Dynamics of Aqueous Electrolyte Solutions: Challenges for Simulations

This Perspective article focuses on recent simulation work on the dynamics of aqueous electrolytes. It is well-established that full-charge, nonpolarizable models for water and ions generally predict solution dynamics that are too slow in comparison to experiments. Models with reduced (scaled) charges do better for solution diffusivities and viscosities but encounter issues describing other dynamic phenomena such as nucleation rates of crystals from solution. Polarizable models show promise, especially when appropriately parametrized, but may still miss important physical effects such as charge transfer. First-principles calculations are starting to emerge for these properties that are in principle able to capture polarization, charge transfer, and chemical transformations in solution. While direct ab initio simulations are still too slow for simulations of large systems over long time scales, machine-learning models trained on appropriate first-principles data show significant promise for accurate and transferable modeling of electrolyte solution dynamics.

Automated summary

This Perspective article discusses recent simulation work on aqueous electrolyte dynamics. Full-charge, nonpolarizable models for water and ions tend to underestimate solution dynamics compared to experiments. Models with reduced charges perform better for diffusivities and viscosities, but struggle with other dynamic phenomena like crystal nucleation rates. Polarizable models show promise, but may still miss important effects like charge transfer. First-principles calculations are emerging to capture polarization, charge transfer, and transformations in solution, while machine-learning models trained on such data can accurately model electrolyte solution dynamics.