Abstract

High-temperature properties of ceria surfaces are important for many applications. Here, we report the temperature dependencies of surface energy for (111) and (110) ${\mathrm{CeO}}_{2}$ obtained in the framework of the extended two-stage up-sampled thermodynamic integration using Langevin dynamics. The method was used together with machine-learning potentials called moment tensor potentials (MTPs), which were fitted to the results of the ab initio molecular dynamics calculations for (111) and (110) ${\mathrm{CeO}}_{2}$ at different temperatures. The parameters of MTP training and fitting were tested, and the optimal algorithm for the ceria systems was proposed. We found that the temperature increases from 0 to 2100 K led to the decrease of the Helmholtz free energy of (111) ${\mathrm{CeO}}_{2}$ from 0.78 to 0.64 $\mathrm{J}/{\mathrm{m}}^{2}$. The energy of (110) ${\mathrm{CeO}}_{2}$ dropped from 1.19 $\mathrm{J}/{\mathrm{m}}^{2}$ at 0 K to 0.92 $\mathrm{J}/{\mathrm{m}}^{2}$ at 1800 K. We show that it is important to consider anharmonicity, as simple consideration of volume expansion gives the wrong temperature dependencies of the surface energies.

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