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Nanomaterial-based Electrochemical Biosensors

Şensoy, Kübra Gençdağ, Akpınar, Fatma, Muti, Mihrican·2024·Current Nanoscience

Abstract

Nanomaterials often show very different sizes, shapes, and stability properties. They also facilitate electron transfer and can be easily modified with chemical ligands and biomolecules. These properties, combined with the ease of miniaturizing nanoscales and their application to sensing devices, make nanomaterials well suited for essential chemical/biochemical sensing applications. : Nanomaterials are superior materials not only due to their structural properties but also their functional properties. Using various methods makes it possible to change the available and stack properties. : Nano-sized materials are preferred in modern technological systems because they have a large surface area and different optical and electronic properties. : In this study, electrochemical biosensor applications based on sensors modified with various nanomaterials were evaluated in terms of analytical parameters, such as detection limit, linear range, and features, such as easy fabrication, storage stability, and reproducibility. Besides, the advantages of using nanomaterials were examined under 6 different headings as enzyme biosensors, immunosensors, nucleic acid sensors, cell, phage, and aptasensors.

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Metadata

Authors
Şensoy, K. G., Akpınar, F., & Muti, M.
Venue
Current Nanoscience
Published
2024-01
Volume
20
Issue
1
Pages
18-30
ISSN
1573-4137 (ISSN-L)
OpenAlex
W4292542249
Cited by
701
References
0
FWCI
0.47
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Nanomaterial-based Electrochemical Biosensors. https://app.cochat.ai/papers/10.2174/1573413718666220819143711
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Şensoy, K. G., Akpınar, F., & Muti, M. (2024). Nanomaterial-based Electrochemical Biosensors. Current Nanoscience. https://doi.org/10.2174/1573413718666220819143711

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.