Issue 32, 2019

Magnetite nanoparticles coated with surfactant Sylgard 309 and its application as an adsorbent for paraben extraction from pharmaceutical and water samples

Abstract

In this paper, the extraction of parabens using a newly developed sorbent, Sylgard 309@MNP, is presented. Sylgard 309@MNP was prepared by coating Fe3O4 nanoparticles with the non-ionic surfactant Sylgard 309. It was characterised based on scanning electron microscopy, Fourier-transform infrared, X-ray diffraction, and vibrating sample magnetometry which confirmed the successful functionalisation of Sylgard 309 on the surface of Fe3O4 nanoparticles. The adsorption efficiency of the synthesised Sylgard 309@MNP in magnetic solid phase extraction towards selected parabens, namely methylparaben, ethylparaben, propylparaben, and benzylparaben, was evaluated using HPLC-UV. Under optimal conditions, the proposed method was then applied in various samples. The validation of the method shows good linearity (0.1–1.00 μg mL−1) with the coefficient of determination (R2) > 0.9995. The limits of detection (LOD) and quantification (LOQ) of the developed method are in the range of 0.02–0.03 μg mL−1 and 0.08–0.09 μg mL−1 respectively. The extraction recovery from pharmaceutical and personal care products, water samples, and cosmetics was in the range of 60–120%, 72–119%, and 110–120% with the relative standard deviation (RSD) of 0.64–11.8%, 0.04–11.6%, and 0.04–13.9%, respectively. This method was successfully used for analysing parabens in real samples.

Graphical abstract: Magnetite nanoparticles coated with surfactant Sylgard 309 and its application as an adsorbent for paraben extraction from pharmaceutical and water samples

Supplementary files

Article information

Article type
Paper
Submitted
30 May 2019
Accepted
21 Jul 2019
First published
23 Jul 2019

Anal. Methods, 2019,11, 4126-4136

Magnetite nanoparticles coated with surfactant Sylgard 309 and its application as an adsorbent for paraben extraction from pharmaceutical and water samples

M. M. Ariffin, N. M. Sohaimi, B. S. Yih and N. M. Saleh, Anal. Methods, 2019, 11, 4126 DOI: 10.1039/C9AY01147A

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