Photocatalytic decomposition of metronidazole by zinc hexaferrite coated with bismuth oxyiodide magnetic nanocomposite: Advanced modelling and optimization with artificial neural network

Abstract

The objective of the present study was to employ a green synthesis method to produce a sustainable ZnFe₁₂O₁₉/BiOI nanocomposite and evaluate its efficacy in the photocatalytic degradation of metronidazole (MNZ) from aqueous media. An artificial neural network (ANN) model was developed to predict the performance of the photocatalytic degradation process using experimental data. More importantly, sensitivity analysis was conducted to explore the relationship between MNZ degradation and various experimental parameters. The elimination of MNZ was assessed under different operational parameters, including pH, contaminant concentration, nanocomposite dosage, and retention time. The outcomes exhibited high a desirability performance of the ANN model with a coefficient correlation (R²) of 0.99. Under optimized circumstances, the MNZ elimination efficiency, as well as the reduction in chemical oxygen demand (COD) and total organic carbon (TOC), reached 92.71%, 70.23%, and 55.08%, respectively. The catalyst showed the ability to be regenerated 8 times with only a slight decrease in its photocatalytic activity. Furthermore, the experimental data obtained demonstrated a good agreement with the predictions of the ANN model. As a result, this study fabricated the ZnFe₁₂O₁₉/BiOI nanocomposite, which gave potential implication value in the effective decontamination of pharmaceutical compounds.

Keywords: Artificial neural network; Green magnetic nanocomposite; Pharmaceutical wastewater; Photocatalytic process; Sensitivity analysis; ZnFe(12)O(19)/BiOI.