Process Systems Engineering

Volume 6: Molecular Systems Engineering
1. Auflage 2010
ISBN: 978-3-527-31695-3
Verlag: WILEY-VCH

Buch, Englisch, Band 6, 318 Seiten, Format (B × H): 170 mm x 240 mm, Gewicht: 754 g

Reihe: Process Systems Engineering

Inspired by the leading authority in the field, the Centre for Process Systems Engineering at Imperial College London, this book includes theoretical developments, algorithms, methodologies and tools in process systems engineering and applications from the chemical, energy, molecular, biomedical and other areas. It spans a whole range of length scales seen in manufacturing industries, from molecular and nanoscale phenomena to enterprise-wide optimization and control. As such, this will appeal to a broad readership, since the topic applies not only to all technical processes but also due to the interdisciplinary expertise required to solve the challenge.

The ultimate reference for years to come.

Autoren/Hrsg.

Adjiman, Claire

Galindo, Amparo

Weitere Mitwirkende

Pistikopoulos, Efstratios N.

Georgiadis, Michael

Dua, Vivek

Fachgebiete

• Interdisziplinäres Wissenschaften Wissenschaften Interdisziplinär Naturwissenschaften, Technik, Medizin
• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Verfahrenstechnik, Chemieingenieurwesen

Inhaltsverzeichnis

Preface

CRYSTALOPTIMIZER: AN EFFICIENT ALGORITHM FOR LATTICE ENERGY MINIMIZATION OF ORGANIC CRYSTALS USING ISOLATED-MOLECULE QUANTUM MECHANICAL CALCULATIONS

Introduction and Background

Lattice Energy Calculation

CrystalOptimizer: Minimization Using LAMs

Results and Discussion

Conclusions

AN INTRODUCTION TO COARSE-GRAINING APPROACHES: LINKING ATOMISTIC AND MESOSCALES

Introduction

Rigorous Coarse Graining: Partition Function Matching

Coarse Graining by Matching a Specific Property

Coarse Graining for Specific Mesoscale Simulation Techniques

Conclusions and Future Outlook

Appendix A: Dissipative Particle Dynamics

Appendix B: Dynamic Mean-Field Density Functional Theory

HIERARCHICAL MODELING OF POLYMERIC SYSTEMS AT MULTIPHLE TIME AND LENGTH SCALES

Introduction

Atomistic Molecular Dynamics and Monte Carlo Simulation of Polymers: Basic Concepts and Recent Developments

Atomistic Molecular Dynamics and Monte Carlo Simulation of Polymers: Applications

Techniques for the Simulation of the Solubility and Permeability Properties of Polymers

Current Trends

Conclusions and Outlook

GROUP CONTRIBUTION METHODOLOGIES FOR THE PREDICTION OF THERMODYNAMIC PROPERTIES AND PHASE BEHAVIOR IN MIXTURES

Introduction

Pure Component GC Methods

Activity Coefficient GC Methods

GC Methods in Equations of State

The Statistical Associating Fluid Theory (SAFT)

