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dc.contributor.authorTeixeira, Guilherme G.
dc.contributor.authorPeres, António M.
dc.contributor.authorEstevinho, Letícia
dc.contributor.authorGeraldes, Pedro
dc.contributor.authorGarcía Cabezón, Ana Cristina 
dc.contributor.authorMartín Pedrosa, Fernando 
dc.contributor.authorRodríguez Méndez, María Luz 
dc.contributor.authorDias, Luís G.
dc.date.accessioned2023-05-26T07:54:44Z
dc.date.available2023-05-26T07:54:44Z
dc.date.issued2022
dc.identifier.citationChemosensors, 2022, Vol. 10, Nº. 7, 261es
dc.identifier.issn2227-9040es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/59698
dc.descriptionProducción Científicaes
dc.description.abstractA lab-made electronic nose (Enose) with vacuum sampling and a sensor array, comprising nine metal oxide semiconductor Figaro gas sensors, was tested for the quantitative analysis of vapor–liquid equilibrium, described by Henry’s law, of aqueous solutions of organic compounds: three alcohols (i.e., methanol, ethanol, and propanol) or three chemical compounds with different functional groups (i.e., acetaldehyde, ethanol, and ethyl acetate). These solutions followed a fractional factorial design to guarantee orthogonal concentrations. Acceptable predictive ridge regression models were obtained for training, with RSEs lower than 7.9, R2 values greater than 0.95, slopes varying between 0.84 and 1.00, and intercept values close to the theoretical value of zero. Similar results were obtained for the test data set: RSEs lower than 8.0, R2 values greater than 0.96, slopes varying between 0.72 and 1.10, and some intercepts equal to the theoretical value of zero. In addition, the total mass of the organic compounds of each aqueous solution could be predicted, pointing out that the sensors measured mainly the global contents of the vapor phases. The satisfactory quantitative results allowed to conclude that the Enose could be a useful tool for the analysis of volatiles from aqueous solutions containing organic compounds for which Henry’s law is applicable.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherMDPIes
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectElectronics - Dectectorses
dc.subjectElectrónica - Sensoreses
dc.subject.classificationElectronic nosees
dc.subject.classificationNariz electrónicaes
dc.subject.classificationMOS sensor arrayes
dc.subject.classificationConjunto de sensores MOSes
dc.subject.classificationQuantitative analysises
dc.subject.classificationAnálisis cuantitativoes
dc.subject.classificationRidge regressiones
dc.subject.classificationRegresión de crestaes
dc.titleEnose lab made with vacuum sampling: Quantitative applicationses
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holder© 2022 The Authorses
dc.identifier.doi10.3390/chemosensors10070261es
dc.relation.publisherversionhttps://www.mdpi.com/2227-9040/10/7/261es
dc.identifier.publicationfirstpage261es
dc.identifier.publicationissue7es
dc.identifier.publicationtitleChemosensorses
dc.identifier.publicationvolume10es
dc.peerreviewedSIes
dc.description.projectFundación para la Ciencia y la Tecnología (FCT, Portugal) y Fondo Europeo de Desarrollo Regional (FEDER) under Programme PT2020 - (grants UID/AGR/00690/2019 y LA/P/0007/2020)es
dc.identifier.essn2227-9040es
dc.rightsAtribución 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones
dc.subject.unesco2203 Electrónicaes
dc.subject.unesco3312 Tecnología de Materialeses


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