Machine learning reveals factors that control ion mobility in anti-perovskite solid electrolytes
Kwangnam Kim, Donald J. Siegel
Abstract
Machine learning is used to identify and assess the relative importance of features that control ion mobility in anti-perovskite solid electrolytes. Lattice properties such as hopping distance and channel width have the largest impact.
Topics & Concepts
ElectrolyteIonPerovskite (structure)Materials scienceFast ion conductorLattice (music)Control (management)Computer scienceChemical physicsArtificial intelligenceChemistryPhysicsCrystallographyPhysical chemistryElectrodeAcousticsOrganic chemistryAdvanced Battery Materials and TechnologiesPerovskite Materials and ApplicationsAdvanced Thermoelectric Materials and Devices