We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
Innovative Materials Science via Machine Learning.
- Authors
Gao, Chaochao; Min, Xin; Fang, Minghao; Tao, Tianyi; Zheng, Xiaohong; Liu, Yangai; Wu, Xiaowen; Huang, Zhaohui
- Abstract
Nowadays, the research on materials science is rapidly entering a phase of data‐driven age. Machine learning, one of the most powerful data‐driven methods, have been being applied to materials discovery and performances prediction with undoubtedly tremendous application foreground. Herein, the challenges and current progress of machine learning are summarized in materials science, the design strategies are classified and highlighted, and possible perspectives are proposed for the future development. It is hoped this review can provide important scientific guidance for innovating materials science and technology via machine learning in the future.
- Subjects
MACHINE learning; MATERIALS science
- Publication
Advanced Functional Materials, 2022, Vol 32, Issue 1, p1
- ISSN
1616-301X
- Publication type
Article
- DOI
10.1002/adfm.202108044