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An Aptamer-based Sensor for Unchelated GadoliniumIII
Published on: January 9, 2017
Sensitive and selective detection of Hg2+ in tap and canal water via self-enhanced ECL aptasensor based on
Libo Li1, Bainian Chen1, Lijun Luo2
1Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education, School of Agricultural Engineering, Jiangsu University, Zhenjiang, Jiangsu, 212013, China.
Abstract:
In the present study, a novel self-enhanced electrochemiluminescence (ECL) aptasensor which combined self-enhanced ECL composite as signal response element and aptamer as the specific recognition element was firstly proposed for the sensitive and selective detection of Hg2+. Innovatively, the luminophore Ru(bpy)32+-doped silica nanoparticles functionalized with 3-aminopropyltriethoxysilane (NH2-Ru@SiO2) and the co-reactant nitrogen doped graphene quantum dots (NGQDs) were bound together to form the self-enhanced ECL composite, NH2-Ru@SiO2-NGQDs, by electrostatic adsorption. Satisfactorily, high and stable luminous efficiency of NH2-Ru@SiO2-NGQDs was obtained benefited from the short electron transfer distance and low energy loss of self-enhanced-typal ECL composite. For the fabrication of the self-enhanced ECL aptasensor for Hg2+ detection, the Hg2+ aptamer, of which one end was connected to NH2-Ru@SiO2-NGQDs, and the other end was fixed on glass carbon electrode (GCE) surface through Au-S bond, was served as a bridge. Upon the addition of Hg2+, the aptamer was bent due to the formation of thymine-Hg2+-thymine (T-Hg2+-T) specific structure, which caused the self-enhanced ECL composite was close to the GCE surface. On this basis, a linearly enhanced ECL signal was acquired with the concentration of Hg2+ in the range of 5.0 × 10-11 M - 1.0 × 10-6 M with excellent selectivity, repeatability and stability in 3 min for each assay. In addition, the proposed aptasensor showed satisfying accuracy and practicability for Hg2+ analysis in tap and canal water verified by the inductively coupled plasma-mass spectrometry (ICP-MS) method.
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