Biosynthesis and Optimization of ZnO Nanoparticles Using Leaf Extract for Electrochemical Sensor and Antibacterial Activity.

In this study, zinc oxide nanoparticles (ZnO NPs) were synthesized using an aqueous extract of the () plant. The I-optimal coordinate exchange randomized response surface methodology (RSM) was used to optimize the effect of the zinc acetate precursor, temperature, and time on ZnO NPs by designing nine runs. From ANOVA analysis, the significance and validity of the designed model showed that the optimal values of the zinc acetate precursor, temperature, and time during ZnO NPs synthesis were found to be ∼0.06 M, ∼30 °C, and ∼1.35 h, respectively. The obtained ZnO NPs under these optimized conditions were characterized and explored by UV-vis, TGA/DTA, FTIR, XRD, SEM-EDX, TEM, HRTEM, and SAED. Furthermore, the electrocatalytic performance of ZnO NPs was performed for sulfamethoxazole (SMZ) sensing activity with a 0.3528 μM (S/N = 3) limit of detection (LOD). In addition, an antibacterial study revealed that ZnO NPs confirmed an excellent zone of inhibition against , , , and pathogenic drug resistance bacterial strains at concentrations of 50, 75, and 100 μg/mL. Thus, ZnO NPs synthesized using the leaf have a potential electrocatalytic activity for diverse organic pollutant detection as well as a desirable material for such drug resistance antimicrobial strains.