Structures and Ion Transport Properties of Hydrate-Melt Electrolytes: A Machine-Learning Potential Molecular Dynamics Study

Y Okuno, JOURNAL OF PHYSICAL CHEMISTRY B, 129, 3639-3651 (2025).

DOI: 10.1021/acs.jpcb.4c07559

High-concentration aqueous electrolytes (hydrate-melts) have attracted significant attention for lithium-ion batteries due to their nonflammability and low toxicity. In these electrolytes, the static and dynamic structures of the solvent play a crucial role in determining various properties, such as the ionic conductivity, of the system. To clarify the solvent structure and ion diffusion mechanism, we conducted molecular dynamics simulations using a machine learning potential for Li and Na hydrate-melts. By analyzing the dynamical interaction between ions and their coordinating molecules, we found the ligand exchange of H2O molecules coordinated to cations occurs frequently. As a result, it is considered that the kinetic energy of H2O is transferred to cations and drives the diffusion of cations in the hydrate-melts. This ion transport mechanism is different from the conventionally understood vehicle-type or hopping-type ion transport mechanism. The comparison of Na hydrate-melts and Li hydrate-melts shows the higher diffusion of Na relative to Li. It was suggested that there exists an optimal value for the strength of interaction between cations and H2O molecules, which influences ion diffusion, and that the interaction for Na is close to this optimal value compared to that of the Li.

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