaceuticals were used further to perform a solvent screening method. This method is really costly and time-consuming in industry. The authors [19,20] have developed an algorithm to find the best combination of solvents, temperatures, and pressures for the best yield of pharmaceutical production using the NRTL-SAC model. In conclusion, the NRTL-SAC model and other similar ones open a new window for the engineers and scientists to have a wider, more accurate, and rapid predictions of the solubility of active pharmaceuticals in mixtures of solvents.

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Engineers, Wash‐ ington, DC, November 1969. J. Gmehling and U. Onken. Vapor-Liquid Equilibrium Data Collection. DECHEMA, Franckfurt/Main, 1977. U. Weidlich, J. Gmehling. A modified UNIFAC model. 1. Prediction of VLE, hE. Ind. Eng. Chem. Res., 1987, 26 (7), pp 1372-1381. M. Sheikhzadeh, S. Rohani, M. Taffish, S. Murad. Solubility analysis of buspirone hy‐ drochloride polymorphs: Measurements and prediction. Int. J. Pharm. 338 (2007) 55-63. S. Gracin, T. Brinck, and A. C. Rasmuson. Prediction of solid organic compounds in solvents by UNIFAC. Ind. Eng. Chem. Res. 2002, 41, 5114-5124. A. T. Kan and M. B. Tomson. UNIFAC prediction of aqueous and nonaqueous solu‐ bilities of chemicals with environmental interest. Environ. Sci. Technol. 1996, 30, 1369-1376. C. C. Chen and Y. Song. Extension of nonrandom two-liquid segment activity coeffi‐ cient model for electrolytes. Ind. Eng. Chem. Res. 2005, 44, 8909-8921. Ehsan Sheikholeslamzadeh and Sohrab Rohani. Solubility prediction of pharmaceuti‐ cal and chemical compounds in pure and mixed solvents using predictive models. Ind. Eng. Chem. Res. (2011) 51, 464-473. Ehsan Sheikholeslamzadeh and Sohrab Rohani. Vapour-liquid and vapour-liquidliquid equilibrium modeling for binary, ternary, and quaternary systems of solvents. Fluid Phase Equilibria, 333, 97-105. Ehsan Sheikholeslamzadeh, Chau-Chyun Chen, and Sohrab Rohani. Optimal solvent screening for the crystallization of pharmaceutical compounds from multisolvent systems. Ind. Eng. Chem. Res. (2012) 51, 13792-13802. Ehsan Sheikholeslamzadeh and Sohrab Rohani. Modeling and optimal control of sol‐ ution mediated polymorphic transformation of l-glutamic acid. Ind. Eng. Chem. Res. (2013) 52, 2633-2641. Stichlmair, J., Fair, J., Bravo, J. L. Separation of azeotropic mixtures via enhanced dis‐ tillation. Chem. Eng. Prog. B 1989, 85, 63. Chen, R., Zhong, L., Xu, C. Isobaric vapor-liquid equilibrium for binary systems of toluene + ethanol and toluene + isopropanol at (1013.3, 121.3, 161.3, and 201.3) kPa. J. Chem. Eng. Data. 2011, 57, 155. Pequenín, A., Carlos Asensi, J., Gomis V. Isobaric vapor−liquid−liquid

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equilibrium and vapor−liquid equilibrium for the quaternary system water−ethanol−cyclohexane −isooctane at 101.3 kPa. J. Chem. Eng. Data, 2010, 55, 1227. 26. Pequenín, A., Carlos Asensi, J., Gomis V. Experimental determination of quaternary and ternary isobaric vapor-liquid-liquid equilibrium and vapor-liquid equilibrium for the systems water-ethanol-hexane-toluene and water-hexane-toluene at 101.3 kPa. J. Chem. Eng. Data, 2010, 56, 3991. 27. Kamihama, N., Matsuda, H., Kurihara, K., Tochigi, K., Oba, S. Isobaric vapor-liquid equilibria for ethanol + water + ethylene glycol and its constituent three binary sys‐ tems. J. Chem. Eng. Data. dx.doi. org/10.1021/je2008704.

12 Bismuth Telluride Solubility Limit and Dopant Effects on the Electronic Properties of Lead Telluride

Dana Ben-Ayoun and Yaniv Gelbstein Department of Materials Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel

ABSTRACT The demand for energy efficiency has motivated many researchers to seek for novel methods capable of enhancing the conversion of heat to electricity. Most of the recently published methods for thermoelectric (TE) efficiency enhancement discuss on the reduction of the lattice thermal conductivity, with a minor focus on improved electronic optimization. This is attributed mainly to the fact that the electronic properties are correlated and opposing Citation: Dana Ben-Ayoun and Yaniv Gelbstein (April 12th 2019). Bismuth Telluride Solubility Limit and Dopant Effects on the Electronic Properties of Lead Telluride [Online First], IntechOpen, DOI: 10.5772/intechopen.84602. Copyright: © 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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each other upon increasing the carrier concentration. It has been reported that the system of PbTe-BiTe has potentially high TE performance; this chapter is focused on a detailed investigation of the co-effect of bismuth as an effective electronic dopant and at the same time, as a second phase promoter in the PbTe matrix. (PbTe)x(BiTe)1−x alloys were thermoelectrically examined and the values were analyzed analytically by the general effective media (GEM) approach. Keywords: Thermoelectric, PbTe, BiTe, solubility, GEM

INTRODUCTION In the past decades, global climate changes, caused by combustion of fossil fuels and greenhouse gases emission, became a major environmental concern, accompanied with the dilution of conventional energy resources, raising the need for a renewable energy alternatives. Thermoelectricity dealing with this concern, is based on a direct conversion of waste heat into usable electrical energy; even a partial conversion of this waste heat will get us one step closer toward a cleaner and greener world. This goal has been achieved by thermoelectric converters and successfully initiated by the development of various highly efficient thermoelectric material classes. Such materials require a unique combination of the electrical and lattice properties (Seebeck coefficient (α), electrical resistivity (ρ), electronic thermal conductivity (κe), and lattice thermal conductivity (κl)), enabling the highest possible thermoelectric figure of merit values ZT = α2T/[ρ(κe + κl)], where T is the absolute temperature, for achieving significant conversion efficiencies. Since the electronic properties are strongly interdependent and follow opposite trends (𝛼 and 𝜌 are decreased, and κe is increased) upon increasing the carrier concentration, most of the published studies were mainly focused on applying advanced nano-structuring approaches for κl reduction. In the case of IV–VI-based chalcogenides and their alloys (known as among the most efficient thermoelectric alloys for intermediate working temperatures of up to 600°C) such nano-structuring approaches resulted in a significant increase of ZT up to ~2.5, due to an effective scattering of phonons without adversely affecting the electronic properties [1]. Yet, it is worth mentioning that such approaches already succeeded in reaching ultralow thermal conductivity [2], lightening the fact that other approaches, related to electronic optimization of chalcogenides for further enhancement of ZT, are

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still required. Among the IV–VI-based chalcogenides, lead telluride is one of the most commonly used thermoelectric materials, but the maximal ZT achieved is only ~0.8 [3] which is still insufficient for converters in widespread industrial use. While thermoelectric properties are dependent on the carrier concentration, materials with carrier concentration higher than 1019 cm−3 are required. For undoped lead telluride, the change in the carrier concentration and carrier type is obtained by a method that enables the stoichiometry to be changed through thermal annealing in a Pb-rich (for n-type conductivity) or Te-rich (for p-type conductivity). One of the key methods for optimizing the electronic properties of these materials is by adding doping elements to the melt, while the most universally recognized lead telluride dopant is bismuth; it allows obtaining such carrier concentrations that can provide applicative values of thermoelectric conversion efficiency. The thermoelectric properties of the compounds in the system have been investigated, the processes taking place upon increasing the dopant concentration was also studied, but such researches were mainly focused on compositions within the solid solution up to the theoretical solubility limit [4, 5]. This present work, considering our synthesis process, investigates the bismuth effects in the matrix, beneath and beyond the solubility limit, as an effective electronic dopant yet at the same time, as a second phase promoter in the PbTe matrix. Moreover, to the best of our knowledge, most of the previous researches did not investigated the individual electronic contributions of the involved secondary phases embedded in the matrix on the effective thermoelectric transport properties. The general effective media (GEM) approach [6] enables to estimate the transport properties based on experimentally measured properties of each of the involved phases. Since the approach is taking into consideration geometrical aspects, it can be utilized for maximizing the thermoelectric figure of merit of composite materials by artificial alignment of the embedded secondary phase in the composite. Figure 1a shows the high potential of compositions with low amount of bismuth content, in the vicinity of the solubility limit, to attain high absolute Seebeck coefficient values. Figure 1b, demonstrates the potential to enhance the thermoelectric conversion efficiency while considering the co-effect of bismuth as an electronic donor dopant and as a secondary phase promoter in PbTe.

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Figure 1: (a) Bismuth concentration dependence of the room temperature Seebeck coefficient, α, scheme demonstrating the interstitial to substitutional pattern dissolution limit (at ~0.3%) which continues with the GEM calculations for two phase composites consisting an increasing amount of embedded metallic secondary phase. (b) The enhancement of the figure of merit, ZT, in the system along most of the temperature range required for practical operation.

EXPERIMENTAL Three (PbTe)x(BiTe)1−x alloys, with different x values (Table 1), were synthesized from pure elements (5 N), mixed in the right stoichiometric ratio, and sealed in evacuated quartz ampoules under vacuum of 10−6 Torr. The ampoules were placed in a rocking furnace (Thermcraft Inc., Winston Salem, NC, USA) at 1000°C for 15 minutes, then water quenched. The cast ingots were milled to a maximal powder particle size of ~250 μm using agate mortar and pestle. The sieved powder was hot pressed (HPW5 Hot Press, FCT System GmbH, Rauenstein, Germany) under a mechanical pressure of 21 MPa at 730°C for 30 minutes under argon atmosphere, resulting in high density values of >98% of the theoretical density. Table 1: The investigated alloys notations Alloy i ii iii iv

Bi [%at] 5% 1% 0.3% 0.1%

Matrix (PbTe)0.95(BiTe)0.05 (PbTe)0.99(BiTe)0.01 (PbTe)0.997(BiTe)0.003 (PbTe)0.999(BiTe)0.001

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The thermoelectric transport properties of each alloy were measured up to 450°C as follows. The Seebeck coefficient, α, and electrical resistivity, ρ, were determined using the four-point probe method (Linseis LSR-3/800 Seebeck coefficient/electrical resistance measuring system). The thermal diffusivity, γ, was determined using the flash diffusivity method (LFA 457, NETZSCH). The total thermal conductivity, κ, was calculated using κ = γ·CP ·δ, where CP is the specific heat which was determined using differential scanning calorimetry (DSC 404, NETZSCH), and δ is the density of the sample measured using Archimedes method. The crystal structure of the alloys was analyzed by X-ray powder diffraction (Rigaku DMAX 2100 powder diffractometer). The microstructure of the alloys was observed using scanning electron microscopy (SEM, JSM5600, JEOL, Akishima, Japan) equipped with a backscattered electron detector. The chemical composition was measured using an energydispersive X-ray spectroscopy (EDS).

RESULTS AND DISCUSSION PbTe has a NaCl cubic crystal structure with space group Fm-3m, melts congruently at 924°C [7]; BiTe has a BiSe trigonal crystal structure with space group P-3m1, consists of 12 close-packed layers along the c axis, melts at 540°C [8]. As can be seen by the XRD diffractogram presented in Figure 2a, the reflections are all belong to the lead telluride matrix in the rock salt structure, with no evidence of other phase’s peaks. A reason for that might be that the amount of the second phase precipitants detected in the SEM analysis (Figure 3a and b) is clearly less than the detection limit of the XRD analysis.

Figure 2: (a) XRD diffractogram of the investigated i, ii, iii, and iv alloys and

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(b) a magnification of the (420) reflection at ~64°, indicating a volume decrease upon increasing the bismuth content.

Figure 3: BSE-SEM micrographs of the investigated (a) i, (b) iii, and (c) iv alloys indicating in the inset the compositional modulations.

As shown in Figure 2b, with increasing the bismuth content in the lead telluride matrix, the peaks are constantly shifted toward higher angles, reflecting a constant decrease in the lattice parameter. This may be related to the fact that Bi3+ has lower ionic radius (1.03 A [9]) compared to the ionic radius of Pb2+ (1.19 A [9]), while bismuth substitutes lead in the NaCl structure. Moreover, it is well known that introducing bismuth to the PbTe matrix creates cation vacancies, which might also contribute to the decrease in lattice parameter while releasing internal stresses/lattice strains. Although broadening of the peaks due to lattice internal stresses caused by bismuth interstitial atoms would be expected, it was not observed in the investigated samples, probably due to the fact that the amount of bismuth at alloy iv is too small to affect the lattice. Back-scattered electrons SEM micrographs of the investigated alloys are presented in Figure 3a–c. In Figure 3a of the investigated alloy i, compositional modulations reveal bright bismuth precipitants along with precipitants composed of several compositions. Since the contrast in backscattered electrons SEM micrographs is correlated directly to its atomic number, it is obvious that the brighter the phase, the more bismuth it contains; thus, the precipitants contain a PbBiTe ternary phase surrounded by a brighter bismuth-rich phase. In alloy iii, PbBiTe ternary phase precipitant can be also detected (Figure 3b). The exact composition of the ternary phases, in both samples, could not be defined using EDS analysis. For alloy iv, a single-phase matrix, without any precipitant was detected, indicating a full solubility of the elements as can be seen in the representative micrograph in Figure 3c.

