Li2O concentration influenced local structure and properties of molten LiCl salt by machine learning driven molecular dynamics simulation

Pyroprocessing is one of the promising technologies for the reprocessing of spent nuclear fuel. In the electrolytic reduction process of pyroprocessing, LiCl serves as the electrolyte with a minor addition of Li2O as the initial oxygen ion input. Investigating the impact of Li2O concentration on the molten salt system is essential for enhancing the efficiency of electrolytic reduction. In the present study, the LiCl-Li2O system is simulated using deep potential molecular dynamics simulation. The properties including self-diffusion coefficient, shear viscosity, ionic conductivity, heat capacity, radial distribution functions, coordination numbers, short-range order, medium-range order, Voronoi structure, and angle distribution functions are explored at different Li2O concentrations. This study reveals that the variations of physical properties at different Li2O concentrations in LiCl molten salt can be attributed to the changes in local structure. For example, unnormal high proportions of two Voronoi structures are found in the molten salt when the Li2O concentration increases, which may explain the changes of properties. These findings offer valuable insights for refining the parameters of electrolytic reduction and elucidating the correlation between microscopic and macroscopic phenomena.