Identification of potential solid-state Li-ion conductors with semi-supervised learning
Forrest A. L. Laskowski, Daniel B. McHaffie, Kimberly A. See
Abstract
A semi-supervised machine learning pipeline is reported for the discovery of new Li-ion solid-state electrolytes. The approach is experimentally validated with the synthesis and characterization of a new superionic conductor predicted by the model.
Topics & Concepts
Fast ion conductorPipeline (software)ConductorIdentification (biology)Electrical conductorSolid-stateCharacterization (materials science)IonElectrolyteMaterials scienceComputer scienceNanotechnologyEngineering physicsChemistryEngineeringElectrodePhysical chemistryBotanyComposite materialOrganic chemistryProgramming languageBiologyMachine Learning in Materials ScienceAdvancements in Battery MaterialsAdvanced Battery Materials and Technologies