Fluoride salts are prospective materials for applications in the next-generation nuclear reactors and their thermophysical properties at various conditions are of interest. Experimental measurement of the properties of these salts is challenging 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 FLiBe (66.6% LiF – 33.3% BeF<sub>2</sub>) and FLiBe with Cr and O impurities, predicted by DFT-D3 method. We then used the developed potential to obtain several thermophysical properties of FLiBe including viscosity, specific heat capacity, thermal conductivity, etc., with and without impurities using molecular dynamics simulations. Our results show that the MTP potential approximates the potential energy surface very well and is much faster compared to the traditional machine learning approaches such as neural networks. In addition, the obtained thermal properties of FLiBe are in very good agreement with experiments.

Thermophysical properties of FLiBe with Cr and O impurities using moment tensor potentials

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