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CuO/TiO(2)/ZnO NPs Anchored Hydrogen Exfoliated Graphene: To Comprehend the Role of Graphene in Catalytic Reduction of p-Nitrophenol
[Image: see text] The present study deals with sonochemically in situ synthesis of a novel functional catalyst using hydrogen exfoliated graphene (HEG) supported titanium dioxide (TiO(2)) and copper sulfate (CuSO(4)) doped with zinc oxide (ZnO) (abbreviated as Ti/Cu/Zn-HEG). The synthesis of the Ti/...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10652271/ https://www.ncbi.nlm.nih.gov/pubmed/38024706 http://dx.doi.org/10.1021/acsomega.3c03859 |
Sumario: | [Image: see text] The present study deals with sonochemically in situ synthesis of a novel functional catalyst using hydrogen exfoliated graphene (HEG) supported titanium dioxide (TiO(2)) and copper sulfate (CuSO(4)) doped with zinc oxide (ZnO) (abbreviated as Ti/Cu/Zn-HEG). The synthesis of the Ti/Cu/Zn-HEG nanocomposite (NCs) catalyst was confirmed through its characterizations by XRD, SEM-EDX, TEM, XPS, FTIR, and BET methods. It was assessed for catalytic conversion of a model aromatic compound para-nitrophenol (p-NP) in an aqueous solution. The p-NP is a nitroaromatic compound that has a toxic and mutagenic effect. Its removal from the water system is necessary to protect the environment and living being. The newly synthesized Ti/Cu/Zn-HEG NCs were applied for their higher stability and catalytic activity as a potential candidate for reducing p-NP in practice. The operating parameters, such as p-NP concentration, catalyst dosage, and operating time were optimized for 150 ppm, 400 ppm, and 10 min through response surface methodology (RSM) in Design-Expert software to obtain the maximum reduction p-NP up to 98.4% at its normal pH of 7.1 against the controls (using HEG, Ti/Cu-HEG, and Zn-HEG). Analysis of variance of the response suggested the regression equation to be significant for the process with a major impact on catalyst concentration and operating time. The model prediction data (from RSM) and experimental data were corroborated well as reflected through model’s low relative error (RE < 0.10), high regression coefficient (R(2) > 0.97), and Willmott d-index (d(will-index) > 0.95) values. |
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