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The logic behind this is that, at alloy iv, the dissolution pattern is by interstitial occupation mechanism. It is assumed that bismuth occupation in interstitial sites is less preferred with increasing the bismuth content (iii) → (i), and the dissolution pattern changes to a substitutional pattern (in line with XRD diffractograms shift, described above); the tendency to participate as a second phase is growing and its effect on the transport properties can be explained by the percolation theory as described by Rogacheva et al. [10]. Upon increasing the bismuth content, percolation passages are formed, causing spatial redistribution of the impurity atoms by self-interaction. By further introduction of bismuth to the matrix, bismuth clusters are formed. Taking the above into consideration, it is reasonable to assume that with increasing the amount of bismuth impurity in the matrix, the probability to form pure bismuth precipitants is growing. Moreover, the high number of ternary compounds existing in bismuth rich PbBiTe system [11], is an indication of a relatively easy restructuring of the lattice. We assume that the precipitant modulations observed might be a result of complexes formation whose composition corresponds to the composition of intermediary phases [10]. Overall, the system is influenced by the percolation effects, and goes through intermediate processes of complex and intermediate structure formations, that can give a reasonable explanation for the observations. The Seebeck coefficient α, electrical resistivity ρ, thermal conductivity κ and figure of merit ZT, for the investigated alloys are presented in Figure 4a–d.

Figure 4: Temperature dependence of (a) Seebeck coefficient, (b) electrical

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resistivity, (c) thermal conductivity, and (d) the thermoelectric figure of merit for the investigated i, ii, iii, and iv alloys.

The Bi3+ tendency to substitute Pb2+ creates one free electron, a fact which obviously affect the electronic properties of the materials. The Seebeck coefficient at room temperature for alloy i (−55 μVK−1) indicates the large amount of bismuth introduction to the PbTe matrix; the precipitants acting as a secondary metallic phase, enhancing the carrier concentration. Decreasing the bismuth concentration (alloys ii and iii) resulted in a gradual improvement of the Seebeck coefficient (−140 and −200 μVK−1, respectively); a dramatic expected change when considering the decreased metallic secondary phase amount. By further decreasing the bismuth content (alloy iv), the absolute Seebeck coefficient decreased (−135 μVK−1). As can be seen in Figure 3c, there is full solubility of bismuth in the PbTe matrix; considering that fact, the reason for the unexpected behavior of Seebeck coefficient might be plant in the dissolution pattern changes as a function of bismuth content. As described above, at low amounts of bismuth, as in alloy iv, the dissolution pattern changed to interstitial pattern, where the bismuth electronic activity is relatively low. In that context, a maximum in the absolute Seebeck coefficient values can be reached in the vicinity of the bismuth concentration of alloy iii, where the threshold for the substitutional dissolution pattern is reached and it changes to interstitial pattern. A similar trend observed in Figure 4b, from (i) → (iii), can be seen in the electrical resistivity values. This behavior supports the theory above and is attributed to the increased metallic contribution of the precipitates. Yet, one must keep in mind that bismuth impurities and precipitants cause defect formation in the crystal lattice which consequently scatter the charge carriers and increase the electrical resistivity. While comparing alloy ii and iv, the increased electrical resistivity in alloy ii is attributed to the low mobility due to charge carriers scattering. Moreover, the overlapping between the curves of alloys i and iv is attributed to the fact that in alloy i the charge carrier concentration is relatively high compared to alloy iv, while at the same time, in alloy i the mobility of the charge carriers is relatively low compared to alloy iv. In the last case, these two effects compensate each other and overall, they are affected by the bismuth both as a donor and as a precipitant initiator. Since the thermal conductivity is affected both by bismuth as an effective electronic donor, but also as a phonon scatter source, both contributions were analyzed. The electronic contribution to the thermal conductivity, as shown in Figure 5a, was analyzed using Wiedemann-Franz relation, κe = L ρ−1 T,

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where L is the Lorentz constant equal to 2.45 10−8 WΩK−2 calculated in a previously described procedure [12], ρ is the measured electrical resistivity (Figure 4b), and T is the absolute temperature. κe values follow the expected similar but opposite trends to the ρ values. The lattice contribution to the thermal conductivity, as shown in Figure 5b, was calculated by subtracting the calculated κe out of the measured κtot (Figure 4c); the gradual change in the κlas a function of bismuth content is associated with the cation vacancies described before for iv, and continues with increased lattice defects, created by the gradually phase separation observed in Figure 3a–b, acting as a phonon scattering source. The overlapping curves can be explained by the fact that the phase separation shown in iii (Figure 3b) is minor thus might affect κl in a very small manner, within the measurement error of the curves. Overall the results indicate a reduction of ~20 and ~44% upon increased doping compared to pristine PbTe.

Figure 5: Temperature dependence of the (a) electronic contribution and (b) lattice contribution to the thermal conductivity of the investigated alloys.

It is noted that the dominant thermal conduction mechanism is a bit different between the alloys. While alloys i and iv are affected by both lattice and charge carrier thermal conductions in the same manner, since their contributions are in the same order of magnitude, alloys ii and iii charge carrier thermal conduction is very low. This fact opens a window of opportunities for a possible further ZT enhancement by reducing the precipitants (observed in Figure 3b) size into the nano-scale for reduction of κl. While combining both the thermal and electrical contributions to the thermoelectric efficiency (Figure 4d) it can be concluded that at 450°C, ~40% improvement compared to pristine PbTe was obtained; improvement that is attributed to an optimization between both bismuth contributions as

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an effective electronic dopant and as a second phase initiator. In order to further investigate the electronic contribution of the secondary phase due to the geometrical morphology and amount, the general effective media (GEM) approach was applied [6]. The effective thermoelectric transport properties, for composite materials consisting of two separate phases, were calculated based on the effective thermal conductivity, κeff, and effective electrical resistivity, ρeff, calculated using Eq. (1) and the effective Seebeck coefficient, αeff, using Eq. (2) [13]. (1)

(2) Where α1, ρ1, κ1 represent the secondary phase embedded in the matrix; α2, ρ2, κ2, represent the matrix; x1 and (1 − x1) represent the relative amounts of each of the phases; t represent the homogenous level of distribution of the secondary phase in the matrix, while t = 1 stands for an even distribution [14, 15]; A represents the morphological alignment and ranges from “series” (for A = 0) to “parallel” (for A = ∞∞ ) relative to the electrical potential or temperature gradients, while A = 2 corresponds to a spherical morphology of the secondary phase [14, 15]. By applying the GEM approach to the investigated case of an embedded bismuth secondary phase inside alloy iiimatrix, the applied transport properties were the reported values for pure bismuth (−50 μVK−1 [16], 0.129 mΩ cm, and 7.97 W mK−1 at room temperature [17]) and the experimental data for alloy iii at room temperature (Figure 4a–c). A was chosen to be equal to different morphological alignment conditions, represented by 0, 2, 8 and infinity. Using the above data, the effective thermoelectric transport properties, shown in Figure 6a–d, were calculated. The measured room temperature experimental values for our i and ii investigated alloys, are shown in Figure 6as black stars; taking into consideration the 10% measurement error, they follow the curve which represent infinitesimal A and uneven distribution of the phase (t ≠ 1). The conclusion is in line with Figure 3a–b, where the precipitants location is mainly in the grain boundary, forcing an elongated shape for the most of them.

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Figure 6: Calculated GEM curves at room temperature of (a) effective Seebeck coefficient, (b) effective electrical resistivity and (c) effective thermal conductivity as a function of the embedded bismuth percentage, under different morphological alignment and uneven distribution conditions (t = 0.5).

As been presented in the experimentally measured values (Figure 4a–c), and is in agreement with previously reports, in low amounts of bismuth in the matrix the transport properties are acting abnormally, with regard to the changing pattern of dissolution, up to a point where the dissolution pattern remains steady. Above that level, the GEM evaluation can predict the transport properties in a very reliable way, since the transport properties of the composite are expected to act as a composite with an increasing amount of a secondary metallic phase. In our homogeneous distribution level and morphological alignment conditions, it can be seen that up to 0.1%, a slight change in bismuth concentration is accompanied with a drastic change in the electronic properties of the composite. A drastic degradation in the absolute Seebeck coefficient along with a great improvement in the electrical conductivity, sums up in an increased power factor (α2ρ−1); yet while considering the thermal conductivity increment, the overall room temperature thermoelectric

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efficiency is decreased. On the other hand, the “series” morphological alignment condition at room temperature, exhibits more moderate changes that might allow bigger introduction of bismuth to the matrix, which will reduce the lattice contribution to the thermal conductivity, and at the same time will not affect as drastically the electronic properties. This finding implies on a potential method for enhancing the thermoelectric efficiency by an artificial “series” morphological alignment of the secondary phase which can lead to possible further study. The reason for the small mismatches observed in our GEM calculations, might be related to the fact that the matrix was represented by alloy iii; it is well known that even a slight change in impurity content, affect substantially the transport properties.

CONCLUSIONS The co-effect of bismuth as an effective electronic dopant and at the same time, as a second phase promoter in the PbTe matrix was investigated and explained in details with regard to the dissolution pattern transition. These two effects on the thermoelectric properties were demonstrated and resulted in a ~40% ZT enhancement compared to the pristine PbTe. The GEM analysis of composites with an increased amount of precipitates paved a potential route for further enhancement of the thermoelectric efficiency upon an artificial serial alignment of the embedded secondary phase in the composite.

ACKNOWLEDGMENTS The work was supported by the Israel Science Foundation (ISF) Individual Research Grant No. 455/16. The authors would like to thank Mr. Yair George for the synthesis of the alloys and specimens preparation.

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Hazan E, Madar N, Parag M, Casian V, Ben-Yehuda O, Gelbstein Y. Effective electronic mechanisms for optimizing the thermoelectric properties of GeTe-rich alloys. Advanced Electronic Materials. 2015;1(11):1-7 2. Xu B, Feng T, Agne MT, Zhou L, Ruan X, Snyder GJ, et al. Highly porous thermoelectric nanocomposites with low thermal conductivity and high figure of merit from large-scale solution-synthesized Bi2Te2.5Se0.5 hollow nanostructures. Angewandte Chemie, International Edition. 2017;56(13):3546-3551 3. Komisarchik G, Gelbstein Y, Fuks D. Solubility of Ti in thermoelectric PbTe compound. Intermetallics. 2017;89:16-21 4. Zhu P, Imai Y, Isoda Y, Shinohara Y, Jia X, Zou G. Compositiondependent thermoelectric properties of PbTe doped with Bi2Te3. Journal of Alloys and Compounds. 2006;420(1-2):233-236 5. Christakudi TA, Christakudis GC, Borissova LD. Thermoelectric power of solid solutions (PbTe)1–x(Bi2Te3)x with 0 ≦ x ≦ 0.02. Physica Status Solidi. 1995;190(2):537-544 6. Gelbstein Y. Simulation of morphological effects on thermoelectric power, thermal and electrical conductivity in multi-phase thermoelectric materials. In: Skipidarov S, Nikitin M, editors. Thermoelectrics for Power Generation. London, UK: IntechOpen; 2016. pp. 286-301 7. Noda Y, Ohba S, Sato S, Saito Y. Charge distribution and atomic thermal vibration in lead chalcogenide crystals. Acta Crystallographica Section B. 1983;39(3):312-317 8. Shimazaki H, Ozawa T. BiTe, a new mineral from the Tsumo mine, Japan. American Mineralogist. 1978;63:1162-1165 9. Shannon R. Revised effective ionic radii and systematic studies of interatomie distances in halides and chaleogenides. Acta Crystallographica. 1976;A32:751-767 10. Rogacheva E, Vodorez O, Pinegin V, Nashchekina O. Evidence for selforganization processes in PbTeBi2Te3 semiconductor solid solutions. Journal of Materials Research. 2011;26(13):1627-1633 11. Karpinskii OG, Shelimova LE, Avilov ES, Kretova MA, Zemskov VS. X-ray diffraction study of mixed-layer compounds in the PbTeBi2Te3 system. Inorganic Materials. 2002;38(1):17-24 12. Gelbstein Y, Dashevsky Z, Dariel MP. High performance n-type

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PbTebased materials for thermoelectric applications. Physica B: Condensed Matter. 2005;363(1-4):196-205 Gelbstein Y. Phase morphology effects on the thermoelectric properties of Pb0.25Sn0.25Ge0.5Te. Acta Materialia. 2013;61(5):1499-1507 Bergman DJ, Levy O. Thermoelectric properties of a composite medium. Journal of Applied Physics. 1991;70(11):6821-6833 Webman I, Jortner J, Cohen MH. Thermoelectric power in inhomogeneous materials. Physical Review B. 1977;16(6):2959-2964 Goldsmid H. Bismuth-antimony alloys. Physica Status Solidi. 1970;7:7-28 Khalouk K, Chaib C, Gasser J-G. Electrical and thermal conductivities and Seebeck coefficient of liquid copper-bismuth alloys. Philosophical Magazine Letters. 2009;89(3):249-262

13 Decomposition and Mineralization of Dimethyl Phthalate in an Aqueous Solution by Wet Oxidation

Dar-Ren Ji1, Chia-Chi Chang1, Shih-Yun Chen1, Chun-Yu Chiu2, Jyi-Yeong Tseng1, Ching-Yuan Chang1,3, Chiung-Fen Chang4, Sheng-Wei Chiang5, Zang-Sie Hung1, Je-Lueng Shie6, Yi-Hung Chen7, and Min-Hao Yuan1,7 Graduate Institute of Environmental Engineering, National Taiwan University, Taipei 106, Taiwan 1

Department of Cosmetic Science and Application, Lan Yang Institute of Technology, Yilan 261, Taiwan

2

3

Department of Chemical Engineering, National Taiwan University, Taipei 106, Taiwan

Department of Environmental Science and Engineering, Tunghai University, Taichung 407, Taiwan 4

Chemical Engineering Division, Institute of Nuclear Energy Research, Atomic Energy Council, Lungtan, Taoyuan 325, Taiwan 5

6

Department of Environmental Engineering, National Ilan University, Yilan 260, Taiwan

Citation: Ji DR, Chang CC, Chen SY, et al. Decomposition and Mineralization of Dimethyl Phthalate in an Aqueous Solution by Wet Oxidation. ScientificWorldJournal. 2015;2015:164594. doi:10.1155/2015/164594. Copyright: 2015 Dar-Ren Ji et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Department of Chemical Engineering and Biotechnology, National Taipei University of Technology, Taipei 106, Taiwan 7

ABSTRACT Dimethyl phthalate (DMP) was treated via wet oxygen oxidation process (WOP). The decomposition efficiency η DMP of DMP and mineralization efficiency η TOC of total organic carbons were measured to evaluate the effects of operation parameters on the performance of WOP. The results revealed that reaction temperature T is the most affecting factor, with a higher T offering higher η DMP and η TOC as expected. The η DMP increases as rotating speed increases from 300 to 500 rpm with stirring enhancement of gas liquid mass transfer. However, it exhibits reduction effect at 700 rpm due to purging of dissolved oxygen by overstirring. Regarding the effects of pressure P , a higher P T provides more oxygen for the forward reaction with DMP, T while overhigh P T increases the absorption of gaseous products such as CO2 and decomposes short-chain hydrocarbon fragments back into the solution thus hindering the forward reaction. For the tested P T of 2.41 to 3.45 MPa, the results indicated that 2.41 MPa is appropriate. A longer reaction time of course gives better performance. At 500 rpm, 483 K, 2.41 MPa, and 180 min, the η DMP and η TOCare 93 and 36%, respectively.

