Response surface methodology optimization and modeling of green synthesis conditions for TiO2-ZnO nanocomposites using Vigna unguiculata L. extract

Abstract

Developing a more efficient and sustainable method than conventional chemical and physical approaches to synthesize TiO₂-ZnO nanocomposites is essential to reduce environmental impact. Green synthesis offers a sustainable alternative, minimizing toxic solvents and utilizing renewable biological sources. TiO₂-ZnO NCs is a well-known binary nanocomposite with different potential biomedical, photocatalysis and solar cell applications due to its excellent physiochemical properties. This study presents the response surface methodology, optimization, and modeling of the reaction conditions of TiO₂-ZnO NCs by green synthesis using the co-precipitation method from Vigna unguiculata L. extract as a reducing and stabilizing agent. Optimization of independent reaction conditions such as amount of dopant, reaction temperature, initial pH, and stirring time was performed using Response Surface Methodology-Box Behnken Design (RSM-BBD) of the design expert version 13 software (DX13). The strength and amount of active site of the synthesized TiO₂-ZnO NCs were calculated by back titration analysis. The results show that TiO₂-ZnO NCs were successfully precipitated and the optimization study obtained shows that the optimum number of active sites (8.881 mmol/g) of the TiO₂-ZnO NCs was achieved at 10.00% MR of TiO_2, 90 °C reaction temperature, initial pH of 11 and 23 min stirring time. The optimal reaction conditions were supported and confirmed by the solution ramp functions and bar graph plots. Statistically, the regression model and analysis of variance (ANOVA) revealed that the initial pH was the most significant parameter among the selected reaction conditions with the probability value (p-values) of 0.0011. The two-dimensional (2D) contour and three-dimensional (3D) response surface plots demonstrated a good interaction between the reaction variables during the biosynthesis. The porosity, particle size distribution (PSD) and specific surface area (SSA) of optimized TiO₂-ZnO NCs were evaluated using the nonlinear density functional theory (NLDFT) method. Consequently, the pore volume, pore size and SSA for the developed TiO₂-ZnO NCs were found to be 5.45×10^-2 cm³/g, 3.23 nm, and 351.80 m²/g, respectively, indicating that the optimized TiO₂-ZnO NCs are mesoporous in nature. This work indicated that mesoporous TiO₂-ZnO NCs were prepared through the novel use of Vigna unguiculata L. extract. RSM-BBD was successfully used in the design of experiment, model development, and optimization of highly active TiO₂-ZnO NCs production.