Issue 11, 2014

Rapid electrodeposition of a gold–Prussian blue nanocomposite with ultrahigh electroactivity for dual-potential amperometric biosensing of uric acid

Abstract

We report a new and efficient protocol for rapid electrodeposition of a gold–Prussian blue ((Au–PB)REd) nanocomposite with ultrahigh electroactivity on an Au electrode by cyclic voltammetry in 0.1 M aqueous K2SO4 containing 1 mM K3Fe(CN)6, 1 mM HAuCl4, and 0.1 mM Fe2(SO4)3, and an electrochemical quartz crystal microbalance and scanning electron microscopy were utilized to investigate the electrodeposition. The (Au–PB)REd/Au electrode was then cast-coated with a urate oxidase (UOx)–poly(anilineboronic acid) (PABA)–Pt nanoparticle (PtNP) bionanocomposite and chitosan (CS) for high-performance amperometric biosensing of uric acid (UA) in the dual-potential mode. The UOx–PABA–PtNP bionanocomposite was prepared through chemical oxidation of anilineboronic acid (ABA) by sodium chloroplatinate in the presence of UOx. The thus-fabricated CS/UOx–PABA–PtNP/(Au–PB)REd/Au enzyme electrode worked well under optimized conditions through both oxidation and reduction determination of enzyme-generated H2O2, which responded linearly to UA concentrations from 0.3 μM to 0.65 mM with a sensitivity of 223 μA mM−1 cm−2 and a limit of detection (LOD) of 0.2 μM (0.7 V vs. SCE), and from 0.2 μM to 0.25 mM with a sensitivity of 247 μA mM−1 cm−2 and a LOD of 0.1 μM (−0.05 V vs. SCE), being superior to most analogues hitherto reported for biosensing of UA.

Graphical abstract: Rapid electrodeposition of a gold–Prussian blue nanocomposite with ultrahigh electroactivity for dual-potential amperometric biosensing of uric acid

Supplementary files

Article information

Article type
Paper
Submitted
28 Dec 2013
Accepted
18 Mar 2014
First published
19 Mar 2014

Analyst, 2014,139, 2904-2911

Rapid electrodeposition of a gold–Prussian blue nanocomposite with ultrahigh electroactivity for dual-potential amperometric biosensing of uric acid

W. Wang, C. Qin, Q. Xie, X. Qin, L. Chao, Y. Huang, M. Dai, C. Chen, J. Huang and J. Hu, Analyst, 2014, 139, 2904 DOI: 10.1039/C3AN02390G

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