A theoretical study of thermal properties and structural evolution in binary carbonates phase change material: Machine learning-enhanced sampling strategy.

Thermal energy storage and utilization has been widely concerned due to the intermittency, renewability, and economy of renewable energy. In this paper, the potential energy function of binary Na2CO3-K2CO3 salt was first constructed using the Deep Potential GENerator (DPGEN) enhanced sampling method. Deep potential molecular dynamics simulations were performed to calculate the thermal properties and structural evolution of binary carbonates. The results show that as the temperature increases from 1073 to 1273 K, the viscosity and thermal conductivity decrease from 5.011 mPa s and 0.502 W/(m K) to 2.526 mPa s and 0.481 W/(m K), respectively. The decrease in viscosity is related to the distance and interaction between the molten salt ions. In addition, the diffusion coefficients, energy barriers, ionic radius, angular distribution function, and coordination number of molten salt were calculated and analyzed. The CO32- exhibits a stable planar triangular structure. The ionic radius of Na+ is smaller than that of K+, which makes Na+ suffer less spatial hindrance during motion and has a higher diffusion coefficient. The energy barriers that Na+ needs to overcome to escape the Coulomb force is greater than that of K+ ions, so molten salt containing Na+ may possess greater heat storage potential. We believe that the potential function constructed with DPGEN enhanced sampling strategy can provide more convincing results for predicting the thermal properties of molten salts. This paper aims to provide a technical route to develop the novel complex molten salt phase change material for thermal energy storage.