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Articles

Green synthesis: Photocatalytic degradation of textile dyes using metal and metal oxide nanoparticles-latest trends and advancements

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Pages 2617-2723 | Published online: 30 Dec 2019
 

Abstract

The balance between economic development and environmental damage is also evident in the problem of pollution and waste management. Increased economic activity, mainly in industrial countries, has seen a rise in pollution generated from waste including sewage, trash, and litter. Particularly, the textile industry produces a significant amount of liquid effluent pollutants due to the vast amounts of water used in fabric processing. Dyes are a major class of synthetic organic compounds used in many industries (textile, pharmaceutical, rubber, etc.). Nearly 50,000 tons of dyes are discharged into the environment annually. This has resulted in significant water pollution worldwide. The reduction of these dye compounds from industrial wastewater has been achieved using chemical, physical, and biological methods. However, these approaches are time-consuming, costly, and pose disposal problems. Currently, photocatalytic degradation by nanoparticles is attracting significant attention. In photocatalytic degradation, the pollutants are degraded under UV-visible light irradiation in the presence of catalysts. Compared to the conventional methods, this technique is inexpensive and does not form any polycyclic products. In this review, we focus on different green-synthesized NPs such as Au, Ag, Pt, Pd, ZnO, CuO, α-Fe2O3, TiO2, CeO2, SnO2, and NiO together with and their applications in photocatalytic activities.

    Highlights

  • The review focuses on the green synthesis of metal/ metal oxide nanoparticles

  • Green synthesized metal/metal oxide photocatalysts is comprehensively reviewed

  • Factors affecting the photo-catalytic degradation of dyes also discussed

  • Classification of dyes and photocatalytic mechanism of metal/ metal oxide nanoparticles was highlighted

Graphical Abstract

Additional information

Funding

This work was supported by National Research Foundation of Korea (NRF) 2017R1D1A1B03035957, MSIP-2018R1A2B6006056 and 2019R1F1A1060655.

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