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Classification of weathered petroleum oils by multi-way analysis of gas chromatography-mass spectrometry data using PARAFAC2 parallel factor analysis

Citation

Ebrahimi, D and Li, J and Hibbert, DB, Classification of weathered petroleum oils by multi-way analysis of gas chromatography-mass spectrometry data using PARAFAC2 parallel factor analysis, Journal of Chromatography A, 1166, (1-2) pp. 163-170. ISSN 0021-9673 (2007) [Refereed Article]

DOI: doi:10.1016/j.chroma.2007.07.085

Abstract

The application of multi-way parallel factor analysis (PARAFAC2) is described for the classification of different kinds of petroleum oils using GC–MS. Oils were subjected to controlled weathering for 2, 7 and 15 days and PARAFAC2 was applied to the three-way GC–MS data set (MS × GC × sample). The classification patterns visualized in scores plots and it was shown that fitting multi-way PARAFAC2 model to the natural three-way structure of GC–MS data can lead to the successful classification of weathered oils. The shift of chromatographic peaks was tackled using the specific structure of the PARAFAC2 model. A new preprocessing of spectra followed by a novel use of analysis of variance (ANOVA)-least significant difference (LSD) variable selection method were proposed as a supervised pattern recognition tool to improve classification among the highly similar diesel oils. This lead to the identification of diagnostic compounds in the studied diesel oil samples.

Item Details

Item Type:Refereed Article
Research Division:Chemical Sciences
Research Group:Analytical Chemistry
Research Field:Separation Science
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in the Chemical Sciences
Author:Li, J (Dr Jianfeng Li)
ID Code:54721
Year Published:2007
Web of Science® Times Cited:27
Deposited By:Austn Centre for Research in Separation Science
Deposited On:2009-02-27
Last Modified:2009-02-27
Downloads:0

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