INTRODUCTION Phthalic acid esters (PAEs) including dimethyl phthalate (DMP) are major plasticizer to improve the mechanical properties of polymers. These polymers in turn were used for making tableware such as forks, spoons, dishes, cups, and lunchboxes. In fact, the PAEs are added via noncovalent bonding with the polymers. It means PAEs are easily released to the hot soup, heated food, and oily contents from the tableware and are orally ingested daily [1, 2]. PAEs are endocrine disrupter substances (EDSs) too. Their derivatives exhibit the similar structure with endocrine of human and other animals, thus inducing the possibility of cancer of human and the sex development of male. The worst influence of EDSs to the ecosystem would be extinction for endanger species [3, 4]. Although PAEs can be effectively removed from the aqueous phase by adsorption [5] which also has been applied to treat other EDSs [6, 7],

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it needs the regeneration of exhausted adsorbent and the post treatment of concentrated regeneration solution. Activated sludge based biological sewage treatment system needs 20 d to reach 71% mineralization efficiency and is not beneficial to deal with toxic DMP. It was biodegraded to monomethyl phthalate (MMP) and phthalic acid (PA) after treatment of 2.5 d [8–10]. Some advanced solutions were proposed such as photolysis [11–13], photocatalysis [11–15], electrochemical [16, 17], and oxidantadded oxidation [11, 14, 18, 19] methods. Most of these treatments need postbiological process to further mineralize the decomposed compounds. The unconsumed oxidant residue needs to be neutralized for matching the effluent standard [14, 15]. Processes of wet air oxidation (WAP) and wet oxygen oxidation (WOP) with (CWAP and CWOP) and without catalysts have been successfully employed for oxidation treatments [20–30]. For example, in a study on the treatment of high-strength industrial wastewater, Lin and Ho [27] reported that the chemical oxygen demand (COD) removal efficiencies (ηCOD) via WAP, WOP, and CWAP with CuSO4 catalyst were 65, 73, and 75%, respectively, at 473 K, 3 MPa, 300 rpm, 1 L/min gas flow rate, and 2 h. The application of WAP and WOP has the advantages avoiding the posttreatment of unwanted residual oxidant species and no need for the recovery and regeneration of catalyst, compared with oxidant-added oxidation and catalytic oxidation, respectively. The abundant dissolved oxygen left can improve the performance of regular biological sewage system if needed [18]. Moreover, WOP gives η COD only slightly less than catalytic oxidation while higher than WAP. This study thus employed WOP to treat the DMP-containing aqueous solution.

EXPERIMENTAL MATERIALS AND METHODS Materials DMP with purity of 99.5% was supplied by Hayashi Pure Chemical Industries Ltd. (Osaka, Japan). The mobile phase of high performance liquid chromatography (HPLC) was composed as acetonitrile (CH3CN) : DI water = 1 : 1, where acetonitrile of 100% purity was from J. T. Baker, Phillipsburg, NJ. The solvent for apparatus cleaning is acetone (C3H4O) with purity of 99.5% by Mallinckrodt Chemicals, St. Louis, MD. The reagents for measurement of total organic carbon (TOC) were (1) carrier gas: 99.99% N2from San Fu Chemical Co. Ltd., Taipei, Taiwan; (2) oxidant: sodium peroxydisulfate, Na2S2O8 (99% purity), from Nacalai Tesque, Kyoto, Japan;

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(3) standard solution: anhydrous potassium biphthalate, KHP, C8H5KO4 (99.0% purity), from Riedel-de Haën, Seelze, Germany. The reaction gas O2 (99.99% purity) and air (O2 : N2 = 20 : 80, 99.99% purity) were purchased from San Fu Chemical Co. Ltd., Taipei, Taiwan.

Methods The pressurized autoclave reaction system is shown in Figure 1. A 1 L bench top reactor is used. It is made of stainless steel 316 and equipped with a stirring rotor (DC-2RT44, Hsing-Tai Machinery Ind. Co., Taipei, Taiwan), pressure display module, and K-type thermal couple. The temperature of heater (Model-TC-10A, Macro Fortunate, Taipei, Taiwan) is controlled with temperature controller (Model-BMW-500, Newlab Instrument Co., Taipei, Taiwan). Mass flow controller of Model 5850E manufactured by Brooks (Hatfield, PA) is employed to control the gas flow rate.

Figure 1: Schematic diagram of wet oxygen oxidation system.

The bearing is cooled by cooling water from circulating bath (Model-B403, Firstek Scientific, Taipei, Taiwan). The upper cap of vessel has six holes with five for two sampling valves, thermal couple, pressure gauge, and release valve, while one for spare port. The experiments were batch type with volume of liquid of DMP solution (V L) of 400 mL. The

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sampling valves are connected to cooling coil. The pressured vapor was captured to the coil and then cooled while keeping the pressure of the reactor. After 5 mL liquor was sampled, the noncollected cooled liquid was conducted back to the reactor. The initial concentration (C 0) of DMP solution was 100 mg/L. The concentrations of DMP of samples (C) were analyzed by high performance liquid chromatography (HPLC, Viscotek Model 500, Houston, TX), while those of total organic carbon (TOC) were analyzed by TOC analyzer (Model 1010, O.I. Analytical, NY). The column of HPLC is 516C-18 of 25 cm × 4.6 mm with ID 5 μm (Supelco Inc., Bellefonte, PA). The TOC analyzer uses nondispersive infrared (NDIR) detector, with carrier gas of N2, oxidative agent of 10% sodium peroxydisulfate solution, and TOC standard solution of anhydrous potassium biphthalate. The precision of experimental data was indicated in figures by error bar with standard deviation (σ n−1) above and below the average value.

The batch WOP process was performed in two stages. The first is heating stage. The DMP-containing solution, which was prebubbled by N2 to purge out the residual oxygen, was filled into the autoclave reactor and then heated from room temperature 283 K to the set reaction temperature (T) without any oxidant. The tested temperatures were 463, 473, and 483 K. The initial time (t) was noted as 0i, while the final time of the first stage as 0f. In the second stage, the working gas O2 was introduced into the reactor at t = 0f to the desired operation pressure (P T) to continue the oxygen oxidation reaction.

The major operation parameters of batch WOP were examined including (1) the stirring speed (Nr), (2) reaction temperature T, and (3) operation pressure P T. The initial pH value (pH0) was not adjusted while reflected by the C 0. Values of parameters are listed in Table 1 referring to those of others [27, 29]. For example, Lin and Ho [27] performed the experiments with Nr = 100–400 rpm, P T = 2.5–5.0 MPa, and T = 423–513 K. They reported that (1) 300 rpm and 3 MPa were appropriate and (2) T was the most important operation variable with marginal enhancing effect for T above 498 K. The present study extended Nr to 500–700 rpm, while it employed P T and T in the proper ranges of those of Lin and Ho [27]. Table 1: Operation parameters and range of WOP Parameter of operation Rotation speed Nr, rpm Temperature T, K

Operation range 300, 500, 700 463, 473, 483

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2.41, 2.67, 3.10, 3.45 Pure O2

RESULTS AND DISCUSSION Effects of Rotation Speeds Nr Figure 2 illustrate the variation of decomposition efficiency of DMP (η DMP) with reaction time t at various rotation speeds (Nr = 300, 500, and 700 rpm). Other conditions are reaction temperature T = 473 K and operation pressure P T = 2.41 MPa. As expected, more DMP is decomposed with longer t giving higher ηDMP. The η DMP is 66, 78, and 66% at t = 180 min for Nr = 300, 500, and 700 rpm, respectively. In general, a good gas liquid mixing assists the reaction. Thus, an increase of Nr from 300 to 500 rpm increases the gas liquid mass transfer and offers a higher η DMP. However, the dissolved oxygen needed for reaction may be tripped or purged out from liquid to gas as further increasing the Nr, say to 700 rpm, reducing the η DMP. The Nr of 500 rpm leads to better increasing trend of η DMP.

Figure 2: Time variation of decomposition efficiency of DMP (η DMP) via WOP at various rotating speeds Nr. ⋄, □, and △: Nr = 300, 500, and 700 rpm. C 0 = 100 mg L−1, V L = 400 mL, T = 473 K, and P T = 2.41 MPa. Working gas after time = 0f is O2. ↕: Mean and Standard deviation (SD, n − 1 method) at t = 0f: 14.8 ± 2.8.

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It is noted that although the effects of Nr of low rpm, say below 300 rpm, on the system performance were not investigated in this study, its qualitative effects may be realized referring to the work of Lin and Ho [27] dealing with the treatment of high-strength industrial wastewater. They examined the effects of Nr from 100 to 400 rpm on the chemical oxygen demand removal efficiencies η COD, indicating apparently significant effect as Nr below 300 rpm. An Nr of 300 rpm was thus adopted for their further experiments. This thus justified the adoption of 500 rpm for the followed experiments of the present study, assuring the good mixing. The effect of reaction time on the pH value of DMP-containing solution during WOP at different Nr is depicted in Figure 3. The decrease of pH value as oxidation decomposition takes place indicates the formation of acidic products. Although the decompositions are significant from 60 to 180 min as shown in Figure 2, the pH value stays nearly the same at about 4 after 60 min. This might be due to the cause that some intermediate acidic products from the decomposition of DMP are further broken down to small acidic fragments of low solubility being released to gas phase, leaving the pH value of liquid essentially not altered for t longer than 60 min. The negligible effect of Nr on pH value as Nr is sufficiently high as 300 rpm or higher might be attributed to the balance of enhancement of gas liquid mass transfer and the purge of small acidic fragments by rotation stirring.

Figure 3: Time variation of pH value for the decomposition of DMP via WOP

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at various Nr. ⋄, □, and △: Nr = 300, 500, and 700 rpm. C 0 = 100 mg L−1, V L = 400 mL, T = 473 K, and P T = 2.41 MPa. Working gas after time = 0f is O2. ↕: Mean and Standard deviation (SD, n − 1 method) at t = 0f: 4.4 ± 0.1.

Effects of Reaction Temperature T Figures 4 and 5 show the time variations of η DMP and η TOC at reaction temperatures T of 463, 473, and 483 K for the case with Nr = 500 rpm and P T = 2.41 MPa. In the heating period from 0i to 0f without oxidant, DMP underwent mainly the hydrothermal decomposition accompanied with slight mineralization. The η DMP is 17% for 463 and 473 K while 45% for 483 K at the end of heating period with no oxygen. The decomposition of DMP is very vigorous at high temperature. But the η TOC is lower than 10% for all three temperatures because of the oxidant lack. With the presence of oxygen, the η DMP was greatly enhanced while η TOC moderately improved. The results indicated the low reactivity of acidic product fragments with oxygen. As expected, both η DMP and η TOC increased as reaction time and temperature increased. At T = 483 K and t = 180 min, the η DMP and η TOC were 93 and 36%, respectively.

Figure 4: Time variation of η DMP via WOP at various temperatures T. ⋄, □, and ○: T = 463, 473, and 483 K. C 0 = 100 mg L−1, V L = 400 mL, P T = 2.41 MPa, and Nr = 500 rpm. Working gas after time = 0f is O2.

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Figure 5: Time variation of mineralization efficiency of DMP (η TOC) via WOP at various T. ⋄, □, and ○: T = 463, 473, and 483 K. C 0 = 100 mg L−1, V L = 400 mL, P T = 2.41 MPa, and Nr = 500 rpm. Working gas after time = 0f is O2.

Figure 6 demonstrates the variation of pH value with time at various temperatures. As in Figure 3, the pH value decreased with time, while it levels off at a longer time depending on the temperature, for example, at 60 min for higher temperatures of 473 and 483 K while at 120 min for lower temperature of 464 K. Thus, a higher temperature case promotes the decomposition reaction, generally lowering and leveling the pH value faster than the lower temperature case. For 483 K, the pH value decreases to a leveling value of around 4 after 60 min.

