In situ transmission electron microscopy and artificial intelligence enabled data analytics for energy materials

Energy materials are vital to energy conversion and storage devices that make renewable resources viable for electrification technologies. In situ transmission electron microscopy(TEM) is a powerful approach to characterize the dynamic evolution of material structure, morphology, and chemistry at the atomic scale in real time and in operando. In this review, recent advancements of in situ TEM techniques for studying energy materials, including catalysts, batteries, photovoltaics, and thermoelectrics, are systematically discussed and summarized. The topics include a broad range of material transformations that are in situ stimulated by heating, biasing, lighting, electron-beam illuminating, and cryocooling under vacuum, liquid, or gas environments within TEM, as well as the mechanistic understanding of the associated solid-solid, solid-liquid, and solid-gas reactions elucidated by in situ TEM examination and operando measurements. Special focus is also put on the emerging progress of artificial intelligence enabled microscopy data analytics, including machine learning enhanced tools for retrieving useful information from massive TEM imaging, diffraction, and spectroscopy datasets, highlighting its merits and potential for automated in situ TEM experimentation and analysis. Finally, the pressing challenges and future perspectives on in situ TEM study for energy-related materials are discussed.