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

dc.contributor.author Ebrahimi Mohammadi, Diako en_US
dc.contributor.author Li, Jianfeng en_US
dc.contributor.author Hibbert, D. Brynn en_US
dc.date.accessioned 2021-11-25T13:02:11Z
dc.date.available 2021-11-25T13:02:11Z
dc.date.issued 2007 en_US
dc.description.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. © 2007 Elsevier B.V. All rights reserved. en_US
dc.identifier.issn 0021-9673 en_US
dc.identifier.uri http://hdl.handle.net/1959.4/38988
dc.language English
dc.language.iso EN en_US
dc.rights CC BY-NC-ND 3.0 en_US
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/3.0/au/ en_US
dc.source Legacy MARC en_US
dc.subject.other Crude petroleum en_US
dc.subject.other Data structures en_US
dc.subject.other Diesel fuels en_US
dc.subject.other Gas chromatography en_US
dc.subject.other Mass spectrometry en_US
dc.subject.other Mathematical models en_US
dc.title Classification of weathered petroleum oils by multi-way analysis of gas chromatography-mass spectrometry data using PARAFAC2 parallel factor analysis en_US
dc.type Journal Article en
dcterms.accessRights open access
dspace.entity.type Publication en_US
unsw.accessRights.uri https://purl.org/coar/access_right/c_abf2
unsw.description.publisherStatement The Journal of Chromatography A is published by Elsevier, http://www.elsevier.com/wps/find/homepage.cws_home en_US
unsw.identifier.doiPublisher http://dx.doi.org/10.1016/j.chroma.2007.07.085 en_US
unsw.relation.faculty Science
unsw.relation.ispartofissue 1-2 en_US
unsw.relation.ispartofjournal Journal of Chromatography A en_US
unsw.relation.ispartofpagefrompageto 163-170 en_US
unsw.relation.ispartofvolume 1166 en_US
unsw.relation.originalPublicationAffiliation Ebrahimi Mohammadi, Diako, Chemistry, Faculty of Science, UNSW en_US
unsw.relation.originalPublicationAffiliation Li, Jianfeng, Chemistry, Faculty of Science, UNSW en_US
unsw.relation.originalPublicationAffiliation Hibbert, D. Brynn, Chemistry, Faculty of Science, UNSW en_US
unsw.relation.school School of Chemistry *
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