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Combinatoric analysis of heterogeneous stochastic self-assembly

机译:异构随机自组装的组合分析

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We analyze a fully stochastic model of heterogeneous nucleation and self-assembly in a closed system with a fixed total particle number M, and a fixed number of seeds N_s. Each seed can bind a maximum of N particles. A discrete master equation for the probability distribution of the cluster sizes is derived and the corresponding cluster concentrations are found using kinetic Monte-Carlo simulations in terms of the density of seeds, the total mass, and the maximum cluster size. In the limit of slow detachment, we also find new analytic expressions and recursion relations for the cluster densities at intermediate times and at equilibrium. Our analytic and numerical findings are compared with those obtained from classical mass-action equations and the discrepancies between the two approaches analyzed.
机译:我们分析了具有固定总粒子数M和固定种子N_s的封闭系统中的异质成核和自组装的完全随机模型。每个种子最多可以结合N个粒子。得出了一个用于簇大小分布的离散主方程,并使用动力学蒙特卡洛模拟在种子密度,总质量和最大簇大小方面找到了相应的簇浓度。在缓慢脱离的极限中,我们还发现了在中间时间和平衡时的簇密度的新解析表达式和递归关系。我们的分析和数值结果与从经典质量作用方程式获得的结果和两种分析方法之间的差异进行了比较。

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