Simple Structural Descriptor Obtained from Symbolic Classification for Predicting the Oxygen Vacancy Defect Formation of Perovskites.

Liu, Siyu; Wang, Jing; Duan, Zhongtao; Wang, Kongxiang; Zhang, Wanlu; Guo, Ruiqian; Xie, Fengxian

Liu, Siyu; Wang, Jing; Duan, Zhongtao; Wang, Kongxiang; Zhang, Wanlu; Guo, Ruiqian; Xie, Fengxian.

Affiliation

Liu S; Institute of Future Lighting, Academy for Engineering and Technology, Fudan University, Shanghai 200433, China.
Wang J; Institute for Electric Light Sources, School of Information Science and Technology, Fudan University, Shanghai 200433, China.
Duan Z; Institute for Electric Light Sources, School of Information Science and Technology, Fudan University, Shanghai 200433, China.
Wang K; Institute for Electric Light Sources, School of Information Science and Technology, Fudan University, Shanghai 200433, China.
Zhang W; Institute for Electric Light Sources, School of Information Science and Technology, Fudan University, Shanghai 200433, China.
Guo R; Institute of Future Lighting, Academy for Engineering and Technology, Fudan University, Shanghai 200433, China.
Xie F; Institute for Electric Light Sources, School of Information Science and Technology, Fudan University, Shanghai 200433, China.

ACS Appl Mater Interfaces ; 14(9): 11758-11767, 2022 Mar 09.

Article in En | MEDLINE | ID: mdl-35196010

Key words

machine learning; perovskite; structure descriptor; symbolic classification; vacancy defects

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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: ACS Appl Mater Interfaces Journal subject: BIOTECNOLOGIA / ENGENHARIA BIOMEDICA Year: 2022 Document type: Article Affiliation country: Country of publication:

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