Issue 16, 2018

A renewable test strip combined with solid-state ratiometric fluorescence emission spectra for the highly selective and fast determination of hydrazine gas

Abstract

N2H4 is one of the most toxic and explosive chemicals. In particular, N2H4 vapor is dangerously unstable. However, the determination of N2H4 gas has lagged behind the detection of N2H4 in aqueous solution or biological fluid in terms of the crucial ability to discriminate and quantify N2H4. Despite the multitude of fluorescent probe-coated test strips that have been used for N2H4 gas detection, these techniques mainly rely on the observation by eye of fluorescence color changes, which will hamper the discrimination of subtle color changes on the test strips due to the limited capacity of the eye to perceive and differentiate colors. Herein, we developed a new technique combining a renewable test strip and solid-state ratiometric fluorescence readout. The results confirmed that the prepared test strips could be used as a solid-state fluorescence sensor for the fast capture (within 5 min) and quantification of N2H4 gas. Additionally, the test strips could be easily renewable. Thus, this test strip-based approach provides an efficient tool for N2H4 gas detection, which is particularly significant for the real-time monitoring of N2H4 gas in airports and the environmental atmosphere in chemical plant regions. This design concept presents a new avenue for developing solid-state fluorescence sensors for gas detection.

Graphical abstract: A renewable test strip combined with solid-state ratiometric fluorescence emission spectra for the highly selective and fast determination of hydrazine gas

Supplementary files

Article information

Article type
Paper
Submitted
15 May 2018
Accepted
06 Jul 2018
First published
09 Jul 2018

Analyst, 2018,143, 3900-3906

A renewable test strip combined with solid-state ratiometric fluorescence emission spectra for the highly selective and fast determination of hydrazine gas

Y. Wang, H. Xiang, R. Zhao and C. Huang, Analyst, 2018, 143, 3900 DOI: 10.1039/C8AN00903A

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