Speciation of La 3+ -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 3 -H 2 O 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 ab initio 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 K ) for LaCl n 3- n ( n = 1-4) are extensively investigated under a wide range of temperatures and pressures. Empirical density models for log K calculation are fitted with these data and can accurately predict log K 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 3+ dominates and becomes the more prevalent species.