JOURNAL ARTICLE

Cyanide‐based Covalent Organic Frameworks for Enhanced Overall Photocatalytic Hydrogen Peroxide Production.

  • Published In: Angewandte Chemie International Edition, 2024, v. 63, n. 19. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Zhou, Enbo; Wang, Futong; Zhang, Xiang; Hui, Yangdan; Wang, Yaobing 3 of 3

Abstract

Photocatalytic oxygen reduction to produce hydrogen peroxide (H2O2) is a promising route to providing oxidants for various industrial applications. However, the lack of well‐designed photocatalysts for efficient overall H2O2 production in pure water has impeded ongoing research and practical thrusts. Here we present a cyanide‐based covalent organic framework (TBTN‐COFs) combining 2,4,6‐trimethylbenzene‐1,3,5‐tricarbonitrile (TBTN) and benzotrithiophene‐2,5,8‐tricarbaldehyde (BTT) building blocks with water‐affinity and charge‐separation. The ultrafast intramolecular electron transfer (<500 fs) and prolonged excited state lifetime (748 ps) can be realized by TBTN‐COF, resulting in a hole accumulated BTT and electron‐rich TBTN building block. Under one sun, the 11013 μmol h−1 g−1 yield rate of H2O2 can be achieved without any sacrificial agent, outperforming most previous reports. Furthermore, the DFT calculation and in situ DRIFTS spectrums suggesting a Yeager‐type absorption of *O2⋅− intermediate in the cyanide active site, which prohibits the formation of superoxide radical and revealing a favored H2O2 production pathway. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Angewandte Chemie International Edition. 2024/05, Vol. 63, Issue 19, p1
  • Document Type:Article
  • Subject Area:Chemistry
  • Publication Date:2024
  • ISSN:1433-7851
  • DOI:10.1002/anie.202400999
  • Accession Number:176988366
  • Copyright Statement:Copyright of Angewandte Chemie International Edition 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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