A machine learning approach to identifying perovskite materials in A 2 BB′X 6 compounds
Source abstract
Abstract
This study proposes an efficient machine learning model based on atomic statistical characteristics that can accurately predict the formation of perovskite structures in A 2 BB'X 6 -type double perovskite materials.
Only a short abstract or summary was supplied by the source.
Source: crossref · Quality: short
Research context
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Affiliations
School of Physics and New Energy, Chongqing University of Technology, Chongqing, 400054, P. R. China
Chongqing Key Laboratory of New Energy Storage Materials and Devices, Chongqing University of Technology, Chongqing, 400044, P. R. China
International Institute for Carbon-Neutral Energy Research (WPI-I2CNER), Kyushu University, 744 Motooka, Nishi, 819-0395, Fukuoka, Japan
Center for Energy Systems Design (CESD), International Institute for Carbon-Neutral Energy Research (WPI-I2CNER), Kyushu University, 744 Motooka, Nishi, 819-0395, Fukuoka, Japan
Funding
Chongqing Graduate Student Research Innovation Project · Chongqing Municipal Education Commission
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