Full Description
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.
Contents
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
