2022 Fiscal Year Annual Research Report
Atomistic Insights into Interfacial Characteristics for Energy Conversion
| Project/Area Number |
21F30701
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| Research Institution | Shinshu University |
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Principal Investigator |
古山 通久 信州大学, 先鋭領域融合研究群先鋭材料研究所, 教授(特定雇用) (60372306)
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| Co-Investigator(Kenkyū-buntansha) |
VALADEZ HUERTA GERARDO 信州大学, 先鋭領域融合研究群先鋭材料研究所, 外国人特別研究員
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| Project Period (FY) |
2021-07-28 – 2023-03-31
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| Keywords | Neural Network Potential / Heterogeneous Catalysis / Interface / Molecular Simulation / Catalyst / Supported Nanoparticles / Dissociation |
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| Outline of Annual Research Achievements |
The study aims to analyze interfaces by using a universal neural network potential. We targeted the adsorption and catalytic properties of N2 on a Ru
nanoparticle supported on a La0.5Ce0.5O1.75-x reduced slab. This heterogeneous system shows a strong-metal support interaction (SMSI), which cannot be investigated by conventional methods. By developing automated procedure, N2 adsorption properties on all ontop sites of 200 different catalyst configurations were investigated, giving 15600 different adsorption results in total. Statistical analyses was conducted to identify the catalyst structure representing the real-system. The relation between activation barrier and local structure was carefully discussed, to identify the essential factor behind the experimentally observed high activity.
To further investigate the interfacial properties of supported nanocatalyst, combinations of different metal and support materials are prepared. Automated procedure was further extended to explore the adsorption properties of other small molecules, which are fundamental in key reactions such as carbon-neutral fuel synthesis, oxygen reduction reaction in fuel cells, and oxygen evolotion reaction in water electrolysis.
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| Research Progress Status |
令和4年度が最終年度であるため、記入しない。
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| Strategy for Future Research Activity |
令和4年度が最終年度であるため、記入しない。
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