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二维多分散随机密堆积问题的解析解

Analytical solution for the polydisperse random close packing problem in 2D

Alessio Zaccone

AI总结:

本文基于已验证的拥挤平衡模型,提出二维多分散硬磁盘随机密堆积密度的解析理论,能预测其随直径分布标准差均值比$s$的变化,对$s=0.246$的幂律分布预测结果与最新数值估计吻合良好。

摘要:

本文利用拥挤平衡模型[A. Zaccone, Phys. Rev. Lett. 128, 028002 (2022)],为二维多分散硬磁盘的随机密堆积密度$ϕ_\textrm{RCP}$提供了一种解析理论。该模型已通过硬球相图中最大随机堵塞(MRJ)线的大量数值分析得到验证[Anzivino等, J. Chem. Phys. 158, 044901 (2023)]。该解依赖于硬磁盘流体的状态方程,并预测了$ϕ_\textrm{RCP}$作为磁盘直径分布标准差与其均值之比$s$的函数。对于$s=0.246$的幂律尺寸分布,该理论得出$ϕ_\textrm{RCP}=0.892$,与基于蒙特卡洛交换算法的最新数值估计$ϕ_\textrm{RCP}=0.905$[Ghimenti、Berthier、van Wijland, Phys. Rev. Lett. 133, 028202 (2024)]吻合良好。

英文摘要:

An analytical theory for the random close packing density, $ϕ_\textrm{RCP}$, of polydisperse hard disks is provided using an equilibrium model of crowding [A. Zaccone, Phys. Rev. Lett. 128, 028002 (2022)] which has been justified on the basis of extensive numerical analysis of the maximally random jammed (MRJ) line in the phase diagram of hard spheres [Anzivino et al., J. Chem. Phys. 158, 044901 (2023)]. The solution relies on the equations of state for the hard disk fluid and provides predictions for $ϕ_\textrm{RCP}$ as a function of the ratio, $s$, of the standard deviation of the distribution of disk diameters to its mean. For a power-law size distribution with $s=0.246$, the theory yields $ϕ_\textrm{RCP} =0.892$, which compares well with the most recent numerical estimate $ϕ_\textrm{RCP} =0.905$ based on the Monte-Carlo swap algorithms [Ghimenti, Berthier, van Wijland, Phys. Rev. Lett. 133, 028202 (2024)].

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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