|
|
JAIST Repository >
d. 融合科学系 >
d10. 学術雑誌論文等 >
d10-1. 雑誌掲載論文 >
このアイテムの引用には次の識別子を使用してください:
http://hdl.handle.net/10119/18868
|
| タイトル: | Direct Design of Active Catalysts for Low Temperature Oxidative Coupling of Methane via Machine Learning and Data Mining |
| 著者: | Ohyama, Junya
Kinoshita, Takaaki
Funada, Eri
Yoshida, Hiroshi
Machida, Masato
Nishimura, Shun
Uno, Takeaki
Fujima, Jun
Miyazato, Itsuki
Takahashi, Lauren
Takahashi, Keisuke |
| 発行日: | 2020-10-30 |
| 出版者: | Royal Society of Chemistry |
| 誌名: | Catalysis Science & Technology |
| 巻: | 11 |
| 号: | 2 |
| 開始ページ: | 524 |
| 終了ページ: | 530 |
| DOI: | 10.1039/D0CY01751E |
| 抄録: | Direct design of low temperature oxidative coupling of methane (OCM) catalysts is proposed via machine learning and data mining. 58 OCM catalysts are experimentally synthesized and evaluated. Collected 58 data are then classified by unsupervised machine learning in multi-dimensional space where active catalysts group for low temperature OCM is identified. Data mining then identifies the physical rule within the group. Catalysts satisfying such physical rule is designed where 2 undiscovered low temperature OCM catalysts are found and experimentally validated. Thus, machine learning and data mining reveal the hidden physical rule behind the catalysis leading to the direct design of catalysts. Hence, machine learning and data mining open up the insight of powerful strategy for designing catalysts. |
| Rights: | Copyright (C) 2021 Royal Society of Chemistry. Junya Ohyama, Takaaki Kinoshita, Eri Funada, Hiroshi Yoshida, Masato Machida, Shun Nishimura, Takeaki Uno, Jun Fujima, Itsuki Miyazato, Lauren Takahashi and Keisuke Takahashi, Catalysis Science & Technology, 2021, 11(2), 524-530. https://doi.org/10.1039/D0CY01751E - Reproduced by permission of the Royal Society of Chemistry |
| URI: | http://hdl.handle.net/10119/18868 |
| 資料タイプ: | author |
| 出現コレクション: | d10-1. 雑誌掲載論文 (Journal Articles)
|
このアイテムのファイル:
| ファイル |
記述 |
サイズ | 形式 |
|---|
| S-NISHIMURA-T-0501-4.pdf | | 580Kb | Adobe PDF | 見る/開く |
|
当システムに保管されているアイテムはすべて著作権により保護されています。
|
