| 研究実績の概要 |
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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