Structural design of organic battery electrode materials: from DFT to artificial intelligence

Abstract Redox‐active organic materials are emerging as the new playground for the design of new exciting battery materials for rechargeable batteries because of the merits including structural diversity and tunable electrochemical properties that are not easily accessible for the inorganic counterparts. More importantly, the sustainability developed by using naturally abundant chemical elements (C, H, N, O and S) makes them as an ideal alternative material for Li‐ion batteries (LIBs). However, the identification and screening of proper organic materials is still challenging in the past decades. Assisted by the artificial intelligence, this review will give a summary of the theoretical design aspects of redox‐active organic materials from density‐functional theory (DFT) to machine learning (ML) methods in the past two decades, with a particular emphasis on the calculation method to predict the chemical/electrochemical stability and reversibility. This review will also analyze and discuss the challenges and perspectives for the development of organic battery materials.