In Situ Transmission Electron Microscopy and Three-Dimensional Electron Tomography for Catalyst Studies

作     者：Chen Sun Kuo Liu Jian Zhang Qian Liu Xijun Liu Lili Han Chen Sun;Kuo Liu;Jian Zhang;Qian Liu;Xijun Liu;Lili Han

作者机构：College of ChemistryFuzhou UniversityFuzhou 350116China State Key Laboratory of Structural ChemistryFujian Institute of Research on the Structure of MatterChinese Academy of SciencesFuzhou 350002China Key Laboratory of Spin Electron and Nanomaterials of Anhui Higher Education InstitutesSuzhou UniversitySuzhou 234000China Institute for Advanced StudyChengdu UniversityChengdu 610106 China MOE Key Laboratory of New Processing Technology for Non-Ferrous Metals and Materialsand Guangxi Key Laboratory of Processing for Non-Ferrous Metals and Featured MaterialsSchool of ResourceEnvironments and MaterialsGuangxi UniversityNanning 530004China 

出 版 物：《Chinese Journal of Structural Chemistry》 (结构化学（英文）)

年 卷 期：2022年第41卷第10期

页      面：56-76页

核心收录：

学科分类：081705[工学-工业催化] 08[工学] 0817[工学-化学工程与技术] 080502[工学-材料学] 0805[工学-材料科学与工程（可授工学、理学学位）] 

基　　金：supported by National Key Research and Development Program of China (2019YFA0210403) 

主　　题：in situ TEM catalyst electron tomography 3D reconstruction artificial intelligence machine learning 

摘      要：An in-depth understanding of the catalytic reaction mechanism is the key to designing efficient and stable catalysts. In situ transmission electron microscope(TEM) is the most powerful tool to visualize and analyze the microstructures of catalysts during catalysis. In situ TEM combined with three-dimensional(3D) electron tomography(ET) reconstruction technique enables interrogations of catalysts’ structural dynamics and chemical changes in high temporal and spatial dimensions. In this review, we discuss and summarize the recent advances in in situ TEM together with 3D ET for catalyst studies. Topics include the latest research progress of in situ TEM imaging as well as 3D visualization and quantitative analysis of catalysts. We also pay particular attention to artificial intelligence(AI)-enhanced smart 3D ET. These include deep learning(DL)-based data compression and storage for the analysis of large TEM data, recovery of wedge-shaped information lost in 3D ET reconstructions, and DL models for reducing residual artifacts in 3D reconstructed images. Finally, the challenges and development prospects of current in situ TEM and 3D ET research are discussed.