Cited by 24Microfluidic and Bio-sensing TechnologiesElectrochemical Analysis and ApplicationsElectrochemical sensors and biosensors

Electrokinetic preconcentration and electrochemical detection of Escherichia coli at a microelectrode

Frkonja-Kuczin, Ariana, Ray, Louis, Zhao, Zhiling, Konopka, Michael C., Boika, Aliaksei·2018·Electrochimica Acta

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Crossref · 10.1016/j.electacta.2018.05.120

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  • The first reported strategy to detect single bacteria impacts is to decorate E. coli cells with Ag nanoparticles, which can be oxidized during stochastic collisions at a UME biased at the appropriate potential.

    “The first reported strategy to detect single bacteria impacts is to decorate the E. coli cells with Ag nanoparticles, which can be oxidized during stochastic collisions at a UME biased at the appropriate potential [23,37].”

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References 46 · Cited by 24

Authors
Frkonja-Kuczin, A., Ray, L., Zhao, Z., Konopka, M. C., & Boika, A.
Affiliations
University of Akron (US)
Corresponding author
Boika, Aliaksei
Venue
Electrochimica Acta
Publisher
Elsevier BV
Published
2018-08
Volume
280
Pages
191-196
ISSN
0013-4686 (ISSN-L)
OpenAlex
W2804411138
Cited by
24
References
46
Citations by year
2024: 2 · 2023: 8 · 2022: 3 · 2021: 3 · 2020: 3 · 2019: 2 · 2018: 3
FWCI
1.10
Type
journal article
Language
en
Open access
closed
Locations
Electrochimica Acta (publishedVersion)
Funders
University of Akron
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Microfluidic and Bio-sensing Technologies
  • Physical Sciences › Chemistry › Electrochemistry › Electrochemical Analysis and Applications
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Electrochemical sensors and biosensors
Keywords
Escherichia coli detection, dielectrophoresis, silver nanoparticles, silver oxidation, microelectrodes, bacterial detection

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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