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Synthesis of highly effective CuO–FeSe2 composites for the photodegradation of RhB under visible light

The release of industrial effluents into fresh water is a major contributor of water contamination. Therefore, it is highly desirable to develop a viable solution to this alarming issue to improve the quality of clean water. To enhance the photocatalytic efficiency and hence utilization ratio of CuO...

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Bibliographic Details
Published in:Research on chemical intermediates 2024, Vol.50 (6), p.2501-2518
Main Authors: Ahmad, Furqan, Hussain, Rafaqat, Khan, Sibghat Ullah, Shah, A., Alajmi, Mohamed Fahad, Arif, Muhammad, Hussain, Afzal, Parveen, Iqra, Rahman, Shams ur
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Language:English
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Summary:The release of industrial effluents into fresh water is a major contributor of water contamination. Therefore, it is highly desirable to develop a viable solution to this alarming issue to improve the quality of clean water. To enhance the photocatalytic efficiency and hence utilization ratio of CuO, a series of CuO–FeSe 2 composites with different varying contents of FeSe 2 were prepared through facile synthetic methods. X-ray diffraction (XRD) and energy-dispersive X-rays (EDX) analysis verified that the samples were successfully prepared without any contaminating phases. The average crystallite sizes of CuO and FeSe 2 were computed to be 29 and 21 nm respectively. For the CuO–FeSe 2 composites, the crystallite sizes varied between 25 and 27 nm. The morphology of CuO was comprised of needle-shaped structures, whereas that of FeSe 2 was observed to be flower-shaped structures comprising of irregular crystals. A red shift in the bandgap of CuO–FeSe 2 composites was observed with the increase in FeSe 2 concentration. The prepared photocatalysts were utilized to evaluate their efficiency under visible light against Rhodamine B (RhB). Among all the prepared composites, CuO–75% FeSe 2 revealed a remarkable performance and degraded 96% RhB in 180 min. Rate constants for the degradation of the dye were determined by applying the Langmuir–Hinshelwood model.
ISSN:0922-6168
1568-5675
DOI:10.1007/s11164-024-05286-6