Random Sampling Technique To Predict the Molecular Weight Distribution in Free-Radical Polymerization That Involves Polyfunctional Chain Transfer Agents
Random Sampling Technique To Predict the Molecular Weight Distribution in Free-Radical Polymerization That Involves Polyfunctional Chain Transfer Agents
复制标题
随机取样技术预测涉及多官能链转移剂的自由基聚合中的分子量分布
DOI：
10.1021/ma950693h
复制
发表时间：
1996
期刊：
影响因子：
5.5
通讯作者：
H. Tobita
中科院分区：
文献类型：
--
作者：
H. Tobita
随机取样技术是从反应混合物中的无限数量的聚合物分子中取样，用于预测涉及多官能链转移剂 (P-CTA) 的自由基聚合过程中分子量分布 (MWD) 的发展。对于链转移常数为 1 并且链终止主要由链转移反应主导的理想情况，可以以简单的方式导出完整 MWD 以及平均分子量的解析解。对于更复杂的反应系统，由于双分子终止反应和 P-CTA 的取代效应，非随机历史依赖动力学非常重要，基于随机采样技术的蒙特卡罗模拟使人们能够非常有效地估计统计特性的发展。当涉及双分子终止反应和/或取代效应时，MWD 不一定会因聚合物而变窄......
A random sampling technique in which polymer molecules are sampled from an infinite number of polymer molecules in the reaction mixture is used to predict the molecular weight distribution (MWD) development during free-radical polymerization that involves polyfunctional chain transfer agents (P-CTAs). For an ideal case where the chain transfer constant is unity and chain stoppage is dominated by chain transfer reactions, the analytical solutions for the full MWD as well as the average molecular weights can be derived in a straightforward manner. For more complex reaction systems where nonrandom history-dependent kinetics is important due to bimolecular termination reactions and the substitution effect of the P-CTAs, the Monte Carlo simulation on the basis of the random sampling technique enables one to estimate the statistical property development quite effectively. When bimolecular termination reactions and/or the substitution effects are involved, the MWD does not necessarily become narrower with polyme...