Recent Advance of Machine Learning in Selecting New Materials
Received date: 2022-11-01
Online published: 2022-12-26
Supported by
National Natural Science Foundation of China(21922801); National Natural Science Foundation of China(22090032); National Natural Science Foundation of China(22090030); Natural Science Foundation of Beijing(2202036)
The new material industry is the foundation of technological change in many related fields, and also the forerunner of the development of new energy, aerospace, electronic information and other high-tech industries. Traditional means cannot meet the development needs of modern society because of disadvantages such as high cost, low efficiency and long commercial cycle. In recent years, with the application of big data combined with artificial intelligence in a deeper degree, data-driven machine learning has made great progress in the design, screening and performance prediction of new materials, which has greatly promoted the development and application of new materials. In this review, the basic process of machine learning, the algorithms commonly used in materials science and the relevant materials database are summarized. This review focuses on the application of machine learning in different functions, as well as the performance prediction in the fields of catalyst materials, lithium-ion batteries, semiconductor materials and alloy materials, presenting the latest progress in materials development. Finally, machine learning in the application of new materials are analyzed and prospected.
Xingyi Qi , Yaofeng Hu , Ruoyu Wang , Yaqing Yang , Yufei Zhao . Recent Advance of Machine Learning in Selecting New Materials[J]. Acta Chimica Sinica, 2023 , 81(2) : 158 -174 . DOI: 10.6023/A22110446
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