Atomic Defects in Layered Transition Metal Dichalcogenides for Sustainable Energy Storage and the Intelligent Trends in Data Analytics

Defects in layered transition metal dichalcogenides play a crucial role in the development of high-energy-density and high-safety electrochemical devices for sustainable energy storage systems. Although transmission electron microscopy prevails as an indispensable tool for visualizing defects at the atomic scale, manual analysis in such data-intensive scenarios generally lacks both efficiency and accuracy. Fortunately, the emergence of machine learning is transforming the paradigm of electron microscopy data analytics, offering a potent tool to expedite the discovery of novel structures and knowledge. In this review, we briefly introduce the atomic structures of typical defect configurations in transition metal dichalcogenides, along with their beneficial effects on electrochemical redox kinetics and stability when used in batteries and supercapacitors. Then, the latest innovations in the defect-engineered transition metal dichalcogenides for advanced energy storage devices, and the progress made in machine learning methodologies for their application in high-throughput electron microscopy analytics are systematically summarized. Finally, this review is concluded with perspectives on the remaining challenges and future opportunities in intelligent defect characterizations and engineering toward the next-generation energy storage systems.