Going beyond atom visualization—Characterization of supported two-atom single-cluster catalysts with scanning transmission electron microscopy

Cheng Li; Jun-Chi Chen; Xing-Kun Wang; Ming-Hua Huang; Wolfgang Theis; Jun Li; Meng Gu

doi:10.1007/s40843-022-2416-2

Going beyond atom visualization—Characterization of supported two-atom single-cluster catalysts with scanning transmission electron microscopy

Cheng Li, Jun-Chi Chen, Xing-Kun Wang, Ming-Hua Huang, Wolfgang Theis^*, Jun Li^*, Meng Gu^*

^*Corresponding author for this work

Physics and Astronomy

Research output: Contribution to journal › Article › peer-review

Abstract

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.

Original language	English
Pages (from-to)	2733–2740
Number of pages	8
Journal	Science China Materials
Volume	66
Issue number	7
Early online date	27 Apr 2023
DOIs	https://doi.org/10.1007/s40843-022-2416-2
Publication status	Published - Jul 2023

Bibliographical note

Acknowledgments:
This work was supported by the National Key Research and Development Project (2022YFA1503900, 2022YFA1503000, and 2022YFA1203400), Shenzhen Fundamental Research Funding (JCYJ20210324115809026, JCYJ20220818100212027, and JCYJ20200109141216566), Shenzhen Science and Technology Program (KQTD20190929173815000), Guangdong scientific program with contract no. 2019QN01L057, Guangdong Innovative and Entrepreneurial Research Team Program (2019ZT08C044) to Gu M and the computational study is supported by the National Natural Science Foundation of China (22033005) to Li J and is partially sponsored by Guangdong Provincial Key Laboratory of Catalysis (2020B121201002). We are grateful to the Pico Center at SUSTech CRF that receives support from Presidential fund and Development and Reform Commission of Shenzhen Municipality. The computational resource is supported by the Center for Computational Science and Engineering at SUSTech and the CHEM high-performance supercomputer cluster (CHEM-HPC) located at the Department of Chemistry, SUSTech.

Keywords

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

ASJC Scopus subject areas

General Materials Science

Access to Document

10.1007/s40843-022-2416-2

Cite this

@article{b3ba2796274f45f4a520cc6663590f00,

title = "Going beyond atom visualization—Characterization of supported two-atom single-cluster catalysts with scanning transmission electron microscopy",

abstract = "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.",

keywords = "aberration-corrected HAADF-STEM, big data statistics, DFT simulation, image processing, single-cluster catalysts",

author = "Cheng Li and Jun-Chi Chen and Xing-Kun Wang and Ming-Hua Huang and Wolfgang Theis and Jun Li and Meng Gu",

note = "Acknowledgments: This work was supported by the National Key Research and Development Project (2022YFA1503900, 2022YFA1503000, and 2022YFA1203400), Shenzhen Fundamental Research Funding (JCYJ20210324115809026, JCYJ20220818100212027, and JCYJ20200109141216566), Shenzhen Science and Technology Program (KQTD20190929173815000), Guangdong scientific program with contract no. 2019QN01L057, Guangdong Innovative and Entrepreneurial Research Team Program (2019ZT08C044) to Gu M and the computational study is supported by the National Natural Science Foundation of China (22033005) to Li J and is partially sponsored by Guangdong Provincial Key Laboratory of Catalysis (2020B121201002). We are grateful to the Pico Center at SUSTech CRF that receives support from Presidential fund and Development and Reform Commission of Shenzhen Municipality. The computational resource is supported by the Center for Computational Science and Engineering at SUSTech and the CHEM high-performance supercomputer cluster (CHEM-HPC) located at the Department of Chemistry, SUSTech.",

year = "2023",

month = jul,

doi = "10.1007/s40843-022-2416-2",

language = "English",

volume = "66",

pages = "2733–2740",

journal = "Science China Materials",

issn = "2095-8226",

publisher = "Springer",

number = "7",

}

TY - JOUR

T1 - Going beyond atom visualization—Characterization of supported two-atom single-cluster catalysts with scanning transmission electron microscopy

AU - Li, Cheng

AU - Chen, Jun-Chi

AU - Wang, Xing-Kun

AU - Huang, Ming-Hua

AU - Theis, Wolfgang

AU - Li, Jun

AU - Gu, Meng

N1 - Acknowledgments: This work was supported by the National Key Research and Development Project (2022YFA1503900, 2022YFA1503000, and 2022YFA1203400), Shenzhen Fundamental Research Funding (JCYJ20210324115809026, JCYJ20220818100212027, and JCYJ20200109141216566), Shenzhen Science and Technology Program (KQTD20190929173815000), Guangdong scientific program with contract no. 2019QN01L057, Guangdong Innovative and Entrepreneurial Research Team Program (2019ZT08C044) to Gu M and the computational study is supported by the National Natural Science Foundation of China (22033005) to Li J and is partially sponsored by Guangdong Provincial Key Laboratory of Catalysis (2020B121201002). We are grateful to the Pico Center at SUSTech CRF that receives support from Presidential fund and Development and Reform Commission of Shenzhen Municipality. The computational resource is supported by the Center for Computational Science and Engineering at SUSTech and the CHEM high-performance supercomputer cluster (CHEM-HPC) located at the Department of Chemistry, SUSTech.

PY - 2023/7

Y1 - 2023/7

N2 - 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.

AB - 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.

KW - aberration-corrected HAADF-STEM

KW - big data statistics

KW - DFT simulation

KW - image processing

KW - single-cluster catalysts

U2 - 10.1007/s40843-022-2416-2

DO - 10.1007/s40843-022-2416-2

M3 - Article

AN - SCOPUS:85154536397

SN - 2095-8226

VL - 66

SP - 2733

EP - 2740

JO - Science China Materials

JF - Science China Materials

IS - 7

ER -

Going beyond atom visualization—Characterization of supported two-atom single-cluster catalysts with scanning transmission electron microscopy

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this