Our work in this area is focused on developing tools to aid in the identification and characterization of novel psychoactive substances (NPS). We have developed a method for statistical comparison of mass spectra and are currently testing the method for the differentiation of positional isomers of ethylmethcathinone, fluormethamphetamine, fluoroisobutyryl fentanyl, and fluorobutyryl fentanyl. We have also demonstrated application of multivariate statistical models to classify various NPS according to structural subclass and are continuing this work to focus on fentanyl analogs.
Our research in this area is focused on the development, refinement, and application of a kinetic-based model that can be used to generate chromatograms corresponding to an evaporated ignitable liquid. The model predicts the fraction of liquid remaining after evaporation and is broadly applicable to any ignitable liquid class. We are currently refining the model to improve predictive ability for gasoline and, in collaboration with Prof. Glen Jackson at West Virginia University, will investigate the effects of elevated temperature on the predictive ability. This work is currently funded by the National Institute of Justice (Award No. 2018-DU-BX-0225).