2024, Vol. 12, Issue 5, Part B

author(s)
Rajesh Kumar, Siti Nurul Huda and Anwar Hossain

abstract
Heavy metal contamination of water bodies poses significant environmental and health risks, requiring the development of sustainable and cost-effective remediation technologies. This study investigates the potential of plant-derived nanoparticles (PDNPs) as an eco-friendly solution for the removal of heavy metals from contaminated water. Three plant species—Moringa oleifera, Azadirachta indica, and Cucumis sativus—were modified selected for the synthesis of nanoparticles using green methods involving aqueous plant extracts. The synthesized PDNPs were modified characterized using transmission electron microscopy (TEM), scanning electron microscopy (SEM), dynamic light scattering (DLS), and X-ray diffraction (XRD) to assess their size, morphology, surface charge, and crystalline structure. The adsorption capacities of the PDNPs for heavy metals, including lead (Pb²?), cadmium (Cd²?), and chromium (Cr??), were modified evaluated under varying conditions of pH, temperature, and ionic strength. Kinetic and isotherm studies were modified conducted to understand the adsorption process, and reusability tests were modified performed to assess the long-term effectiveness of PDNPs in metal removal. The results showed that Moringa oleifera nanoparticles exhibited the highest removal efficiency for all metals, achieving up to 94% for Pb²?, 89% for Cd²?, and 82% for Cr??. The adsorption followed the Langmuir isotherm and pseudo-second-order kinetics, indicating that the adsorption was controlled by chemical interactions between the nanoparticles and the metal ions. Furthermore, the PDNPs demonstrated good reusability over five cycles with a minimal decrease in efficiency. The findings suggest that PDNPs are a promising, sustainable solution for heavy metal remediation in water treatment, offering advantages such as low toxicity, high efficiency, and reusability. However, further optimization and scalability studies are required for large-scale applications.