Comparative Analysis of Green and Chemical Synthesis Approaches for Lead Ion Detection Using Iron Oxide Nanoparticles
Lead (Pb²⁺) contamination poses a significant threat to human health and the environment due to its high toxicity, bioaccumulation, and persistence. The development of efficient and selective sensing mechanisms for Pb²⁺ detection is, therefore, crucial for environmental monitoring and industrial applications. In this study, iron oxide nanoparticles (FeO NPs) were synthesized using both green and chemical methods and employed as fluorescence-based sensors for the selective detection of Pb²⁺ ions in an aqueous medium. The green synthesis method utilized plant-derived extracts, resulting in FePE-NPs, while the chemically synthesized nanoparticles were designated as FeCH-NPs. Comparative analysis demonstrated that FePE-NPs exhibited superior performance, with a lower limit of detection (LOD) of 19.57 nM, compared to 29.43 nM for FeCH-NPs. The FePE-NPs also exhibited greater selectivity for Pb²⁺ over competing metal ions due to their enhanced surface functionality and biocompatibility. Characterization techniques, including UV-vis, FTIR, XRD, DLS, and FE-SEM, confirmed the successful synthesis and stability of the nanoparticles. Additionally, real water sample testing revealed high recovery rates (94–98% for FePE-NPs and 90–97% for FeCH-NPs), further validating their potential for practical applications. The study highlights the advantages of green synthesis, which not only enhances the sensing efficiency but also promotes sustainable and eco-friendly nanoparticle fabrication. The findings suggest that FePE-NPs serve as an efficient, cost-effective, and environmentally friendly sensor for detecting trace levels of lead ions in contaminated water sources, paving the way for future advancements in green nanotechnology for environmental remediation.
Publication Details
- Journal
- MatSci express.
- Published
- 2025-06-01
- DOI
- https://doi.org/10.69626/mse.2025.0113
- Primary Topic
- Geochemistry and Geologic Mapping
- Type
- article
- Field-Weighted Citation Impact
- 0.00