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Development of solution-gated graphene transistor model for biosensors

The distinctive properties of graphene, characterized by its high carrier mobility and biocompatibility, have stimulated extreme scientific interest as a promising nanomaterial for future nanoelectronic applications. In particular, graphene-based transistors have been developed rapidly and are consi...

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Autores principales: Karimi, Hediyeh, Yusof, Rubiyah, Rahmani, Rasoul, Hosseinpour, Hoda, Ahmadi, Mohammad T
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3926859/
https://www.ncbi.nlm.nih.gov/pubmed/24517158
http://dx.doi.org/10.1186/1556-276X-9-71
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author Karimi, Hediyeh
Yusof, Rubiyah
Rahmani, Rasoul
Hosseinpour, Hoda
Ahmadi, Mohammad T
author_facet Karimi, Hediyeh
Yusof, Rubiyah
Rahmani, Rasoul
Hosseinpour, Hoda
Ahmadi, Mohammad T
author_sort Karimi, Hediyeh
collection PubMed
description The distinctive properties of graphene, characterized by its high carrier mobility and biocompatibility, have stimulated extreme scientific interest as a promising nanomaterial for future nanoelectronic applications. In particular, graphene-based transistors have been developed rapidly and are considered as an option for DNA sensing applications. Recent findings in the field of DNA biosensors have led to a renewed interest in the identification of genetic risk factors associated with complex human diseases for diagnosis of cancers or hereditary diseases. In this paper, an analytical model of graphene-based solution gated field effect transistors (SGFET) is proposed to constitute an important step towards development of DNA biosensors with high sensitivity and selectivity. Inspired by this fact, a novel strategy for a DNA sensor model with capability of single-nucleotide polymorphism detection is proposed and extensively explained. First of all, graphene-based DNA sensor model is optimized using particle swarm optimization algorithm. Based on the sensing mechanism of DNA sensors, detective parameters (I(ds) and V(gmin)) are suggested to facilitate the decision making process. Finally, the behaviour of graphene-based SGFET is predicted in the presence of single-nucleotide polymorphism with an accuracy of more than 98% which guarantees the reliability of the optimized model for any application of the graphene-based DNA sensor. It is expected to achieve the rapid, quick and economical detection of DNA hybridization which could speed up the realization of the next generation of the homecare sensor system.
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spelling pubmed-39268592014-02-20 Development of solution-gated graphene transistor model for biosensors Karimi, Hediyeh Yusof, Rubiyah Rahmani, Rasoul Hosseinpour, Hoda Ahmadi, Mohammad T Nanoscale Res Lett Nano Express The distinctive properties of graphene, characterized by its high carrier mobility and biocompatibility, have stimulated extreme scientific interest as a promising nanomaterial for future nanoelectronic applications. In particular, graphene-based transistors have been developed rapidly and are considered as an option for DNA sensing applications. Recent findings in the field of DNA biosensors have led to a renewed interest in the identification of genetic risk factors associated with complex human diseases for diagnosis of cancers or hereditary diseases. In this paper, an analytical model of graphene-based solution gated field effect transistors (SGFET) is proposed to constitute an important step towards development of DNA biosensors with high sensitivity and selectivity. Inspired by this fact, a novel strategy for a DNA sensor model with capability of single-nucleotide polymorphism detection is proposed and extensively explained. First of all, graphene-based DNA sensor model is optimized using particle swarm optimization algorithm. Based on the sensing mechanism of DNA sensors, detective parameters (I(ds) and V(gmin)) are suggested to facilitate the decision making process. Finally, the behaviour of graphene-based SGFET is predicted in the presence of single-nucleotide polymorphism with an accuracy of more than 98% which guarantees the reliability of the optimized model for any application of the graphene-based DNA sensor. It is expected to achieve the rapid, quick and economical detection of DNA hybridization which could speed up the realization of the next generation of the homecare sensor system. Springer 2014-02-11 /pmc/articles/PMC3926859/ /pubmed/24517158 http://dx.doi.org/10.1186/1556-276X-9-71 Text en Copyright © 2014 Karimi et al.; licensee Springer. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Nano Express
Karimi, Hediyeh
Yusof, Rubiyah
Rahmani, Rasoul
Hosseinpour, Hoda
Ahmadi, Mohammad T
Development of solution-gated graphene transistor model for biosensors
title Development of solution-gated graphene transistor model for biosensors
title_full Development of solution-gated graphene transistor model for biosensors
title_fullStr Development of solution-gated graphene transistor model for biosensors
title_full_unstemmed Development of solution-gated graphene transistor model for biosensors
title_short Development of solution-gated graphene transistor model for biosensors
title_sort development of solution-gated graphene transistor model for biosensors
topic Nano Express
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3926859/
https://www.ncbi.nlm.nih.gov/pubmed/24517158
http://dx.doi.org/10.1186/1556-276X-9-71
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