元动力学
统计物理学
蒙特卡罗方法
亚稳态
熵(时间箭头)
蒙特卡罗分子模拟
物理
结晶
能源景观
粒子(生态学)
胶粒
材料科学
最大熵原理
计算机科学
相变
混合蒙特卡罗
各向异性
马尔科夫蒙特卡洛
晶体结构预测
胶体
统计物理中的蒙特卡罗方法
作者
Charlotte Shiqi Zhao,Sun-Ting Tsai,Sharon C. Glotzer
标识
DOI:10.1073/pnas.2537764123
摘要
For more than two decades, metadynamics has been a powerful tool for improving the sampling of rare events and metastable states in molecular systems. It has been sparingly used, however, to study the crystallization of colloidal systems, especially those comprised of hard particles with anisotropic shapes. In this work, we propose a method, hard particle Monte Carlo metadynamics (HPMC-MetaD), that combines the HPMC-scheme with metadynamics, thereby extending the application of metadynamics to hard particle systems whose phase transitions are driven solely by entropy. As illustrative examples, we use HPMC-MetaD to study five shapes previously reported to be candidate glass formers because of their stubbornness to crystallization. With HPMC-MetaD, we observe crystallization for all five shapes and construct entropy landscapes. These results demonstrate the effectiveness of HPMC-MetaD as a tool for exploring self-assembly in hard particle systems, which will enable a more comprehensive understanding of the underlying mechanisms, ultimately allowing predictive control over the assembly pathways.
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