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Figure 6: Time variation of pH value for the decomposition of DMP via WOP at various T. ⋄, □, and ○: T = 463, 473, and 483 K. C 0 = 100 mg L−1, V L = 400 mL, P T = 2.41 MPa, and Nr = 500 rpm. Working gas after time = 0f is O2. ↕: Mean and Standard deviation (SD, n − 1 method) at t = 0i: 5.6 ± 0.3.

Effects of Operation Pressure P T Figures 7 and 8 present the η DMP and η TOC versus time at P T of 2.41, 2.76, 3.10, and 3.45 MPa with Nr = 500 rpm and T = 483 K. Both η DMP and η TOC increase with time as expected. The oxygen was filled to reach the desired pressure right after heating period, that is, at t = 0f. There is no oxidant in the time period from 0i to 0f. The DMP is hydrothermally decomposed in heating period, giving η DMP of around 33 to 45%. The DMP is only slightly mineralized with low η TOC of about 0.3 to 3.1%. In the presence of oxygen, both η DMP and η TOC are enhanced as decomposition and mineralization proceed. The oxidative decomposition of DMP essentially consists of twostage reversible reactions as illustrated in Figure 10, which is discussed in the next section. The decomposition of DMP and intermediates to short-chain aliphatic acid and then CO2 are proposed by referring to the mechanism for the ozonation of DMP with UV and catalyst presented by Chang et al. [11]. An increase of oxygen as well as temperature enhances the forward reactions toward mineralization way, while the accumulation of CO2 reversely inhibits the mineralization according to Le Chatelier’s principle

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[31]. Thus, sufficient oxygen with satisfactorily high PT is needed to ensure the forward oxidative decomposition reaction of DMP. For example, P T at 2.41 MPa yields η DMP and η TOC of 93 and 36% at 180 min, respectively. Although higher P T with more oxygen favors the forward decomposition reaction of DMP by oxygen, the absorption of accumulated gaseous products such as CO2 and decomposed short-chain hydrocarbon fragments in the closed reaction system increases as P T increases. The reabsorption of gaseous products back into the solution thus inhibits the forward reaction. Hence, as indicated in Figures 7 and 8, P T of 2.41 MPa is more appropriate than those of 2.76 to 3.45 MPa.

Figure 7: Time variation of η DMP via WOP at various pressures. □, △, +, and ×: P T = 2.41, 2.76, 3.10, and 3.45 MPa. C 0 = 100 mg L−1, V L = 400 mL, T = 483 K, and Nr = 500 rpm. Working gas after time = 0f is O2. ↕: Mean and Standard deviation (SD, n − 1 method) at t = 0f: 38.2 ± 5.3.

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Figure 8: Time variation of η TOC via WOP at various pressures. ○, △, +, and ×: P T = 2.41, 2.76, 3.10, and 3.45 MPa. C 0 = 100 mg L−1, V L = 400 mL, T = 483 K, and Nr = 500 rpm. Working gas after time = 0f is O2. ↕: Mean and Standard deviation (SD, n − 1 method) at t = 0f: 1.5 ± 1.3.

Figure 10: Two stages for the decomposition of DMP via WOP.

Figure 9 plots pH value versus time at various P T. The reduction of pH value in hydrothermal decomposition period is more vigorous than that in the oxidative decomposition period. The trend is similar to that of Figure 3 previously discussed. The increase of P T higher than 2.41 MPa exhibits negligible effect on the pH value. The pH value levels off, indicating the limited oxidative mineralization to CO2 and the gas liquid absorption balance of acidic compounds of CO2 and decomposed short-chain hydrocarbon fragments.

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Figure 9: Time variation of pH value for decomposition of DMP via WOP at various pressures. ○, △, +, and ×: P T = 2.41, 2.76, 3.10, and 3.45 MPa. C 0 = 100 mg L−1, V L = 400 mL, T = 483 K, and Nr = 500 rpm. Working gas after time = 0f is O2. ↕: Mean and Standard deviation (SD, n − 1 method) at t = 0i: 5.2 ± 0.2 and at t = 0f: 4.1 ± 0.2.

It is noted that the P T was the sum of partial pressures of oxygen (P O2) and water vapor (P WV). The saturation P WV varies with temperature and is about 2.3 MPa at 483 K [27]. Setting P T at 2.41 and 3.45 MPa gave P O2 of 0.11 and 1.15 MPa, respectively, for supplying the oxygen for mineralization reaction. Referring to the study of Lin and Ho [27] using 2.5 MPa as the lowest setting at 473 K, this analysis thus did not employ P T lower than 2.41 MPa at 483 K.

Mechanism of Two-Stage Decomposition of DMP via WOP In this test, the reactions are involved in components of DMP, oxygen, intermediate products, and ultimate end products of CO2 and H2O. The intermediates are the decomposed short-chain hydrocarbon fragments which are acidic as reflected by the low pH value. Accordingly, the mechanism of two-stage decomposition of DMP via WOP may be depicted in Figure 10. In the heating stage without oxygen, DMP is essentially hydrothermally decomposed to acidic fragments lowering the pH value with significant η , while forming little CO2 with low η TOC. With the introduction of oxygen DMP in the second stage, oxidation of DMP and its decomposed fragments takes

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place, destructing them into short-chain acids such as aliphatic acids or more completely to CO2 and H2O. The produced CO2, however, was kept within the closed-batch reaction system in this study. The stoichiometry equation for the forward oxidation reaction of DMP can expressed as follows: C10H10O4 + 10.5O2 ⟶ 10CO2 + 5H2O

(1)

For complete mineralization of DMP, each mole DMP consumes 10.5 moles of O2 while producing 10 moles of CO2. The CO2 partial pressure contributed from the complete mineralization of DMP is about 0.045 MPa by consuming 0.047 MPa O2. This reaction reduces the total pressure slightly. In fact, the oxygen is not a limited factor because the minimum pressure applied is 2.41 MPa exceeding the need. However, the mineralization of reaction (1) is hindered by the accumulation of product CO2 in the closed-batch reaction system. It forces the backward reaction of reaction (1) according to Le Chatelier’s principle [31]. The equilibrium balance of the forward and backward reaction thus limits the complete mineralization of DMP. A release of CO2 gas out from the reaction system would certainly assist approaching the complete mineralization of DMP.

Comparison with Results of Others Comparison of the results of this study with others is illustrated in Table 2. The present WOP can reach ηDMP of 93% as high as the advanced methods (AMs) of electrochemical oxidation, photocatalytic degradation, and photocatalytic ozonation. The η TOC of WOP of 36% is lower than those of the aforementioned AMs at some conditions, however, comparable at other conditions. It is noted that the WOP simply uses oxygen with demand of the thermal energy, while other AMs need to employ chemical agents, catalysts, and ozone along with electric or UV energies. Thus, the WOP is comparatively simple to apply. The discrepancy of incomplete mineralization of WOP may be consummated with the postbiological treatment if necessary [20]. The predecomposition of DMP by WOP certainly greatly enhances the followed biological processing.

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Table 2: Comparison with some results of others for the decomposition of DMP via various methods Study

Method

Result

Bauer et al. [1]

Anaerobic process in field municipal landfill leachates

DMP was completely hydrolysis to phthalic acid but no cleavage for aromatic ring at different pH values

Wang et al. [16]

Electro-Fenton methods by electrodes: traditional graphite cathode (G), carbon nanotube sponge (CNTS), and graphite gas diffusion electrode (GDE)

η TOC: G, 15%; GDE, 35%; CNTS, 75%

Souza et al. [17]

Electrochemical oxidation on Fdoped Ti/β-PbO2 anode in filter press reactor

DMP was completely decomposed under electrolyte Na2SO4 and low current densities (10 mA), η TOC = 25%

Chang et al. [11]

Catalytic ozonation (OZ) in highgravity rotating packed bed (HG) with catalyst (Pt/-Al2O3) and ultraviolet (UV) (mix of UV-C, UV-B, and UV-A with 200–280, 280–315, and 315–400 nm and with intensities of 3.73, 1.59, and 3.99 W m−2)

η DMP at 50 min: near 100% for Pt-OZ and UV-Pt-OZ η TOC at 1 h: 45% (OZ); 56% (UV-OZ); 57% (Pt-OZ); 68% (UV-Pt-OZ)

Chen et al. [13]

Photocatalytic degradation using magnetic poly(methyl methacrylate) (mPMMA) and UV 254 nm

η DMP at 4 h: 55–100% via TiO2/ mPMMA (C1); 68–100% via Pt-TiO2/ mPMMA (C2) η TOC at 4 h: 7.5–37.5 % via C1; 11–64% via C2

Chen et al. [19]

Photocatalytic ozonation using TiO2, Al2O3, and TiO2/Al2O3catalysts

η DMP at 30 min: 2–22% without O3, 90–100% with O3. η TOC: 16–93%, 32–97% at 1, 4 h

Chen et al. [12]

Photocatalysis using magnetic PtTiO2/mPMMA

UV 185 nm contributes better removal efficiency than UV 254 nm

This study

Wet oxygen oxidation

η DMP and η TOC are 93 and 36% at Nr = 500 rpm, T = 483 K, P T = 2.41 MPa, and t = 180 min

CONCLUSIONS This study treated the toxic endocrine disrupter substance (EDC) of DMP via wet oxidation using oxygen (WOP) without other oxidant additives, being beneficial to the subsequent biological process if necessary, while avoiding the treatment of unwanted oxidant residues. The WOP effectively

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decomposed the DMP, indicating its feasible application for the treatment of other EDCs. Among the three factors investigated, namely, rotation speed Nr, reaction temperature T, and operation pressure P T, the effects of T are most significant. The proper conditions found are at 483 K, 2.41 MPa, and 500 rpm. The η and η TOC of 93% and 36%, respectively, can be achieved at 180 min. DMP The produced CO2 kept in the closed-batch reaction system seems to resist the further mineralization reaction from intermediates. The application of sequential release of CO2 while addition of O2 to improve the η TOC is thus suggested.

ACKNOWLEDGMENT The authors are grateful for the financial supports of this research provided by the Ministry of Science and Technology (formerly the National Science Council) of Taiwan.

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14 Aqueous Solution Chemistry of Ammonium Cation in the Auger Time Window

Daniel Hollas 1, Marvin N. Pohl2,4, Robert Seidel 2, Emad F. Aziz2,3, Petr Slavíček1,5, and Bernd Winter2,6 Department of Physical Chemistry, University of Chemistry and Technology, Prague, Technická 5, 16628, Prague, Czech Republic

1

Helmholtz-Zentrum Berlin für Materialien und Energie, Methods for Material Development, AlbertEinstein-Straße 15, D-12489, Berlin, Germany

2

School of Chemistry, Monash University, 3800 Clayton, Victoria, Australia

3

Department of Physics, Freie Universität Berlin, Arnimallee 14, D-141595, Berlin, Germany

4

Citation: Hollas D, Pohl MN, Seidel R, Aziz EF, Slavíček P, Winter B. Aqueous Solution Chemistry of Ammonium Cation in the Auger Time Window. Sci Rep. 2017;7(1):756. Published 2017 Apr 7. doi:10.1038/s41598-017-00756-x. Copyright: © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/.

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J. Heyrovský Institute of Physical Chemistry, Dolejškova 3, 18223, Prague 8, Czech Republic 5

Present address: Fritz-HaberInstitut der Max-Planck-Gesellschaft, Faradayweg 4-6, D-14195, Berlin, Germany 6

ABSTRACT We report on chemical reactions triggered by core-level ionization of ammonium cation in aqueous solution. Based on a combination of photoemission experiments from a liquid microjet and high-level ab initio simulations, we identified simultaneous single and double proton transfer occurring on a very short timescale spanned by the Auger-decay lifetime. Molecular dynamics simulations indicate that the proton transfer to a neighboring water molecule leads to essentially complete formation of H3O+ (aq) and core-ionized ammonia ⁎(aq) within the ~7 fs lifetime of the nitrogen 1s core hole. A second proton transfer leads to a transient structure with the proton shared between the remaining NH2 moiety and another water molecule in the hydration shell. These ultrafast proton transfers are stimulated by very strong hydrogen bonds between the ammonium cation and water. Experimentally, the proton transfer dynamics is identified from an emerging signal at the high-kinetic energy side of the Auger-electron spectrum in analogy to observations made for other hydrogen-bonded aqueous solutions. The present study represents the most pronounced charge separation observed upon core ionization in liquids so far.

