Distilling universal activity descriptors for perovskite catalysts from multiple data sources <i>via</i> multi-task symbolic regression.

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作者： Zhilong,Song ^[1] ; Xiao,Wang ^[2] ; Fangting,Liu ^[1] ; Qionghua,Zhou ^[1] ; Wan-Jian,Yin ^[3] ; Hao,Wu ^[4] ; Weiqiao,Deng ^[5] ; Jinlan,Wang ^[2]

作者单位： School of Physics, Southeast University, Nanjing, 211189, China. qh.zhou@seu.edu.cn. ^[1] Institute of Molecular Sciences and Engineering, Institute of Frontier and Interdisciplinary Science, Shandong University, Qingdao, Shandong, 266237, China. dengwq@sdu.edu.cn. ^[2] Suzhou Laboratory, Suzhou, China. ^[3] College of Energy, Soochow Institute for Energy and Materials InnovationS (SIEMIS), Soochow University, Suzhou, 215006, China. wjyin@suda.edu.cn. ^[4] Light Industry Institute of Electrochemical Power Source, Soochow University, Suzhou, 215006, China. ^[5]

DOI 10.1039/d3mh00157a

PMID 36960653

发布时间 2023-05-10

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Materials horizons

2023年10卷5期

1651-1660页

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Distilling universal activity descriptors for perovskite catalysts from multiple data sources <i>via</i> multi-task symbolic regression.

Materials horizons

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Distilling universal activity descriptors for perovskite catalysts from multiple data sources <i>via</i> multi-task symbolic regression.

Materials horizons

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Materials horizons

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