Current techniques used to analyze automotive paint samples include microscopy, fourier – transform infrared (FTIR) spectroscopy, and pyrolysis gas chromatography - mass spectrometry (Py-GC-MS). These techniques are performed in the respective order listed above. Out of the three techniques currently used in this field, the one that has the highest discriminatory power is py-GC-MS; however, this technique is time consuming and destructive toward the sample. One hundred automotive paint samples were analyzed using FTIR, Py-GC-MS and direct analysis in real time-high resolution mass spectrometry (DART-HRMS) to determine how DART-HRMS compared to Py-GC-MS in terms of discriminatory capability. DART-HRMS takes approximately 4 minutes to run a sample while Py-GC-MS takes around 24 minutes per sample. The vast difference in analysis run times between the two techniques could help prevent and/or get rid of current backlogs in forensic trace labs. The clear coat and base coat of automotive paint samples were analyzed using DART-HRMS to compare the different information obtained for the separate layers. The accuracies of the models, based on LDA, were 86.77%, 87.98%, 95.61%, and 98.20% for DART-HRMS (base coat), FTIR, Py-GC-MS, and DART-HRMS (clear coat), respectively. This demonstrates that DART-HRMS can be utilized when analyzing automotive paint samples to achieve a higher discriminatory power while also analyzing samples in a fraction of the time that Py-GC-MS takes.
If this is your thesis or dissertation, and want to learn how to access it or for more information about readership statistics, contact us at STARS@ucf.edu.
Master of Science (M.S.)
College of Sciences
Length of Campus-only Access
Masters Thesis (Campus-only Access)
Jones, Kaitlin, "Characterization of Clear Coat and Base Coat Automotive Paint Analysis Using DART-HRMS and Comparison of FTIR Spectroscopy, Py-GC-MS, and DART-HRMS for Clear Coat Analysis" (2020). Electronic Theses and Dissertations, 2020-. 238.