Molecular dynamics-machine learning approaches for the accurate prediction of electrochemical windows of ionic liquid electrolytes for dual-ion batteries
Surya Sekhar Manna, Souvik Manna, Biswarup Pathak
Abstract
We have considered different cation and anion based ionic liquids and predicted the electrochemical window of 660 ionic liquid-based electrolytes using machine learning techniques for dual ion battery studies.
Topics & Concepts
Ionic liquidElectrochemical windowIonElectrolyteElectrochemistryDual (grammatical number)Battery (electricity)Ionic bondingMolecular dynamicsMaterials scienceComputer scienceChemical physicsInorganic chemistryChemistryIonic conductivityElectrodeComputational chemistryPhysicsThermodynamicsPhysical chemistryOrganic chemistryCatalysisLiteratureArtPower (physics)Advancements in Battery MaterialsIonic liquids properties and applicationsMachine Learning in Materials Science