Artificial neural network modeling of photocatalytic removal of a disperse dye using synthesized of ZnO nanoparticles on montmorillonite

• Synthesis and immobilization of zinc oxide nanoparticles on montmorillonite.
• Characterization of the ZnO/MMT nanocomposite by XRD, SEM, TEM, and BET.
• Photocatalysis of a disperse dye by synthesized ZnO/MMT nanocomposite.
• ANN modeling of the effect of the ZnO/MMT/UV-C process in removal of the dye.

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.

Schematics of synthesis of ZnO nanoparticles on montmorillonite.Figure optionsDownload as PowerPoint slide