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Visual determination of ferric ions in aqueous solution based on a high selectivity and sensitivity ratiometric fluorescent nanosensor

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Abstract

A novel ratiometric fluorescent nanosensor for visual sensing of Fe3+ has been developed by integrating yellow-emissive rhodamine derivatives (RhB) onto the surface of silica nanospheres embedded with red CdTe QDs. Such a nanohybrid fluorescent sensor, RhB–CdTe@SiO2 QDs, displays two distinct emission peaks 556 nm and 651 nm under a single excitation wavelength in the presence of Fe3+. The yellow fluorescence of RhB could be selectively increased by Fe3+ due to the strong chelating ability of RhB toward Fe3+, while the red fluorescence of CdTe QDs is almost constant, resulting in a distinct fluorescence color transformation from red to yellow, which can be applied for the visual detection of Fe3+. This approach shows high sensitivity and selectivity toward Fe3+, and the detection limit is determined to be 20.5 nM, which is lower than the maximum level (0.3 mg L−1, equivalent to 5.4 μM) of Fe3+ ions permitted in drinking water by the U.S. Environmental Protection Agency (EPA). For practical application, we dope the mixture of RhB–CdTe@SiO2 QDs and PVA onto the filter paper and fabricate test strips for direct visual inspection of Fe3+ in water. The paper based sensor has a visual detection limit of 1 μM by the naked eye, showing its promising application for onsite visual quantification of ferric ions without the need for elaborate equipment.

Graphical abstract: Visual determination of ferric ions in aqueous solution based on a high selectivity and sensitivity ratiometric fluorescent nanosensor

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Publication details

The article was received on 07 Aug 2017, accepted on 21 Sep 2017 and first published on 22 Sep 2017


Article type: Paper
DOI: 10.1039/C7AY01917C
Citation: Anal. Methods, 2017, Advance Article
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    Visual determination of ferric ions in aqueous solution based on a high selectivity and sensitivity ratiometric fluorescent nanosensor

    H. Wu, L. Yang, L. Chen, F. Xiang and H. Gao, Anal. Methods, 2017, Advance Article , DOI: 10.1039/C7AY01917C

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