dc.contributor.author | Rezayei, Elham | |
dc.contributor.author | Beheshtian, Javad | |
dc.contributor.author | Shayeganfar, Farzaneh | |
dc.contributor.author | Ramazani, Ali | |
dc.date.accessioned | 2022-05-23T14:48:47Z | |
dc.date.available | 2022-05-23T14:14:22Z | |
dc.date.available | 2022-05-23T14:48:47Z | |
dc.date.issued | 2022-05 | |
dc.date.submitted | 2021-12 | |
dc.identifier.issn | 1610-2940 | |
dc.identifier.issn | 0948-5023 | |
dc.identifier.uri | https://hdl.handle.net/1721.1/142640.2 | |
dc.description.abstract | Abstract
Selectivity of dopamine (DA), uric acid (UA), and ascorbic acid (AA) is an open challenge of electrochemical sensors in the field of biosensing. In this study, two selective mechanisms for detecting DA, UA, and AA biomolecules on the pristine boron nitride nanosheets (BNNS) and functionalized BNNS with tryptophan (Trp), i.e., Trp@BNNS have been illustrated through density functional density (DFT) calculation and charge population analysis. Our findings reveal that the adsorbed biomolecules on Trp@BNNS indicate the less sensitivity factor of biomolecule separation than the functionalized biomolecules with Trp (Trp@biomolecule) adsorbed on pristine BNNS. From the calculations, strong adsorption of Trp@biomolecule on the pristine substrate corresponds to enhancing of electron charge transfer and electrical dipole moment. Our analysis is in good agreement with the previous theoretical and experimental results and suggests new pathway for electrode modification for electrochemical biosensing. | en_US |
dc.publisher | Springer Science and Business Media LLC | en_US |
dc.relation.isversionof | https://doi.org/10.1007/s00894-022-05158-z | en_US |
dc.rights | Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. | en_US |
dc.source | Springer Berlin Heidelberg | en_US |
dc.title | Fundamental mechanisms of hexagonal boron nitride sensing of dopamine, tryptophan, ascorbic acid, and uric acid by first-principles study | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Journal of Molecular Modeling. 2022 May 20;28(6):158 | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Mechanical Engineering | |
dc.relation.journal | Journal of Molecular Modeling | en_US |
dc.eprint.version | Author's final manuscript | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dc.date.updated | 2022-05-21T03:28:36Z | |
dc.language.rfc3066 | en | |
dc.rights.holder | The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature | |
dspace.embargo.terms | Y | |
dspace.date.submission | 2022-05-21T03:28:36Z | |
mit.journal.volume | 28 | en_US |
mit.journal.issue | 6 | en_US |
mit.license | PUBLISHER_POLICY | |
mit.metadata.status | Authority Work Needed | en_US |