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説明:

We have developed an open-source software called CrySPY, which is a crystal structure
prediction tool written in Python 3, and runs on Unix/Linux platforms. CrySPY enables anyone
to easily perform crystal structure prediction simulations for materials discovery and design,
and automates structure generation, structure optimization, energy evaluation, and efficiently
selecting candidates using machine learning. Several searching algorithms are available such
as random search, evolutionary algorithm, Bayesian optimization, and Look Ahead based on
Quadratic Approximation. Machine learning is employed to efficiently select candidates for
priority optimization. CrySPY does not require complex machine learning techniques for users.
In the latest version of CrySPY, both atomic and molecular random structures can be gener-
ated. CrySPY supports VASP, QUANTUM ESPRESSO, OpenMX, soiap, and LAMMPS for local
structure optimization and energy evaluation. CrySPY is distributed under the MIT license at
https://github.com/Tomoki-YAMASHITA/CrySPY. Documentation of CrySPY is also available at
https://Tomoki-YAMASHITA.github.io/CrySPY_doc.

権利情報:

• Creative Commons BY Attribution 4.0 International
  

キーワード: crystal structure prediction, Bayesian optimization, LAQA, first-principles calculations, evolutionary algorithm

刊行年月日: 2021-01-01

出版者: Informa UK Limited

掲載誌:

• Science and Technology of Advanced Materials: Methods (ISSN: 27660400) vol. 1 issue. 1 p. 87-97

研究助成金:

• Support Program for Starting Up Innovation Hub Materials research by Information Integration Initiative (MI 2 I) project
• JST JPMJCR1502
• MEXT CDMSI
• JSPS KAKENHI JP18K13474
• JSPS KAKENHI JP20J13011

原稿種別: 出版者版 (Version of record)

MDR DOI:

公開URL: https://doi.org/10.1080/27660400.2021.1943171

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更新時刻: 2024-04-02 23:51:18 +0900

MDRでの公開時刻: 2023-02-10 10:31:36 +0900