Modeling in Membranes and Membrane-Based Processes

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.

• Acknowledgement xiii1 Introduction: Modeling and Simulation for Membrane Processes 1Anirban Roy, Aditi Mullick, Anupam Mukherjee and Siddhartha MoulikReferences 62 Thermodynamics of Casting Solution in Membrane Synthesis 9Shubham Lanjewar, Anupam Mukherjee, Lubna Rehman, Amira Abdelrasoul and Anirban Roy2.1 Introduction 102.2 Liquid Mixture Theories 112.2.1 Theories of Lattices 112.2.1.1 The Flory-Huggins Theory 112.2.1.2 The Equation of State Theory 122.2.1.3 The Gas-Lattice Theory 132.2.2 Non-Lattice Theories 132.2.2.1 The Strong Interaction Model 132.2.2.2 The Heat of Mixing Approach 132.2.2.3 The Solubility Parameter Approach 142.2.3 The Flory–Huggins Model 152.3 Solubility Parameter and Its Application 182.3.1 Scatchard-Hildebrand Theory 182.3.1.1 The Regular Solution Model 182.3.1.2 Application of Hildebrand Equation to Regular Solutions 192.3.2 Solubility Scales 202.3.3 Role of Molecular Interactions 212.3.3.1 Types of Intermolecular Forces 212.3.4 Intermolecular Forces: Effect on Solubility 232.3.5 Interrelation Between Heat of Vaporization and Solubility Parameter 242.3.6 Measuring Units of Solubility Parameter 252.4 Dilute Solution Viscometry 262.4.1 Types of Viscosities 272.4.2 Viscosity Determination and Analysis 282.5 Ternary Composition Triangle 322.5.1 Typical Ternary Phase Diagram 332.5.2 Binodal Line 342.5.2.1 Non-Solvent/Solvent Interaction 362.5.2.2 Non-Solvent/Polymer Interaction 362.5.2.3 Solvent/Polymer Interaction 362.5.3 Spinodal Line 362.5.4 Critical Point 372.5.5 Thermodynamic Boundaries and Phase Diagram 382.6 Conclusion 402.7 Acknowledgment 40List of Abbreviations and Symbols 40Greek Symbols 42References 423 Computational Fluid Dynamics (CFD) Modeling in Membrane-Based Desalination Technologies 47Pelin Yazgan-Birgi, Mohamed I. Hassan Ali and Hassan A. Arafat3.1 Desalination Technologies and Modeling Tools 483.1.1 Desalination Technologies 483.1.2 Tools in Desalination Processes Modeling 493.1.3 CFD Modeling Tool in Desalination Processes 553.2 General Principles of CFD Modeling in Desalination Processes 563.2.1 Reverse Osmosis (RO) Technology 613.2.2 Forward Osmosis (FO) Technology 653.2.3 Membrane Distillation (MD) Technology 683.2.4 Electrodialysis and Electrodialysis Reversal (ED/EDR) Technologies 733.3 Application of CFD Modeling in Desalination 773.3.1 Applications in Reverse Osmosis (RO) Technology 773.3.2 Applications in Forward Osmosis (FO) Technology 953.3.3 Applications in Membrane Distillation (MD) Technology 1083.3.4 Applications in Electrodialysis and Electrodialysis Reversal (ED/EDR) Technologies 1213.4 Commercial Software Used in Desalination Process Modeling 122Conclusion 132References 1334 Role of Thermodynamics and Membrane Separations in Water-Energy Nexus 145Anupam Mukherjee, Shubham Lanjewar, Ridhish Kumar, Arijit Chakraborty, Amira Abdelrasoul and Anirban Roy4.1 Introduction: 1st and 2nd Laws of Thermodynamics 1464.2 Thermodynamic Properties 1484.2.1 Measured Properties 1484.2.2 Fundamental Properties 1494.2.3 Derived Properties 1494.2.4 Gibbs Energy 1494.2.5 1st and 2nd Law for Open Systems 1524.3 