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Efficient ionic medium supported reduced graphene oxide-based sensor for selective sensing of dopamine

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Abstract

A highly sensitive and electroactive reduced graphene oxide is achieved by directly reducing the ionic medium supported graphene oxide on the electrode surface. The ionic medium supported reduced graphene oxide (im-rGO) has revealed enhanced electrochemical activity compared to water medium reduced graphene oxide under the same set of conditions. The im-rGO has revealed excellent kinetics. The ionic medium supported reduced graphene oxide modified graphite pencil electrode (im-rGO/GPE) was used for selective trace level quantification of dopamine (DA) in human urine. The developed sensor was comprehensively investigated by field emission-scanning electron microscopy (FE-SEM), electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), Raman spectroscopy, and Fourier-transform infrared spectroscopy (FTIR). The im-rGO on the electrode surface has effectively increased the electroactive surface area for DA from 0.063 to 0.631 cm2. The charge transfer coefficient (α) and the apparent heterogeneous electron transfer rate constant (ks) were calculated to be 0.61 and 5.81 s−1, respectively. A very low LOD of 95 nM was achieved without using any noble or precious metals in combination. The im-rGO/GPE has shown an excellent capability to sense dopamine in the presence of a high concentration of ascorbic acid. The ionic medium supported reduction of GO is the fastest and most cost-effective approach to enhance the sensitivity of the sensor for dopamine in a short time.

Graphical abstract: Efficient ionic medium supported reduced graphene oxide-based sensor for selective sensing of dopamine

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Supplementary files

Article information


Submitted
17 May 2020
Accepted
09 Jun 2020
First published
10 Jun 2020

This article is Open Access

Mater. Adv., 2020, Advance Article
Article type
Paper

Efficient ionic medium supported reduced graphene oxide-based sensor for selective sensing of dopamine

N. Baig, A. Kawde and M. Ibrahim, Mater. Adv., 2020, Advance Article , DOI: 10.1039/D0MA00322K

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