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In‐Situ Dynamic Carburization of Mo Oxide with Unprecedented High CO Formation Rate in Reverse Water‐Gas Shift Reaction.

  • Published In: Angewandte Chemie, 2024, v. 136, n. 51. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Du, Xiangze; Li, Rongtan; Xin, Hui; Fan, Yamei; Liu, Chengxiang; Feng, Xiaohui; Wang, Jianyang; Dong, Cui; Wang, Chao; Li, Dan; Fu, Qiang; Bao, Xinhe 3 of 3

Abstract

In situ construction of active structure under reaction conditions is highly desired but still remains challenging in many important catalytic processes. Herein, we observe structural evolution of molybdenum oxide (MoOx) into highly active molybdenum carbide (MoCx) during reverse water‐gas shift (RWGS) reaction. Surface oxygen atoms in various Mo‐based catalysts are removed in H2‐containing atmospheres and then carbon atoms can accumulate on surface to form MoCx phase with the RWGS reaction going on, both of which are enhanced by the presence of intercalated H species or Pt‐dopants in MoOx. The structural evolution from MoOx to MoCx is accompanied by enhanced CO2 conversion, which is positively correlated with the surface C/Mo ratio but negatively with the surface O/Mo ratio. As a result, an unprecedented CO formation rate of 7544.6 mmol ⋅ gcatal−1 ⋅ h−1 at 600 °C has been achieved over in situ carbonized H‐intercalated MoO3 catalyst, which is even higher than those from noble metal catalysts. During 100 h stability test only a minimal deactivation rate of 2.3 % is observed. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Angewandte Chemie. 2024/12, Vol. 136, Issue 51, p1
  • Document Type:Article
  • Subject Area:Chemistry
  • Publication Date:2024
  • ISSN:0044-8249
  • DOI:10.1002/ange.202411761
  • Accession Number:181516693
  • Copyright Statement:Copyright of Angewandte Chemie is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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