Minimum Energy of Separation Calculation: A Thermodynamic Approach 1534.3.1 Non-Idealities in Electrolyte Solutions 1544.3.2 Solution Thermodynamics 1544.3.2.1 Solvent 1554.3.2.2 Solute 1554.3.2.3 Electrolyte 1564.3.3 Models for Evaluating Properties 1574.3.3.1 Evaluation of Activity Coefficients Using Electrolyte Models 1574.3.4 Generalized Least Work of Separation 1594.3.4.1 Derivation 1604.4 Desalination and Related Energetics 1644.4.1 Evaporation Techniques 1664.4.2 Membrane-Based New Technologies 1674.5 Forward Osmosis for Water Treatment: Thermodynamic Modelling 1734.5.1 Osmotic Processes 1734.5.1.1 Osmosis 1744.5.1.2 Draw Solutions 1754.5.2 Concentration Polarization in Osmotic Process 1774.5.2.1 External Concentration Polarization 1774.5.2.2 Internal Concentration Polarization 1784.5.3 Forward Osmosis Membranes 1804.5.4 Modern Applications of Forward Osmosis 1804.5.4.1 Wastewater Treatment and Water Purification 1814.5.4.2 Concentrating Dilute Industrial Wastewater 1814.5.4.3 Concentration of Landfill Leachate 1814.5.4.4 Concentrating Sludge Liquids 1824.5.4.5 Hydration Bags 1824.5.4.6 Water Reuse in Space Missions 1824.6 Pressure Retarded Osmosis for Power Generation: A Thermodynamic Analysis 1834.6.1 What is Pressure Retarded Osmosis? 1834.6.2 Pressure Retarded Osmosis for Power Generation 1844.6.3 Mixing Thermodynamics 1864.6.3.1 Gibbs Energy of Solutions 1864.6.3.2 Gibbs Free Energy of Mixing 1874.6.4 Thermodynamics of Pressure Retarded Osmosis 1884.6.5 Role of Membranes in Pressure Retarded Osmosis 1904.6.6 Future Prospects of Pressure Retarded Osmosis 1914.7 Conclusion 1924.8 Acknowledgment 192Nomenclature 1921. Roman Symbols 1922. Greek Symbols 1933. Subscripts 1944. Superscripts 1945. Acronyms 194References 1955 Modeling and Simulation for Membrane Gas Separation Processes 201Samaneh Bandehali, Hamidreza Sanaeepur, Abtin Ebadi Amooghin and Abdolreza MoghadassiAbbreviations 201Nomenclatures 202Subscripts 2035.1 Introduction 2035.2 Industrial Applications of Membrane Gas Separation 2055.2.1 Air Separation or Production of Oxygen and Nitrogen 2055.2.2 Hydrogen Recovery 2065.2.3 Carbon Dioxide Removal from Natural Gas and Syn Gas Purification 2105.3 Modeling in Membrane Gas Separation Processes 2105.3.1 Mathematical Modeling for Membrane Separation of a Gas Mixture 2105.3.2 Modeling in Acid Gas Separation 2185.4 Process Simulation 2215.4.1 Gas Treatment Modeling in Aspen HYSYS 2225.5 Modeling of Gas Separation by Hollow-Fiber Membranes 2255.6 CFD Simulation 2275.6.1 Hollow Fiber Membrane Contactors (HFMCs) 2275.7 Conclusions 228References 2296 Gas Transport through Mixed Matrix Membranes (MMMs): Fundamentals and Modeling 237Rizwan Nasir, Hafiz Abdul Mannan, Danial Qadir, Hilmi Mukhtar, Dzeti Farhah Mohshim and Aymn Abdulrahman6.1 History of Membrane Technology 2376.2 Separation Mechanisms for Gases through Membranes 2386.3 Overview of Mixed Matrix Membranes 2426.3.1 Material and Synthesis of Mixed Matrix Membrane 2426.3.2 Performance Analysis of Mixed Matrix Membranes 2426.4 MMMs Performance Prediction Models 2436.4.1 New Approaches for Performance Prediction of MMMs 2466.5 Future Trends and Conclusions 2466.6 Acknowledgment 253References 2537 