- 著者
-
田村 綾子
Gerardo VALADEZ HUERTA
難波 優輔
久間 馨
古山 通久
- 出版者
- Society of Computer Chemistry, Japan
- 雑誌
- Journal of Computer Chemistry, Japan (ISSN:13471767)
- 巻号頁・発行日
- vol.21, no.4, pp.129-133, 2022 (Released:2023-06-22)
- 参考文献数
- 9
Multi-element alloy nanoparticles have attracted attention for their potentially high catalytic properties. However, a high degree of freedom in configurations of metal atoms within nanoparticle increases the distinct adsorption sites, making it difficult to theoretically analyze its catalytic properties because the first-principles calculation requires a considerable computational cost. In this study, we develop a sequential scheme to calculate hundreds of adsorption sites by employing a pre-trained universal neural network potential named PFP. Our automated scheme is applied to CO single-molecule adsorption of CO onto PtRuIr ternary alloy nanoparticles. The calculation results are first compared with DFT results to confirm the accuracy. Adsorption energies in the alloy systems are widely distributed in comparison with those of the monometal counterparts, indicating that the alloy nanoparticle includes adsorption sites with various catalytic activities.