JOURNAL ARTICLE

Fe3O4@Co3S4 Nanocatalyst: Enhanced Activation of Peroxymonosulfate for Acetaminophen Degradation.

  • Published In: NANO (1793-2920), 2024, v. 19, n. 7. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Guan, Xiaotong; Jiang, Yu; Meng, Liang 3 of 3

Abstract

How to accelerate the electron transfer to promote the circulating efficiency of Fe 2 + /Fe 3 + is a key problem to be solved, so that magnetic particles can activate peroxymonosulfate well to efficiently degrade acetaminophen (ACE). Herein, a Fe3O4@Co3S4 catalyst was prepared by modifying Co3S4 nanosheets on the surface of magnetic Fe3O4 particles. The Co 2 + in the modified layer Co3S4 accelerates the rate of electron transfer between Fe 2 + and Fe 3 + , thus promoting the circulating efficiency of Fe 2 + /Fe 3 + . Fe3O4@Co3S4/PMS system can degrade over 95% of ACE within 5 min. Quenching experiment and ESR tests prove that non-radical 1O2 and SO 4 • − played predominant roles in the advanced oxidation process. And after six cycles, the degradation rate could still be higher than 50%. A Fe3O4@Co3S4 catalyst was prepared by modifying Co3S4 nanosheets on the surface of magnetic Fe3O4 particles. The Co2+ in the modified Co3S4 layer accelerates the rate of electron transfer between Fe2+ and Fe3+, thus promoting the circulating efficiency of Fe2+/Fe3+. Fe3O4@Co3S4/PMS system can degrade over 95% of ACE within 5 mins. The Fe3O4@Co3S4 catalyst is of great potential application value in removal of organic pollution and environmental purification. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:NANO (1793-2920). 2024/06, Vol. 19, Issue 7, p1
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2024
  • ISSN:1793-2920
  • DOI:10.1142/S1793292023501084
  • Accession Number:178334203
  • Copyright Statement:Copyright of NANO (1793-2920) is the property of World Scientific Publishing Company 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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