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Department of Materials Science and Engineering, Kyushu Institute of Technology, Tobata-ku, Kitakyushu 804-8550, Japan
Department of Materials Science and Engineering, Kyushu Institute of Technology, Tobata-ku, Kitakyushu 804-8550, Japan
抄録
We propose a method to efficiently search for superconductors with higher critical temperature Tc by machine learning based on a superconductor database. The Tc prediction and the search for new superconductors are still difficult problems. With the progress of computer power and calculation algorithms, the possibility of finding new materials with higher Tc at high throughput is emerging. Using the obtained Tc prediction model, the scope is expanded to the search space of multielement materials that have never been searched, and candidates for superconductors with higher Tc that can be synthesized are proposed.
雑誌名
Applied Physics Express
巻
12
号
7
ページ
073003-1 - 073003-4
発行年
2019-06-28
出版者
IOP Publishing
ISSN
1882-0778
1882-0786
書誌レコードID
AA12295133
DOI
https://doi.org/10.7567/1882-0786/ab2922
権利
Copyright (c) 2019 The Japan Society of Applied Physics