Issue 46, 2023

A colorimetric sensor with dual-ratio and dual-mode for detection of nicotine in tobacco samples

Abstract

Nicotine (NIC) is a harmful substance, drug, pesticide and chemical that is widely found in tobacco. It has carcinogenic, teratogenic and neurotoxic effects that have raised serious concerns. Herein, a colorimetric sensor with dual-ratio and dual-mode for the detection of NIC in tobacco samples was reported. The localized surface plasmon resonance signals of gold nanoparticles (AuNPs) and AuNPs-NIC are used as dual-ratio signals. The absorbance ratio of NIC to AuNPs or the absorbance ratio of NIC to AuNPs-NIC and the wavelength shift value of AuNPs-NIC are applied as dual-mode. Transmission electron microscopy, energy dispersive spectroscopy, dynamic light scattering spectroscopy, ultraviolet-visible spectrophotometry, cyclic voltammetry, and potentiostatic methods were used to characterize the sensor. Further analysis of NIC was conducted through morphological fitting and theoretical calculations. Under optimal conditions, the sensor shows a wide linear range of 5–500 μM. The detection limits for NIC are 2.48 μM, 1.63 μM and 1.34 μM, respectively. The experimental result shows that the dual-ratio signal of AuNPs and AuNPs-NIC has good selectivity and sensitivity, and can effectively reduce the interference of impurities on NIC detection. And the dual-mode of detection for NIC improves the accuracy and comparability of the result significantly. In addition, the proposed sensor was also applied to test NIC in tobacco samples with satisfactory recovery.

Graphical abstract: A colorimetric sensor with dual-ratio and dual-mode for detection of nicotine in tobacco samples

Supplementary files

Article information

Article type
Paper
Submitted
05 Sep 2023
Accepted
07 Oct 2023
First published
23 Oct 2023

Anal. Methods, 2023,15, 6377-6384

A colorimetric sensor with dual-ratio and dual-mode for detection of nicotine in tobacco samples

J. Li, P. Liang, H. Song, X. Yu, S. Hu, J. Wang, C. Cheng, Y. Zhao and Z. Su, Anal. Methods, 2023, 15, 6377 DOI: 10.1039/D3AY01571H

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