Accelerating the discovery of disordered multi-component solid-state electrolytes using machine learning interatomic potentials
Yanhao Deng, Li Yan, Gopalakrishnan Sai Gautam, Bonan Zhu, Zeyu Deng
Abstract
Machine learning interatomic potentials, fine-tuned for complex solid-state electrolytes, enable accurate modeling and discovery of novel compositions with enhanced ion transport for next-generation batteries.
Topics & Concepts
Component (thermodynamics)ElectrolyteMaterials scienceSolid-stateState (computer science)Interatomic potentialComputer scienceChemical physicsStatistical physicsChemistryPhysicsEngineering physicsMolecular dynamicsThermodynamicsComputational chemistryPhysical chemistryElectrodeAlgorithmMachine Learning in Materials ScienceSolid-state spectroscopy and crystallographyAdvanced Thermoelectric Materials and Devices