Modeling and optimization of heterogeneous Fenton-like and photo-Fenton processes using reusable Fe₃O₄-MWCNTs

In this work, iron (II, III) oxide (Fe₃O₄) was synthesized and incorporated onto multi-walled carbon nanotubes (MWCNTs) to prepare Fe₃O₄-MWCNTs composite in a quest for evaluating its performance and reusability in both Fenton-like and photo-Fenton processes. The characterization of Fe₃O₄-MWCNTs by X-ray diffraction (XRD), transmission electron microscopy (TEM), Fourier-transform infrared (FTIR) spectroscopy, and energy dispersive X-ray (EDX) spectroscopy showed that the prepared catalyst can behave as a composite. Methylene blue (MB) was used as a substrate for evaluation of Fenton-like and photo-Fenton processes. The reusability of the catalyst and the influence of operation parameters such as pH, H₂O₂ dosage, and catalyst loading were investigated. Complete degradation of MB was attained by Fe₃O₄-MWCNTs in the aforementioned processes, whereas the removal efficiency of MB by using bare MWCNTs under the same conditions was 52%, which suggests that the generated oxidant species due to the reactions between H₂O₂ and leached iron contribute to the degradation of MB. A degradation pathway was proposed based on the oxidation intermediates that have been detected by mass spectrometry. The reusability of Fe₃O₄-MWCNTs has been examined in four consecutive cycles. The final removal of MB in the fourth cycle was 94%. The optimization of MB removal was investigated by response surface methodology (RSM) based on central composite design (CCD). Moreover, an artificial neural network (ANN) of type feed-forward back propagation was employed to model the influence of operating conditions. The ANN model revealed a high correlation in the prediction of the removal efficiency (R² = 0.9934).