Machine-Learning Molecular Dynamics Reveals Grotthuss Transport in Concentrated Electrolytes
Øystein Gullbrekken, Sondre Kvalvåg Schnell
Abstract
Proton transfer is responsible for the anomalous high conductivity in acidic or basic aqueous solutions. Yet, the contribution of the proton transfer mechanism to the conductivity of concentrated aqueous solutions is unknown. In this work, we compute the transport properties of KOH(aq) systems with different concentrations, using Molecular Dynamics simulations with a Machine Learning Interatomic Potential (MLIP), which includes proton transfer. We quantify the contribution of the proton transfer mechanism to the diffusivities of hydroxide ions and water molecules, and the ionic conductivity and transport numbers of the electrolytes. The contribution is substantial at lower concentrations, but diminishes at very high concentrations.
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