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Electrospun iridium oxide nanofibers for direct selective electrochemical detection of ascorbic acid

Title
Electrospun iridium oxide nanofibers for direct selective electrochemical detection of ascorbic acid
Author(s)
Kim, Su-jinKim, Yu LimYu, AreumLee, JiyoungLee, Sang CheolLee, ChongmokKim, Myung HwaLee, Youngmi
Issued Date
2014-06
Citation
Sensors and Actuators B: Chemical, v.196, pp.480 - 488
Type
Article
Author Keywords
Iridium oxideNanofiberElectrospinningAscorbic acidAmperometryVoltammetry
Keywords
GLASSY-CARBON ELECTRODEELECTROANALYTICAL APPLICATIONSGOLD NANOPARTICLESDOPAMINEOXIDATIONSENSORNANOSTRUCTURESFABRICATIONNANOWIRESBIOSENSOR
ISSN
0925-4005
Abstract
We report the electrochemical activity of IrOx (0 < x ≤ 2) nanofibers prepared by electrospinning for the oxidations of biological species including L-ascorbic acid (AA), 4-acetamidophenol (AP), dopamine (DA), glucose, β-nicotinamide adenine dinucleotide (NADH), and uric acid (UA). Compared to bare glassy carbon electrode, IrOx nanofibers show high electroactivity for all the tested species and facilitate AA oxidation most significantly, shifting the oxidation potential to the less positive direction by ∼485 mV in linear sweep voltammetry while the oxidation of glucose is almost negligible at both electrodes. The amperometric response of IrO x nanofibers at the applied potential of -0.01 V (vs. SCE) is linearly proportional to the AA concentration, exhibiting high sensitivity (194.4 ± 6.8 μA mM-1 cm-2, n = 5), fast response time (t95% = 2.9 ± 1.2 s, n = 5), low detection limit (<0.4 μM), and exclusive selectivity over AP, DA, glucose, NADH, and UA at their physiological levels. In addition, excellent potential resolution of IrO2 nanofibers, sufficient to differentiate AA, DA, NADH, and UA, is confirmed by differential pulse voltammetry. This results support that IrO x nanofibers are good potential sensing materials selectively for AA and/or simultaneously for AA, DA, NADH, UA in complex biological samples. © 2014 Elsevier B.V.
URI
http://hdl.handle.net/20.500.11750/5255
DOI
10.1016/j.snb.2014.02.032
Publisher
Elsevier
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Division of Intelligent Robotics 1. Journal Articles

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