CrySPY

Openness:3 ★★★
Document quality:2 ★★☆

CrySPY is a crystal structure prediction tool by utilizing first-principles calculations and a classical MD program. Only by inputting chemical composition, crystal structures can be automatically generated and searched. In ver. 0.6.1, random search, Bayesian optimization, and LAQA are available as searching algorithms. CrySPY is interfaced with VASP, Quantum ESPRESSO, and LAMMPS.

Information
Last Update:2024/07/18

Official site

https://tomoki-yamashita.github.io/CrySPY_doc/

License

MIT License

Availability	System requirements find_wy Python 2.7 COMBO numpy pandas pymatgen Interfaces VASP Quantum ESPRESSO soiap LAMMPS
Core Developers	Tomoki Yamashita (National Institute for Materials Science) Nobuya Sato (National Institute of Advanced Industrial Science and Technology) Hiori Kino (National Institute for Materials Science) Takashi Miyake (National Institute of Advanced Industrial Science and Technology) Koji Tsuda (Graduate School of Frontier Sciences, The University of Tokyo) Tamio Oguchi (Institute of Scientific and Industrial Research, Osaka University)
Target substance/model	inorganic compounds
Physical quantities that can be computed	formation energy
Methodology	random search, Bayesian optimization, LAQA
Parallelization	Not supported
Related keywords	Bayesian Optimization
Document	Yamashita, N. Sato, H. Kino, T. Miyake, K. Tsuda, and T. Oguchi, Phys. Rev. Materials 2, 013803 (2017).
Other	2024 HPCI Software Award【Development Category】Encouragement Award https://www.hpci-c.jp/hrdevelop/award.html (in Japanese) Related sites MatDaCs: https://mat-dacs.dxmt.mext.go.jp/en/list/336

Information Last Update:2024/07/18

Official site

License

System requirements

Interfaces

Information
Last Update:2024/07/18