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5.0022451.pdf | 1.99 MB | Adobe PDF | 見る/開く |
タイトル: | Data-driven design of glasses with desirable optical properties using statistical regression |
著者: | Tokuda, Yomei Fujisawa, Misa Packwood, Daniel M. Kambayashi, Mei Ueda, Yoshikatsu https://orcid.org/0000-0001-5896-9859 (unconfirmed) |
著者名の別形: | 徳田, 陽明 藤沢, 美沙 パックウッド, ダニエル 上林, 芽生 上田, 義勝 |
発行日: | Oct-2020 |
出版者: | American Institute of Physics Inc. |
誌名: | AIP Advances |
巻: | 10 |
号: | 10 |
論文番号: | 105110 |
抄録: | In this study, we used a data-driven approach to build models for assisting the design of new glasses with high refractive index and low dispersion. Our models, which are based on multiple linear regression and kernel ridge regression, achieved high accuracy in predicting optical properties of glasses based on their composition alone. Using the predictions of these models as a guide, we fabricated new glasses in our laboratory. In agreement with model predictions, these glasses had promising optical properties. This work therefore demonstrates a successful example of data-driven materials design and can be used as a template for designing glasses or other materials with other desirable properties. |
著作権等: | © 2020 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license. |
URI: | http://hdl.handle.net/2433/267486 |
DOI(出版社版): | 10.1063/5.0022451 |
出現コレクション: | 学術雑誌掲載論文等 |
このアイテムは次のライセンスが設定されています: クリエイティブ・コモンズ・ライセンス