Monte Carlo Methods in Polymer Reaction Engineering

Apply Monte Carlo methods to predict polymer microstructure and properties
 
Understanding polymer microstructure is critical for engineering functional polymers with targeted macroscopic properties. Monte Carlo Methods in Polymer Reaction Engineering: From Mechanisms to Molecular Architecture provides the first practical treatment of Monte Carlo modeling techniques applied specifically to polymer reaction engineering, equipping readers to program their own simulation algorithms.
 
The book progresses from simple principles to complex modeling scenarios through practical case studies and worked examples. Readers develop the ability to build Monte Carlo algorithms for solving specific polymerization problems. Coverage spans different Monte Carlo methods in a unified framework, connecting reaction mechanisms directly to molecular architecture predictions for real-world polymer systems.
 
Readers will also find:
 
* A didactic structure that builds from foundational Monte Carlo principles to advanced polymer reaction engineering applications with increasing complexity
* Practical case studies demonstrating how Monte Carlo methods predict and control polymer microstructure in academic and industrial settings
* Unified coverage of multiple Monte Carlo methods presented within a single coherent framework tailored to polymer reaction engineering problems
* Worked examples showing how reaction mechanisms connect to molecular architecture predictions for functional polymer design
 
Designed for polymer chemists, chemical engineers, materials scientists, and plastics technologists in both academia and industry, this book provides the practical tools needed to apply Monte Carlo simulation to polymerization systems. PhD students in materials science and engineering sciences will find it a direct path to developing their own modeling capabilities.

1 Preface
 
2 Introduction
2.1 The Uniform Distribution and the Generation of Random Numbers
2.2 Polymerizations are Stochastic Processes
2.3 A Preliminary Monte Carlo Simulation Algorithm
2.4 Chain Length and Molecular Weight Averages
2.5 Final Thoughts
2.6 Extra Readings
 
3 Steady State Monte Carlo Models
3.1 Case Study 3.1: Styrene Free-Radical Polymerization
3.2 Case Study 3.2: Free-Radical Copolymerization of Styrene and Methyl Methacrylate
3.3 Case Study 3.3: Coordination Polymerization with the Formation of Long Chain Branches
3.4 Final Thoughts
3.5 Extra Readings
 
4 Dynamic Monte Carlo Models
4.1 Case Study 4.1 ? Part 1: Step-Growth Polymerization
4.2 Gillespie?s Method: A Stochastic Approach to Dynamic Simulation
4.3 Case Study 4.1 ? Part 2: Gillespie Algorithm for Step-Growth Polymerization
4.4 Case Study 4.1 ? Part 3: Non-Stoichiometric Step-Growth Polymerization
4.5 Reaction Networks and Competing Events
4.6 How to Select the Size of the Control Volume
4.7 Case Study 4.2: Dynamic Styrene Free-Radical Polymerization with Gel Effect
4.8 Case Study 4.3: ATRP Copolymerization of Styrene and n-Butyl Acrylate
4.9 Case Study 4.4: Thermal Degradation of Polystyrene
4.10 Final Thoughts
4.11 Extra Readings
 
5 Optimization of Monte Carlo Methods
5.1 Big O Notation and Computational Complexity
5.2 Compilation versus Interpretation
5.3 Homopolymerization Geometric Sampling
5.4 Copolymerization Geometric Sampling
5.5 Minimizing Random Number Generation Overhead
5.6 Balancing Accuracy and Speed
5.7 Disjoint Set Union for Gelation Tracking
5.8 GPU Parallel Computing
5.9 Final Thoughts
5.10 Extra Readings
 
6 Epilogue: Creating Molecules to Understand Them
6.1 Lessons from Monte Carlo Simulation
6.2 Ten Rules for Writing Monte Carlo Algorithms
6.3 The Expanding Role of Monte Carlo Methods in Polymer Reaction Engineering
6.4 Final Thoughts
 
Appendix A: Instantaneous Chain Length Distribution (CLD) of Polymers Made by Free Radical Polymerization

João Soares is a Professor in the Department of Chemical and Materials Engineering at the University of Alberta and has published more than 180 articles in referred journals, written 12 book chapters, and is an author of the book Polyolefin Reaction Engineering published by Wiley-VCH in 2012. He has offered 27 public and 22 in-house industrial short courses all over the world in his areas of expertise. He is the Editor-in-Chief for the Canadian Journal of Chemical Engineering. He is also a member of the Executive Advisory Board of Wiley-VCH Macromolecular journals and responsible for the coordination of Macromolecular Reaction Engineering. Professor Soares is a Fellow of the Chemical Institute of Canada, and a Professional Engineer in the Provinces of Ontario and Alberta. He is the recipient of various scientific awards and consults for several polyolefin-manufacturing companies in Canada, USA, Europe, Asia, and the Middle East.
 
Amanda Brandão is a PhD student at the Universidade Federal do Rio de Janeiro, working with kinetic of polymerization systems with long chain branches. Her main research interests are: optimal experimental design, modeling and simulation of polymerization systems and optimization of chemical reactors. She got her BSc in Chemical Engineering at Pontifical Catholic University of Rio de Janeiro, and concluded her M.Sc. in Chemical Engineering at Program at Federal University of Rio de Janeiro, working with model discrimination in polymerization systems.

• By (author) Joao B. P. Soares
• By (author) Mohammed Al-Khayyat
• By (author) Amanda L. T. Brandao