INTRODUCTION Electron spectroscopy using high energetic X-ray radiation has become a thriving method for electronic-structure investigations of matter1. For example, X-ray-based spectroscopies contribute significantly to the ongoing discussion on water structure in liquid phase2–4. X-rays are also known to trigger various chemical reactions by core ionization which leads to the formation of highly excited radicals5, 6. Such processes play an important role, for instance, in the radiation damage of biomolecules7. The mechanistic details are not yet fully understood, mostly due to the ultrashort timescale of the elementary relaxation processes involving both electron and nuclear motion8, which are difficult to access by experiment. In addition, X-ray studies from aqueous phase, particularly those based on electron detection,

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have been challenging because of the short electron mean free path. The introduction of the liquid-microjet technique has overcome this major problem and enabled liquid-phase photoelectron spectroscopy. Valuable information on the electronic structure, including valence and core-level binding energies of solute and solvent, has been obtained since then9, 10. In addition, spectroscopy of electrons generated by second-order (relaxation) processes has considerably contributed to our understanding of the ultrafast electron and nuclear dynamics initiated by X-rays11, 12. Ionization of molecules or ions by high-energy radiation leads to the formation of excited species which relax either via radiative (X-ray fluorescence) or non-radiative (Auger-type autoionization) decay channels. In the case of autoionization, the core hole formed upon core ionization is refilled by a valence electron while another valence electron is ejected. Nonradiative decay is dominant for light atoms. It can be a local (Auger decay) or non-local process with different autoionization mechanisms13. Non-local processes have been recently explored for hydrogen-bonded small molecules in aqueous solution, including water (aq)5, 14, hydrogen peroxide (aq)15, ammonia (aq)16, glycine (aq)16, formaldehyde (aq)17, formaldimine (aq)17, and hydrogen sulfide (aq)17. For a given molecule AHq (aq) with charge q in aqueous phase, core ionization leads to the formation of highly excited radicals (AHq+1)⁎. The asterisk denotes a core-hole excited state. In an Auger process, this singly ionized state autoionizes locally by forming a doublyionized species AHq+2. We denote the respective local two-hole final state as 2 h. This notation is used to distinguish from final states produced by non-local autoionization processes of (AHq+1)⁎ where electronic relaxation includes neighboring molecules. The core hole is then refilled by a valence electron, but instead of ejecting a local Auger electron, an electron is emitted from a water molecule in the first hydration shell. Accordingly, this socalled intermolecular Coulombic decay (ICD) creates two positive charges shared between two molecular partners, e.g. AHq+1 ⋯ H2O+. This delocalized final state is referred to as 1h1h(one-hole-one-hole). The above mentioned ionization and relaxation processes can be expressed as: (1) (2) (3) Other types of non-local relaxation processes involving even more

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molecular units such as the electron-transfer mediated decay (ETMD) are also possible13, 18. The non-local decay processes can have a considerable spectral contribution, sometimes comparable to that of the local Auger process. This is the case when autoionization is accompanied by proton dynamics5, 12. In the so-called proton-transfer mediated charge separation (PTM-CS) process5, the core-ionized molecule releases a proton which is then shared with another water molecule from the hydration shell, forming a transient structure analogous to the Zundel cation in water, in which the proton is shared equally between the two species19:

(AHq+1)⁎ ⋯ H2O → [Aq⁎ ⋯ H+ ⋯ H2O].

(4)

Note that unlike Equations (2) and (3), Equation (4) does not consider the final autoionization event. The electron can be ejected either from the molecule A (local) or the neighboring water unit (non-local); the final products are [Aq+1 ⋯ H+ ⋯ H2O] or [Aq ⋯ H+ ⋯ H2O+], respectively. The charge separation, leading to the transient core-excited species, is thus supported by the proton motion which has been identified in previous studies20–25. Theoretical analysis of this process in liquid water has shown that Zundeltype transients have an increased probability to decay via ICD14, creating 1h1h states. PTM-CS is experimentally identified by an isotope effect in the autoionization spectra. Specifically, the 1 h1 h states have a lower energy than the 2 h states (by approximately 5 eV in liquid water5) due to the reduced Coulomb repulsion, giving rise to increased signal intensity at the high-kinetic energy side of the respective Auger spectra. Notice that local Auger decay for the manifold of the Zundel-analogue structures will also produce 1 h1 h states, with energies similar to the ones produced by ICD12, 14 . Experimentally, the occurrence of PTM-CS is identified from a larger intensity of the characteristic 1 h1 h signal for the lighter isotope, i.e. H2O in normal liquid water versus D2O in deuterated liquid water. This is because the lighter and faster moving proton forms the Zundel-type structures more efficiently compared to the heavier deuteron within the core-hole lifetime (approximately 4 fs for O 1s25 and 6.4 fs for N 1s26). It has been found from studies of other hydrogen-bonded solutes in aqueous solutions that the probability of PTM-CS strongly correlates with hydrogenbond strength, which naturally makes this particular spectral fingerprint a rather sensitive probe of hydration structure12. This dependence made us to explore how PTM-CS manifests in a much stronger hydrogen-bonded system as compared to the ones studied so far. A large effect is expected when going from neutral to cationic molecule. Our study case is ammonium

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in water, (aq), which forms stronger hydrogen bonds with water than does neutral NH3 27. The ⋯H2O system is stabilized dominantly by a strong ion – dipole interaction. By theoretically analyzing the coreionization-induced relaxation processes of (aq), we are able to predict how likely PTM-CS is and how an extra charge influences the structure of the transient species. Regarding the previously studied neutral molecules (H2O, H2O2, and NH3)5, 15, 16, our computational analysis addresses several aspects unique to . First, having one more hydrogen atom than NH3, the probability for a proton transfer is expected to increase. Second, unlike NH3, is positively charged already before the core ionization resulting in a double positive charge after ionization. This increases both the Coulomb repulsion between the parent molecule and a proton, as well as the attraction between a water oxygen and a proton. Third, the ionized doubly-charged state possibly enables double-proton transfer. All these conditions are in favor of the PTM-CS process and should result in a much stronger isotope effect and possibly in the occurrence of additional spectral features than observed in all previous studies. Understanding the relaxation processes in (aq) is a prerequisite for analyzing autoionization spectra of several biologically relevant molecules, for instance amino acids in their different protonation states in aqueous phase.

METHODS Calculations We have addressed three aspects in our calculations: (i) the structure of the ion in aqueous solution, (ii) the energetics of the autoionization processes, and (iii) the proton dynamics on the core-ionized potential energy surface (PES). The first aspect was approached by ab initio molecular dynamics (MD) simulations for the solution in thermal equilibrium. The energetics of the autoionization process was investigated using quantum chemical methods. The dynamics on the core-ionized PES were investigated using semi-classical ab initio MD simulations for finite-size cluster models. The ab initio MD simulations of the solvated ammonium ion in thermal equilibrium were performed using the QuickStep module of the CP2K program28, 29, utilizing the mixed plane-wave/Gaussian basis set approach with periodic boundary conditions30. We applied the BLYP functional with molecularly optimized DZVP-MOLOPT-SR basis set31 and Goedecker-

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Teter-Hutter pseudopotentials32. The cutoff frequency for the plane waves was set to 400 Ry. The system consisted of 63 water molecules and one solute molecule, and the density was set to 1 g/ml. After initial equilibration for ~2 ps, the simulation was performed in the NVT ensemble for 23 ps with 0.5 fs time steps, keeping fixed temperature of 300 K. To model the nuclear quantum effects important for the PTM-CS process, we have used the approximate quantum thermostat approach based on the generalized Langevin equation (GLE)33, 34. Unlike more rigorous techniques such as path integral MD, the quantum thermostat naturally provides also approximate quantum momentum distributions33 needed for subsequent semi-classical simulations. It was previously shown that the quantum thermostat technique (albeit in slightly different implementation) is a good approximation to Wigner distributions even for anharmonic systems35. A proper sampling of momenta is of critical importance especially for ultrafast processes where the dynamics is dominated by wave packet dispersion rather than the slope of the potential14, 36. To calculate the absolute energy position of the leading local Auger peak, we first calculated the energy of the leading Auger peak in the gas phase as the difference between the core-ionized state and the ground state of the doublyionized system at the CCSD(T)/cc-pCVTZ level. The core-ionized state was calculated with the maximum overlap method (MOM)37, 38 applied to the CCSD(T)/cc-pCVTZ electronic structure level. Furthermore, a relativistic correction due to the removal of the N 1s electron was added as described in ref. 39. The correction amounts to 0.43 eV for an oxygen atom, and 0.23 eV for a nitrogen atom. A constant solvent shift was approximated via the implicit solvation C-PCM model40, 41. The non-equilibrium approach0|; was used because of the ultrafast nature of the Auger decay. The initial polarization was computed for ground-state configuration, and only the electronic part of the polarization was allowed to relax in the subsequent calculations of core and doubly ionized final states. The solute cavity was constructed using Bondi radii42, 43, multiplied by a factor of 1.2. This approach was tested for liquid water and aqueous ammonia where validation with experimental data is possible. To investigate proton-transfer dynamics, we constructed a twodimensional PES scan along the proton-transfer coordinate for the coreionized ( )⁎(H2O)3 cluster using the MOM-MP2/cc-pCVDZ approach. The optimized ground-state geometry of the cluster was calculated at the MP2/cc-pCVTZ level with a counterpoise correction44. The static PES scan, however, does not provide conclusive information on whether the process of

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interest actually takes place. Therefore, we performed dynamical simulations of larger ( )⁎(H2O)20 clusters on the core-ionized PES calculated on-thefly at the MOM-B3LYP/cc-pVDZ level. Initial geometries and velocities were taken from the ab initio CP2K simulation described above. The system was simulated for 10 fs, corresponding to the nitrogen core-hole lifetime (~6.4 fs26), and the time step was set to 0.25 fs. A total of 400 trajectories was launched. We repeated all simulations for the deuterated systems to model the isotope effect. We have carefully examined the convergence of the results with respect to the size of the cluster and the level of electronic structure theory; the results of this analysis can be found in the Supplementary Material. To speed up the calculations for larger clusters, we have implemented the MOM method in the development version of the GPU code TeraChem45, 46. We have validated our implementation against the results from the MOM method as implemented in the Q-Chem package47. The geometric structure of the (H2O)3 was optimized using Gaussian 48 code . The ab initiocalculations using MOM-MP2 and MOM-CCSD(T) were done with the QCHEM program47 while MOM-B3LYP calculations were done using the development version of TeraChem code45, 46. All MD simulations were performed with the in-house Abin code49 while forces and energies were taken each timestep from an external ab initio program (either QCHEM, CP2K or TeraChem). The estimate of the interaction energies between hydrogen bonded dimers was done at the CCSD(T)/CBS level using the MOLPRO code50.

Experiment Photoelectron- and Auger-electron spectroscopy measurements were conducted at the U49/2-PGM-1 undulator beamline at the BESSY II synchrotron-radiation facility in Berlin. Auger-electron spectra associated with the nitrogen 1s ionization of aqueous were collected using 500 eV photon energy, illuminating a 25 μm diameter liquid microjet at a temperature of approximately 18 °C and traveling with a velocity of approximately 80 ms−1. Experimental details of the liquid-microjet technique have been described previously51, 52. Emitted electrons were detected using a hemispherical electron-energy analyzer at normal angle with respect to the polarization direction of the incident light. Since the angular distribution of second-order electrons is isotropic, the detection geometry has no effect on the data discussed here. The energy resolution of the U49 beamline was better than 230 meV at the photon energies used here and the energy resolution

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of the hemispherical energy analyzer was constant with kinetic energy, approximately 200 meV at 40 eV pass energy. Ammonium chloride aqueous solutions were prepared from NH4Cl salt (Sigma Aldrich # A9434, >99.5% purity) which was dissolved in neat liquid water, corresponding to 2 molar (M) concentration. The same procedure was applied for preparing a 2 M aqueous solutions of deuterated ammonium chloride, dissolving ND4Cl salt (Sigma Aldrich # 175676, >98% purity) in heavy water.

RESULTS AND DISCUSSION In order to discuss the results of our combined theoretical and experimental studies on the proton-transfer mediated charge separation processes in aqueous , we first present computation-based evidence for this process. We then show that the predicted behavior is in very good agreement with our experimental spectra. Let us start by analyzing the hydrogen-bond strength between water solvent and in the ground-state configuration. As we have shown before, PTM-CS gets more pronounced as the hydrogen bonding gets stronger12. While the ammonia molecule is a poor hydrogen-bond donor16, exhibits 27 strong hydrogen bonding . This can be inferred already from the analysis of molecular dimers. The ⋯H2O complex is stabilized by 87 kJ/mol, which is much stronger compared to the NH3 ⋯ H2O (10 kJ/mol) and the H2O ⋯ H2O (21 kJ/mol) complexes, as calculated at the CCSD(T)/CBS level. We note that the NH3∙∙∙H2O complex in which NH3 acts as a hydrogen-bond donor does not represent a true minimum on the potential energy surface. The values reported here were calculated for the geometry obtained via constrained minimization, which further highlights the weak hydrogenbonding between neutral ammonia and water. The bond strengths correlate with the intermolecular distances between the heavy atoms (N/O and O) contributing to the hydrogen bonds in the dimers: ~2.67 Å bond length for ammonium, ~2.9 Å for water, and ~3.24 Å for ammonia. MD simulations of the fully hydrated solute in periodic boundary conditions provide a more detailed characterization of the hydrogen-bond strength. In Fig. 1 we show the proton densities (calculated in a quasi-classical way) projected onto two coordinates which characterize the strength of the hydrogen bonding: the O/N–O distance and the O/N–H∙∙∙O angle. The optimum angle for a strong hydrogen bond is 180°, corresponding to perfect collinearity of the hydrogen bond. By taking water as a benchmark for a system with strong hydrogen bonds, we see from Fig. 1A that (aq) exhibits similar hydrogen bond

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lengths (2.5 Å–3.0 Å) and angles (120°–180°) for the strongest hydrogen bond. For NH3 on the other hand, both parameters (2.8 Å–3.3 Å and 100°–180°) are essentially outside the region of strong hydrogen bonding. Remarkably, even the second-strongest hydrogen bond in (aq) is almost as strong as the strongest hydrogen bond in H2O (aq), as presented in Fig. 1B. Note that (aq) can form up to four hydrogen donor-bonds to surrounding water molecules; the average coordination number is 3.3 according to our simulations. The existence of two strong hydrogen bonds in (aq) has crucial implications for the overall relaxation processes, potentially enabling the transfer of two protons upon core ionization as will be discussed next.

