Modeling in Membranes and Membrane-Based Processes
Description
In addition, this breakthrough new volume covers the fundamentals of polymer membrane pore formation mechanisms, covering not only a wide range of modeling techniques, but also has various facets of membrane-based applications. Thus, this book can be an excellent source for a holistic perspective on membranes in general, as well as a comprehensive and valuable reference work.
Whether a veteran engineer in the field or lab or a student in chemical or process engineering, this latest volume in the "Advances in Membrane Processes" is a must-have, along with the first book in the series, Membrane Processes, also available from Wiley-Scrivener.
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Anirban Roy, PhD, is an Assistant Professor in the Department of Chemical Engineering at BITS Pilani Goa campus. He designs processes for water treatment for applications like industrial wastewater and greywater and has a startup through which he develops membrane-based technologies for both water as well as for biomedical device applications. He has published 14 articles in journals of international repute, filed five patents, and published a book on hemodialysis.
Siddhartha Moulik, PhD, is currently working in and has experience across multiple areas, including chemical engineering, biomass, water management, and others. He has been associated with various industrial sponsored projects for organizations such as TATA Steel, Dr. Reddy's Laboratories, and Tata Chemicals Ltd. He has published 16 articles in international scientific journals, filed one patent, published one book, Membrane Processes, also available from Wiley-Scrivener, and ten book chapters. He is also the recipient of 12 prestigious awards.
Reddi Kamesh, PhD, is a scientist with the Process Engineering and Technology Transfer Dept., CSIR-IICT, Hyderabad, India. He has authored one book chapter and over 40 papers in peer-reviewed international journals and proceedings of conferences. He has been the recipient of the Ambuja Young Researchers Award from Indian Institute of Chemical Engineers (IIChE).
Aditi Mullick, PhD, did her dissertation in wastewater engineering, and her area of research includes the application of novel and sustainable environment friendly routes for water treatment related to organic and inorganic pollutant degradation. She has published seven articles in international journals, filed one patent, and published one book. She is also the recipient of five prestigious national awards and fellowship.
Content
Acknowledgement xiii
1 Introduction: Modeling and Simulation for Membrane Processes 1
Anirban Roy, Aditi Mullick, Anupam Mukherjee and Siddhartha Moulik
References 6
2 Thermodynamics of Casting Solution in Membrane Synthesis 9
Shubham Lanjewar, Anupam Mukherjee, Lubna Rehman, Amira Abdelrasoul and Anirban Roy
2.1 Introduction 10
2.2 Liquid Mixture Theories 11
2.2.1 Theories of Lattices 11
2.2.1.1 The Flory-Huggins Theory 11
2.2.1.2 The Equation of State Theory 12
2.2.1.3 The Gas-Lattice Theory 13
2.2.2 Non-Lattice Theories 13
2.2.2.1 The Strong Interaction Model 13
2.2.2.2 The Heat of Mixing Approach 13
2.2.2.3 The Solubility Parameter Approach 14
2.2.3 The Flory-Huggins Model 15
2.3 Solubility Parameter and Its Application 18
2.3.1 Scatchard-Hildebrand Theory 18
2.3.1.1 The Regular Solution Model 18
2.3.1.2 Application of Hildebrand Equation to Regular Solutions 19
2.3.2 Solubility Scales 20
2.3.3 Role of Molecular Interactions 21
2.3.3.1 Types of Intermolecular Forces 21
2.3.4 Intermolecular Forces: Effect on Solubility 23
2.3.5 Interrelation Between Heat of Vaporization and Solubility Parameter 24
2.3.6 Measuring Units of Solubility Parameter 25
