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Selective Functionalization Blended with Scaffold Conductivity in Graphene Acid Promotes H2O2Electrochemical Sensing
Author(s) -
Anna Lenarda,
Aristides Bakandritsos,
Manuela Bevilacqua,
Claudio Tavagnacco,
Michele Melchionna,
Alberto Naldoni,
Tomáš Steklý,
Michal Otyepka,
Radek Zbořil,
Paolo Fornasiero
Publication year - 2019
Publication title -
acs omega
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.779
H-Index - 40
ISSN - 2470-1343
DOI - 10.1021/acsomega.9b02881
Subject(s) - ascorbic acid , graphene , electrochemistry , materials science , biosensor , conductivity , detection limit , selectivity , surface modification , electrode , nanotechnology , electrochemical gas sensor , combinatorial chemistry , chemical engineering , chemistry , catalysis , organic chemistry , chromatography , food science , engineering
The widespread industrial use of H 2 O 2 has provoked great interest in the development of new and more efficient materials for its detection. Enzymatic electrochemical sensors have drawn particular attention, primarily because of their excellent selectivity. However, their high cost, instability, complex immobilization, and inherent tendency toward denaturation of the enzyme significantly limit their practical usefulness. Inspired by the powerful proton-catalyzed H 2 O 2 reduction mechanism of peroxidases, we have developed a well-defined and densely functionalized carboxylic graphene derivative (graphene acid, GA) that serves as a proton source and conductive electrode for binding and detecting H 2 O 2 . An unprecedented H 2 O 2 sensitivity of 525 μA cm -2 mM -1 is achieved by optimizing the balance between the carboxyl group content and scaffold conductivity of GA. Importantly, the GA sensor greatly outperforms all reported carbon-based H 2 O 2 sensors and is superior to enzymatic ones because of its simple immobilization, low cost, and uncompromised sensitivity even after continuous operation for 7 days. In addition, GA-based sensing electrodes remain highly selective in the presence of interferents such as ascorbic acid, paracetamol, and glucose, as well as complex matrices such as milk. GA-based sensors thus have considerable potential for use in practical industrial sensing technologies.

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