Artificial Intelligence-Powered Materials Science

被引：6
作者：
Bai, Xiaopeng [2 ,3 ]
Zhang, Xingcai [1 ]
机构：
[1] Stanford Univ, Dept Mat Sci & Engn, Stanford, CA 94305 USA
[2] Univ Hong Kong, Dept Mech Engn, Hong Kong 999077, Peoples R China
[3] Chinese Univ Hong Kong, Dept Phys, Shatin, Hong Kong 999077, Peoples R China
来源：
NANO-MICRO LETTERS | 2025年 / 17卷 / 01期
关键词：
Artificial intelligence; Machine learning; Sustainable materials; Data-driven; Materials innovation; METHANE STORAGE; NEURAL-NETWORKS; SMALL MOLECULES; MACHINE; DESIGN; DISCOVERY; REDUCTION; OPTIMIZATION; PREDICTIONS; FRAMEWORKS;
D O I：
10.1007/s40820-024-01634-8
中图分类号：
TB3 [工程材料学];
学科分类号：
0805 ; 080502 ;
摘要：
The advancement of materials has played a pivotal role in the advancement of human civilization, and the emergence of artificial intelligence (AI)-empowered materials science heralds a new era with substantial potential to tackle the escalating challenges related to energy, environment, and biomedical concerns in a sustainable manner. The exploration and development of sustainable materials are poised to assume a critical role in attaining technologically advanced solutions that are environmentally friendly, energy-efficient, and conducive to human well-being. This review provides a comprehensive overview of the current scholarly progress in artificial intelligence-powered materials science and its cutting-edge applications. We anticipate that AI technology will be extensively utilized in material research and development, thereby expediting the growth and implementation of novel materials. AI will serve as a catalyst for materials innovation, and in turn, advancements in materials innovation will further enhance the capabilities of AI and AI-powered materials science. Through the synergistic collaboration between AI and materials science, we stand to realize a future propelled by advanced AI-powered materials.
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页数：30
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