Correspondence Address: Prof. Bin Lin, School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu 611731, P.R. China, (E-mail): firstname.lastname@example.org
© The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
for stability of perovskites is selected out by linear regression. The results demonstrate a high-efficient and non-priori-knowledge investigation of structure-composition-property relationships for perovskite materials, providing a new road to discover advanced energy materials.
Deng Q, Lin B. Automated machine learning structure-composition-property relationships of perovskite materials for energy conversion and storage. Energy Mater 2021;1:[Accept]. https://dx.doi.org/10.20517/energymater.2021.10