Genetic Algorithm Driven Force Field Parameterization for Molten Alkali-Metal Carbonate and Hydroxide Salts

摘要

Molten alkali-metal carbonates and hydroxides play important roles in the molten carbonate fuel cell and in Earth's geochemistry. Molecular simulations allow us to study these systems at extreme conditions without the need for difficult experimentation. Using a genetic algorithm to fit ab intio molecular dynamics-computed densities and radial distribution functions, as well as experimental enthalpies of formation, we derive new classical force fields able to accurately predict liquid chemical potentials. These fitting properties were chosen to ensure accurate liquid phase structure and energetics. Although the predicted dynamics is slow when compared to experiments, in general the trends in dynamic properties across different systems still hold true. In addition, these newly parametrized force fields can be extended to the molten carbonate-hydroxide mixtures by using standard combining rules.