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Progress and challenges in structural, in situ and operando characterization of single-atom catalysts by X-ray based synchrotron radiation techniques

  • Yuhang Liu
  • , Xiaozhi Su*
  • , Jie Ding
  • , Jing Zhou
  • , Zhen Liu
  • , Xiangjun Wei*
  • , Hong Bin Yang*
  • , Bin Liu*
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

Single-atom catalysts (SACs) represent the ultimate size limit of nanoscale catalysts, combining the advantages of homogeneous and heterogeneous catalysts. SACs have isolated single-atom active sites that exhibit high atomic utilization efficiency, unique catalytic activity, and selectivity. Over the past few decades, synchrotron radiation techniques have played a crucial role in studying single-atom catalysis by identifying catalyst structures and enabling the understanding of reaction mechanisms. The profound comprehension of spectroscopic techniques and characteristics pertaining to SACs is important for exploring their catalytic activity origins and devising high-performance and stable SACs for industrial applications. In this review, we provide a comprehensive overview of the recent advances in X-ray based synchrotron radiation techniques for structural characterization and in situ/operando observation of SACs under reaction conditions. We emphasize the correlation between spectral fine features and structural characteristics of SACs, along with their analytical limitations. The development of IMST with spatial and temporal resolution is also discussed along with their significance in revealing the structural characteristics and reaction mechanisms of SACs. Additionally, this review explores the study of active center states using spectral fine characteristics combined with theoretical simulations, as well as spectroscopic analysis strategies utilizing machine learning methods to address challenges posed by atomic distribution inhomogeneity in SACs while envisaging potential applications integrating artificial intelligence seamlessly with experiments for real-time monitoring of single-atom catalytic processes. © 2024 The Royal Society of Chemistry.
Original languageEnglish
Pages (from-to)11850-11887
JournalChemical Society Reviews
Volume53
Issue number24
Online published22 Oct 2024
DOIs
Publication statusPublished - 21 Dec 2024

Funding

This work was supported by the National Natural Science Foundation of China (no. 22075195, 22102207, 22475145 and U1932203), the Shanghai Municipal Science and Technology Major Project, the Photon Science Center for Carbon Neutrality, the City University of Hong Kong startup fund (9020003), the ITF-RTH-Global STEM Professorship (9446006), the JC STEM Lab of Advanced CO2 Upcycling, and the Youth Innovation Promotion Association of the Chinese Academy of Sciences (2023303).

RGC Funding Information

  • RGC-funded

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