The analysis of tires and tire traces using FTIR Py-GC/MS

Abstract

The ability of three analytical techniques to analyse and differentiate tire rubber samples is presented. The three techniques examined were Attenuated Total Reflectance (ATR) Spectroscopy, Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS), and Pyrolysis-Gas ChromatographylMass Spectrometry (Py-GClMS). Both ATR and DRIFTS showed poor discrimination of the samples. Of 27 samples examined using ATR and DRIFTS, ATR was able to differentiate 11, while DRIFTS was only able to differentiate 3. Py-GCIMS showed good discrimination of the 59 samples examined based on two techniques: target compound identification (TCI) and linear discriminant analysis (LOA). Target compound identification was able to differentiate 47% of the samples from all the rest, while 28% of the samples were not able to be discriminated from only one other sample, and 25% of the samples could not be differentiated. LDA was able to discriminate 89.8% of the samples using 38 variables, 83.1% of the samples using only six principal components, and 98.3% of the samples when all sample information, significantly date of manufacture, was different. LDA was able to correctly classify 94.9% of the samples based on brand only. It appears that Py- GC/MS is the technique of choice and should be used as a stand-alone technique.