期刊
BIOSENSORS & BIOELECTRONICS
卷 38, 期 1, 页码 270-277出版社
ELSEVIER ADVANCED TECHNOLOGY
DOI: 10.1016/j.bios.2012.05.045
关键词
AuNPs@SiO2-MIPs; Core-shell structure; Sol-gel technique; Electrochemical sensor; Dopamine
类别
资金
- National Natural Science Foundation of China [21175044]
- Programs of the Science & Technology Commission of Shanghai Municipality [10JC1404000]
- Research Fund for the Doctoral Program of Higher Education [20100076110002]
- Shanghai Key Laboratory of Green Chemistry and Chemical Processes
A novel core-shell composite of gold nanoparticles (AuNPs) and SiO2 molecularly imprinted polymers (AuNPs@SiO2-MIPs) was synthesized through sol-gel technique and applied as a molecular recognition element to construct an electrochemical sensor for determination of dopamine (DA). Compared with previous imprinting recognition, the main advantages of this strategy lie in the introduction and combination of AuNPs and biocompatible porous sol-gel material (SiO2). The template molecules (DA) were firstly adsorbed at the AuNPs surface due to their excellent affinity, and subsequently they were further assembled onto the polymer membrane through hydrogen bonds and pi-pi interactions formed between template molecules and silane monomers. Cyclic voltammetry (CV) was carried out to extract DA molecules from the imprinted membrane, and as a result, DA could be rapidly and effectively removed. The AuNPs@SiO2-MIPs was characterized by ultraviolet visible (UV-vis) absorbance spectroscopy, transmission electron microscope (TEM) and Fourier transform infrared spectrometer (FT-IR). The prepared AuNPs@SiO2-MIPs sensor exhibited not only high selectivity toward DA in comparison to other interferents, but also a wide linear range over DA concentration from 4.8 x 10(-8) to 5.0 x 10(-5) M with a detection limit of 2.0 x 10(-8) M (S/N=3). Moreover, the new electrochemical sensor was successfully applied to the DA detection in dopamine hydrochloride injection and human urine sample, which proved that it was a versatile sensing tool for the selective detection of DA in real samples. (c) 2012 Elsevier B.V. All rights reserved.
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