Other Predictive Methods

Concluding Remarks

OPTIMIZATION-BASED APPROACHES TO COMPUTATIONAL MOLECULAR DESIGN

Introduction and Motivation

Quantitative Structure-Property Relationships

Problem Formulations for CAMD

Mathematical Techniques for the Solution of CAMD Optimization Problems

The Tabu Search Algorithm

Case Study

Conclusions and Future Directions

MOLECULAR MODELING OF FORMULATED CONSUMER PRODUCTS

Introduction

Performance Properties of Complex Liquid Formulations

Stability Assessment of Multiphase Formulations

Process Factors: Metastable States of Multiphase Mixtures

Summary

RECENT ADVANCES IN DE NOVO PROTEIN DESIGN

Introduction

De Novo Approach with Fold Specificity

De Novo Approach with Approximate Binding Affinity

Applications and Representative Results

Summary

PRINCIPLES AND METHODOLOGIES FOR THE CONTROLLED FORMATION OF SELF-ASSEMBLED NANOSCALE STRUCTURES WITH DESIRED GEOMETRIES

Overview of the Controlled Nanostructure Formation Approach

Statistical Mechanics and Ergodicity

Methodological Procedures for the Controlled Formation of Desired Nanostructures

Summary

COMPUTER-AIDED METHODOLOGIES FOR THE DESIGN OF REACTION SOLVENTS

Introduction

Solvent Effects on Reactions and the Transition-State Theory

Capturing Solvent Effects with an Empirical Approach

Solvent Design for an Sn2 Reaction with an Empirical Model

Concluding Remarks

Preface
CRYSTALOPTIMIZER: AN EFFICIENT ALGORITHM FOR LATTICE ENERGY MINIMIZATION OF ORGANIC CRYSTALS USING ISOLATED-MOLECULE QUANTUM MECHANICAL CALCULATIONS
Introduction and Background
Lattice Energy Calculation
CrystalOptimizer: Minimization Using LAMs
Results and Discussion
Conclusions
AN INTRODUCTION TO COARSE-GRAINING APPROACHES: LINKING ATOMISTIC AND MESOSCALES
Introduction
Rigorous Coarse Graining: Partition Function Matching
Coarse Graining by Matching a Specific Property
Coarse Graining for Specific Mesoscale Simulation Techniques
Conclusions and Future Outlook
Appendix A: Dissipative Particle Dynamics
Appendix B: Dynamic Mean-Field Density Functional Theory
HIERARCHICAL MODELING OF POLYMERIC SYSTEMS AT MULTIPHLE TIME AND LENGTH SCALES
Introduction
Atomistic Molecular Dynamics and Monte Carlo Simulation of Polymers: Basic Concepts and Recent Developments
Atomistic Molecular Dynamics and Monte Carlo Simulation of Polymers: Applications
Techniques for the Simulation of the Solubility and Permeability Properties of Polymers
Current Trends
Conclusions and Outlook
GROUP CONTRIBUTION METHODOLOGIES FOR THE PREDICTION OF THERMODYNAMIC PROPERTIES AND PHASE BEHAVIOR IN MIXTURES
Introduction
Pure Component GC Methods
Activity Coefficient GC Methods
GC Methods in Equations of State
The Statistical Associating Fluid Theory (SAFT)
Other Predictive Methods
Concluding Remarks
OPTIMIZATION-BASED APPROACHES TO COMPUTATIONAL MOLECULAR DESIGN
Introduction and Motivation
Quantitative Structure-Property Relationships
Problem Formulations for CAMD
Mathematical Techniques for the Solution of CAMD Optimization Problems
The Tabu Search Algorithm
Case Study
Conclusions and Future Directions
MOLECULAR MODELING OF FORMULATED CONSUMER PRODUCTS
Introduction
Performance Properties of Complex Liquid Formulations
Stability Assessment of Multiphase Formulations
Process Factors: Metastable States of Multiphase Mixtures
Summary
RECENT ADVANCES IN DE NOVO PROTEIN DESIGN
Introduction
De Novo Approach with Fold Specificity
De Novo Approach with Approximate Binding Affinity
Applications and Representative Results
Summary
PRINCIPLES AND METHODOLOGIES FOR THE CONTROLLED FORMATION OF SELF-ASSEMBLED NANOSCALE STRUCTURES WITH DESIRED GEOMETRIES
Overview of the Controlled Nanostructure Formation Approach
Statistical Mechanics and Ergodicity
Methodological Procedures for the Controlled Formation of Desired Nanostructures
Summary
COMPUTER-AIDED METHODOLOGIES FOR THE DESIGN OF REACTION SOLVENTS
Introduction
Solvent Effects on Reactions and the Transition-State Theory
Capturing Solvent Effects with an Empirical Approach
Solvent Design for an Sn2 Reaction with an Empirical Model
Concluding Remarks

Über Autor(innen)

Efstratios N. Pistikopoulos is a Professor of Chemical Engineering at Imperial College London and Director of its Centre for Process Systems Engineering (PSE). He graduated in Chemical Engineering from Aristotle University of Thessaloniki, Greece and was awarded a PhD from Carnegie Mellon University, USA. He has authored/ co-authored over 200 publications, holds editorial positions on several editorial boards and has been involved in over 50 major research projects and contracts. Prof. Pistikopoulos is co-founder and Director of two successful spin-off companies stemming from his research at Imperial, Process Systems Enterprise (PSE) Limited and Parametric Optimization Solutions (PAROS) Limited and consults widely to numerous process industry companies.

Michael C. Georgiadis is Associate Professor in the Department of Engineering Informatics and Telecommunications at University of Western Macedonia, Greece and honorary research fellow in the Centre for Process Systems Engineering at Imperial College London. He was manager of academic business development for Process Systems Enterprise Ltd. He obtained his Chemical Engineering Diploma from Aristotle University of Thessaloniki, Greece and an MSc and PhD From Imperial College London. Dr. Georgiadis has authored over 55 papers and two books. He has a long experience in the management and participation of more than 20 collaborative research contracts and projects and consults to Process Systems Enterprise Ltd and Parametric Optimization Solutions Ltd.

Vivek Dua is a Lecturer in the Department of Chemical Engineering at University College London. He holds a degree in Chemical Engineering from Panjab University, Chandigarh, India and MTech in chemical engineering from the Indian Institute of Technology, Kanpur. He joined Kinetics Technology India Ltd. as a Process Engineer before moving to Imperial College London, where he obtained his PhD in Chemical Engineering. He was an Assistant Professor in the Department of Chemical Engineering at Indian Institute of Technology, Delhi before joining University College London. He is a co-founder of Parametric Optimization Solutions (PAROS) Ltd.

Process Systems Enterprise (PSE), provider of the gPROMS advanced process simulation and modelling environment, is the 2007 winner of the Royal Academy of Engineering's MacRobert Award. The award, the UK's most prestigious for engineering, recognises the successful development of innovative ideas. The PSE team was presented with the MacRobert gold medal by HRH Prince Philip.