Brasil | Artículos de revistas

Prediction of the physicochemical properties of gasoline by comprehensive two-dimensional gas chromatography and multivariate data processing

dc.creatorde Godoy, LAF
dc.creatorPedroso, MP
dc.creatorFerreira, EC
dc.creatorAugusto, F
dc.creatorPoppi, RJ
dc.date2011
dc.date45717
dc.date2014-08-01T18:34:27Z
dc.date2015-11-26T17:06:29Z
dc.date2014-08-01T18:34:27Z
dc.date2015-11-26T17:06:29Z
dc.date.accessioned2018-03-28T23:54:57Z
dc.date.available2018-03-28T23:54:57Z
dc.identifierJournal Of Chromatography A. Elsevier Science Bv, v. 1218, n. 12, n. 1663, n. 1667, 2011.
dc.identifier0021-9673
dc.identifierWOS:000288725300013
dc.identifier10.1016/j.chroma.2011.01.056
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/80916
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/80916
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1279869
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.descriptionThe estimation of physicochemical parameters such as distillation points and relative densities still plays an important role in the quality control of gasoline and similar fuels. Their measurements according to standard ASTM procedures demands specific equipments and are time and work consuming. An alternative method to predict distillation points and relativity density by multivariate analysis of comprehensive two-dimensional gas chromatography with flame ionization detection (GC x GC-FID) data is presented here. Gasoline samples, previously tested according to standard methods, were used to build regression models, which were evaluated by external validation. The models for distillation points were built using variable selection methods, while the model for relativity density was built using the whole chromatograms. The root mean square prediction differences (RMSPD) obtained were 0.85%, 0.48%, 1.07% and 1.71% for 10, 50 and 90% v/v of distillation and for the final point of distillation, respectively. For relative density, the RMSPD was 0.24%. These results suggest that GC x GC-FID combined with multivariate analysis can be used to predict these physicochemical properties of gasoline. (C) 2011 Elsevier B.V. All rights reserved.
dc.description1218
dc.description12
dc.description1663
dc.description1667
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.languageen
dc.publisherElsevier Science Bv
dc.publisherAmsterdam
dc.publisherHolanda
dc.relationJournal Of Chromatography A
dc.relationJ. Chromatogr. A
dc.rightsfechado
dc.rightshttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dc.sourceWeb of Science
dc.subjectGasoline
dc.subjectComprehensive two-dimensional gas chromatography
dc.subjectMultivariate analysis
dc.subjectBrazilian Gasoline
dc.subjectAdulteration
dc.subjectQuality
dc.subjectIdentification
dc.subjectQuantification
dc.subjectSpectroscopy
dc.subjectKerosene
dc.titlePrediction of the physicochemical properties of gasoline by comprehensive two-dimensional gas chromatography and multivariate data processing
dc.typeArtículos de revistas


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