Abstract

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.

Notes

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Graduation Date

2020

Semester

Summer

Advisor

Bridge, Candice

Degree

Master of Science (M.S.)

College

College of Sciences

Department

Chemistry

Degree Program

Forensic Science

Format

application/pdf

Identifier

CFE0008187; DP0023541

URL

https://purls.library.ucf.edu/go/DP0023541

Language

English

Release Date

August 2021

Length of Campus-only Access

1 year

Access Status

Masters Thesis (Campus-only Access)

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