Monte Carlo Applications in Polymer Science (Lecture Notes in Chemistry, 27)

Bruns, W., Motoc, I., O*Driscoll, K. F.

ISBN 10: 3540111654 / ISBN 13: 9783540111658

Published by Springer, 1981

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Bibliographic Details

• Title: Monte Carlo Applications in Polymer Science (Lecture Notes in Chemistry, 27)
• Publisher: Springer
• Publication Date: 1981
• Language: English
• ISBN 10: 3540111654
• ISBN 13: 9783540111658
• Binding: Paperback
• Condition: Very Good
• Dust Jacket Condition: Dust Jacket Included
• Book Type: book

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Synopsis

The aim of this chapter is to discuss in detail the Monte Carlo algorithms developed to compute the sequence distributions in polymers. Because stereoregular polymers constitute a unique form of copolymer, the stereosequence distributions in vinyl homopolymers and the sequence distributions in copolymers can be computed using the same algorithms. Also included is a brief review of probabilistic models (i. e., Bernoulli trials and Markov chains) frequently used to compute the sequence distribtuion. The determination of sequence distributions is important for the under- standing of polymer physical properties, to compute the monomer reactivity para- meters and to discriminate among polymerization mechanisms. 2. 2. Short review of analytical models, Monte Carlo algorithms and computer programs. l A Bernoullian model was developed by Price. Within this model the probability of a given state of the system is independent of the previous state and does not condition the next state. The Bernoullian behaviour has been shown 24 to describe cls-trans distributions among 1, 4 additions in polybutadienes -, 5 the comonomer distribution in ethylene-vinyl acetate copolymer, and configura- 6 tional distributions in polystyrene, poly (vinyl chloride)7, poly (vinyl alcohol)7 Consider the binary copolymerization: 1, J=1,2 (1) where - MI*, I = 1,2, is an ionic or radical polymeric chain end, and M, J = 1,2, J is a monomer. Because the final state (i. e.