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dc.contributor.authorMaia Rigo, Tainara Rodrigues-
dc.contributor.authorFlumignan, Danilo Luiz-
dc.contributor.authorBoralle, Nivaldo-
dc.contributor.authorOliveira, Jose Eduardo de-
dc.date.accessioned2014-05-20T14:21:16Z-
dc.date.accessioned2016-10-25T17:41:55Z-
dc.date.available2014-05-20T14:21:16Z-
dc.date.available2016-10-25T17:41:55Z-
dc.date.issued2009-08-01-
dc.identifierhttp://dx.doi.org/10.1021/ef8010977-
dc.identifier.citationEnergy & Fuels. Washington: Amer Chemical Soc, v. 23, n. 8, p. 3954-3959, 2009.-
dc.identifier.issn0887-0624-
dc.identifier.urihttp://hdl.handle.net/11449/26363-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/26363-
dc.description.abstractIn (his work, the combination of hydrogen nuclear magnetic resonance ((1)H NMR) fingerprinting of gasoline with pattern-recognition analyses provides an approach to distinguish Brazilian commercial gasoline, processed in different states of Brazil. Hierarchical cluster analyses (HCA) and principal component analyses (PCA) were carried out on chemical shifts in order to observe any natural grouping feature. while soft independent modeling of class analogy (SIMCA) was performed to classify external samples into previously origin-defined classes. PCA demonstrated that a small number of variables dominate the total data variability since the first three principal components (PCs) accounted for 64.9% of total variability; whereas a HCA dendrogram shows five natural cluster grouping features. Following optimized (1)H NMR-SIMCA algorithm, sensitivity values in the training set with leave-one-out cross-validation (86.0%) and external prediction set (77.3%) were obtained. Governmental laboratories could employ this method as a rapid screening analysis for origin authentication related to tax evasion purposes.en
dc.description.sponsorshipAgência Nacional do Petróleo, Gás Natural e Biocombustíveis (ANP)-
dc.description.sponsorshipGas Natural e Biocombustiveis - ANP-
dc.description.sponsorshipFUN-DUNESP-
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)-
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
dc.description.sponsorshipFUND-UNESP-
dc.format.extent3954-3959-
dc.language.isoeng-
dc.publisherAmer Chemical Soc-
dc.sourceWeb of Science-
dc.title(1)H NMR Fingerprinting of Brazilian Commercial Gasoline: Pattern-Recognition Analyses for Origin Authentication Purposesen
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationUNESP, CEMPEQC, Ctr Monitoring & Res Qual Fuels Biofuels Crude Oi, BR-14800900 Araraquara, SP, Brazil-
dc.description.affiliationUNESP, Inst Chem, Dept Organ Chem, BR-14800900 Araraquara, SP, Brazil-
dc.description.affiliationUnespUNESP, CEMPEQC, Ctr Monitoring & Res Qual Fuels Biofuels Crude Oi, BR-14800900 Araraquara, SP, Brazil-
dc.description.affiliationUnespUNESP, Inst Chem, Dept Organ Chem, BR-14800900 Araraquara, SP, Brazil-
dc.identifier.doi10.1021/ef8010977-
dc.identifier.wosWOS:000269088300017-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofEnergy & Fuels-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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