2.4 Dilute Solution Viscometry 26
2.4.1 Types of Viscosities 27
2.4.2 Viscosity Determination and Analysis 28
2.5 Ternary Composition Triangle 32
2.5.1 Typical Ternary Phase Diagram 33
2.5.2 Binodal Line 34
2.5.2.1 Non-Solvent/Solvent Interaction 36
2.5.2.2 Non-Solvent/Polymer Interaction 36
2.5.2.3 Solvent/Polymer Interaction 36
2.5.3 Spinodal Line 36
2.5.4 Critical Point 37
2.5.5 Thermodynamic Boundaries and Phase Diagram 38
2.6 Conclusion 40
2.7 Acknowledgment 40
List of Abbreviations and Symbols 40
Greek Symbols 42
References 42
3 Computational Fluid Dynamics (CFD) Modeling in Membrane-Based Desalination Technologies 47
Pelin Yazgan-Birgi, Mohamed I. Hassan Ali and Hassan A. Arafat
3.1 Desalination Technologies and Modeling Tools 48
3.1.1 Desalination Technologies 48
3.1.2 Tools in Desalination Processes Modeling 49
3.1.3 CFD Modeling Tool in Desalination Processes 55
3.2 General Principles of CFD Modeling in Desalination Processes 56
3.2.1 Reverse Osmosis (RO) Technology 61
3.2.2 Forward Osmosis (FO) Technology 65
3.2.3 Membrane Distillation (MD) Technology 68
3.2.4 Electrodialysis and Electrodialysis Reversal (ED/EDR) Technologies 73
3.3 Application of CFD Modeling in Desalination 77
3.3.1 Applications in Reverse Osmosis (RO) Technology 77
3.3.2 Applications in Forward Osmosis (FO) Technology 95
3.3.3 Applications in Membrane Distillation (MD) Technology 108
3.3.4 Applications in Electrodialysis and Electrodialysis Reversal (ED/EDR) Technologies 121
3.4 Commercial Software Used in Desalination Process Modeling 122
Conclusion 132
References 133
4 Role of Thermodynamics and Membrane Separations in Water-Energy Nexus 145
Anupam Mukherjee, Shubham Lanjewar, Ridhish Kumar, Arijit Chakraborty, Amira Abdelrasoul and Anirban Roy
4.1 Introduction: 1st and 2nd Laws of Thermodynamics 146
4.2 Thermodynamic Properties 148
4.2.1 Measured Properties 148
4.2.2 Fundamental Properties 149
4.2.3 Derived Properties 149
4.2.4 Gibbs Energy 149
4.2.5 1st and 2nd Law for Open Systems 152
4.3 Minimum Energy of Separation Calculation: A Thermodynamic Approach 153
4.3.1 Non-Idealities in Electrolyte Solutions 154
4.3.2 Solution Thermodynamics 154
4.3.2.1 Solvent 155
4.3.2.2 Solute 155
4.3.2.3 Electrolyte 156
4.3.3 Models for Evaluating Properties 157
4.3.3.1 Evaluation of Activity Coefficients Using Electrolyte Models 157
4.3.4 Generalized Least Work of Separation 159
4.3.4.1 Derivation 160
4.4 Desalination and Related Energetics 164
4.4.1 Evaporation Techniques 166
4.4.2 Membrane-Based New Technologies 167
4.5 Forward Osmosis for Water Treatment: Thermodynamic Modelling 173
4.5.1 Osmotic Processes 173
4.5.1.1 Osmosis 174
4.5.1.2 Draw Solutions 175
4.5.2 Concentration Polarization in Osmotic Process 177
4.5.2.1 External Concentration Polarization 177
4.5.2.2 Internal Concentration Polarization 178
4.5.3 Forward Osmosis Membranes 180
4.5.4 Modern Applications of Forward Osmosis 180
4.5.4.1 Wastewater Treatment and Water Purification 181
4.5.4.2 Concentrating Dilute Industrial Wastewater 181
4.5.4.3 Concentration of Landfill Leachate 181
4.5.4.4 Concentrating Sludge Liquids 182
4.5.4.5 Hydration Bags 182
4.5.4.6 Water Reuse in Space Missions 182
4.6 Pressure Retarded Osmosis for Power Generation: A Thermodynamic Analysis 183
4.6.1 What is Pressure Retarded Osmosis? 183
4.6.2 Pressure Retarded Osmosis for Power Generation 184
4.6.3 Mixing Thermodynamics 186
4.6.3.1 Gibbs Energy of Solutions 186
4.6.3.2 Gibbs Free Energy of Mixing 187
4.6.4 Thermodynamics of Pressure Retarded Osmosis 188
4.6.5 Role of Membranes in Pressure Retarded Osmosis 190
4.6.6 Future Prospects of Pressure Retarded Osmosis 191
4.7 Conclusion 192
4.8 Acknowledgment 192
Nomenclature 192
1. Roman Symbols 192
2. Greek Symbols 193
