Affiliation:
1. School of Materials Science and Engineering and Tianjin Key Laboratory of Composite and Functional Materials, Tianjin University, Tianjin 300350, P. R. China
Abstract
Machine learning can predict the properties of phase change azobenzene derivatives and guide molecular design to further improve their photothermal conversion performance.
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
China Postdoctoral Science Foundation
China Academy of Space Technology
Publisher
Royal Society of Chemistry (RSC)
Cited by
2 articles.
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