Speaker

Ryo Maezono

Japan Advanced Institute of Science and Technology

Date＆Time

2022.07.13（Wed）PM 13:00

Location

Zoom Meeting ID：950 680 6742 Password：2022

https://zoom.us/j/9506806742?pwd=TzEzUitXOTI1akFMSWhsU0R0K2FwZz0

Reporter

Dr. Ryo Maezono (PhD/Applied Physics) is a full Professor at JAIST (Japan Advanced Institute of Science and Technology), school of Information Science, working on Simulation Science Research area. He got his BSc (1995) and PhD (2000) in Applied Physics at Tokyo University, majoring condensed matter theory working on the phase diagrams of magnetic oxides. He was a JSPS fellow, working on the magnetic properties of oxides. He got a postdoctoral position at Cavendish Laboratory, Cambridge University (2000-2002), and moved to NIMS (National Institute of Materials Science, Japan), as a tenure researcher (2001-2007). In 2007, he moved to JAIST as a tenure-track lecturer, and promoted to a tenure faculty in 2011, and to a full-professor in 2017. Since his postdoc in Cambridge, he has worked on Diffusion Monte Carlo (DMC) electronic structure calculations using massive parallel computations. He has published several DMC works using world top class huge parallel calculations, exploring cutting-edge of numerical quantum many-body problem. As a computer scientist, he has contributed also to the education of simulation science for students and industries, which contents are published in his two books. As a researcher of computational materials science, he leads several industrial collaborations with companies (Toyota-Motor/Sumitomo-Mining/Shin-Etsu Chemicals/Asahi grass Inc. Denso Inc./Morita Chemical Inc.).

Abstract

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. His 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 Python3 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.