Machine learning-assisted materials development and device management in batteries and supercapacitors: performance comparison and challenges
Swarn Jha, Matthew Yen, Yazmin Soto Salinas, Evan M. Palmer, John Anzel Villafuerte, Hong Liang
Abstract
This review compares machine learning approaches for property prediction of materials, optimization, and energy storage device health estimation. Current challenges and prospects for high-impact areas in machine learning research are highlighted.
Topics & Concepts
SupercapacitorComputer scienceEnergy storageCurrent (fluid)Energy (signal processing)Artificial intelligenceMachine learningSystems engineeringEngineeringElectrical engineeringElectrochemistryStatisticsChemistryMathematicsPhysical chemistryElectrodePower (physics)PhysicsQuantum mechanicsAdvanced Battery Technologies ResearchMachine Learning in Materials ScienceAdvancements in Battery Materials