4.7 Article

A novel bimetallic Fe-Cu-CNT catalyst for effective catalytic wet peroxide oxidation: reaction optimization and mechanism investigation

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CHEMICAL ENGINEERING JOURNAL
卷 479, 期 -, 页码 -

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ELSEVIER SCIENCE SA
DOI: 10.1016/j.cej.2023.147320

关键词

Catalytic wet peroxide oxidation; Advanced oxidation process; Bimetallic catalyst; Methylene blue; Carbon nanotube

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Treatment of organic wastewater using catalytic wet peroxide oxidation (CWPO) is important. A new bimetallic Fe-Cu-CNT catalyst was developed and optimized for efficient treatment. The catalyst showed better performance under low pH, high MB concentration, and moderate temperature conditions. Hydroxyl radicals played a crucial role in the treatment process.
Treatment of organic wastewater is of great importance and can be carried out by catalysis technologies such as catalytic wet peroxide oxidation (CWPO). A novel bimetallic Fe-Cu-CNT catalyst was first developed by a facile hydrothermal method; Fe species (Fe (II) and Fe (III)) and Cu species (Cu (I) and Cu (II)) were used to fabricate the catalyst with the CNTs, which was stable during testing. Methylene blue (MB) was chosen as model compound for the study; the optimization for treatment by the Box-Behnken design indicated that a combination of low pH, high MB concentration and intermediate temperature led to better treatment performance. The CWPO reaction obeyed the 2nd-order kinetic equation and the catalyst activity increased with an increase in the Cu content. The reaction induction period was shortened with decreasing Fe:Cu ratio. The cycling reaction between Fe3+/Fe2+ and Cu2+/Cu+ pairs generated a large number of oxidative radicals and improved the pollutant degradation efficiency. Finally, the reaction rate equation of CWPO over Fe-Cu-CNT was derived, and it was experimentally illustrated that hydroxyl radicals played a crucial role in the treatment. This study demonstrates that the optimized Fe-Cu-CNT has great potentials for treatment of organic wastewater with higher efficiency and lower cost.

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