This first practical approach to introduce Monte Carlo methods to those working in polymer science makes use of case studies to present a unified and comprehensive overview of various methods.
The author, one of the leading experts in the field, teaches readers how to program Monte Carlo algorithms to solve their own specific problems in polymer reaction engineering, starting with simple principles and moving on to more complex examples. Additional educational software is available online.
The handbook is aimed at polymer scientists and engineers in academia and industry, but is of equal interest to PhD students.
The author, one of the leading experts in the field, teaches readers how to program Monte Carlo algorithms to solve their own specific problems in polymer reaction engineering, starting with simple principles and moving on to more complex examples. Additional educational software is available online.
The handbook is aimed at polymer scientists and engineers in academia and industry, but is of equal interest to PhD students.
Table of Contents
IntroductionThe statistical nature of polymerization and Markov processes
Steady state MC methods
The chemical master equation
Stochastic simulation algorithms
The direct method
The first reaction method
The next reaction method
The optimized reaction method
The sorting direct method
Extensions of stochastic simulation algorithms
Tau–leaping methods
MC methods for stiff systems
Hybrid Deterministic/MC Methods
Concluding remarks
