Speciation of La-Cl Complexes in Hydrothermal Fluids from Deep Potential Molecular Dynamics.

The stability of rare earth element (REE) complexes plays a crucial role in quantitatively assessing their hydrothermal migration and transformation. However, reliable data are lacking under high-temperature hydrothermal conditions, which hampers our understanding of the association behavior of REE. Here a deep learning potential model for the LaCl-HO system in hydrothermal fluids is developed based on the first-principles density functional theory calculations. The model accurately predicts the radial distribution functions compared to molecular dynamics (AIMD) simulations. Furthermore, species of La-Cl complexes, the dissociation pathway of the La-Cl complexes dissociation process, and the potential of mean forces and corresponding association constants (log) for LaCl ( = 1-4) are extensively investigated under a wide range of temperatures and pressures. Empirical density models for log calculation are fitted with these data and can accurately predict log data from both experimental results and AIMD simulations. The distribution of La-Cl species is also evaluated across a wide range of temperatures, pressures, and initial chloride concentration conditions. The results show that La-Cl complexes are prone to forming in a low-density solution, and the number of bonded Cl ions increases with rising temperature. In contrast, in a high-density solution, La dominates and becomes the more prevalent species.