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Nanocomposites of poly(l-methionine), carbon nanotube–graphene complexes and Au nanoparticles on screen printed carbon electrodes for electrochemical analyses of dopamine and uric acid in human urine solutions

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Abstract

A sensitive electrochemical sensor featuring novel composites of gold and carbon nanocomplexes alongside a polymerized amino acid was developed for the determination of uric acid (UA) and dopamine (DA) concentrations in both buffer and human urine sample solutions. The sensor was fabricated by electropolymerization of L-methionine (L-Met) followed by coating of carbon nanotube–graphene complexes and electrodeposition of gold nanoparticles on a screen printed carbon electrode surface. The electrode surfaces were characterized by field emission scanning electron microscopy and energy dispersive spectroscopy, and the electrochemical properties were investigated by cyclic voltammetry and differential pulse voltammetry. Linear ranges of 0.05–3 μM and 1–35 μM with limits of detection of 0.0029 and 0.034 μM were achieved for DA and UA, respectively. In addition, the developed sensor was applied for the analysis of native UA and DA concentrations in undiluted and diluted human urine samples. The UA analysis results were compared to those obtained using high performance liquid chromatography and a fluorometric assay kit while the DA analysis results were compared to those obtained using liquid chromatography-tandem mass spectrometry.

Graphical abstract: Nanocomposites of poly(l-methionine), carbon nanotube–graphene complexes and Au nanoparticles on screen printed carbon electrodes for electrochemical analyses of dopamine and uric acid in human urine solutions

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Article information


Submitted
31 Dec 2019
Accepted
18 Feb 2020
First published
27 Feb 2020

Analyst, 2020, Advance Article
Article type
Paper

Nanocomposites of poly(L-methionine), carbon nanotube–graphene complexes and Au nanoparticles on screen printed carbon electrodes for electrochemical analyses of dopamine and uric acid in human urine solutions

Y. Si, Y. E. Park, J. E. Lee and H. J. Lee, Analyst, 2020, Advance Article , DOI: 10.1039/C9AN02638J

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