2015
DOI: 10.1039/c4ay02730b
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Differentiation of vehicle top coating paints using pyrolysis-gas chromatography/mass spectrometry and multivariate chemometrics with statistical comparisons

Abstract: The aim of this work was to evaluate the capabilities and feasibility of using the averaged mass spectra obtained from pyrograms for assessing the group distributions and similarities of vehicle paint samples.To achieve this, all the profiles of averaged mass spectra were examined using hierarchical cluster analysis and principal component analysis after data processing. The pyrograms of 54 vehicle top coating samples were characterized by mass fragments chosen from 15 major paint constituents commonly used in… Show more

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Cited by 9 publications
(3 citation statements)
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“…The second approach for pigment identification was a modified version of the method published by Yang et al ( 2014 ). They used a statistical comparison of average mass spectra (AMS) of vehicle top-coatings to describe hierarchical cluster similarity with reference samples of different manufacturers.…”
Section: Resultsmentioning
confidence: 99%
“…The second approach for pigment identification was a modified version of the method published by Yang et al ( 2014 ). They used a statistical comparison of average mass spectra (AMS) of vehicle top-coatings to describe hierarchical cluster similarity with reference samples of different manufacturers.…”
Section: Resultsmentioning
confidence: 99%
“…Furthermore, traditional methods usually identify the features reflected by visual comparison of spectra of samples, and the method is often not accurate enough. Nowadays, multivariate statistical methods make a decisive contribution to providing objective interpretations of the data and comparison of samples [36, 37].…”
Section: Introductionmentioning
confidence: 99%
“…Nowadays, multivariate statistical methods make a decisive contribution to providing objective interpretations of the data and comparison of samples [36,37].…”
Section: Introductionmentioning
confidence: 99%