dc.contributor.author | Toral López, Alejandro | |
dc.contributor.author | González Marín, Enrique | |
dc.contributor.author | Godoy Medina, Andrés | |
dc.date.accessioned | 2022-07-06T10:11:54Z | |
dc.date.available | 2022-07-06T10:11:54Z | |
dc.date.issued | 2022-06-17 | |
dc.identifier.citation | Nanoscale Adv., 2022, Advance Article. DOI: [10.1039/d2na00357k] | es_ES |
dc.identifier.uri | http://hdl.handle.net/10481/75848 | |
dc.description.abstract | Biological Field-Effect Transistors (BioFETs) have already demonstrated enormous potential for detecting
minute amounts of ions and molecules. The use of two-dimensional (2D) materials has been shown to
boost their performance and to enable the design of new applications. This combination deserves
special interest in the current pandemic caused by the SARS-CoV-2 virus which demands fast, reliable
and cheap detection methods. However, in spite of the experimental advances, there is a lack of
a comprehensive and in-depth computational approach to capture the mechanisms underlying the
sensor behaviour. Here, we present a multiscale platform that combines detailed atomic models of the
molecules with mesoscopic device-level simulations. The fine-level description exploited in this
approach accounts for the charge distribution of the receptor, its reconfiguration when the target binds
to it, and the consequences in terms of sensitivity on the transduction mechanism. The results
encourage the further exploration of improved sensor designs and 2D materials combined with diverse
receptors selected to achieve the desired specificity. | es_ES |
dc.description.sponsorship | MCIN/AEI PID2020-116518GB-I00 | es_ES |
dc.description.sponsorship | FEDER/Junta de Andalucia-Consejeria de Transformacion Economica, Industria, Conocimiento y Universidades PY20_00633
B-RNM-375-UGR18 | es_ES |
dc.description.sponsorship | European Commission 825213
945539 | es_ES |
dc.description.sponsorship | Spanish Government FPU16/04043 | es_ES |
dc.description.sponsorship | Klaus Tschira Foundation | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Royal Society of Chemistry | es_ES |
dc.rights | Atribución-NoComercial 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc/4.0/ | * |
dc.title | Graphene BioFET sensors for SARS-CoV-2 detection: a multiscale simulation approach | es_ES |
dc.type | journal article | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/825213 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/945539 | es_ES |
dc.rights.accessRights | open access | es_ES |
dc.identifier.doi | 10.1039/d2na00357k | |
dc.type.hasVersion | VoR | es_ES |