Dustgeer, Mohsin Raza and Jilani, Asim and Ansari, Mohammad Omaish and Shakoor, Muhammad Bilal and Ali, Shafaqat and Imtiaz, Aniqa and Zakria, Hazirah Syahirah and Othman, Mohd. Hafiz Dzarfan (2024) Reduced graphene oxide supported polyaniline/copper (II) oxide nanostructures for enhanced photocatalytic degradation of Congo red and hydrogen production from water. Journal of Water Process Engineering, 59 (NA). NA. ISSN 2214-7144
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Official URL: http://dx.doi.org/10.1016/j.jwpe.2024.105053
Abstract
Industries release numerous toxic and carcinogenic organic compounds into natural water reservoirs which poses worldwide threat to both aquatic life and human beings. In this study, ternary nanocomposites comprising CuO nanoparticles, reduced graphene oxide (rGO), and polyaniline (Pani) were prepared by hydrothermal methodology. The Pani@rGO/CuO composites demonstrated a significant degradation efficiency up to 91.67 % for Congo red dye (CR) under optimized conditions of dosage and concentration. Notably, the reaction rate constant (k) of Pani@rGO/CuO for CR dye was 3.27 times greater than that of pure CuO. Additionally, the hydrogen production capability of Pani@rGO/CuO was evaluated, and it exhibited the highest performance of 16.7 mmol h−1 g−1. The integration of rGO and Pani with CuO enhanced CR dye degradation and hydrogen production by providing additional adsorption sites. Furthermore, the hybridization of CuO with rGO and Pani increased the functionality and binding sites for interaction with CR dye thereby resulting in improved adsorption efficiency. The concentration of CR and the catalyst dosage also influenced the degradation process. Hence, the response surface methodology was utilized to create 13 sets of randomized experiments by altering the catalyst dosage and degradation time to predict the degradation of CR dye.
Item Type: | Article |
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Uncontrolled Keywords: | green energy, nanocomposites, photocatalytic hydrogen production, wastewater treatment |
Subjects: | Q Science > Q Science (General) |
Divisions: | Science |
ID Code: | 109002 |
Deposited By: | Yanti Mohd Shah |
Deposited On: | 27 Jan 2025 07:43 |
Last Modified: | 27 Jan 2025 07:43 |
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