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Issue 22, 2016
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GR–Fe3O4NPs and PEDOT–AuNPs composite based electrochemical aptasensor for the sensitive detection of penicillin

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Abstract

In this work, a novel electrochemical aptasensor was developed for the sensitive detection of the antibiotic penicillin, which used a penicillin aptamer as the specific recognition element and a novel composite film consisting of a magnetic graphene nanocomposite (GR–Fe3O4NPs) and a poly(3,4-ethylenedioxythiophene)–gold nanoparticles composite (PEDOT–AuNPs) as the platform. Firstly, GR–Fe3O4NPs was fabricated on a bare glassy carbon electrode (GCE) surface. Secondly, the first film was modified with the PEDOT–AuNPs composite and the as-modified electrode had a much larger surface area and a greatly improved electronic transmission rate. Subsequently, a penicillin aptamer was assembled on the modified electrode via Au–N bonds between the AuNPs and –NH2 groups of the aptamer. The structures of the GR–Fe3O4NPs and PEDOT–AuNPs composite have been investigated by scanning electron microscopy (SEM). Cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS) and differential pulse voltammetry (DPV) were used to demonstrate the electrochemical performance of the as-prepared aptasensor. Under optimized conditions, the proposed aptasensor exhibited high sensitivity for the detection of penicillin with a wide linear range from 0.1 to 200 ng mL−1 and a low detection limit of 0.057 ng mL−1. The proposed aptasensor also showed good stability, satisfactory reproducibility and high specificity. Finally, the proposed aptasensor was successfully used for the detection of penicillin in a real sample.

Graphical abstract: GR–Fe3O4NPs and PEDOT–AuNPs composite based electrochemical aptasensor for the sensitive detection of penicillin

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Article information


Submitted
24 Feb 2016
Accepted
25 Apr 2016
First published
10 May 2016

Anal. Methods, 2016,8, 4391-4397
Article type
Paper

GR–Fe3O4NPs and PEDOT–AuNPs composite based electrochemical aptasensor for the sensitive detection of penicillin

J. Zhao, W. Guo, M. Pei and F. Ding, Anal. Methods, 2016, 8, 4391
DOI: 10.1039/C6AY00555A

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