3. Subscripts 194
4. Superscripts 194
5. Acronyms 194
References 195
5 Modeling and Simulation for Membrane Gas Separation Processes 201
Samaneh Bandehali, Hamidreza Sanaeepur, Abtin Ebadi Amooghin and Abdolreza Moghadassi
Abbreviations 201
Nomenclatures 202
Subscripts 203
5.1 Introduction 203
5.2 Industrial Applications of Membrane Gas Separation 205
5.2.1 Air Separation or Production of Oxygen and Nitrogen 205
5.2.2 Hydrogen Recovery 206
5.2.3 Carbon Dioxide Removal from Natural Gas and Syn Gas Purification 210
5.3 Modeling in Membrane Gas Separation Processes 210
5.3.1 Mathematical Modeling for Membrane Separation of a Gas Mixture 210
5.3.2 Modeling in Acid Gas Separation 218
5.4 Process Simulation 221
5.4.1 Gas Treatment Modeling in Aspen HYSYS 222
5.5 Modeling of Gas Separation by Hollow-Fiber Membranes 225
5.6 CFD Simulation 227
5.6.1 Hollow Fiber Membrane Contactors (HFMCs) 227
5.7 Conclusions 228
References 229
6 Gas Transport through Mixed Matrix Membranes (MMMs): Fundamentals and Modeling 237
Rizwan Nasir, Hafiz Abdul Mannan, Danial Qadir, Hilmi Mukhtar, Dzeti Farhah Mohshim and Aymn Abdulrahman
6.1 History of Membrane Technology 237
6.2 Separation Mechanisms for Gases through Membranes 238
6.3 Overview of Mixed Matrix Membranes 242
6.3.1 Material and Synthesis of Mixed Matrix Membrane 242
6.3.2 Performance Analysis of Mixed Matrix Membranes 242
6.4 MMMs Performance Prediction Models 243
6.4.1 New Approaches for Performance Prediction of MMMs 246
6.5 Future Trends and Conclusions 246
6.6 Acknowledgment 253
References 253
7 Application of Molecular Dynamics Simulation to Study the Transport Properties of Carbon Nanotubes-Based Membranes 257
Maryam Ahmadzadeh Tofighy and Toraj Mohammadi
7.1 Introduction 258
7.2 Carbon Nanotubes (CNTs) 259
7.3 CNTs Membranes 263
7.4 MD Simulations of CNTs and CNTs Membranes 265
7.5 Conclusions 271
References 272
8 Modeling of Sorption Behaviour of Ethylene Glycol-Water Mixture Using Flory-Huggins Theory 277
Haresh K Dave and Kaushik Nath
8.1 Introduction 278
8.2 Materials and Method 281
8.2.1 Chemicals 281
8.2.2 Preparation and Cross-Linking of Membrane 281
8.2.3 Determination of Membrane Density 281
8.2.4 Sorption of Pure Ethylene Glycol and Water in the Membrane 282
8.2.5 Sorption of Binary Solution in the Membrane 282
8.2.6 Model for Pure Solvent in PVA/PES Membrane Using F-H Equation 283
8.2.7 Model for Binary EG-Water Sorption Using F-H Equation 285
8.3 Results and Discussion 289
8.3.1 Sorption in the PVA-PES Membrane 289
8.3.2 Determination of F-H Parameters Between Water and Ethylene Glycol (Xw-EG) 290
8.3.3 Determination of F-H Parameters for Solvent and Membrane (¿wm and ¿EGm) 292
8.3.4 Modeling of Sorption Behaviour Using F-H Parameters 293
8.4 Conclusions 296
Nomenclature 297
Greek Letters 298
Acknowledgement 298
References 298
9 Artificial Intelligence Model for Forecasting of Membrane Fouling in Wastewater Treatment by Membrane Technology 301
Khac-Uan Do and Félix Schmitt
9.1 Introduction 302
9.1.1 Membrane Filtration in Wastewater Treatment 302
9.1.2 Membrane Fouling in Membrane Bioreactors and its Control 302
9.1.3 Models for Membrane Fouling Control 304
9.1.4 Objectives of the Study 305
9.2 Materials and Methods 305
9.2.1 AO-MBR System 305
9.2.2 The AI Modeling in this Study 305
9.2.3 Analysis Methods 307
9.3 Results and Discussion 308
9.3.1 Membrane Fouling Prediction Based on AI Model 308
9.3.2 Discussion on Using AI Model to Predict Membrane Fouling 316
9.4 Conclusion 320
Acknowledgements 321
References 321
10 Membrane Technology: Transport Models and Application in Desalination Process 327
Lubna Muzamil Rehman, Anupam Mukherjee, Zhiping Lai and Anirban Roy
10.1 Introduction 328
10.2 Historical Background 331
