Energy shortage is a severe challenge nowadays. It has affected the development of new energy sources. Artificial intelligence (AI), such as learning and analyzing, has been widely used for various advantages. It has been successfully applied to predict materials, especially energy storage materials. In this paper, we present a survey of the present status of AI in energy storage materials via capacitors and Li-ion batteries. We picture the comprehensive progress of AI in energy storage materials, including the advantages and disadvantages of material data to support AI. Finally, we provide some ideas to solve those challenges.

With the characteristics of high-speed calculation and high-accuracy prediction, artificial intelligence (AI) which also known as machine intelligence, including deep learning, machine learning, etc., have shown great advantages in cross-field applications. In material science field, AI can be used to discover new materials and predict corresponding critical properties. At present, AI has been used in the exploitation of energy conversion materials and other energy-related materials. In this review, we summary the current achievements of AI applications in energy conversions, analyze the advantages and disadvantages of AI techniques in material researches and point out future development prospects.