[15a-D411-1~11] 15.7 Crystal characterization, impurities and crystal defects

[15a-D411-6] SHRY: a Suite for High-throughput generation of models with atomic substitutions implemented by python

Keishu Utimula¹, 〇Kousuke Nakano², Genki I. Prayogo¹, Kenta Hongo^2,4,5, Ryo Maezono^2,3 (1.Sch. Mater. Sci., JAIST, 2.Sch. Info. Sci., JAIST, 3.RIKEN, 4.NIMS, 5.PRESTO, JST)

Keywords:atomic substitution, First-principle calculation

We considered the problem how to handle the exploding number of possibilities to choose atomic sites to be replaced by substituents in the supercell modeling of alloys, solid solutions, intermetallic compounds and doped materials. The number sometimes amounts to ~ trillions and hence straightforward manner to write out all the configurations to be sorted into group-theoretically equivalent clusters becomes not practically feasible due to the lack of the storage capacity even though there are several tools available to perform this straightforward method. We have developed a stochastic framework to avoid the shortage of capacity, implemented in a package of Python scripts, named as 'SHRY'. The package provides several different methods to estimate the number of the symmetrically equivalent structures from the statistical estimates obtained in the stochastic operations. A prominent conclusion derived here is that the statistical variation of the number of equivalent structures obtained by sorting the limited number of sampling of substitutions is working as a promising measure to estimate the total number of equivalent structures for the whole distribution even without performing the whole sampling.