Issue 4, 2015

A colorimetric nitrite detection system with excellent selectivity and high sensitivity based on Ag@Au nanoparticles

Abstract

Excessive uptake of NO2 is detrimental to human health, but the currently available methods used to sensitively detect this ion in the environment are cumbersome and expensive. In this study, we developed an improved NO2 detection system based on a redox etching strategy of CTAB-stabilized Ag–Au core–shell nanoparticles (Ag@AuNPs). The detection mechanism was verified by UV-Vis spectroscopy, TEM and XPS. The detection system produces a color change from purple to colorless in response to an increase of NO2 concentration. The selectivity of detection of NO2, both with the unaided eye and by measurement of UV-Vis spectra, is excellent in relation to other ions, including Cu2+, Co2+, Ni2+, Cr3+, Al3+, Pb2+, Cd2+, Ca2+, Ba2+, Zn2+, Mn2+, Mg2+, Fe3+, Hg2+, Ag+, K+, F, PO43−, C2O42−, SO32−, CO32−, SO42−, NO3 and CH3–COO (Ac). The limit of detection (LOD) for NO2 is 1.0 μM by eye and 0.1 μM by UV-Vis spectroscopy. The LOD by eye is lower than the lowest previously reported value (4.0 μM). There is a good linear relationship between A/A0 and the concentration of NO2 from 1.0 to 20.0 μM NO2, which permits a quantitative assay. The applicability of our detection system was also verified by analysis of NO2 in tap water and lake water. The results demonstrate that our Ag@AuNP-based detection system can be used for the rapid colorimetric detection of NO2 in complex environmental samples, with excellent selectivity and high sensitivity.

Graphical abstract: A colorimetric nitrite detection system with excellent selectivity and high sensitivity based on Ag@Au nanoparticles

Supplementary files

Article information

Article type
Paper
Submitted
28 Aug 2014
Accepted
13 Dec 2014
First published
15 Dec 2014

Analyst, 2015,140, 1076-1081

A colorimetric nitrite detection system with excellent selectivity and high sensitivity based on Ag@Au nanoparticles

T. Li, Y. Li, Y. Zhang, C. Dong, Z. Shen and A. Wu, Analyst, 2015, 140, 1076 DOI: 10.1039/C4AN01583E

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