Issue 19, 2022

Rapid and sensitive detection of Hg2+ with a SERS-enhanced lateral flow strip

Abstract

Mercury ions are some of the most toxic heavy metal ions widely distributed in the environment. Hg2+ cannot be degraded by microorganisms and can accumulate in the body through the food chain, posing a great threat to human health. Herein, a method combining surface-enhanced Raman scattering (SERS) with a lateral flow strip (LFS) (SERS-LFS) was developed for the rapid and quantitative analysis of Hg2+. The recognition of Hg2+ by the LFS depends on a specific T–Hg–T strategy. Rhodamine 6G (R6G), as a SERS reporter, was assembled on the surface of Au@Ag core–shell nanoparticles, which served as an effective SERS substrate on both the T and C lines of the LFS. Using this SERS-LFS, the presence of target Hg2+ could be measured through the appearance of an orange color on the T line of the LFS. Furthermore, with the direct measurement of SERS on the T lines of the LFS, the SERS signal could be collected even at a low concentration of Hg2+, at which point the signal on the T lines could not be observed. Based on the intensities of the characteristic peak at 1513 cm−1 of R6G collected on the T lines of the LFS, a linear relationship was obtained in the range of 0.01 nM to 1 nM, and the detection limit of the LFS was greatly improved by at least 20 times over the colorimetric results of the traditional LFS based on naked-eye observation. More importantly, this SERS-LFS did not affect the intrinsic simplicity of the LFS. This developed SERS-LFS holds great potential in practical routine screening in food safety and environmental monitoring.

Graphical abstract: Rapid and sensitive detection of Hg2+ with a SERS-enhanced lateral flow strip

Article information

Article type
Paper
Submitted
13 Jul 2022
Accepted
15 Aug 2022
First published
16 Aug 2022

Analyst, 2022,147, 4337-4347

Rapid and sensitive detection of Hg2+ with a SERS-enhanced lateral flow strip

L. Yao, Y. Chen, R. Wang, C. Yan, J. Xu, B. Yao, J. Cheng and W. Chen, Analyst, 2022, 147, 4337 DOI: 10.1039/D2AN01100J

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