Pretti Evan, Shen Vincent K, Mittal Jeetain, Mahynski Nathan A
Department of Chemical and Biomolecular Engineering, Lehigh University, 111 Research Drive, Bethlehem, Pennsylvania 18015-4791, United States.
Chemical Sciences Division, National Institute of Standards and Technology, Gaithersburg, Maryland 20899-8320, United States.
J Phys Chem A. 2020 Apr 23;124(16):3276-3285. doi: 10.1021/acs.jpca.0c00846. Epub 2020 Apr 8.
The accurate prediction of stable crystalline phases is a long-standing problem encountered in the study of conventional atomic and molecular solids as well as soft materials. One possible solution involves enumerating a reasonable set of candidate structures and then screening them to identify the one(s) with the lowest (free) energy. Candidate structures in this set can also serve as starting points for other routines, such as genetic algorithms, which search optimization. Here, we present a framework for crystal structure enumeration of two-dimensional systems that utilizes a combination of symmetry- and stoichiometry-imposed constraints to compute valid configurations of particles that tile Euclidean space. With mild assumptions, this produces a computationally tractable total number of proposed candidates, enabling multicomponent systems to be screened by direct enumeration of possible crystalline ground states. The python code that enables these calculations is available at https://github.com/usnistgov/PACCS.
准确预测稳定的晶相是传统原子和分子固体以及软材料研究中长期存在的问题。一种可能的解决方案是列举一组合理的候选结构，然后对其进行筛选，以确定能量最低的结构。该集合中的候选结构也可以作为其他程序（如遗传算法）的起点，这些程序用于搜索优化。在这里，我们提出了一个二维系统晶体结构枚举框架，该框架利用对称性和化学计量学施加的约束相结合，来计算平铺欧几里得空间的粒子的有效构型。在适度假设下，这会产生计算上易于处理的候选结构总数，从而能够通过直接枚举可能的晶体基态来筛选多组分系统。实现这些计算的Python代码可在https://github.com/usnistgov/PACCS获取。
