Issue 37, 2019

Mono-6-thio-β-cyclodextrin-functionalized AuNP/two-dimensional TiO2 nanosheet nanocomposite for the electrochemical determination of trace methyl parathion in water

Abstract

In this study, two-dimensional (2D) TiO2 nanosheets (TiO2NSs) composited with Au nanoparticles and mono-6-thio-β-cyclodextrin (SH-β-CD) monolayers were prepared for constructing an electrochemical sensing interface on a glassy carbon electrode (SH-β-CD/AuNP/TiO2NS/GCE) surface. Because of the outstanding advantages of a large active surface area, excellent electron-transfer speed and electrocatalytic activity of AuNPs/TiO2NSs and the selective recognition properties of SH-β-CD, the as-prepared sensor could remarkably improve the electrochemical response signals of trace methyl parathion (MP) pesticide. The square-wave voltammetry (SWV) signal of MP at the as-prepared sensor was ca. 4.2 and 5.7 times larger than that at the AuNP/TiO2NS/GCE and TiO2NS/GCE without SH-β-CD, respectively, while a weak SWV signal was detected at the AuNP/GCE. Therefore, both AuNP/TiO2NS hybrids and SH-β-CD played important roles in the sensing of MP. A wide linear relationship was obtained between the SWV signals and MP concentrations from 1.5–60.0 nM with a low MP detection limit of 0.05 nM (0.012 ppb) being experimentally achieved under the optimum conditions. The as-prepared sensor also showed a higher response selectivity to MP than to other aromatic pesticide molecules and was further applied in the determination of MP in real river samples.

Graphical abstract: Mono-6-thio-β-cyclodextrin-functionalized AuNP/two-dimensional TiO2 nanosheet nanocomposite for the electrochemical determination of trace methyl parathion in water

Article information

Article type
Paper
Submitted
26 Jun 2019
Accepted
11 Aug 2019
First published
06 Sep 2019

Anal. Methods, 2019,11, 4751-4760

Mono-6-thio-β-cyclodextrin-functionalized AuNP/two-dimensional TiO2 nanosheet nanocomposite for the electrochemical determination of trace methyl parathion in water

X. Fu, C. Zhang, X. Li, J. Zhang and G. Wei, Anal. Methods, 2019, 11, 4751 DOI: 10.1039/C9AY01338E

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