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Design and finite element modeling of two–dimensional nanomechanical biosensors for SARS–CoV–2 detection

SARS–CoV–2 is the causative agent of COVID–19 disease. The development of different variants has increased the prevalence, pathogenicity, and mortality of the SARS–CoV–2. Prompt diagnosis and timely initiation of therapy can undoubtedly minimize the damage caused by this virus. In this study, a wide...

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Autores principales: Payandehpeyman, J., Parvini, N., Moradi, K., Hashemian, N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9303063/
https://www.ncbi.nlm.nih.gov/pubmed/35891677
http://dx.doi.org/10.1016/j.diamond.2022.109263
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author Payandehpeyman, J.
Parvini, N.
Moradi, K.
Hashemian, N.
author_facet Payandehpeyman, J.
Parvini, N.
Moradi, K.
Hashemian, N.
author_sort Payandehpeyman, J.
collection PubMed
description SARS–CoV–2 is the causative agent of COVID–19 disease. The development of different variants has increased the prevalence, pathogenicity, and mortality of the SARS–CoV–2. Prompt diagnosis and timely initiation of therapy can undoubtedly minimize the damage caused by this virus. In this study, a wide range of emerging single layer two–dimensional materials (SL2DMs), including graphene, grapheme oxide (GO), reduced graphene oxide (rGO), hexagonal boron nitride (h–BN), Ti3C2Tx MXene, and MoS2that can be used to fabricate highly sensitive biosensors, are analyzed using the finite element method based on antigen–antibody interaction. Important design parameters including sensor size, sensor aspect ratio, number of viruses, and applying in-plane strain on sensor performance are analyzed using frequency shift technique. In the following, an analytical relationship that can predict the limit of detection (LOD) according to the above parameters is proposed. The results show that all the above materials have a good performance in detecting viruses in the sample range of 10–100 viruses. This range can be reduced significantly by applying strains of less than 0.1. Also, applying strain increases shift frequency index by 2 to 3 times, which is a significant result. The maximum and minimum sensor performance are obtained for GO and Ti3C2Tx, respectively. The results of this paper can be used to build a new generation of two–dimensional biosensors for rapid detection of COVID–19 and other viruses.
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spelling pubmed-93030632022-07-22 Design and finite element modeling of two–dimensional nanomechanical biosensors for SARS–CoV–2 detection Payandehpeyman, J. Parvini, N. Moradi, K. Hashemian, N. Diam Relat Mater Article SARS–CoV–2 is the causative agent of COVID–19 disease. The development of different variants has increased the prevalence, pathogenicity, and mortality of the SARS–CoV–2. Prompt diagnosis and timely initiation of therapy can undoubtedly minimize the damage caused by this virus. In this study, a wide range of emerging single layer two–dimensional materials (SL2DMs), including graphene, grapheme oxide (GO), reduced graphene oxide (rGO), hexagonal boron nitride (h–BN), Ti3C2Tx MXene, and MoS2that can be used to fabricate highly sensitive biosensors, are analyzed using the finite element method based on antigen–antibody interaction. Important design parameters including sensor size, sensor aspect ratio, number of viruses, and applying in-plane strain on sensor performance are analyzed using frequency shift technique. In the following, an analytical relationship that can predict the limit of detection (LOD) according to the above parameters is proposed. The results show that all the above materials have a good performance in detecting viruses in the sample range of 10–100 viruses. This range can be reduced significantly by applying strains of less than 0.1. Also, applying strain increases shift frequency index by 2 to 3 times, which is a significant result. The maximum and minimum sensor performance are obtained for GO and Ti3C2Tx, respectively. The results of this paper can be used to build a new generation of two–dimensional biosensors for rapid detection of COVID–19 and other viruses. Elsevier B.V. 2022-10 2022-07-22 /pmc/articles/PMC9303063/ /pubmed/35891677 http://dx.doi.org/10.1016/j.diamond.2022.109263 Text en © 2022 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Payandehpeyman, J.
Parvini, N.
Moradi, K.
Hashemian, N.
Design and finite element modeling of two–dimensional nanomechanical biosensors for SARS–CoV–2 detection
title Design and finite element modeling of two–dimensional nanomechanical biosensors for SARS–CoV–2 detection
title_full Design and finite element modeling of two–dimensional nanomechanical biosensors for SARS–CoV–2 detection
title_fullStr Design and finite element modeling of two–dimensional nanomechanical biosensors for SARS–CoV–2 detection
title_full_unstemmed Design and finite element modeling of two–dimensional nanomechanical biosensors for SARS–CoV–2 detection
title_short Design and finite element modeling of two–dimensional nanomechanical biosensors for SARS–CoV–2 detection
title_sort design and finite element modeling of two–dimensional nanomechanical biosensors for sars–cov–2 detection
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9303063/
https://www.ncbi.nlm.nih.gov/pubmed/35891677
http://dx.doi.org/10.1016/j.diamond.2022.109263
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