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Träfflista för sökning "WFRF:(Rodrigues Luiz F.) srt2:(2017)"

Sökning: WFRF:(Rodrigues Luiz F.) > (2017)

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1.
  • dos Santos, Victor Hugo J. M., et al. (författare)
  • Classification of Fuel Blends Using Exploratory Analysis with Combined Data from Infrared Spectroscopy and Stable Isotope Analysis
  • 2017
  • Ingår i: Energy & Fuels. - : American Chemical Society (ACS). - 0887-0624 .- 1520-5029. ; 31:1, s. 523-532
  • Tidskriftsartikel (refereegranskat)abstract
    • Chemometric tools were applied for exploratory analysis and classification of fuel blends using the combined information on Fourier transform infrared spectroscopy and stable isotope analysis through isotope ratio mass spectrometry. Principal component analysisand hierarchical clustering analysis were applied for exploratory analysis, while support vector machine (SVM) was used to classify the biodiesel/diesel blends. All of the chemometric models used present better results from the combination of spectral information with isotopic data for biodiesel contents of over 10% in the mixture, with the best results being Obtained from the SVM classification. Therefore, the development presented in this paper could become an important technique to improve the discrimination of the feedstock used in biodiesel production and a resource for quality control in industry.
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2.
  • dos Santos, Victor Hugo J. M., et al. (författare)
  • Discriminant analysis of biodiesel fuel blends based on combined data from Fourier Transform Infrared Spectroscopy and stable carbon isotope analysis
  • 2017
  • Ingår i: Chemometrics and Intelligent Laboratory Systems. - : Elsevier. - 0169-7439 .- 1873-3239. ; 161, s. 70-78
  • Tidskriftsartikel (refereegranskat)abstract
    • A multivariate approach was used for classification of fuel blends using the combined information from Fourier Transform Infrared Spectroscopy (FTIR) and stable carbon isotopes analysis by Isotope Ratio Mass Spectrometry (IRMS). Linear Discriminant Analysis (LDA) and Partial Least Squares Discriminant Analysis (PLS-DA) were applied to the classification of biodiesel/diesel fuel blends containing 0-100% (v/v) of biodiesel. The LDA and PLS-DA methods were able to discriminate samples ranging from 10% to 100% biodiesel (v/v) using the combined information from FTIR and IRMS. Since the global trend is toward a gradual increase in the percentage of biodiesel in fuel blends, the technique presented in this paper could be an important development in improving the traceability and identification of different raw materials used in biodiesel production.
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