Published:Journal of Chromatographic Science,
ISSN 0021-9665Volume
38, Number 3, March 2000, pp. 100–108
Forensic
Discrimination of Automotive Paint Samples Using Pyrolysis-Gas Chromatography–Mass
Spectrometry with Multivariate StatisticsBrian
K. Kochanowski and Stephen L. Morgan Department of Chemistry & Biochemistry, The University
of South Carolina, Columbia, SC 29208
Analytical
pyrolysis-gas chromatography (Py-GC) has been a standard method for the forensic
analysis of automotive paint for a number of decades. Automotive paints are
often identified by visual comparison of pyrograms for peak presence and intensities;
however, such analyses can be subjective and time consuming. A preliminary investigation
based on Py-GC–mass spectrometric analysis of 100 automobile paint samples
of five different colors is presented. Designed experiments are employed to
select pyrolysis conditions for adequate discrimination. Pattern recognition
techniques including principal component analysis and canonical variates analysis
are used to visualize clustering of pyrograms to validate comparisons between
different automotive paint pyrograms. These methods have the potential to ease
the interpretation task for data sets involving a large number of comparisons.
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