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説明:

The data-driven strategy has emerged as an important approach for the rapid screening of high-performance single-atom catalysts (SACs). However, the lack of a comprehensive SACs database seriously hinders the widespread application of this strategy. Herein, we construct a public SACs database comprising 1197 samples via doping nonmetallic atoms (B, N. O, P, and S) in the coordination environment and regulating 3d metal centers (Ti, V, Cr, Mn, Fe, Co, Ni, Cu, and Zn). Based on density functional theory calculations, the electronic structural properties (i.e., Bader charge and d-band center) and binding energies are obtained. According to the binding energy calculations, 657 stable catalyst configurations are identified. Subsequently, the corresponding adsorption energies for O2, O, and NO are calculated. Moreover, machine learning (ML) models, specifically extreme gradient boosting regression

権利情報:

• Creative Commons BY-NC-ND Attribution-NonCommercial-NoDerivs 4.0 International
  

キーワード: High-Performance Catalysts

刊行年月日: 2025-03-13

出版者: American Chemical Society (ACS)

掲載誌:

• Journal of Physical Chemistry C (ISSN: 19327447) vol. 129 issue. 10 p. 5043-5053

研究助成金:

• National Natural Science Foundation of China 52006073
• National Natural Science Foundation of China 52176104

原稿種別: 出版者版 (Version of record)

MDR DOI:

公開URL: https://doi.org/10.1021/acs.jpcc.5c00491

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更新時刻: 2025-12-19 16:30:28 +0900

MDRでの公開時刻: 2025-12-19 14:11:49 +0900