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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/26351
Title: 
Screening Brazilian Commercial Gasoline Quality by ASTM D6733 GC and Pattern-Recognition Multivariate SIMCA Chemometric Analysis
Author(s): 
Institution: 
Universidade Estadual Paulista (UNESP)
ISSN: 
0009-5893
Sponsorship: 
  • Agência Nacional do Petróleo, Gás Natural e Biocombustíveis (ANP)
  • Gas Natural e Biocombustiveis-ANP
  • Fundação para o Desenvolvimento da UNESP (FUNDUNESP)
  • Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
  • Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Abstract: 
The combination of ASTM D6733 gas chromatographic fingerprinting data with pattern-recognition multivariate soft independent modeling of class analogy (SIMCA) chemometric analysis provides an original and alternative approach to screening Brazilian commercial gasoline quality in a monitoring program for quality control of automotive fuels. SIMCA was performed on chromatographic fingerprints to classify the quality of the gasoline samples. Using SIMCA, it was possible to correctly classify 94.0% of commercial gasoline samples, which is considered acceptable. The method is recommended for quality-control monitoring. Quality control and police laboratories could employ this method for rapid monitoring.
Issue Date: 
1-Apr-2009
Citation: 
Chromatographia. Wiesbaden: Vieweg, v. 69, n. 7-8, p. 719-727, 2009.
Time Duration: 
719-727
Publisher: 
Vieweg
Keywords: 
  • Gas chromatography
  • ASTM D6733
  • Brazilian commercial gasoline
  • Pattern recognition multivariate SIMCA
  • Quality control
Source: 
http://dx.doi.org/10.1365/s10337-009-0958-6
URI: 
Access Rights: 
Acesso restrito
Type: 
outro
Source:
http://repositorio.unesp.br/handle/11449/26351
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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