Multi-Response Optimization of Green-Synthesized Ag₂O and ZnO Nanoparticles via Box-Behnken Design for Enhanced Wastewater Treatment Performance

The green synthesis of metal oxide nanoparticles (NPs) is a sustainable approach for water remediation, but it often suffers from uncontrolled size and morphology, limiting adsorption efficiency. In this work, Terminalia catappa leaf extract is used to optimize the methodical production of zinc oxide (ZnO) and silver oxide (Ag2O) nanoparticles. The effects of temperature (25–80 °C), extract-to-precursor volume ratio (2–11 mL), and pH (5–12) on the optical characteristics (UV-Vis absorbance wavelength) of the NPs were modeled and optimized using a three-factor Box-Behnken Design (BBD). The major factor in quadratic models was pH, which was very significant (p < 0.0001). Low pH (~5), moderate temperature (~52.5 °C), and a moderate extract volume (~6.5 mL) were shown to be the ideal circumstances for minimal wavelength (a sign of smaller, more stable NPs). XRD, SEM-EDX, and BET were used to evaluate the optimized Ag2O and ZnO NPs, confirming their high surface area and crystalline, spherical form. A new Ag2O/ZnO/CNT was created by anchoring these NPs on functionalized multi-walled carbon nanotubes (MWCNTs). nanocomposite. Promising removal efficiency for heavy metals (Cd, Cr, Fe, Ni, Pb, Zn) was demonstrated by preliminary adsorption testing on municipal wastewater. To create customized metal oxide nanoparticles with enhanced properties for environmental applications, this work develops a statistically guided green synthesis procedure.