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Monte Carlo scheme for generation and relaxation of dense and nearly jammed random structures of freely jointed hard-sphere chains

机译:用于自由连接的硬球链的密集和几乎卡住的随机结构的生成和松弛的蒙特卡洛方案

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摘要

We describe a general Monte Carlo (MC) suite for the efficient relaxation of dense systems of freely jointed chains of hard spheres for packing densities (phi) ranging from dilute ones (phi approximate to 0.1) up to the vicinity of the maximally random jammed (MRJ) state (phi approximate to 0.639). Key components of the new MC scheme are as follows: (i) modified versions of state-of-the-art chain-connectivity altering moves tailored to function efficiently even for very dense random chain assemblies and (ii) localized MC moves, all executed in an adaptive configurational-bias pattern. Two different athermal systems were simulated consisting of 100 and 50 chains with average lengths N-av = 12 and 24, respectively, over a wide range of packing densities. In all cases studied, computational efficiency is compared against corresponding results obtained from extensive applications of conventional MC techniques; it is shown that the proposed MC scheme outperforms by several orders of magnitude all existing methods in relaxing the short- and long-range characteristics of the simulated systems and is thus the only available vehicle to generate and equilibrate (and successively characterize) representative model chain configurations near the MRJ state. Structural results, obtained from averaging over very long MC trajectories, show the dependence of bonded geometry (quantified by the bending and torsion angle distributions), chain dimensions (quantified by the end-to-end distance and radius of gyration) and local packing on volume fraction.
机译:我们描述了一个通用的蒙特卡洛(MC)套件,用于有效松弛硬球自由连接链的致密系统,其填充密度(phi)范围从稀疏(phi约为0.1)到最大随机卡塞( MRJ)状态(phi大约为0.639)。新MC方案的关键组成部分如下:(i)先进版本的链连接改变动作的修改版本,即使对于非常密集的随机链组件,其定制也可有效运行,并且(ii)局部MC动作均已执行以自适应配置偏向模式。模拟了两个不同的无热系统,分别由100条和50条链组成,平均链长分别为N-av = 12和24,在很宽的装填密度范围内。在所有研究的案例中,将计算效率与从常规MC技术的广泛应用中获得的相应结果进行比较;结果表明,所提出的MC方案在放宽模拟系统的短期和长期特性方面比所有现有方法好几个数量级,因此是生成和平衡(并连续表征)代表性模型链的唯一可用工具。 MRJ状态附近的配置。通过对非常长的MC轨迹进行平均而获得的结构结果表明,粘结几何形状(通过弯曲和扭转角分布进行量化),链条尺寸(通过端到端距离和回转半径进行量化)和局部堆积的依赖性体积分数。

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