Data-Driven Advances in Electrochemical Energy and Sensing: Artificial Intelligence Approaches from Concept to Application
The intersection of machine learning (ML) and electrochemical research is catalyzing transformative advancements in energy storage and conversion technologies. This review critically examines the role of ML and deep learning (DL) in optimizing electrochemical systems, focusing on batteries, supercapacitors, fuel cell...