Publication:
Optimization of multilayer graphene-based gas sensors by ultraviolet photoactivation

dc.contributor.authorPeña Moreno, Álvaro
dc.contributor.authorMatatagui Cruz, Daniel
dc.contributor.authorRicciardella, Filiberto
dc.contributor.authorSacco, Leandro
dc.contributor.authorVollebregt, Sten
dc.contributor.authorOtero, Daniel
dc.contributor.authorLópez Sánchez, Jesús
dc.contributor.authorMarín Palacios, Pilar
dc.contributor.authorHorrillo, Mari Carmen
dc.date.accessioned2023-06-22T12:28:21Z
dc.date.available2023-06-22T12:28:21Z
dc.date.issued2022-11-01
dc.descriptionCRUE-CSIC (Acuerdos Transformativos 2022) © 2022 The Author(s). Author A. P. received funding from grant PRE2019-0875001234, Ministerio de Ciencia e Innovación (MCI), Spain. D. M. received funding from Comfuturo, Consejo Superior de Investigaciones Científicas, Spain. Authors A. P., D. M., D. O., P. M., and M- C. H. received funding from projects RTI2018-095856-B-C21 and –C22, Ministerio de Ciencia e Innovación, Spain. A. P. and P. M. received funding S2018/ NMT-4321, Comunidad de Madrid. J. L.-S. received funding from project PID2020-114192RB-C41, Ministerio de Asuntos Económicos y Transformación Digital (MINECO).
dc.description.abstractNitrogen dioxide (NO2) is a potential hazard to human health at low concentrations, below one part per million (ppm). NO2 can be monitored using gas sensors based on multi-layered graphene operating at ambient temperature. However, reliable detection of concentrations on the order of parts per million and lower is hindered by partial recovery and lack of reproducibility of the sensors after exposure. We show how to overcome these longstanding problems using ultraviolet (UV) light. When exposed to NO2, the sensor response is enhanced by 290 % − 550 % under a 275 nm wavelength light emitting diode irradiation. Furthermore, the sensor’s initial state is completely restored after exposure to the target gas. UV irradiation at 68 W/m2 reduces the NO2 detection limit to 30 parts per billion (ppb) at room temperature. We investigated sensor performance optimization for UV irradiation with different power densities and target gases, such as carbon oxide and ammonia. Improved sensitivity, recovery, and reproducibility of UV-assisted graphene-based gas sensors make them suitable for widespread environmental applications.
dc.description.departmentDepto. de Física de Materiales
dc.description.facultyFac. de Ciencias Físicas
dc.description.refereedTRUE
dc.description.sponsorshipMinisterio de Ciencia e Innovación (MICINN)
dc.description.sponsorshipMinisterio de Asuntos Económicos y Transformación Digital (MINECO)
dc.description.sponsorshipComunidad de Madrid
dc.description.sponsorshipConsejo Superior de Investigaciones Científicas (CSIC)
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/75412
dc.identifier.doi10.1016/j.apsusc.2022.155393
dc.identifier.issn0169-4332
dc.identifier.officialurlhttps://doi.org/10.1016/j.apsusc.2022.155393
dc.identifier.relatedurlhttps://www.sciencedirect.com
dc.identifier.urihttps://hdl.handle.net/20.500.14352/72601
dc.journal.titleApplied Surface Science
dc.language.isoeng
dc.page.initial155393
dc.publisherElsevier
dc.relation.projectID(PRE2019-0875001234; RTI2018-095856-B-C21; RTI2018-095856-B-C22)
dc.relation.projectIDPID2020-114192RB-C41
dc.relation.projectIDS2018/ NMT-4321
dc.relation.projectIDComFuturo
dc.rightsAtribución-NoComercial 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttps://creativecommons.org/licenses/by-nc/3.0/es/
dc.subject.cdu538.9
dc.subject.keywordGraphene gas sensors
dc.subject.keywordUltraviolet
dc.subject.keywordNitrogen dioxide
dc.subject.keywordLimit of detection
dc.subject.keywordAmmonia
dc.subject.keywordCarbon monoxide
dc.subject.ucmFísica de materiales
dc.titleOptimization of multilayer graphene-based gas sensors by ultraviolet photoactivation
dc.typejournal article
dc.volume.number610
dspace.entity.typePublication
relation.isAuthorOfPublicationd86ef57b-de51-4d2c-b7df-d1c3ef8333c8
relation.isAuthorOfPublication9e073de0-a959-4bf3-b130-a0de3b1f7933
relation.isAuthorOfPublication.latestForDiscoveryd86ef57b-de51-4d2c-b7df-d1c3ef8333c8
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