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Copy toner samples were analyzed using scanning electron microscopy with X-ray dispersive analysis (SEM-EDX) and pyrolysis gas chromatography/mass spectrometry (Py-GC/MS). Principal component and cluster analysis of SEM data for 166 copy toner samples established 13 statistically different subgroups, with the presence or absence of a ferrite base being a major division. When toners were compared for which both SEM and reflection-absorption infrared spectral data were available, 41% of the samples could be assigned to specific manufacturers. Py-GC/MS on poly(styrene:acrylate)-based toners produced eight peaks relevant to toner differentiation. One third of the toners clustered in a small group that contained five statistically different subgroups. Of the 57 toners for which both Py-GC/MS and SEM data were available, 31 could be differentiated using the combined analytical results. The synergy of the complementary information provided by Py-GC/MS and SEM narrows matching possibilities for forensic investigations involving copied or laser printed documents.

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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