Improved kinetic Monte Carlo simulation of chemical composition-chain length distributions in polymerization processes

Composite binary trees are introduced for an improved kinetic Monte Carlo (kMC) calculation of chemical composition-chain length distributions (CC-CLDs) in polymerization processes, such as the bivariate copolymer composition-CLD (CoC-CLD). For the calculation of the CC-CLD, each leaf node of the main tree, which reflects the number of macromolecules with a given chain length, serves as a root node for a sub-tree containing information on the CC distribution for the macromolecules with the selected chain length. For low maximum chain lengths of 1000, the improvement consists already in a reduction of the kMC operations by a factor between 103 and 106. The approach is illustrated for the calculation of the CoC-CLD in free and atom transfer radical copolymerization of methyl methacrylate and styrene while accounting for potential diffusional limitations. Main focus is on the capability of the algorithm to ensure an accurate calculation of the average copolymer composition including high chain lengths.

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