| 期刊全称 | Artificial Intelligence for Materials Science | | 影响因子2023 | Yuan Cheng,Tian Wang,Gang Zhang | | 视频video | | | 发行地址 | Presents fundamental information about AI principles and algorithms.Describes the most important and commonly adopted analytical methods in computational material science.Features applications of mach | | 学科分类 | Springer Series in Materials Science | | 图书封面 |  | | 影响因子 | .Machine learning methods have lowered the cost of exploring new structures of unknown compounds, and can be used to predict reasonable expectations and subsequently validated by experimental results. As new insights and several elaborative tools have been developed for materials science and engineering in recent years, it is an appropriate time to present a book covering recent progress in this field..Searchable and interactive databases can promote research on emerging materials. Recently, databases containing a large number of high-quality materials properties for new advanced materials discovery have been developed. These approaches are set to make a significant impact on human life and, with numerous commercial developments emerging, will become a major academic topic in the coming years. ..This authoritative and comprehensive book will be of interest to both existing researchers in this field as well as others in the materials science community who wish to take advantage of these powerful techniques. The book offers a global spread of authors, from USA, Canada, UK, Japan, France, Russia, China and Singapore, who are all world recognized experts in their separate areas. With c | | Pindex | Book 2021 |
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发表于 2025-3-21 16:34:35