10.3 Theoretical Background and Transport Models 335
10.3.1 Classical Solution Diffusion Model 336
10.3.2 Extended Solution-Diffusion Model 339
10.3.3 Modified Solution-Diffusion-Convection Model 341
10.3.4 Pore Flow Model (PFM) 342
10.3.5 Electrolyte Transport and Electrokinetic Models 344
10.3.6 Kedem-Katchalsky Model - An Irreversible Thermodynamics Model 346
10.3.7 Spiegler-Kedem Model 346
10.3.8 Mixed-Matrix Membrane Models 347
10.3.9 Thin Film Composite Membrane Transport Models 348
10.3.10 Membrane Distillation 349
10.4 Limitations of Current Membrane Technology 351
10.4.1 External Concentration Polarisation 351
10.4.2 Internal Concentration Polarisation 352
10.4.3 External Concentration Polarisation Due to Membrane Biofouling 354
10.5 Recent Advances of Membrane Technology in RO, FO, and PRO 355
10.5.1 Hybrids 358
10.5.2 Other Membrane Desalination Technologies 359
10.5.2.1 Membrane Distillation 359
10.5.2.2 Reverse Electrodialysis (RED) 360
10.6 Techno-Economical Analysis 360
10.7 Conclusion 362
List of Abbreviations and Symbols 363
Greek Symbols 365
Suffix 366
References 366
Index 375
1
Introduction: Modeling and Simulation for Membrane Processes
Anirban Roy1*, Aditi Mullick2, Anupam Mukherjee1 and Siddhartha Moulik2┼
1 Department of Chemical Engineering, BITS Pilani Goa Campus, Goa India
2 Cavitation and Dynamics Lab, CSIR-Indian Institute of Chemical Technology, Hyderabad, India
Abstract
The chapter introduces the book to the reader. This chapter discusses about the evolution of membrane technology as well as related mathematical modeling. It is needless to state that mathematical modeling is imperative as far as industrial scale up or process feasibility analysis is concerned. However, the interplay of various mathematical modeling has contributed significantly to the development of membrane technology. From molecular interaction to transport models to computational fluid dynamics models to thermodynamic perspectives, mathematical modeling has been an "inseparable" ingredient to one of the most advanced "separation" technology devised by man.
Keywords: Mathematical modeling, simulation, membrane technology
Membrane Separation Process is a frontier area of research with diversified portfolio of applications [1]. The history of membrane based separation process can be traced back to the discovery by Thomas Graham (1805-1869) where he observed solute transported through a vegetable parchment to water. He was the first person to coin the term 'dialysis' for the phenomenon [2]. However, experimental inquisitiveness and industrial translation is a long road to transverse with innumerable challenges to overcome. Two world wars did not serve any good too, but definitely changed the demographic sensitivities as well as did the unthinkable [3]. The wars pushed the human civilizations to look for solutions which challenged the framework of contemporary thought processes. Biomedical engineering to nuclear technology, tremendous advances made in short periods to vanquish the enemy, laid the path for posterity. In this whole journey,mankind witnessed and experienced scarce resources become a plenty and resources, otherwise thought to be inexhaustible became challenged. Water is one such example.
Fast forward to the 1960's, the revolutionary discovery by Sidney Loeb and S.Souirajan changed the complete scenario with invention of phase inversion technology [4-5]. The feasibility of obtaining drinking water from sea became a reality and mankind took a giant leap to it's sustenance. Suddenly it seemed that challenges posed by nature could be overcome by technological advances. Soon the dry lands were dryno more and agricul-turebloomed, civilizations prospered and humankind advanced [4].
