Statistical optimization of silver nanoparticle synthesis by green tea extract and its efficacy on colorimetric detection of mercury from industrial waste water

Environmental Research(2022)

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Abstract
For the optimization of silver nanoparticle production, a central composite design was used with three parameters: AgNO3 concentration, green tea extract concentration, and temperature at three different levels. The size of the synthesized silver nanoparticle, its UV absorbance, zeta potential, and polydispersity index were set as the response parameters. Silver nanoparticles obtained in the optimization process were characterized and its efficacy on colorimetric detection of mercury was evaluated. The response variables were significant for the factors analyzed, and each variable had a significant model (P < 0.05). The ideal conditions were: 1 mM AgNO3, 0.5% green tea extract, and 80 °C temperature. To analyze the produced AgNPs under certain ideal conditions, Fourier transform infrared spectroscopy (FTIR), dynamic light scattering (DLS), transmission electron microscopy (TEM), scanning electron microscopy (SEM), and X-ray diffraction (XRD) were used. The UV–visible spectra of AgNPs revealed an absorption maxima at 424 nm. The XRD pattern reveals a significant diffraction peak at 38.25°, 44.26°, 64.43°, and 77.49°, which corresponds to the (111), (200), (220), and (311) planes of polycrystalline face-centered cubic (fcc) silver, respectively. The TEM and SEM analyses confirmed that the particles were spherical, and dynamic light scattering study determined the average diameter of AgNPs to be 77.4 nm. The AgNPs have a zeta potential of −62.6 mV, as determined by the zeta sizer analysis. The AgNPs detects mercury at a micromolar concentration. Furthermore, the environmentally friendly generated AgNPs were used to detect mercury in a colorimetric method that was effectively employed for analytical detection of Hg2+ ions in an aqueous environment for the purpose of practical application.
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Key words
Green tea extract,AgNPs,Statistical optimization,Central composite design,Detection of Hg2+
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