Results in Chemistry (Aug 2024)

Development of a colorimetric sensor for selective manganese detection using green-synthesized silver nanoparticles from Withania somnifera

  • Mujeeb Ur Rahman,
  • Muhammad Wajid Ullah,
  • Sulaiman Ali Alharbi,
  • Saleh Alfarraj,
  • Mazhar Ul-Islam,
  • Mohamed Yassin Ali,
  • Daochen Zhu

Journal volume & issue
Vol. 10
p. 101733

Abstract

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This study reports the green synthesis of silver nanoparticles (AgNPs) using the fruit extract of Withania somnifera and their application as a colorimetric sensor for selective manganese (Mn2+) ion detection. The synthesis of AgNPs was optimized by varying pH, reaction time, and concentrations of fruit extract and AgNO3. UV–visible spectroscopy revealed that the highest absorbance of AgNPs occurred at pH 11, indicating optimal conditions for NPs formation. The absorbance behavior over time demonstrated the nucleation and stabilization processes, with optimal stability achieved after 1800 min. Increasing concentrations of fruit extract and AgNO3 enhanced NPs synthesis, reaching a plateau at 1.0 mL of extract and 1.0 mM AgNO3, respectively. Transmission electron microscopy (TEM) confirmed the formation of spherical AgNPs of 43–85 nm. Fourier-transform infrared spectroscopy (FTIR) indicated the involvement of functional groups such as O-H and C=O in the reduction and stabilization of AgNPs. The green-synthesized AgNPs exhibited notable antioxidant activity, with moderate free radical scavenging abilities compared to ascorbic acid. The colorimetric detection of Mn2+ was achieved through the aggregation of AgNPs, leading to a visible color change. UV–vis absorption spectra showed a prominent peak at 412 nm, with a linear relationship between absorbance change and Mn2+ concentration, demonstrating high sensitivity and selectivity. Comparative studies with other metal ions (Co2+, Cr3+, Ni2+) confirmed the specificity of AgNPs towards Mn2+. In conclusion, the green-synthesized AgNPs from W. somnifera offer a cost-effective and environmentally friendly approach for Mn2+ detection, with significant potential for environmental monitoring and biomedical applications.

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