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  • Title: Artificial neural network modeling of photocatalytic removal of a disperse dye using synthesized of ZnO nanoparticles on montmorillonite.
    Author: Kıranşan M, Khataee A, Karaca S, Sheydaei M.
    Journal: Spectrochim Acta A Mol Biomol Spectrosc; 2015 Apr 05; 140():465-73. PubMed ID: 25638428.
    Abstract:
    In this study, the photocatalytic ability of ZnO/Montmorilonite (ZnO/MMT) nanocomposite under UV-A, UV-B and UV-C radiation was investigated. ZnO nanoparticles were synthesized on the surface of MMT and used as photocatalyst in decolorization of Disperse Red 54 (DR54) solution. Synthesized nanocomposite was characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM) techniques and nitrogen adsorption/desorption isotherms curves. The average width of synthesized ZnO particles is in the range of 30-45 nm. Effect of UV light regions, initial dye concentration, initial dosage of nanocomposite, and reusability of catalyst was studied on decolorization efficiency. The highest decolorization efficiency was achieved under UV-C radiation. A three-layered feed forward back propagation artificial neural network model was developed to predict the photocatalysis of DR54 under UV-C radiation. According to ANN model the ZnO/MMT dosage with a relative importance of 49.21% is the most influential parameter in the photocatalytic decolorization process.
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