Neural network potential molecular dynamics simulations of (La,Ce,Pr,Nd)0.95(Mg,Zn,Pb,Cd,Ca,Sr,Ba)0.05F2.95

Abstract

Tysonite structure fluorides doped with divalent cations, represented by Ce0.95Ca0.05F2.95, 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 Ce0.95Ca0.05F2.95 because only the F1 site sublattice contributes to F diffusion below this temperature but the remaining F2 and F3 sublattices becomes gradually active above this temperature. The paradox of higher diffusion coefficients in CeF3-based compounds than similar LaF3-based compounds even though the lattice parameters are larger in the latter may be caused by a shallower potential of Ce and F in CeF3 compared to the LaF3 counterparts.