Symmetry-Based Crystal Structure Enumeration in Two Dimensions

被引:5
|
作者
Pretti, Evan [2 ]
Shen, Vincent K. [1 ]
Mittal, Jeetain [2 ]
Mahynski, Nathan A. [1 ]
机构
[1] NIST, Chem Sci Div, Gaithersburg, MD 20899 USA
[2] Lehigh Univ, Dept Chem & Biomol Engn, Bethlehem, PA 18015 USA
来源
JOURNAL OF PHYSICAL CHEMISTRY A | 2020年 / 124卷 / 16期
基金
美国国家科学基金会;
关键词
STRUCTURE PREDICTION; GLOBAL OPTIMIZATION; ALGORITHM; CLUSTERS;
D O I
10.1021/acs.jpca.0c00846
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
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 via 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.
引用
收藏
页码:3276 / 3285
页数:10
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