Figure 1: Hydrogen-bond strengths of liquid water (blue, square symbols), ammonia (black, plus symbols) and ammonium (red, cross symbols) aqueous solutions. Two parameters characterize the hydrogen-bond strength: The N ⋯ O distance (O ⋯ O for water) and the N/O–H ⋯ O angle. Panel (A) shows data for the strongest hydrogen bond (i.e., shortest) and panel (B) corresponds to the second-strongest hydrogen bond. The shaded areas indicate the parameter ranges typically considered for strong hydrogen bonding27.

To explore the possibility of single and double proton transfer in (aq), we analyze the energetics of the proton transfer. Figure 2 shows the computed PES of micro-solvated (H2O)3 for two protons which independently move from the nitrogen atom towards the oxygen atoms of adjacent water molecules. We chose three hydrating water molecules to mimic the average coordination number obtained from our MD simulations. The observed steep energy decrease along both proton-transfer coordinates implies that coreionization-induced proton transfer is energetically favorable, even if two protons move simultaneously. Note that the minimum energy at ~1.8 Å N–H distance in Fig. 2 corresponds to the proton being fully transferred, forming

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H3O+ (aq). However, dynamical calculations are required to confirm that these processes actually occur during the ultrashort 6.4 fs nitrogen core-hole lifetime. The important question that arises is whether the complete protontransfer reactions, as expressed in Equations (5) and (6) below, indeed occur, i.e. whether a new H+–O chemical bond forms before the autoionization event: (5) (6)

Figure 2: Unrelaxed two-dimensional cut through the potential-energy surface of a core-ionized (H2O)3 cluster showing the electronic energy as a function of the N—H distances along the direction of two hydrogen bonds. The N—H ground state distance is 1.1 Å. The minimum energy corresponding to the fully transferred proton is at ~1.8 Å, marked by black dashed lines. Note that the third water molecule in the molecular sketch is omitted for clarity.

To quantify how fast the proton transfer actually is, we have performed dynamical calculations on the N 1s core-ionized state for a larger number of hydration water molecules, (H2O)20 clusters. Figure 3shows calculated proton densities projected onto the N–H/D coordinate for (H2O)20 clusters (Fig. 3A) and (D2O)20 clusters (Fig. 3B) at times t = 0 fs and t = 7 fs after core ionization. We observe that single-proton transfer in the case of (aq) is extremely fast, i.e. the process is practically completed within 7 fs. The center of the proton density curve for the strongest hydrogen bond is at ~1.8 Å (red curve in Fig. 3A), which is almost the minimum-energy distance according to Fig. 2. Note also that the proton density reaches as far as 2.1 Å. The other important observation from Fig. 3A is the considerable

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motion of the second strongest bonding proton, reaching a mean N–H distance of ~1.4 Å, which is half way toward its coordinated water oxygen. Although the dynamics is slowed down for the (D2O)20 cluster, it is still remarkably fast for the strongest bonding deuteron (red curve in Fig. 3B), comparable to the density distribution of the second proton motion for the (H2O)20 cluster. Note that MD simulations in previous studies revealed that the isotope effect in neutral NH3 (aq) is extremely small, almost unnoticeable16.

Figure 3: Time-dependent proton (deuteron) densities along the proton (deuteron) -transfer coordinates obtained from MD simulations on the core-ionized state of the (A) (H2O)20 and (B) (D2O)20 clusters. The initial structures were taken from liquid-phase MD simulations of the solvated ammonium cation in the ground state. Densities along the strongest (dashed line) and second strongest (dotted line) N–H bonds are shown after 7 fs, together with the ground-state proton density (thick line).

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Experimentally, such or analogous reactions have never been observed within the 7). In addition, the impact of these parameters varied with MWNTs possessing different surface functional groups, suggesting that surface functionalization could considerably alter the environmental behaviors and impact of MWNTs. Keywords: multi-walled carbon nanotubes, 1,3,5-trichlorobenzene, desorption, surface functionalization, solution chemistry

INTRODUCTION The unique mechanical, electrical and magnetic properties of multi-walled carbon nanotube (MWNTs) lend great potential to their applications in biomedical engineering, environmental engineering, energy storage and biosensors. The applications and the subsequent implications of MWNTs in environmental engineering derive primarily from their very large specific surface area (SSA) and consequently very large adsorption capacity and strong affinity to a large number of environmental pollutants. As a result, MWNT has been widely studied as a novel adsorbent for a wide variety of environmental pollutants. Earlier results suggested that both the unique structure and surface properties of MWNTs and the physicochemical properties of adsorbate affect the adsorption capacity and affinity of environmental pollutants to MWNTs [1,2,3]. Aromatic compounds, such as chlorophenols or chlorobenzenes, can form π-π interactions between the graphene sheet of CNTs and the benzene ring of aromatic compounds, due to the electronic polarizability of graphene surface on MWNT sidewalls. Compounds containing strong electronegative functional groups generally form stronger bonds with the MWNT surface, due to the electron donor-acceptor interactions.

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After purification, MWNTs generally contain certain functional groups, such as the hydroxyl or carbonyl group, depending upon the purification process and synthesis procedure. Functional groups can also be purposely added by oxidation process [4] or removed by certain physical and chemical treatment (e.g., heat treatment) [5]. Well-controlled experiment can incorporate over 10% of oxides by weight on CNTs surface [6]. The presence of surface functional groups can affect the adsorption process in several ways. For example, the functional groups can significantly alter the overall magnitude of π-π interactions between the adsorbed molecules and graphene sheets by increasing strong medium-range interactions linking π-orbitals of the substituents [7]. Zhang and colleagues [8] reported that surface functional groups of CNTs improved their dispersion in aqueous solutions, but decreased adsorption capacities for the hydrophobic synthetic organic compounds (SOCs). The reduced adsorption was contributed to the formation of water clusters around the oxygen-containing functional groups. Cho et al. [6] also showed that surface oxides on CNTs create polar regions that reduce the surface area available for naphthalene sorption. Gotovac et al. [9] studied the influences of different functional groups and diameters of CNTs on the adsorption of poly-aromatic hydrocarbons (PAHs) and found that acid functionalized CNTs had higher absorbability for the poly-aromatic molecules. MWNT surface can also be modified with other chemicals. For example, NH3-treated MWNTs showed higher adsorption capacity for chlorophenols than as-grown or HNO3-treated MWNTs. Liao and colleagues [3] suggested that better π-π dispersion and hydrophobic interaction are the main driving forces for the enhanced adsorption of NH3treated MWNTs for chlorophenols. In addition to the surface chemistry, solution chemistry also plays a critical role in the adsorption and desorption process. Solution chemistry can alter the speciation of both adsorbates and the functional groups on the adsorbent. Chen and Zhu [10] studied the effects of pH, ionic strength (IS) and the divalent metal ions, as well as the dissolved humic acid (HA) on the adsorption of nonionic aromatic compounds to single-walled carbon nanotubes (SWNTs). They found that divalent ion demonstrated little impact on the adsorption of nonionic aromatic compounds, while the presence of HA sharply reduced adsorption. Increasing pH induced deprotonation of the acidic functional groups (–COOH, –OH) on CNT surface and enhanced the π-electron-donor ability of the graphene surface and, thus, strengthened π-π electron-donor-acceptor (EDA) interactions of the aromatics. For ionizable organic compounds, the difference in solution pH could

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change the chemical speciation and, therefore, changing their adsorption characteristics. Higher pH usually leads to increased ionization, solubility and hydrophilicity. Changes in pH were also found to alter the adsorption of organic compounds to activated carbon and black carbon by modulating the surface characteristics of the adsorbents and the electronic properties of the adsorbate molecules [11,12,13]. Ionic solutes can also affect the adsorption of organic compounds. Chen and colleagues [14] demonstrated that copper ion decreased the adsorption of organic chemical to wood charcoal, because of the development of hydration shell, while silver ion increased the adsorption of organic chemicals, due to the reduced hydrophilicity of local region surrounding the silver ion. The greatest effect, however, may come from natural organic matters (NOMs) in the environment. A main function of NOM is that it facilitates the suspension of CNTs in solution [15,16,17,18]. Surface coating of NOM was postulated as the predominant mechanism for enhanced dispersion [19]. The break of CNT bundles provide more adsorption sites and, thus, improve adsorption [20,21]. On the other hand, the adsorption of NOM on CNT surface occupies some adsorption sites and reduces the available spaces for organic compounds. The net effect of NOM hinges on the relative importance of these competing processes and the interactions between NOM organic compounds and the CNT surface. Despite the significant insights obtained on the physical and chemical mechanisms concerning the adsorption of environmental pollutants to CNTs, current understanding on the desorption process of environmental pollutants from CNTs is still limited. According to a few available studies in the literature, the desorption of polycyclic aromatic hydrocarbons from MWNT bundles did not exhibit any hysteresis, due to the inability of tubular MWNTs to form porous structures [22]. However, a later study showed that desorption hysteresis was observed for a different compound, bisphenol A [23], suggesting that the molecular structure of adsorbates affect the desorption behavior of organic compounds. Previous research also indicated that desorption of organic compounds appeared to follow the two-stage desorption patterns from soils, and the desorption kinetics is dependent on the adsorption energy between the adsorbate and adsorbent, hence the initial concentration of adsorbate on CNTs [24]. In spite of these new insights, the desorption process is still understudied, and new knowledge concerning the impact of environmental conditions and surface properties of CNTs on the desorption process is needed.

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With the rapid buildup of MWNTs in the environment and their strong affinity and large adsorption capacity of some environmental pollutants, concerns have emerged that MWNTs may function as a contaminant carrier in the environment and pose unexpected hazardous risks in places where these contaminants are not expected. Hyung [16] reported that NOMs and CNTs form stable complexes in aqueous solution, which can be transported to different locations with water, and similar interactions can occur between typical environmental pollutants and CNTs. To address this concern, it is important to understand the mechanisms of desorption of environmental pollutants from MWNTs under different environmental conditions. Limited previous research suggested that CNT surface properties, such as the presence of amorphous carbon, affect the desorption characteristics of chlorinated compounds [25,26,27]; yet, detailed investigation is still lacking. The objective of this study was to elucidate how the surface chemistry, such as the functionalization of MWNT surface, and the solution chemistry affected the desorption of pre-laden 1,3,5-trichlorobenzene from MWNTs. 1,3,5-TCB was chosen, because it is a common environmental pollutant and it is not readily biodegradable. The adsorption and desorption are important processes controlling their environmental fate and transport. 1,3,5-TCB is also very toxic. Some recent reports also showed that 1,3,5-TCB is a suspected endocrine disruptor and has been included in the European Union (EU) List of Substances with Suspected Endocrine Effects [28].

RESULTS AND DISCUSSION Effect of Ionic Strength Overall, less than 10% of 1,3,5-TCB were desorbed from MWNTs into the aqueous phase in the batch reactors used in this study under different treatment conditions (e.g., different ionic strength (IS), pH or NOMs). Nevertheless, the desorption of 1,3,5-TCB revealed interesting trends under the impact of different solution chemistry parameters. A one-way ANOVA analysis indicated that the desorption rate was significantly affected by the tested parameters (p < 0.05 for all treatments). In this study, a broad range of ionic strength (IS) was chosen to mimic the IS in freshwater and seawater. The results suggested that desorption of pre-loaded 1,3,5-TCB increased with increasing IS for all MWNTs, irrespective of the nature of functionality on CNT surface. However, the impact appeared to be stronger for un-functionalized MWNTs than

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functionalized MWNTs, especially at lower ionic strength (IS < 0.1 M). The observation may be explained by the fact that unfunctionalized MWNTs still contain some functional groups, even though they are not as concentrated as functionalized MWNTs. Unfuntionalized CNTs also contain higher amorphous carbon and catalysts; yet, their role on the impact of ionic strength on 1,3,5-TCB desorption is not clear. The relatively large error bars for un-functionalized MWNTs were also attributed to the heterogeneity of the un-functionalized MWNT surface. The ion composition of IS showed a difference in term of the IS impact on the desorption process, with the divalent Ca2+ demonstrating a stronger effect than the monovalent Na+. The result of the IS effect is shown in Figure 1.

Figure 1: Change of the desorption rate of pre-loaded 1,3,5-TCB from multiwalled carbon nanotube (MWNTs) with different solution ionic strength and composition. (A) solutions containing CaCl2; (B) solutions containing NaCl. The reported values are the average of three or four replicates. Error bars stand for standard deviation.

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Increasing ion concentrations in the solution could result in the compression of the double layers surrounding MWNTs and, consequently, led to the aggregation of MWNTs. The aggregates of MWNTs could be more compact (squeezing-out) and unfavorable for 1,3,5-TCB adsorption [29]. Increased IS also strengthened the electronic shielding effect on negatively charged MWNT surface and weakened the electrostatic forces, which contributed to the adsorption of 1,3,5-TCB to MWNTs. An earlier study suggested that the electron donor-acceptor interaction between –Cl on 1,3,5TCB and the benzene rings on the CNT surface is the primary molecular force governing the adsorption of 1,3,5-TCN on CNT surface, even though other molecular forces, including the Van der Waals forces, also contribute to the adsorption [30,31]. With increasing ions in the solution, more ions would likely accumulate on the CNT surface, especially the polar regions, and reduce the adsorption of 1,3,5-TCB. The ions could also form a cation-π interaction, which has been shown to inhibit the electrostatic interactions, favoring the desorption of 1,3,5-TCB from CNT surface [31]. In this study, desorption rate was generally higher for un-functionalized MWNTs than functionalized MWNTs. The presence of functional group makes the MWNTs more hydrophilic and more dispersed in water, resulting in a more accessible surface for 1,3,5-TCB [32]. The ion composition effect is understandable in that the bivalent Ca2+ ion can cause a larger electronic screening effect compared with the monovalent Na+ ion and, hence, greater suppression on 1,3,5-TCB adsorption on carbon nanotubes [33]. The cationbridging mechanism may also help interpret the observed phenomenon, because metal ions have been reported to bridge with the functional groups on CNTs by compressing the double layer and, thus, weaken the repulsion between CNTs, which eventually leads them to form aggregate, resulting in less adsorption and more desorption [34,35,36].

