Universal Ion-Transport Descriptors and Classes of Inorganic Solid-State Electrolytes

Solid-state electrolytes (SSE) with high ionic conductivities are pivotal for the development and large-scale adoption of green-energy conversion and storage technologies like fuel cells and electrochemical batteries. Yet, SSE are extremely complex materials for which general rational design principles remain indeterminate. Here, we unite materials modelling, computational power and modern data analysis techniques to advance towards the solution of such a fundamental and technologically pressing problem. Our data-driven survey reveals that the correlations between ionic diffusion and other materials descriptors in general are non-linear and largest when the latter are of vibrational nature and explicitly account for anharmonicity. Surprisingly, principal component and k-means clustering analysis show that elastic and vibrational descriptors, rather than the usual ones related to chemical composition and ionic mobility, are best suited for disentangling the high diversity of SSE. Our findings highlight the need of considering databases that incorporate temperature effects to improve our understanding of SSE, and point towards a generalized approach to the design of energy materials.