Battery Materials Discovery and Smart Grid Management using Machine Learning

Abstract The transition from fossil fuels to renewable energy represents a grand challenge for humankind. For this vision come pass, significant advances in storage technologies such as batteries, which solve the intermittency of energy, need be achieved. Developing new battery materials with higher capacities and longer lifetimes is thus paramount importance. Moreover, presents smart grid management. To end, researchers have begun turning machine learning (ML) techniques: algorithms that learn datasets automatically improve through experience. These can used make predictions informed decisions, accelerate process discovery systems Here we discuss key ML concepts guided important developments In process, also examine critical challenges, future opportunities, how impact.