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Electrochemical sensor for arsenite detection using graphene oxide assisted generation of prussian blue nanoparticles as enhanced signal label.

Authors :
Wen, Shao-Hua
Wang, Yi
Yuan, Yan-Hong
Liang, Ru-Ping
Qiu, Jian-Ding
Source :
Analytica Chimica Acta. Mar2018, Vol. 1002, p82-89. 8p.
Publication Year :
2018

Abstract

An electrochemical sensor was fabricated for arsenite detection using graphene oxide-assisted generation of prussian blue nanoparticles as enhanced redox signal label. The 5′-thiolate-labeled (GT) 21 -ssDNA was first self-assembled on a gold electrode surface via Au-S bond. Graphene oxide can interact with ssDNA through π-π stacking interaction and facilitate the generation of prussian blue nanoparticles on its surface as an electrochemically active indicator. In the absence of arsenite, plenty of graphene oxide/prussian blue nanoparticles can be adsorbed on the electrode surface to produce a stronger redox signal of prussian blue nanoparticles. While in the presence of arsenite, (GT) 21 -ssDNA can recognize and combine with arsenite via hydrogen bonds to form (GT) 21 -ssDNA/arsenite complex with a frizzy structure. The conformational change of (GT) 21 -ssDNA led to less adsorption of graphene oxide/prussian blue nanoparticles on the electrode surface, resulting in a reduced redox response. The arsenite-induced (GT) 21 -ssDNA structure switching can be used for sensitive detection of arsenite with a linear range from 0.2 to 500 ppb and a detection limit down to 0.058 ppb. Benefiting from (GT) 21 -ssDNA containing arsenite recognition sequence, the proposed sensor exhibited excellent specificity against other heavy metal ions. The applicability of the electrochemical biosensor for arsenite assay in real water samples demonstrated the great potential of this strategy for trace arsenite detection in environment. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00032670
Volume :
1002
Database :
Academic Search Index
Journal :
Analytica Chimica Acta
Publication Type :
Academic Journal
Accession number :
127099037
Full Text :
https://doi.org/10.1016/j.aca.2017.11.057