Prayogo GI, Tirelli A, Utimula K, Hongo K, Maezono R, Nakano K. Shry: Application of Canonical Augmentation to the Atomic Substitution Problem.
J Chem Inf Model 2022;
62:2909-2915. [PMID:
35678099 PMCID:
PMC9241080 DOI:
10.1021/acs.jcim.2c00389]
[Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
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A common approach
for studying a solid solution or disordered system
within a periodic ab initio framework is to create
a supercell in which certain amounts of target elements are substituted
with other elements. The key to generating supercells is determining
how to eliminate symmetry-equivalent structures from many substitution
patterns. Although the total number of substitutions is on the order
of trillions, only symmetry-inequivalent atomic substitution patterns
need to be identified, and their number is far smaller than the total.
Our developed Python software package, which is called Shry (Suite for High-throughput generation of models with atomic substitutions
implemented by Python), allows the selection of only symmetry-inequivalent
structures from the vast number of candidates based on the canonical
augmentation algorithm. Shry is implemented in Python 3 and
uses the CIF format as the standard for both reading and writing the
reference and generated sets of substituted structures. Shry can be integrated into another Python program as a module or can
be used as a stand-alone program. The implementation was verified
through a comparison with other codes with the same functionality,
based on the total numbers of symmetry-inequivalent structures, and
also on the equivalencies of the output structures themselves. The
provided crystal structure data used for the verification are expected
to be useful for benchmarking other codes and also developing new
algorithms in the future.
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