  Fluoride salts are prospective materials for applications in some next
generation nuclear reactors and their thermophysical properties at various
conditions are of interest. Experimental measurement of the properties of these
salts is often difficult and, in some cases, unfeasible due to challenges from
high temperatures, impurity control, and corrosivity. Therefore, accurate
theoretical methods are needed for fluoride salt property prediction. In this
work, we used moment tensor potentials (MTP) to approximate the potential
energy surface of eutectic FLiBe (0.66 LiF 0.33 BeF2) predicted by the ab
initio (DFT D3) method. We then used the developed potential and molecular
dynamics to obtain several thermophysical properties of FLiBe, including radial
distribution functions, density, self-diffusion coefficients, thermal
expansion, specific heat capacity, bulk modulus, viscosity, and thermal
conductivity. Our results show that the MTP potential approximates the
potential energy surface accurately and the overall approach yields very good
agreement with experimental values. The converged fitting can be obtained with
less than 600 configurations generated from DFT calculations, which data can be
generated in just 1200 core hours on today's typical processors. The MTP
potential is faster than many machine learning potentials and about one order
of magnitude slower than widely used empirical molten salt potentials such as
Tosi Fumi.
