A materials discovery framework based on conditional generative models applied to the design of polymer electrolytes
Arash Khajeh, X. L. Lei, Weike Ye, Zhenze Yang, Linda Hung, Daniel Schweigert, Ha-Kyung Kwon
Abstract
We introduce a computational materials discovery framework that integrates conditional generation, molecular dynamics simulations, evaluation, and feedback components to design polymer electrolytes with improved ionic conductivity.
Topics & Concepts
Generative grammarPolymer electrolytesElectrolyteGenerative modelComputer scienceMaterials scienceArtificial intelligenceChemistryElectrodeIonic conductivityPhysical chemistryMachine Learning in Materials Science