Despite surging interest in molten salt reactors and thermal storage systems, knowledge of the physicochemical properties of molten salts are still inadequate due to demanding experiments that require high temperature, impurity control, and corrosion mitigation. Therefore, the ability to predict these properties for molten salts from first-principles computations is urgently needed. Herein, we developed and compared a machine-learned neural network force field (NNFF) and a reparametrized rigid ion model (RIM) for a prototypical molten salt LiF–NaF–KF (FLiNaK). We found that NNFF was able to reproduce both the structural and transport properties of the molten salt with first-principles accuracy and classical-MD computational efficiency. Furthermore, the correlation between the local atomic structures and the dynamics was identified by comparing with RIMs, suggesting the significance of polarization of anions implicitly embedded in the NNFF. This work demonstrated a computational framework that can facilitate the screening of molten salts with different chemical compositions, impurities, and additives, and at different thermodynamic conditions suitable for the next-generation nuclear reactors and thermal energy storage facilities.

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The temperature-dependent diffusivity D(T) of hydrogen solute atoms trapped at dislocations-dislocation pipe diffusion of hydrogen-in deformed polycrystalline PdH(x) (x∼10(-3) [H]/[Pd]) has been quantified with quasielastic neutron scattering between 150 and 400 K. We observe diffusion coefficients for trapped hydrogen elevated by one to two orders of magnitude above bulk diffusion. Arrhenius diffusion behavior has been observed for dislocation pipe diffusion and regular bulk diffusion, the latter in well-annealed polycrystalline Pd. For regular bulk diffusion of hydrogen in Pd we find D(T)=D(0)exp(-E(a)/kT)=0.005exp(-0.23  eV/kT)  cm(2)/s, in agreement with the known diffusivity of hydrogen in Pd. For hydrogen dislocation pipe diffusion we find D(T)≃10(-5)exp(-E(a)/kT)  cm(2)/s, where E(a)=0.042 and 0.083 eV for concentrations of 0.52×10(-3) and 1.13×10(-3)[H]/[Pd], respectively. Ab initio computations provide a physical basis for the pipe diffusion pathway and confirm the reduced barrier height.

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