Screening Platform for Promising Na Superionic Conductors for Na-Ion Solid-State Electrolytes

초록

Na-ion batteries are considered a promising alternativeto theanalogous Li-ion batteries because of their low manufacturing cost,large abundance, and similar chemical/electrochemical properties.In particular, research on Na-ion solid electrolytes, which resolvethe flammability issues associated with liquid electrolytes and increasethe energy density obtained using a particular metal anode, is rapidlygrowing. However, the ionic conductivities of these materials arelower than those of liquids. We present a novel classification approachbased on machine learning for identifying Na superionic conductor(NASICON) materials with outstanding ionic conductivities. We obtainednew features based on chemical descriptors such as Na content, elementalradii, and electronegativity. We then classified 3573 NASICON structuresby implementing the ensemble model of gradient boosting algorithms,with an average prediction accuracy of 84.2%. We further validatedthe thermodynamic stability and ionic conductivity values of the materialsclassified as superionic materials by employing density functionaltheory calculations and ab initio molecular dynamics simulations.Na3YTaSi2PO12, Na3HfZrSi2PO12, Na3LaTaSi2PO12, and Na3ScTaSi2PO12 were confirmedas promising NASICON structures that fulfill the requirements of solid-stateelectrolytes.

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