Going beyond atom visualization—Characterization of supported two-atom single-cluster catalysts with scanning transmission electron microscopy 超越原子可视化—利用扫描透射电子显微镜表征双原子单团簇催化剂

Li，Cheng1,2; Chen，Jun Chi3; Wang，Xing Kun4; Huang，Ming Hua4; Theis，Wolfgang2; Li，Jun3,5; Gu，Meng1

2023

10.1007/s40843-022-2416-2

Science China Materials   影响因子和分区

2095-8226

2199-4501

As an innovative development of single-atom catalysts (SACs), single-cluster catalysts (SCCs) such as dual-atom catalysts have attracted considerable interest due to their excellent performance in catalysis. As one of the most powerful and visualizable tools, scanning transmission electron microscopy (STEM) has been widely applied in the characterization of SCCs. Herein, the nitrogen-doped carbon-supported FeFe and CoFe, two representative examples of homonuclear and heteronuclear SCCs, are characterized by STEM. Furthermore, an image processing program is developed to analyze the STEM images and to obtain the locations of atoms, as well as the projected distances between atoms in possible dual-atom pairs. The dimer distances of both CoFe and FeFe catalysts exhibit a trimodal distribution, which can correspond to the energy-favorable atomic structures of the theoretical simulations. Our work offers an avenue for directly revealing the possible atomic configurations of dual-atom sites in SCCs via big data statistics of STEM images and strong theoretical simulations. [Figure not available: see fulltext.].

aberration-corrected HAADF-STEM big data statistics DFT simulation image processing single-cluster catalysts

SCI ; EI

中文

第一 ; 通讯

National Key Research and Development Project["2022YFA1503900","2022YFA1503000","2022YFA1203400"] ; Shenzhen Fundamental Research Funding["JCYJ20210324115809026","JCYJ20220818100212027","JCYJ20200109141216566"] ; Shenzhen Science and Technology Program[KQTD20190929173815000] ; Guangdong scientific program[2019QN01L057] ; Guangdong Innovative and Entrepreneurial Research Team Program[2019ZT08C044] ; National Natural Science Foundation of China[22033005] ; Guangdong Provincial Key Laboratory of Catalysis[2020B121201002]

Materials Science

Materials Science, Multidisciplinary

WOS:000980592200001

SCIENCE PRESS

20231814046530

Atoms ; Big data ; Binary alloys ; Dimers ; Doping (additives) ; High resolution transmission electron microscopy ; Iron alloys ; Scanning electron microscopy

Iron Alloys:545.2 ; Data Processing and Image Processing:723.2 ; Optical Devices and Systems:741.3 ; Chemical Agents and Basic Industrial Chemicals:803 ; Chemical Products Generally:804 ; Organic Polymers:815.1.1 ; Atomic and Molecular Physics:931.3

2-s2.0-85154536397

Scopus

1.Department of Materials Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China
2.School of Physics and Astronomy,University of Birmingham,Birmingham,B15 2TT,United Kingdom
3.Department of Chemistry and Guangdong Provincial Key Laboratory of Catalytic Chemistry,Southern University of Science and Technology,Shenzhen,518055,China
4.School of Materials Science and Engineering,Ocean University of China,Qingdao,266100,China
5.Department of Chemistry and Engineering Research Center of Advanced Rare-Earth Materials of Ministry of Education,Tsinghua University,Beijing,100084,China

Li，Cheng,Chen，Jun Chi,Wang，Xing Kun,等. Going beyond atom visualization—Characterization of supported two-atom single-cluster catalysts with scanning transmission electron microscopy 超越原子可视化—利用扫描透射电子显微镜表征双原子单团簇催化剂[J]. Science China Materials,2023,66(7):2733-2740.

Li，Cheng.,Chen，Jun Chi.,Wang，Xing Kun.,Huang，Ming Hua.,Theis，Wolfgang.,...&Gu，Meng.(2023).Going beyond atom visualization—Characterization of supported two-atom single-cluster catalysts with scanning transmission electron microscopy 超越原子可视化—利用扫描透射电子显微镜表征双原子单团簇催化剂.Science China Materials,66(7),2733-2740.

Li，Cheng,et al."Going beyond atom visualization—Characterization of supported two-atom single-cluster catalysts with scanning transmission electron microscopy 超越原子可视化—利用扫描透射电子显微镜表征双原子单团簇催化剂".Science China Materials 66.7(2023):2733-2740.