Resolving the Solvation Structure and Transport Properties of Aqueous Zinc Electrolytes from Salt-in-Water to Water-in-Salt Using Machine Learning

Dr Deyu Lu

Center for Functional Nanomaterials, Brookhaven National Laboratory

Abstract: ZnCl2 is one of the most soluble inorganic salts containing a multivalent cation. Molten ZnCl2 hydrates at high concentrations have incomplete first solvation shell and are referred to as waterin-salt (WIS). Recently, ZnCl2 WIS electrolytes have shown improved performance compared with dilute electrolytes in aqueous zinc ion batteries. They suppress the water splitting reactions, help regulate the morphologies of Zn plating and improve the Coulombic efficiency of Zn anodes. Here, I report a joint computational and experimental study of the structural and dynamic properties of aqueous ZnCl2 electrolytes with concentrations ranging from salt-in-water (SIW) to WIS. By developing a neural network potential (NNP) model, we perform molecular dynamics (MD) simulations with ab initio accuracy but at much larger length and longer time scales. The NNP predicted structures are validated by the structure factors measured by X-ray total scattering and X-ray absorption spectroscopy experiments. The MD trajectories provide a comprehensive and quantitative picture of the Zn2+ solvation shell structures. We find that the O-H covalent bonds in water are strengthened with increasing salt concentration, thus expanding the electrochemical stability window of aqueous electrolytes. In terms of dynamic properties, the calculated and measured conductivities are in good agreement. Through the analysis of calculated cation transference number, we propose a three-stage charge carrier transport mechanism with increasing concentration: independent ion transport, strongly correlated ion transport, and small positive charge carrier diffusion through negatively charged polymeric clusters. Our study provides fundamental atomic-scale insights into the structure and transport properties of the ZnCl2 electrolyte that can aid the optimization and development of WIS electrolytes for battery applications.