Application of Molecular Dynamics Simulation to Study the Transport Properties of Carbon Nanotubes-Based Membranes 257Maryam Ahmadzadeh Tofighy and Toraj Mohammadi7.1 Introduction 2587.2 Carbon Nanotubes (CNTs) 2597.3 CNTs Membranes 2637.4 MD Simulations of CNTs and CNTs Membranes 2657.5 Conclusions 271References 2728 Modeling of Sorption Behaviour of Ethylene Glycol-Water Mixture Using Flory-Huggins Theory 277Haresh K Dave and Kaushik Nath8.1 Introduction 2788.2 Materials and Method 2818.2.1 Chemicals 2818.2.2 Preparation and Cross-Linking of Membrane 2818.2.3 Determination of Membrane Density 2818.2.4 Sorption of Pure Ethylene Glycol and Water in the Membrane 2828.2.5 Sorption of Binary Solution in the Membrane 2828.2.6 Model for Pure Solvent in PVA/PES Membrane Using F-H Equation 2838.2.7 Model for Binary EG-Water Sorption Using F-H Equation 2858.3 Results and Discussion 2898.3.1 Sorption in the PVA-PES Membrane 2898.3.2 Determination of F-H Parameters Between Water and Ethylene Glycol (Xw−EG) 2908.3.3 Determination of F-H Parameters for Solvent and Membrane (χwm and χEGm) 2928.3.4 Modeling of Sorption Behaviour Using F-H Parameters 2938.4 Conclusions 296Nomenclature 297Greek Letters 298Acknowledgement 298References 2989 Artificial Intelligence Model for Forecasting of Membrane Fouling in Wastewater Treatment by Membrane Technology 301Khac-Uan Do and Félix Schmitt9.1 Introduction 3029.1.1 Membrane Filtration in Wastewater Treatment 3029.1.2 Membrane Fouling in Membrane Bioreactors and its Control 3029.1.3 Models for Membrane Fouling Control 3049.1.4 Objectives of the Study 3059.2 Materials and Methods 3059.2.1 AO-MBR System 3059.2.2 The AI Modeling in this Study 3059.2.3 Analysis Methods 3079.3 Results and Discussion 3089.3.1 Membrane Fouling Prediction Based on AI Model 3089.3.2 Discussion on Using AI Model to Predict Membrane Fouling 3169.4 Conclusion 320Acknowledgements 321References 32110 Membrane Technology: Transport Models and Application in Desalination Process 327Lubna Muzamil Rehman, Anupam Mukherjee, Zhiping Lai and Anirban Roy10.1 Introduction 32810.2 Historical Background 33110.3 Theoretical Background and Transport Models 33510.3.1 Classical Solution Diffusion Model 33610.3.2 Extended Solution-Diffusion Model 33910.3.3 Modified Solution-Diffusion-Convection Model 34110.3.4 Pore Flow Model (PFM) 34210.3.5 Electrolyte Transport and Electrokinetic Models 34410.3.6 Kedem–Katchalsky Model – An Irreversible Thermodynamics Model 34610.3.7 Spiegler–Kedem Model 34610.3.8 Mixed-Matrix Membrane Models 34710.3.9 Thin Film Composite Membrane Transport Models 34810.3.10 Membrane Distillation 34910.4 Limitations of Current Membrane Technology 35110.4.1 External Concentration Polarisation 35110.4.2 Internal Concentration Polarisation 35210.4.3 External Concentration Polarisation Due to Membrane Biofouling 35410.5 Recent Advances of Membrane Technology in RO, FO, and PRO 35510.5.1 Hybrids 35810.5.2 Other Membrane Desalination Technologies 35910.5.2.1 Membrane Distillation 35910.5.2.2 Reverse Electrodialysis (RED) 36010.6 Techno-Economical Analysis 36010.7 Conclusion 362List of Abbreviations and Symbols 363Greek Symbols 365Suffix 366References 366Index 375