Date of Award

Fall 2024

Language

English

Embargo Period

9-24-2024

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

College/School/Department

Department of Chemistry

Program

Chemistry

First Advisor

Rabi Musah

Committee Members

Rabi Musah, Michael Yeung, Mehmet Yigit, Lori Ana Valentίn

Subject Categories

Chemistry

Abstract

While forensic science is a well-established discipline, a number of federal agencies have highlighted challenges that continue to plague the field and the extent to which these challenges remain unaddressed. Examples are the illegal trade of wildlife timber and the drug epidemic. Characterization of these materials requires nuanced method development for compound determination, matrix material-specific protocols, and heavy use of expensive consumables. The application of a technique such as direct analysis in real time – high-resolution mass spectrometry (DART-HRMS) provides the opportunity to circumvent many of the challenges presented by conventional methods. In general, little to no sample preparation is required and a consistent sample analysis approach can be applied to most samples. This work explored the development and application of DART-HRMS through the investigation of the identification of New Psychoactive Substances (NPSs), psychoactive plants, and trade-regulated timber. The procedure for rapid structure determination of NPSs combines neutral loss mass spectral information from DART-HRMS data acquired at multiple voltages under collision-induced dissociation (CID) conditions, thereby resulting in varying levels of molecule fragmentation. This approach falls under the umbrella of “data fusion”, which is a strategy that combines the output from multiple data sets in order to improve the accuracy of the results. A second focus on psychoactive substances is the development of the Database of Psychoactive Plants (DoPP). This tool is designed to be user-friendly and includes an architecture for identifying plant unknowns. The application is based on the observation that plants display specific chemical signatures that are detectable by DART-HRMS. The subsequent automated machine learning processing of libraries of these spectra enabled the rapid discrimination and identification of species, resulting in a chemical signature database containing 57 available plant species. Another focus of this work is the development of an analysis approach to be used in a wildlife forensics context. Depending on the species, trade in timber can be totally or heavily restricted. A current technique used by law enforcement to differentiate species of wood is DART-HRMS, coupled with multivariate statistical analysis. Although this method is useful in a laboratory setting, it is impractical in field applications (such as for the determination of timber species identity in shipping containers at ports). The added dimension of wood headspace analysis by solid phase microextraction (SPME) was used to generate data to complement that acquired using the conventional wood analysis technique to facilitate the development of “stand-off” approaches for the differentiation of wood species based on their volatiles profiles.

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