MatGPT: A Vane of Materials Informatics from Past, Present, to Future

被引:7
|
作者
Wang, Zhilong [1 ,2 ]
Chen, An [1 ,2 ]
Tao, Kehao [1 ,2 ]
Han, Yanqiang [1 ,2 ]
Li, Jinjin [1 ,2 ]
机构
[1] Shanghai Jiao Tong Univ, Natl Key Lab Sci & Technol Micro Nano Fabricat, Shanghai 200240, Peoples R China
[2] Shanghai Jiao Tong Univ, Dept Micro Nano Elect, Key Lab Thin Film & Microfabricat, Minist Educ, Shanghai 200240, Peoples R China
基金
国家重点研发计划;
关键词
AI for Science; artificial intelligence; materials informatics; materials science; CRYSTAL-STRUCTURE PREDICTION; MACHINE LEARNING FRAMEWORK; NEURAL-NETWORK; INORGANIC CRYSTALS; STRUCTURE DATABASE; GUIDED DISCOVERY; OPTIMIZATION; SINGLE; ELECTROCATALYSTS; ELECTROLYTES;
D O I
10.1002/adma.202306733
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Combining materials science, artificial intelligence (AI), physical chemistry, and other disciplines, materials informatics is continuously accelerating the vigorous development of new materials. The emergence of "GPT (Generative Pre-trained Transformer) AI" shows that the scientific research field has entered the era of intelligent civilization with "data" as the basic factor and "algorithm + computing power" as the core productivity. The continuous innovation of AI will impact the cognitive laws and scientific methods, and reconstruct the knowledge and wisdom system. This leads to think more about materials informatics. Here, a comprehensive discussion of AI models and materials infrastructures is provided, and the advances in the discovery and design of new materials are reviewed. With the rise of new research paradigms triggered by "AI for Science", the vane of materials informatics: "MatGPT", is proposed and the technical path planning from the aspects of data, descriptors, generative models, pretraining models, directed design models, collaborative training, experimental robots, as well as the efforts and preparations needed to develop a new generation of materials informatics, is carried out. Finally, the challenges and constraints faced by materials informatics are discussed, in order to achieve a more digital, intelligent, and automated construction of materials informatics with the joint efforts of more interdisciplinary scientists. The continuous innovation of artificial intelligence impacts the cognitive laws and scientific methods, and reconstructs the knowledge and wisdom system in materials science. This article provides the thinking of materials informatics in the future, from the data, descriptor, generative model, directed design model, cotraining model, to experimental automation, to achieve a more digital, intelligent, and automated construction of materials informatics.image
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页数:44
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