This analysis reveals how precursor concentration impacts the catalytic performance and morphology in ZnO nanoparticles, suggesting new wastewater treatment solutions.
Water pollution poses a critical global challenge, necessitating advanced wastewater treatment solutions. Zinc oxide nanoparticles (ZnO NPs) have emerged as efficient catalysts for degrading organic pollutants via advanced oxidation processes. This study investigates the influence of precursor concentration on the morphology and catalytic efficiency of ZnO NPs synthesized via a cost-effective co-precipitation method. ZnO NPs were prepared using varying zinc nitrate hexahydrate concentrations (0.025 M, 0.05 M, 0.1 M, 0.15 M, and 0.2 M) and characterized using X-ray diffraction (XRD) and scanning electron microscopy (SEM). The XRD analysis confirmed the hexagonal wurtzite structure with high crystallinity, while SEM revealed morphological variations, including spherical and agglomerated nanostructures, depending on precursor concentration. The photocatalytic performance of ZnO NPs was evaluated in a visible-light-assisted photo-Fenton process for degrading crystal violet (CV) dye. Results demonstrated that ZnO NPs synthesized at 0.1 M precursor concentration exhibited superior catalytic activity, achieving 91.09% CV degradation within 45 minutes, compared to 75.90% (0.025 M), 88.87% (0.05 M), 85.24% (0.15 M), and 89.89% (0.2 M). Further optimization studies assessed the impact of catalyst dosage, initial dye concentration, and H₂O₂ levels. Increasing catalyst dosage from 30 mg/L to 90 mg/L enhanced degradation efficiency to 95.42%, while higher dye concentrations reduced catalytic performance due to active site saturation. An optimal H₂O₂ concentration of 0.1 M yielded maximum degradation, with excess H₂O₂ inhibiting the process by radical scavenging. This study highlights the critical role of precursor concentration in tailoring ZnO NP properties for efficient wastewater treatment, offering insights into scalable, eco-friendly dye degradation solutions.
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Bote et al. (2025) studied this question.