Response Surface Methodology (RSM) modelling for the photocatalytic optimization study of benzophenone removal using CuWO4/NiO nanocomposite

Emerging contaminants are posing a new water quality challenge, worldwide. The majority of pharmaceutical and personal care products used by us have been regarded as emerging contaminants. Benzophenone is one such chemical found in personal care products, specially in sunscreen creams as an UV-filter. Copper tungstate/nickel oxide (CuWO₄/NiO) nanocomposite with visible (LED) light irradiation has been investigated in degradation of benzophenone, in the present study. The co-precipitation approach was used to produce the aforementioned nanocomposite. XRD, FTIR, FESEM, EDX, Zeta potential, and UV–Vis spectroscopy illustrated the structure, morphology, and other catalytic features. Response surface methodology (RSM) was used to optimize and simulate the photodegradation of benzophenone. Herein, catalyst dose, pH, initial pollutant concentration, and contact time were considered as the independent factor in the design of experiment (DoE) using RSM with percentage degradation as the dependent factor or as a response. The CuWO₄/NiO nanocomposite demonstrated high photocatalytic performance of 91.93% at pH = 11 with a pollutant concentration of 0.5 mg/L and a catalyst dose of 5 mg within 8 h under ideal circumstances. The RSM model was determined to be the most convincible with an R² value of 0.99 and a probability value (P-value) of 0.0033, respectively, with a agreeable projected and actual values. As a result, it is envisioned that this study may provide new avenue for developing a strategy to target such emerging contaminants.