Similar is the story of biomedical sectors. From the world war II, "Surgeon Hero" era, where collaborative knowledge enhancement between section became restricted, this sector experienced exponential growth [3]. During World War II, the government regulations were minimum with regard to human protection from medical trials. The doctors enjoyed tremendous freedom but on the other hand, were continually pressurized to preserve a resource which ran cant life of a soldier. The doctors had to resort to desperate measures in order to preserve a dying soldier's life and often took unthinkable risks in order to try various avenues to restore an organ/ organs for a soldier. Thus the term "Surgeon Hero" was coined as they were the indeed the less celebrated heroes of a deadly war. However during these years, a number of solutions were either tried or their seeds were sown to reap benefits later. From dental implants to intralocular lenses to vascular grafts as well as pacemakers- all were either conceived or tried, attributed to the "Surgeon Hero" era [3, 7, 8]. However, the field of membranes also had its foundation laid due to successful trials of an artificial kidney during these years, which laid to the foundation of Hemodialysis. Hemodialysis had an interesting history as during 1913-1944, as a consequence of two wars, the technological development went on simultaneously in the respective nations involved in the conflict [7-11]. However, one was oblivious of the development of other, so much so that the research of John Abel at Jokhns Hopkins was halted as anticoagulant obtained from leeches were not available. Good quality leeches were soured from Hungary which the WW I stopped to be imported to USA, thereby inhibiting development. Fast forward 1970's, with development of capillary membranes, and Seattle groups "1 m2 hypothesis", membranes for artificial kidney became a lifesaving technology [5].
The two most important fluids in human life- water and blood- in today's world has some relation or the other with membrane technology. Both the reverse osmosis and hemodialysis technology enjoy the major share of a membrane market. Thus, market driven needs of two most important needs for human survival has led to both maturity of technological development as well as customer segmentation. Now, membranes find application in oxygenation, hemoconcentration, artificial kidney, reverse osmosis for desalination, ultrafiltration for general water treatment, as well as for applications like bioreactor systems [6]. In fact, state of art of membranes are being researched and developed for specialized applications like generating power from salinity gradients. Technologies like Pressure Retarded Osmosis (PRO) is the next challenge where the Gibbs Energy of mixing of rivers and sea water is harvested to run turbines [7]. The membrane market is projected to reach a USD 2.8 billion by 2020 [8]. It is thus a great success story for the human race to be able to conceive, prototype, build and sustain a technology and eventually make it a commercial success. However, the most important aspect to note is that such a scale of application as well as commercial maturity took time. It took almost a century for simple "ideas" to find their way, meandering through a plethora of challenges to reach this stage. For any process or technological development at the laboratory scale, there lies innumerable hindrances towards its successful implementation at the commercial level. For developing proper understanding and related challenges for scaling up, mathematical modeling is a very important tool [9]. It provides quick insights in the parameters like flux, fouling and resistance building in membrane system [10] [11]. Modeling not only provides scaling up insights, but also helps understand the irreversibility's occurring in modules. Membrane coupon scale results are often misleading when one tries to understand phenomenon like fouling and pressure loses [12]. Flat sheet membrane coupon scale experiments can yield certain results which can either underpredict or overpredict real life scaled up results. This can, more often than not, give rise to false expectations, thereby giving encouragement or discouragement which is false placed. There are generally three broad kinds of mathematical modeling encountered in literature. The first is modeling for transport process which involves first principle based models and simulation of results. This is the oldest approach which membrane engineers have been resorting to. From simple to fairly complicated systems can easily be solved using this approach. From liquid filtration to gas permeation, first principle based modeling approach has proven to be a versatile approach to understand membrane separation. The second type of modeling approach is based on classical thermodynamics. This approach is extremely useful for modeling systems like phase inversion and pore formation in polymer membrane synthesis [13]. Thermodynamics also helps us in understanding the entropy generation and thus related irreversibilities in processes, which in itself an indication on the probable steps which could be taken to mitigate them. Thermodynamic approach also helps us in understanding feasibility of processes and thus gives an idea on how membrane technology intervention can improve efficiencies. The third kind of modeling approach is more recent and has gained popularity over the years due to (i) advent of computers and (ii) robust algorithms to solve non-linear fluid flow equations. This is called Computational Fluid Dynamics (CFD) modeling and is now extensively used in membrane related applications [14] [15]. A schematic representation is shown in Figure 1.1.
CFD is now being implemented in areas like membrane module design, packing efficiency calculations, flow phenomena understanding and various other domains which was previously unexplored. A classic example of mathematical modeling in membrane systems is design of reverse osmosis (RO) modules [16]. While first principle based modeling and calculations were used previously to understand flux and fouling, thermodynamic modeling has been used to understand the minimum energies of desalination [17]. The first principle modeling and thermodynamic modeling gave an idea on the deviation from theoretical limits and ideas started developing on how to actually engineer systems so that minimum energies for desalination can be obtained [18]. CFD modeling of flow in commercial modules and design of modules were implemented to get better hydrodynamic flow patterns evolving better results in minimized fouling and greater fluxes. This coupled with energy recovery devices have significantly improved the energies of separation in desalination...