Effect of pH The effect of solution pH on the desorption of 1,3,5-TCB from MWNTs are shown in Figure 2. It is apparent that higher pH favored the desorption of 1,3,5-TCB for all MWNTs. The desorption of 1,3,5-TCB displayed somewhat similar patterns for the two functionalized MWNTs, but differed from un-functionalized MWNTs. In the acidic range, the effect of pH was insignificant for un-functionalized MWNTs and MWNTs-COOH, but lead to a gradual increase of 1,3,5-TCB desorption from MWNTs-OH. At a higher pH range, the desorption of 1,3,5-TCB was stable for un-functionalized

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MWNTs. However, the desorption of 1,3,5-TCB continued to increase with the pH at a basic range for both functionalized MWNTs.

Figure 2: Change of the desorption rate of pre-loaded 1,3,5-TCB from MWNTs with solution pH. The reported values are the average of three or four replicates. Error bars represent standard deviation.

It is widely recognized that pH shift could cause the protonationdeprotonation transition of the functional groups on MWNTs and the ionizable compounds. It has been reported that the adsorption of ionizable compounds on CNTs alters with pH, due to the chemical speciation [15,37,38]. 1,3,5TCB is non-ionizable and will maintain neutrality throughout the pH range. Therefore, the observed effect should be attributed to the effect of pH on the deprotonation of functional groups on the CNT surface. The deprotonation of the hydroxyl and carboxyl functional groups on functionalized MWNTs at higher pH would generally make the sites more hydrophilic and encourage the formation of water clusters and discourage the adsorption of 1,3,5-TCB to CNTs, because hydrophobic adsorption was inhibited. According to Dubinin [39], the water molecules adsorbed to the oxygen groups on carbon surface become secondary adsorption sites, which retain other water molecules by means of hydrogen bonding. Formation of water clusters around oxygen groups may affect the adsorption of 1,3,5-TCB by hindering the access of 1,3,5-TCB to the MWNT surface. The formation of water clusters on carboxyl groups has been suspected to block adsorption on

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the carboxyl sites [40] and result in more desorption. One observation, which is worth mentioning, is that the desorption of 1,3,5-TCB from MWNTs-OH increased slowly from pH 3 to 9 and then jumped at pH > 9. The result may stem from the fact that the pKavalues of most R-OH compounds are greater than 11. At pH > 9, about two units around the pKa, deprotonation increased dramatically, compared with pH < 9, resulting in rapid building up of water clusters and more desorption of 1,3,5-TCB. In contrast, most R-COOH compounds have a much smaller pKa, and most of them are expected to fully deprotonate at neutral pH. Therefore, the rapid increase of desorption from MWNTs-COOH after pH 7 may not be explained by the protonationdeprotonation theory. It is likely that after pH 7, the hydroxide ion in solution had a stronger interaction with the electrophilic carbon on the CNT surface and weakened the EDA relationship between MWNT surface and 1,3,5TCB by lowering the charge density on the oxygen molecule. The reason for the gradual drop of desorption from pH 4 to pH 7 for MWNTs-COOH is not clear. Unfunctionalized MWNTs typically contain some functional groups, even though they are more diverse and generally to a lower extent than functionalized MWNTs. The general similarity of the pH effect on all MWNTs investigated in this study may reflect this fact. However, unfunctionalized MWNTs typically possess amorphous carbon and defects on their surface, and it is believed that these features play a pronounced role in the adsorption and desorption process; their effects on the desorption of 1,3,5-TCB and other organic contaminants need further investigation.

Effect of Natural Organic Matter (NOM) The desorption of 1,3,5-TCB under the influence of different concentrations of NOMs is shown in Figure 3. Increases of NOM in solution led to higher desorption for all types of MWNTs. It is generally accepted that NOM plays a crucial role in the adsorption to and desorption from CNTs for all organic compounds. The roles NOMs play are often contradictory in terms of their effect on the adsorption and desorption process. On the one hand, NOMs could facilitate the disperse of CNT bundles in water and make more adsorption sites available for adsorbates, thus increasing the adsorption [41]. On the other hand, NOM would compete with organic compounds for the same adsorption sites or physically block some available adsorption sites for organic compounds, resulting in reduced adsorption. Even though NOMs adsorbed on the CNT surface can function as a new adsorbent, their affinity with organic compounds appears to be smaller than the affinity between CNTs and organic compounds [20]. Both of these competing

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effects are expected to occur during the adsorption and desorption process. With higher dispersion, more MWNT surfaces are exposed to water, which would enhance the desorption of 1,3,5-TCB to the liquid. When the sites become exposed, NOMs might “push away” some of the 1,3,5-TCBs and occupy these sites. However, the similar effect could also apply to 1,3,5TCB; that higher dispersion efficiency would provide more available sites for 1,3,5-TCB. In this study, the increase of NOM concentration generally led to higher desorption, suggesting that this effect is more pronounced for NOM than 1,3,5-TCB. One exception is that the desorption dropped for MWNT-OHs when peptone concentration increased from 0 to 50 mg/L and then rose again with higher peptone concentration. It could be postulated that MWNTs-OH are more “soluble” than other MWNTs and a small fraction of NOM is needed to further disperse them. However, relatively low concentrations of NOM could not occupy all newly opened sites, leaving more space for the adsorption of 1,3,5-TCB. With the increase of NOM in solution, these sites became unavailable to 1,3,5-TCB, and the greater affinity of NOM with MWNTs-OH caused more desorption of 1,3,5-TCB. It is also recognized that NOM is a highly diverse group of large molecular materials and different types of NOMs demonstrate different characteristics of interactions with MWNTs. Peptone is considered as a “fresh” NOM and differs drastically from more mature NOMs, such as humic substances. How different properties of NOMs (e.g., age and degree of aromaticity) affect their interactions with MWNTs and environmental pollutants need more investigation.

Figure 3: Change of the desorption rate of pre-loaded 1,3,5-TCB from MWNTs with concentrations of peptone in solution. The reported values are the average

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of three or four replicates. Error bars stand for standard deviation.

Based on our studies, it is clear that both the solution chemistry and surface properties exert important impacts on the desorption of 1,3,5-TCB from MWNTs. In the natural environment, the solution chemistry is defined by a combination of individual factors, including the ones examined in this investigation. It is essential in future studies to evaluate how those different parameters synergistically affect the desorption of organic compounds from MWNTs. With the continued development in CNT synthesis, more diverse CNTs with unique surface properties will be developed. Future studies should also be extended to evaluate the impacts of other surface functional groups on the adsorption and desorption process. This study provides important insights on the potential environmental implications of the rapid development of carbon-based nanotechnology for the environment. Even though the potential toxicity of CNT itself has been examined extensively, the environmental impact of CNTs resulted from their unique characteristics, such as their huge adsorption capacity for environmental pollutants, has not been fully characterized. Our results suggest that the secondary effect of CNTs vary at different environmental conditions (e.g., freshwater ecosystem vs. estuarine), and the synthesis and modification of surface properties alter the adsorption to and desorption from CNTs for environmental pollutants. Therefore, the potential environmental impact of CNTs needs to be further examined in specific environments. There have been studies to investigate the complex interactions of CNTs and different environmental parameters. What those interactions mean for the adsorption and desorption of environmental pollutants onto CNTs is not clear, but should be explored. The results also suggested that the environmental impact of CNTs with different surface properties vary, and more intensive studies on their environmental consequences will contribute to the manufacturing of CNTs with less environmental impacts.

EXPERIMENTAL SECTION Chemicals 1,3,5-Trichlorobenzene (1,3,5-TCB) 1,3,5-TCB was purchased from Sigma-Aldrich with >99% purity. Selected physicochemical properties of this compound are listed in Supplementary

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Table 1 (Table S1). The molecular structure of 1,3,5-TCB is shown in Supplementary Figure 1A (Figure S1A). Due to the low solubility of 1,3,5-TCB in water, 5000 mg/L of stock solution of 1,3,5-TCB in hexane (>99%) was first prepared; this stock solution was then diluted with deionized (DI) water to different concentrations for the experiments as described below.

Peptone Peptone is commonly used as a representative fresh NOM [42]. Peptone used in this study was also purchased from Sigma-Aldrich. The molecular structure of peptone is shown in Figure S1B.

Carbon Nanotubes Non-functionalized multi-walled carbon nanotubes (MWNTs) and multiwalled carbon nanotubes functionalized with hydroxyl group (MWNT-OH) and carboxyl group (MWNT-COOH) were purchased from U.S. Research Nanomaterials, Inc. According to the manufacturer, the carbon nanotubes were synthesized by the chemical vapor deposition (CVD) method using cobalt, manganese, molybdenum or nickel as catalyst. All MWNTs contained more than 95% of CNTs by weight as determined by thermo gravimetric analysis (TGA). The carbon content was more than 97% for all samples. Other important properties of these MWNTs reported by the manufacturer are summarized in Supplementary Table 2 (Table S2).

Preloading MWNTs with 1,3,5-TCB About 0.5–0.6 g of MWNTs was weighed into a 22 mL vial, and the vial was then filled with DI water to its capacity. The vial was spiked with 1,3,5TCB stock solution (5000 mg/L) to result in a final liquid concentration of 50 mg/L. The volume of hexane in the mixture was kept below 0.1% (v:v) to minimize the co-solvent effect. The vial was then quickly sealed with an aluminum foil-lined Teflon screw cap and placed on a rotary tumbler for 7 days at room temperature (20–23 °C) to achieve equilibrium. The literature has suggested that 7 days are typically adequate for the adsorption and desorption of organic compounds from CNTs to reach equilibrium [24]. At the end of equilibrium, the vial was left on a bench for 1 day to allow MWNT aggregates to settle. The supernatant was transferred to a new vial with a pipette and centrifuged at 14,000 rpm for 10 min to further separate water and MWNTs, which might have been dispersed in the solution, due to tumbling. Our result suggested the fraction is minimum compared with

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the total MWNTs used for loading. About 10 mL of the supernatant was then filtered through 0.2 μm (polytetrafluoroethylene-PTFE) filter. The filtrate was collected and extracted with hexane in a 1:1 ratio (v:v). For the extraction, the hexane and water mixture was shaken vigorously several times and then was tumbled for 3 more days to enhance extraction. Our test with solutions containing a known amount of 1,3,5-TCB suggested that the extraction efficiency of hexane is more than 95%. Following the mixing and separation of the hexane and water phase, 1 mL of solution from the hexane layer was transferred into a Gas Chromatography (GC) vial, and the liquid was directly analyzed for 1,3,5-TCB with a Trace Ultra GC affiliated from an electron capture detector (ECD). ECD is highly sensitive for chlorinated compounds, and the detection limit is in the low µg/L level, significantly lower than the concentrations used in this study. The TCB concentration in the filtrate was determined through a four-point standard curve. The 1,3,5TCB loaded on MWNTS was then calculated based on the following mass balance equation: (1) where Q is the solid concentration, in mg, of 1,3,5-TCB/g MWNTs; Cin is the concentration of 1,3,5-TCB in liquid (in mg/L) before equilibrium (50 mg/L); Vl is the volume of the vial (22 mL); Ce is the concentration of 1,3,5TCB in filtrate (mg/L) determined through GC measurement; M is the mass of MWNTs (g). The experiment was conducted similarly for both functionalized MWNTs to load 1,3,5-TCB on these CNTs. The results suggested that MWNTsOH had greatest affinity for 1,3,5-TCB, followed by MWNTs-COOH and then unfunctionalized MWNTs. Through the adjustment of the amount of MWNTs used in the loading process, the actual concentrations of 1,3,5-TCB on MWNTs were controlled within the range of 2.004–2.346 mg TCB/g MWNTs for all MWNTs in different treatments.

Desorption Experiment The preloaded MWNTs slurry were used to investigate the desorption of 1,3,5-TCB at different environmental conditions. For the desorption study, a certain amount of the CNT slurry was added to a new vial. The vial was then filled with DI water to its capacity and sealed with an aluminum foil lined Teflon cap. The mixture was then tumbled for 7 days in a tumbler. The

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Solution Chemistry: Minerals and Reagents

liquid and MWNTs were separated and 1,3,5-TCB in the liquid quantified, similarly as described above. The precise weight of MWNTs added to the vial was determined at the end of the desorption experiment by drying the residues at 103 °C for a day and calculating the difference between vials containing MWNTs and the blank vial, which was measured before the desorption experiment. The desorption rate defined as the ratio of the concentration of 1,3,5-TCB in water (mg/L) divided by the concentration on MWNTs (mg/g) after equilibrium was then calculated as: (2) where Cl’ is the liquid concentration at equilibrium after the desorption study and was determined through the GC measurement. Cs’ is the solid concentration at equilibrium after desorption and was calculated through the following equation: (3) where Q is the solid concentration obtained from the adsorption study (mg/g), M’ is the mass of preloaded MWNTs added to the vial in the desorption study and Vl is the volume of the vial (22 mL).

