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Neural Network Potential Molecular Dynamics Simulations of (La,Ce,Pr,Nd)(Mg,Zn,Pb,Cd,Ca,Sr,Ba)F. | LitMetric

Neural Network Potential Molecular Dynamics Simulations of (La,Ce,Pr,Nd)(Mg,Zn,Pb,Cd,Ca,Sr,Ba)F.

J Phys Chem B

Department of Energy and Environment, National Institute of Advanced Industrial Science and Technology (AIST), 1-8-31, Midorigaoka, Ikeda, Osaka 563-8577, Japan.

Published: December 2024

Tysonite structure fluorides doped with divalent cations, represented by CeCaF, are a class of good F ion conductors together with fluorite-structured compounds. Computational understanding of the F conduction process is difficult because of the complicated interactions between three symmetrically distinct F sites and the experimentally observed change in the F diffusion mechanism slightly above room temperature, effectively making first-principles molecular dynamics (FP-MD) simulations, which are often conducted well above the transition temperature, useless when analyzing behavior below the transition point. Neural network potential (NNP) MD simulations showed that the F diffusion coefficient is higher when the divalent dopant cation size is similar to the trivalent cation size. The diffusion behavior of F in different sites changes at roughly 500 K in CeCaF because only the F1 site sublattice contributes to F diffusion below this temperature, but the remaining F2 and F3 sublattices become gradually active above this temperature. The paradox of higher diffusion coefficients in CeF-based compounds than similar LaF-based compounds even though the lattice parameters are larger in the latter may be caused by a shallower potential of Ce and F in CeF compared to the LaF counterparts.

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Source
http://dx.doi.org/10.1021/acs.jpcb.4c05624DOI Listing

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