Published February 2019 | Version v1
Journal article

Superlattice stacking by hybridizing layered double hydroxide nanosheets with layers of reduced graphene oxide for electrochemical simultaneous determination of dopamine, uric acid and ascorbic acid

  • 1. Huazhong University of Science and Technology, Key Laboratory for Large-Format Battery Materials and System, Ministry of Education, Hubei Key Laboratory of Material Chemistry and Service Failure, School of Chemistry and Chemical Engineering (China)
  • 2. Huazhong University of Science and Technology, State Key Laboratory of Digital Manufacturing Equipment and Technology (China)

Description

A self-assembled periodic superlattice material was obtained by integrating positively charged semiconductive sheets of a Zn-NiAl layered double hydroxide (LDH) and negatively charged layers of reduced graphene oxide (rGO). The material was used to modify a glassy carbon electrode which then is shown to be a viable sensor for the diagnostic parameters dopamine (DA), uric acid (UA) and ascorbic acid (AA). The modified GCE displays excellent electrocatalytic activity towards these biomolecules. This is assumed to be due to the synergistic effects of (a) excellent interfacial electrical conductivity that is imparted by direct neighboring of conductive rGO to semiconductive channels of LDHs, (b) the superb intercalation feature of LDHs, and (c) the enlarged surface with an enormous number of active sites. The biosensor revealed outstanding electrochemical performances in terms of selectivity, sensitivity, and wide linear ranges. Typically operated at working potentials of −0.10, +0.13 and + 0.27 V vs. saturated calomel electrode, the lower detection limits for AA, DA and UA are 13.5 nM, 0.1 nM, and 0.9 nM, respectively, at a signal-to-noise ratio of 3. The sensor was applied to real-time tracking of dopamine efflux from live human nerve cells.

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Additional details

Identifiers

Publishing Information

Journal Title
Mikrochimica Acta
Journal Volume
186
Journal Issue
2
Journal Page Range
p. 1-11
ISSN
0026-3672
CODEN
MIACAQ

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Copyright (c) 2019 Springer-Verlag GmbH Austria, part of Springer Nature