Solution Chemistry Parameters Three factors, including the solution pH, ionic strength (IS) and NOM (represented by peptone) were evaluated for their influence on the desorption of pre-laden 1,3,5-TCB from MWNT surface. The pH evaluated ranged from 3 to 11. The IS investigated ranged from 0 (DI water) to 0.7 M (the typical IS of sea water). The IS solution was prepared with either NaCl or CaCl2 to investigate the ion composition effect. Peptone was used as a representative of fresh natural organic matter (NOM) in this study. A very wide range of peptone concentration (0.35–300 mg/L) was selected to represent the varying amount of NOMs in different natural environments. The weight effect of NOM was ignored, due to their relative insignificance, compared to the weight of MWNTs. Three or four replicates were prepared for each treatment.

CONCLUSIONS In summary, the desorption of 1,3,5-TCB from MWNTs was affected by both the solution chemistry and the functional groups on the MWNT

Desorption of 1,3,5-Trichlorobenzene from Multi-Walled Carbon....

437

surface. Higher pH, ionic strength or NOMs in solution generally led to more desorption of 1,3,5-TCB from the MWNTs surface, even though the total 1,3,5-TCB desorbed from MWNTs represented only a small fraction of total 1,3,5-TCB in the systems. However, the dynamics could be drastically different in an open system as in the actual environment. Addition of oxygen-containing functional groups (–OH and –COOH) tended to reduce the desorption of 1,3,5-TCB and strongly affected the desorption patterns of 1,3,5-TCB. In addition to the ionic strength of a solution, the ion composition should also be an important consideration in the study of adsorption and desorption of organic compounds. Multivalent ions showed a stronger effect on the desorption of 1,3,5-TCB than monovalent ions. The results suggested that the desorption of environmental pollutants from MWNTs varies with the environmental conditions, and the secondary risks associated with MWNTs of different surface properties need to be evaluated separately.

ACKNOWLEDGEMENTS This project was partially supported by the Agriculture and Food Research Initiative Competitive Grant No. #2011-67006-30181 from the USDA National Institute of Food and Agriculture.

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INDEX A

B

Accelerating surface functionalization 121 Activation approach 233 Active pharmaceutical ingredients (API) 315 Activity coefficients 315, 318, 325, 328, 329, 330, 336 Advanced oxidation processes (AOPs) 401 Air-liquid interface 177 Antibiotic sorption 81, 105 Applying polyacrylamide (PAM) 141 Approximate quantum thermostat approach 380 Aqueous concentration 282 Aromatic hydrocarbon 81, 89, 90 Artificial solar irradiation 404 Atomic force microscopy (AFM) 115 Attenuated total reflection infrared spectroscopy (ATR-IR) 115 Auger-electron spectroscopy 381 Autoclave reaction system 358

Banded hematite quartzite (BHQ) 60 Batch equilibration (BE) 94 Bimolecular quenching 188, 190, 191 Binary interaction parameter 318 Bio-flotation agent (BFA) 153 Biopolymer regeneration 216

C Carbon nanotubes (CNTs) 401 Carboxylic acid group 77 Carboxylic acid group surface concentration 126 Carboxylic acids 216, 232, 233 Catalytic performance 130 Catalytic wet air oxidation (CWAO) 129 Cellulose acylation 232 Cellulose dissolution 205, 206, 207, 208, 209, 210, 212, 213, 214, 216, 217, 218, 220, 221, 222, 225, 226, 231, 236, 238, 240, 241, 244, 245, 254, 255, 256,

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Solution Chemistry: Minerals and Reagents

257, 261, 263, 267, 269, 270 Cellulose matrix 224 Cellulose solubility 211, 214, 226 Chemical compound 57, 61 Chemical modification 220, 228, 244, 245 Chemical oxygen demand (COD) 357 Chemical potential 295 Clay suspension 275 Coal quality 145 Coal structure 138, 143, 149, 160 Collector chemistry interaction 66 Collector consumption 139 Colloidal stability 127 Commercial microwave 403 Commercial viscose fibers 242 Complete mineralization 368 Complex chemical molecules 319, 324 Complex molecules asymmetric 57 Conventional flotation method 140, 142 Conventional flotation process 139 Critical coagulation concentrations (CCC) 126 Crystal lattice 74, 75, 77, 78, 79, 82, 89, 91, 93 Crystalline cellulose 223, 225 Crystalline cellulose structure 223 Cyclodextrins (CDs) 288

D Deep eutectic solvents (DES) 205 Degrade oxalic acid 129 Degree of substitution (DS) 210 Deutsche Forschungsgemeinschaft (DFG) 392 Dissociation reaction notation 12 Dodecyl amine chloride (DAH) 142

Dodecyl trimethyl ammonium chloride (DTAB) 141 Double-proton transfer 379, 386, 387, 391, 392 Dulbecco’s modified Eagle’s medium (DMEM) 166

E Ecological pyramid 51 Effective electronic 342, 343, 348, 350, 352 Effective thermoelectric transport 343, 350 Efficient methylation 207 Electrical double layer model 128 Electrolytic system 2, 3, 12, 31, 37, 39, 40, 41, 44, 45, 46 Electron capture detector (ECD) 435 Electron-donor-acceptor (EDA) 425 Electron donor-acceptor interactions 424 Electronic optimization 341, 342 Electron spectroscopy 376 Electron-transfer mediated decay (ETMD) 378 Electrophoretic mobility 126, 127 Endocrine disrupter substance (EDC) 369 Energy-dispersive X-ray spectroscopy (EDS) 345 Energy efficiency 341 Environmental engineering 424 Equilibrium adsorption coefficient 76 Equilibrium constants 3, 7, 14, 29, 30, 31, 32, 34, 38, 39 Equilibrium solid phase 4, 9, 10, 22, 24, 25, 26

Index

Equilibrium temperature 321, 332 Ethylene glycol monoethyl ether (EGME) 92 Ethylene glycol-water 333, 334

F Faculty Research and Creative Activity Committee (FRCAC) 131 Far-from-equilibrium 280 Field emission transmission 403 Flotation efficiency 139, 140 Fluorescence emission 178, 179, 181, 182, 183, 184, 185, 186, 187, 192, 193, 194 Fluorescence emission signal 181 Fluorescence quenching 178, 179, 180, 182, 186, 188, 192, 193, 194, 199, 200, 201 Fluorescence spectra 179 Fluorescent dye 166, 167 Forster resonance energy transfer (FRET) 177

G Gangue minerals 50, 51, 52, 55, 67 Gas chromatograph 402, 404, 405 Gas chromatograph-mass spectrometer (GC/MS) 404 Gas phase thermal 129 General effective media (GEM) 342, 343, 350 Generalized approach to electrolytic systems (GATES) 2, 3 Generalized electron balance (GEB) 30 Good approximation 380 Good reproducibility 122 Gram-negative pulmonary infec-

445

tions 165 Ground-state geometry 380, 388

H Hazardous mineral 148 Hexadecyl trimethyl ammonium bromide (HTAB) 142 High performance liquid chromatography (HPLC) 357 Homogeneous 9 Human exposure 73 Human health 137 Hydrated peat structure 85 Hydrocarbon radical 57 Hydrocortisone 295, 296, 297, 300, 302, 303, 310, 312 Hydrogen bond formation 293 Hydrogen-bonding potential 85 Hydrogen bonds 208, 210, 234, 238 Hydrophilic 288, 292, 294 Hydrophilic surface 62 Hydrophobic 71, 72, 74, 77, 78, 79, 80, 82, 86, 88, 89, 90, 91, 92, 93, 96, 97, 108, 111 Hydrophobic adsorption 430 Hydrophobic disposition 138 Hydrophobicity 50, 52, 53, 57, 60, 64, 65, 78, 89, 95, 96, 108 Hydrophobic organic chemicals (HOCs) 72 Hydrophobic protein 176, 177, 186 Hydrophobic tendency 144 Hydrothermal process 413 Hydroxyl functional 91 Hydroxyl group 292 Hydroxypropyl methylcellulose (HPMC) 303

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Solution Chemistry: Minerals and Reagents

I Ingenious process development 50 Inherent floatability 138 Initial concentration 404, 409, 410, 411 Intercalation compounds 93 Intermediate byproduct formation 404, 412 Ionomycin-stimulation 170 Isoelectric point (IEP) 148

L Langmuir isotherm 76, 78, 79, 90 Large hydrophilic macromolecules 176 Large molecular materials 432 Linear behavior 187, 188 Linear relationship 304 Liposomal environment 171 Local binary value 330 Local structural homogeneity 179 Low-intensity magnetic separation (LIMS) 51 Lung surfactant 175, 176, 179, 194, 195, 198, 199 Lyso tracker green (LTG) 167

M Marginal sorption energy 80 Mass action law 7, 31, 39 Mass-spectroscopic (MS) 405 Membrane-associated surfactant protein 176 Metallic values 51, 52 Methyl isobutyl carbinol (MIBC) 61 Microbial flotation 59 Microbial oxidation 143 Microwave assisted hydrothermal (MAH) 402

Mineralogical composition 67 Mineral particulate nature 88 Mineral surface 49, 50, 51, 60, 62, 63, 66 Molecular dynamic 379, 390, 392, 395 Molecular modelling 50 Molecular structures 206, 207, 215 Monochromatic wavelength 403 Monomethyl phthalate (MMP) 357 Morphological structure 403 Multi-walled carbon nanotube (MWNTs) 424, 428

N Nano-technological application 402 Natural environment 281, 282 Natural organic matters (NOMs) 426 Natural resource management 51 Non-equilibrium approach 380 Nonionizing compounds 57 Non-linear regression 83 Non-polar hydrocarbon group 57, 61 Normally occurring radioactive material (NORM) 400 Nuclear magnetic resonance (NMR) 403

O Obtain equilibrium 404 Optical absorption spectra 407 Organic compounds 61, 95 Organic molecules 97 Organic pollutant 401 Organic solvent system 95 Oxalic acid decomposition 130 Oxidized mineral 62

Index

Oxygen atom 89, 91 Oxygen-bearing functional 125

P Particulate organic matter (POM) 83 Pharmaceutical product 288, 294, 301 Pharmaceutical products worldwide 288 Phospholipid bilayer 189, 190, 192, 193, 194 Photoelectron spectroscopy 377 Phthalic acid esters (PAEs) 356 Point of zero charge (PZC) 55 Poly-aromatic hydrocarbons (PAHs) 425 Polycyclic aromatic hydrocarbons 83, 103, 104, 107 Polymerization tendency 236 Potential energy surface 379, 382, 391 Potential toxicity 433 Predict organic electrolyte system 319, 324 Predict solid-liquid equilibrium systems 318 Processing strategy 225 Protein conformation 178, 187 Protonation-deprotonation transition 430

Q Quality fluorescence emission spectra 178 Quantitative structure–activity relationships (QSARs) 95 Quantum chemical methods 379 Quartz crystal microbalance (QCM)

447

115 Quaternary ammonium 90, 205, 206, 208, 214, 217, 227, 237, 245, 252, 254, 257, 262 Quaternary ammonium electrolytes (QAEs) 205 Quaternary ammonium hydroxides 205 Quencher accessibility 187, 190

R Raman spectroscopy 115, 121 Redox system 30, 31 Resofurin-fluorescence 167 Respiratory distress syndrome (RDS) 176 Reverse flotation 137, 147, 155, 156, 157, 158 Room-temperature ionic liquid (RTIL) 119

S Scanning electron microscope (SEM) 406 Segment-based mole fraction 330 Signaling pathways 171 Singular value decomposition (SVD) 180, 184 Socio-economic development 51 Soil organic carbon (SOC) 84 Solar spectra 401 Solid-liquid equilibrium 317, 318, 323, 336 Solubility Data Series (SDS) 2 Solubility product 1, 2, 4, 5, 6, 7, 8, 9, 10, 13, 28, 36, 37, 39, 41 Solubility product values 6, 8, 37 Solute solubility 328 Solvent basicity (SB) 216

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Solution Chemistry: Minerals and Reagents

Sorption antagonism 84 Specific surface area (SSA) 424 Stoichiometric compounds 6 Structure-property relationship 115, 131 Superior sensitivity 122 Surface functional 425, 433 Surface functional group 128 Surface functionalization 115, 130 Surface oxidation 116, 127, 129 Surface oxygen 123, 124, 125, 126, 127 Surface texture 138, 139 Surfactant mixture 59 Surfactant physiology 177 Synthesis procedure 425 Synthetic feed mixture 141 Synthetic organic compounds (SOCs) 425 Synthetic surfactant 177, 178, 179, 181, 182, 183, 186, 187, 190, 191, 192, 195, 198

T Textile application 242 Theoretical analysis 390 Thermal conductivity 122, 341, 342, 345, 347, 348, 349, 350, 351, 352, 353 Thermal conductivity detector 402, 405, 413 Thermodynamic equilibrium criteria 320

Thermodynamic model 315, 317, 318, 323, 331 Thermoelectric efficiency 349, 352 Thermo gravimetric analysis (TGA) 434 Traditional analysis methods 115 Transmission electron microscopy (TEM) 114, 115 Tryptophan fluorescence 181, 182, 188

V Vacuum-based characterization 116 Van-der-Waals interactions 93 Vapor-liquid measurement 335 Various acylation reaction 245 Visible light photocatalytic (VLP) 403, 414 Volatile organic compounds (VOCs) 400

W Waste cooking oil (WCO) 153 Wet air oxidation (WAP) 357 Wet high-gradient magnetic separators (WHGMS) 52 Wet high-intensity magnetic separators (WHIMS) 52 Wet oxygen oxidation (WOP) 357

X X-ray diffraction technique 403 X-ray diffraction (XRD) 274 X-ray spectroscopy (EDX) 116