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E-raamat: Phase Equilibria in Ionic Liquid Facilitated Liquid-Liquid Extractions

(Indian Institute of Technology Guwahati, Assam, India), (Indian Institute of Technology Guwahati, Assam, India), (Indian Institute of Technology Guwahati, Assam, India), (Ahmedabad University, India)
  • Formaat: PDF+DRM
  • Ilmumisaeg: 31-Mar-2017
  • Kirjastus: CRC Press Inc
  • Keel: eng
  • ISBN-13: 9781498769495
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Phase Equilibria in Ionic Liquid Facilitated Liquid-Liquid ExtractionsSuurem pilt
  • Formaat: PDF+DRM
  • Ilmumisaeg: 31-Mar-2017
  • Kirjastus: CRC Press Inc
  • Keel: eng
  • ISBN-13: 9781498769495
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This book provides a comprehensive overview of ionic liquid based separation techniques. The glimpse of thermodynamic predictive models along with global optimization techniques will help readers understand the separation techniques at molecular and macroscopic levels. Experimental and characterization techniques are coupled with model based predictions so as to provide multicomponent data for the scientific community. The models will focus more on the a-priori based predictions which gives higher emphasis on hydrogen-bonded systems. Particle Swarm Optimization (PSO) technique will also eventually help the readers to apply optimization technique to an extraction process. The overriding goal of this work is to provide pathways for leading engineers and researchers toward a clear understanding and firm grasp of the phase equilibria of Ionic Liquid systems.
List of Figures
ix
List of Tables
xv
Preface xix
About the Authors xxiii
1 Introduction
1(8)
References
5(4)
2 Liquid--Liquid Equilibria: Experiments, Correlation and Prediction
9(44)
2.1 Introduction
9(3)
2.1.1 Extraction of Butanol from Fermentation Broth
10(1)
2.1.2 Extraction of Biochemicals (Acetic Acid and Furfural) from Aqueous Phase
11(1)
2.1.3 Predictive Models
11(1)
2.2 Extraction Methodology
12(1)
2.3 Characterization Techniques
13(2)
2.4 UNIQUAC and Nonrandom Two-Liquid Model Equations
15(2)
2.5 Genetic Algorithm for Prediction of Model Parameters
17(5)
2.6 Ternary and Quaternary LLE Systems
22(13)
2.6.1 Ternary LLE Systems
22(8)
2.6.2 Quaternary Systems for Butanol Recovery
30(5)
2.7 Prediction of Phase Behavior by Statistical Associating Fluid Theory Models
35(18)
2.7.1 LLE Phase Equilibria Computation
39(4)
Appendix A
43(5)
References
48(5)
3 COSMO-SAC: A Predictive Model for Calculating Thermodynamic Properties on a-priori Basis
53(38)
3.1 Liquid-Phase Thermodynamics
53(2)
3.2 Estimation of Electrostatic Contribution
55(25)
3.2.1 Geometry Optimization of the Molecule
56(1)
3.2.2 Segmented Surface
56(1)
3.2.3 Determination of Segment Properties
57(6)
3.2.4 Computation of the Restoring Free Energy (ΔG)
63(1)
3.2.5 Segment Chemical Potential
64(7)
3.2.6 Sigma Profiles of Simple Compounds
71(2)
3.2.7 Sigma Profiles and Potentials of Ionic Liquids
73(2)
3.2.8 Restoring Free Energy
75(5)
3.3 Predictions of Tie Lines
80(2)
3.4 Predictions of LLE of Ionic Liquid Systems
82(9)
Acknowledgments
87(1)
Appendix: Canonical Partition Functions
87(2)
References
89(2)
4 Application of COSMO-SAC in Complex Phase Behavior: Vapor--Liquid--Liquid Equilibria
91(28)
4.1 Introduction
91(1)
4.2 Thermodynamics of VLLE
92(1)
4.3 Experimental Procedure of VLLE
93(1)
4.4 Computational Techniques of VLLE
94(3)
4.5 VLLE by Equilibrium and Flash Approach
97(4)
4.5.1 Equilibrium Equations
97(2)
4.5.2 Flash Equations
99(2)
4.6 Problem Formulation and Predicted Phase Equilibria of VLLE
101(18)
References
117(2)
5 Modification in COSMO-SAC
119(20)
5.1 Introduction
119(2)
5.2 Hydrogen Bonding in Ionic Liquids
121(2)
5.3 Gaussian-Type Probability for Hydrogen Bonding
123(8)
5.3.1 Computational Details
129(2)
5.4 Application of Modified COSMO-SAC in LLE
131(8)
References
137(2)
6 Particle Swarm Optimization and Application to Liquid--Liquid Equilibrium
139(32)
6.1 Introduction
139(1)
6.2 Computational Details
140(10)
6.2.1 Isothermal Sum Rate Algorithm
140(4)
6.2.2 Particle Swarm Optimization Algorithm
144(2)
6.2.3 Problem Formulation
146(4)
6.3 Results and Discussions
150(21)
6.3.1 Tuning of Particle Swarm Optimization Parameters
150(1)
6.3.2 Cost Optimization Results
151(15)
6.3.3 Effect of Ionic Liquid Cost on Optimization
166(2)
References
168(3)
7 Cuckoo Search Optimization and Application to Liquid--Liquid Equilibrium
171(44)
7.1 Introduction
171(4)
7.2 Cuckoo Search Algorithm
175(2)
7.3 Evaluation of Cuckoo Search, Genetic Algorithm and Particle Swarm Optimization Algorithms on Benchmark Functions
177(1)
7.4 Activity Coefficient Models: Nonrandom Two-Liquid and UNIQUAC
178(4)
7.5 Liquid--Liquid Equilibria Modelling
182(1)
7.6 Implementation of Cuckoo Search Algorithm for Multi-Component IL-Based Systems
182(15)
7.6.1 Effect of Bounds
186(1)
7.6.2 Maximum Number of Iterations and Population Size
186(1)
7.6.3 Comparison with Reported Data
187(10)
7.7 Comparison between Cuckoo Search, Genetic Algorithm and Particle Swarm Optimization Algorithms for Multi-Component Systems
197(1)
7.8 Conclusions
198(17)
Nomenclature
208(1)
References
209(6)
Index 215
Anand Bharti is currently a Research Scholar in the Department of Chemical Engineering, Indian Institute of Technology Guwahati, Guwahati, India

Debashis Kundu is currently a Research Scholar in the Department of Chemical Engineering, Indian Institute of Technology Guwahati, Guwahati, India

Dharamashi Rabari is Assistant Professor at the Institute of Engineering and Technology, Ahmedabad University, Ahmedabad, India

Tamal Banerjee is Associate Professor in the Department of Chemical Engineering at the Indian Institute of Technology Guwahati, India.
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