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An acceleration search method of higher Tc superconductors by a machine learning algorithm
http://hdl.handle.net/10228/00007816
http://hdl.handle.net/10228/000078164532f41b-d145-453a-b564-9961ccaeb3da
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
scunit-2019_01.pdf (777.2 kB)
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| アイテムタイプ | 学術雑誌論文 = Journal Article(1) | |||||
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| 公開日 | 2020-06-29 | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
| 資源タイプ | journal article | |||||
| タイトル | ||||||
| タイトル | An acceleration search method of higher Tc superconductors by a machine learning algorithm | |||||
| 言語 | en | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| 著者 |
松本, 要
× 松本, 要× 堀出, 朋哉 |
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| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | 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. | |||||
| 言語 | en | |||||
| 書誌情報 |
en : Applied Physics Express 巻 12, 号 7, p. 073003, 発行日 2019-06-28 |
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| 出版社 | ||||||
| 出版者 | IOP Publishing | |||||
| 言語 | en | |||||
| DOI | ||||||
| 関連タイプ | isVersionOf | |||||
| 識別子タイプ | DOI | |||||
| 関連識別子 | https://doi.org/10.7567/1882-0786/ab2922 | |||||
| NCID | ||||||
| 収録物識別子タイプ | NCID | |||||
| 収録物識別子 | AA12295133 | |||||
| ISSN | ||||||
| 収録物識別子タイプ | PISSN | |||||
| 収録物識別子 | 1882-0778 | |||||
| ISSN | ||||||
| 収録物識別子タイプ | EISSN | |||||
| 収録物識別子 | 1882-0786 | |||||
| 著作権関連情報 | ||||||
| 権利情報 | Copyright (c) 2019 The Japan Society of Applied Physics | |||||
| 出版タイプ | ||||||
| 出版タイプ | AM | |||||
| 出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa | |||||
| 査読の有無 | ||||||
| 値 | yes | |||||
| 連携ID | ||||||
| 値 | 7796 | |||||
