Full Paper
A Parallelised High Performance Monte Carlo Simulation Approach for Complex Polymerisation Kinetics
Article first published online: 20 JUL 2007
DOI: 10.1002/mats.200700028
Copyright © 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Additional Information
How to Cite
Chaffey-Millar, H., Stewart, D., Chakravarty, M. M. T., Keller, G. and Barner-Kowollik, C. (2007), A Parallelised High Performance Monte Carlo Simulation Approach for Complex Polymerisation Kinetics. Macromol. Theory Simul., 16: 575–592. doi: 10.1002/mats.200700028
Publication History
- Issue published online: 21 AUG 2007
- Article first published online: 20 JUL 2007
- Manuscript Revised: 6 JUN 2007
- Manuscript Accepted: 6 JUN 2007
- Manuscript Received: 10 APR 2007
Funded by
- University of New South Wales (UNSW, Sydney, Australia)
- Faculty of Engineering, UNSW
- Abstract
- Article
- References
- Cited By
Keywords:
- computer modeling;
- kinetics (polym.);
- Monte Carlo simulation;
- parallel computation
Abstract

A novel, parallelised approach to Monte Carlo simulations for the computation of full molecular weight distributions (MWDs) arising from complex polymerisation reactions is presented. The parallel Monte Carlo method constitutes perhaps the most comprehensive route to the simulation of full MWDs of multiple chain length polymer entities and can also provide detailed microstructural information. New fundamental insights have been developed with regard to the Monte Carlo process in at least three key areas: (i) an insufficient system size is demonstrated to create inaccuracies via poor representation of the most improbable events and least numerous species; (ii) advanced algorithmic principles and compiler technology known to computer science have been used to provide speed improvements and (iii) the parallelisability of the algorithm has been explored and excellent scalability demonstrated. At present, the parallel Monte Carlo method presented herein compares very favourably in speed with the latest developments in the h-p Galerkin method-based PREDICI software package while providing significantly more detailed microstructural information. It seems viable to fuse parallel Monte Carlo methods with those based on the h-p Galerkin methods to achieve an optimum of information depths for the modelling of complex macromolecular kinetics and the resulting microstructural information.

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