Issue 8, 2024

Highly selective detection of 2,4-dinitrophenol by fluorescent NH2-MIL-125(Ti) via dual-parameter sensing technology

Abstract

The organic contaminant 2,4-dinitrophenol (2,4-DNP) is widely prevalent and poses significant risks to human health. Although numerous in-depth studies having been reported on the highly sensitive detection of 2,4-DNP, there are still challenges to its selective detection. Here, the fluorescence intensity ratio (I0/I) and emission peak shift (Δλ) were utilized for selective detection of 2,4-DNP by NH2-MIL-125(Ti). Notably, the emission peak of the NH2-MIL-125(Ti) suspension exhibited a remarkable red shift in the presence of 2,4-DNP (Δλ = 26 nm), accompanied by the blue shift or weak red shift of analogs, which provided a solid basis for selective detection of 2,4-DNP. Meanwhile, the I0/I ratio of the NH2-MIL-125(Ti) suspension exhibited a robust linear correlation with 2,4-DNP at the low concentration range (0–70 μM). The interaction of the analyte with NH2-MIL-125(Ti) was revealed to involve intermolecular charge transfer (ICT) and fluorescence resonance energy transfer (FRET) through XPS, FTIR, and UV-vis absorption spectroscopy. Additionally, we achieved the detection of 2,4-DNP using a smartphone by recognizing both the blue (B) values and the luminance (L) values. The obtained results demonstrated that the NH2-MIL-125(Ti) probe based on dual-parameter sensing technology exhibited excellent potential for selectively detecting 2,4-DNP in water environments, thereby offering significant prospects for its application in water quality assessment.

Graphical abstract: Highly selective detection of 2,4-dinitrophenol by fluorescent NH2-MIL-125(Ti) via dual-parameter sensing technology

Supplementary files

Article information

Article type
Paper
Submitted
19 Nov 2023
Accepted
18 Jan 2024
First published
05 Feb 2024

Anal. Methods, 2024,16, 1206-1214

Highly selective detection of 2,4-dinitrophenol by fluorescent NH2-MIL-125(Ti) via dual-parameter sensing technology

Q. Hu, D. Zhan, A. Saeed, W. Xu and L. Kong, Anal. Methods, 2024, 16, 1206 DOI: 10.1039/D3AY02059B

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