Issue 3, 2022

Ascorbic acid functionalized anti-aggregated Au nanoparticles for ultrafast MEF and SERS detection of tartrazine: an ultra-wide piecewise linear range study

Abstract

Tartrazine, as a synthetic food colorant, is harmful to health upon excessive intake. In this study, we developed a simple, sensitive and ultrafast method to detect tartrazine effectively. Specifically, we successfully used ascorbic acid-functionalized anti-aggregated Au nanoparticles (AuNPs) as enhanced substrates to detect tartrazine in drinks using metal enhanced fluorescence (MEF) and surface-enhanced Raman scattering (SERS) piecewise linearly. The fluorescence intensity and Raman signals of the tartrazine solution enhanced after the addition of AuNPs. There was a good linear correlation between the fluorescence intensity and the concentration of tartrazine from 2.0 μM to 40.0 μM, and the limit of detection (LoD) was 15.4 nM. In addition, the Raman intensity also increased linearly with an increase in the concentration of tartrazine in a wide range (1.0 × 10−5 μM to 1.0 × 10−1 μM) and a lower LoD (0.8 pM) was achieved compared with the results from the fluorescence technique. Both fluorescence and SERS can immediately detect tartrazine in drinks after the substrate was mixed with analytes. Hence, the as-prepared anti-aggregated AuNPs as substrate material achieved a highly sensitive, selective and ultrafast detection of tartrazine via fluorescence and Raman techniques in a wide detection range, providing a novel strategy for the detection of food additives.

Graphical abstract: Ascorbic acid functionalized anti-aggregated Au nanoparticles for ultrafast MEF and SERS detection of tartrazine: an ultra-wide piecewise linear range study

Supplementary files

Article information

Article type
Paper
Submitted
26 Nov 2021
Accepted
29 Dec 2021
First published
30 Dec 2021

Analyst, 2022,147, 436-442

Ascorbic acid functionalized anti-aggregated Au nanoparticles for ultrafast MEF and SERS detection of tartrazine: an ultra-wide piecewise linear range study

M. Li, R. Li, B. Han, H. Ma, X. Hou, Y. Kang, Y. Zhang and J. Wang, Analyst, 2022, 147, 436 DOI: 10.1039/D1AN02139G

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