颗粒中心模型描述了单分散随机堆积的统计特性
A granocentric model captures the statistical properties of monodisperse random packings
摘要：
我们提出了一个广义的granocentric模型提出[Gracel等人，Nature，2009，460，611615]，其能够描述不仅多分散而且单分散的球体填充内部的局部波动。这种极小模型不考虑粒子的相对位置，但它通过有效的蒙特卡罗方法采样的局部随机过程捕获位置无序。无序的特征在于局部参数的分布，如邻居和接触的数量，围绕中心粒子的填充立体角和细胞体积。模型预测与我们的实验数据在单分散随机紧密堆积的PMMA颗粒。此外，该模型可以用来预测在任何包装的局部波动的分布，只要邻居的平均数，接触和包装分数是已知的。这些分布提供了一个微观基础的统计力学框架堵塞的物质，并使我们能够计算热力学量，如在相空间中的可能堵塞的配置压实。
英文摘要：
We present a generalization of the granocentric model proposed in [Clusel et al., Nature, 2009, 460, 611615] that is capable of describing the local fluctuations inside not only polydisperse but also monodisperse packings of spheres. This minimal model does not take into account the relative particle positions, yet it captures positional disorder through local stochastic processes sampled by efficient Monte Carlo methods. The disorder is characterized by the distributions of local parameters, such as the number of neighbors and contacts, filled solid angle around a central particle and the cell volumes. The model predictions are in good agreement with our experimental data on monodisperse random close packings of PMMA particles. Moreover, the model can be used to predict the distributions of local fluctuations in any packing, as long as the average number of neighbors, contacts and the packing fraction are known. These distributions give a microscopic foundation to the statistical mechanics framework for jammed matter and allow us to calculate thermodynamic quantities such as the compactivity in the phase space of possible jammed configurations.
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