No abstract

Thermodynamic properties and atomic configuration of PdRu alloy were investigated using Wang-Landau Monte Carlo method in combination with a newly-developed universal neural network potential. by using this new potential, excess energy of PdRu alloy was calculated. It is found that PdRu alloy in FCC lattice is unstable in the full range of alloy composition. This agrees with previous study based on density functional theory. The combined method was able to determine the configurational density of states, from which thermodynamic properties of the alloy were derived. It is found that when temperature increases, the excess free energy of the alloy is reduced, increasing the possibility of alloy mixing. Depending on the composition, transition peaks appear at finite temperatures where there are changes of preferable atomic arrangement due to the effect of temperature via the configurational entropy.In addition, the analyses on short-range order parameter and bond fraction show that PdRu alloy prefers to be in segregated form, where Pd and Ru are immiscible at low temperature, consistent with the experimental observations. The random mixing of Pd and Ru atoms in the form of solid-solution can occur at high temperature.

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.

With an increase in an element, the configurational entropy effect stabilizes the multi-element materials. However, the expansion of configuration space and heterogeneous surfaces such as nanoparticles preclude the analytical evaluation of configurational entropy. Then, we implemented the Wang-Landau algorithm, which is one of the Monte-Carlo algorithms, for evaluating the configurational entropy and probing the thermodynamic stable configuration of multi-element materials. The regression equation obtained by density functional theory calculation and multiple regression analysis is used in the energy estimation in the sampling. This method was applied to binary alloys in the bulk and ternary alloy nanoparticles and the obtained features of the stable configuration were discussed.