Separations (Feb 2023)

Synthesis and Surface Modification of Iron Oxide Nanoparticles for the Extraction of Cadmium Ions in Food and Water Samples: A Chemometric Study

  • Faheem Shah,
  • Munazza Ghafoor

DOI
https://doi.org/10.3390/separations10020124
Journal volume & issue
Vol. 10, no. 2
p. 124

Abstract

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In this project, a prompt, efficient, and effective method for Cd2+ ions extraction from different food and water samples using magnetic dispersion-based solid phase extraction by functionalized iron oxide nanoparticles was proposed. Iron oxide nanoparticles were synthesized through the co-precipitation method followed by functionalization with tetraethyl orthosilicate (TEOS) and 3-aminopropyl silane (APTES) to obtain Fe3O4@SiO2@APTES. This composite was characterized through different techniques, including vibrating sample magnetometer, dynamic light scattering, zeta potential, FTIR, SEM, XRD, and BET. Variables studied were pH, temperature, sorbent amount, sonication time, and sample and eluent volume affecting the sorption efficacy of freshly synthesized sorbent. Plackett–Burman design was utilized for the identification of significant factors for microextraction of target analyte, while the central composite design was utilized for the optimization of significant factors. Detection and quantification limits obtained were 0.17 and 0.58 μgL−1, respectively, with an enhancement factor of 83.5. Under optimum conditions, Fe3O4@SiO2@APTES showed good stability even after >80 adsorption/desorption cycles run while maintaining over 96% analyte recoveries. The developed method was validated by assessing certified reference materials and standard addition methodology for Cd2+ detection in real samples. To confirm the precision, repeatability (RSDr) and reproducibility (RSDR) were calculated and found as n = 7) and n = 15), respectively. Furthermore, in accordance with the ISO/IEC 17025 recommendations, the validation was also confirmed through a “bottom-up” approach while considering all possible uncertainties in data.

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