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Data-Based Methods for Materials Design and Discovery: Basic Ideas and General Methods.
・ISBN 978-3-031-01255-6 paper EUR 49.99
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| 著者・編者 | Pilania, Ghanshyam / Balachandran, Prasanna V. / Gubernatis, James E. / Lookman, Turab, |
|---|---|
| シリーズ | (Synthesis Lectures on Materials and Optics) |
| 出版社 | (Springer International Publishing AG, SZ) |
| 出版年月 | 2020 |
| ページ数 | 172 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A02-80120＞ |
解説
Machine learning methods are changing the way we design and discover new materials. This book provides an overview of approaches successfully used in addressing materials problems (alloys, ferroelectrics, dielectrics) with a focus on probabilistic methods, such as Gaussian processes, to accurately estimate density functions. The authors, who have extensive experience in this interdisciplinary field, discuss generalizations where more than one competing material property is involved or data with differing degrees of precision/costs or fidelity/expense needs to be considered.