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Chain-by-Chain Monte Carlo Simulation: A Novel Hybrid Method for Modeling Polymerization. Part I. Linear Controlled Radical Polymerization Systems

机译:逐链蒙特卡洛模拟:一种用于建模聚合的新型混合方法。第一部分:线性控制的自由基聚合系统

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摘要

Kinetic Monte Carlo (kMC) simulation is available for simulating microstructure of polymer chains with as much detail as one seeks at the expense of convergence tests and computational costs. A new hybrid deterministic-probabilistic method is developed as an alternative to kMC that builds chains one-by-one or chain-by-chain and it is named "Chain-by-Chain Monte Carlo" method (CBC-MC). The CBC-MC algorithm is tested on the synthesis of styrene/ methyl methacrylate linear gradient copolymers via nitroxide-mediated polymerization and methyl methacrylate/methyl acrylate linear hyperbolic gradient copolymers via atom transfer radical polymerization. Results are compared with kMC and method of moments and confirm that if applicable, full information regarding the microstructure of chains can be obtained using CBC-MC method with reduced simulation times and smaller sample sizes.
机译:动力学蒙特卡罗(kMC)模拟可用于模拟聚合物链的微观结构,其细节与收敛性测试和计算成本一样多。作为kMC的替代方法,开发了一种新的混合确定性-概率方法,该方法以一对一或逐个链的方式构建链,并被称为“逐链蒙特卡洛”方法(CBC-MC)。通过氮氧化物介导的聚合反应合成苯乙烯/甲基丙烯酸甲酯线性梯度共聚物,以及通过原子转移自由基聚合反应合成甲基丙烯酸甲酯/丙烯酸甲酯线性双曲线梯度共聚物,对CBC-MC算法进行了测试。将结果与kMC和矩量法进行比较,并确认如果适用,可以使用CBC-MC方法以减少的模拟时间和较小的样本量获得有关链的微观结构的完整信息。

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