Seminars Archive
New horizons in forensic applications of Raman spectroscopy enabled by machine learning
University at Albany, State University of New York
Abstract
Raman spectroscopy has been known for decades as the most selective spectroscopic technique. The technique is non-destructive, rapid and requires little or no sample preparation. Furthermore, portable Raman instruments are readily available allowing for crime scene accessibility. We have developed and are commercializing now (www.supremetric.com) the first universal method for the confirmatory identification of all main body fluids based on Raman spectroscopic analysis of biological stains. In addition, peripheral and menstrual blood as well as human and animal blood can be differentiated. Application of AI enabled uncovering much more information from the Raman spectral datasets of body fluid stains. Specifically, the time since deposition of bloodstain can be estimated up to two years. Most recently, we demonstrated the proof-of-concept for phenotype profiling based on Raman spectroscopy of dry traces of body fluids including determining sex, race, and age group of the donor.
Gunshot residue (GSR) is an important type of trace evidence, which is often associated with a violent crime. Organic GSR (OGSR) has been the focus of many forensic researchers for several reasons. First, the total amount of OGSR generated due to the discharge of a firearm is much larger than the amount of IGSR. OGSR particles could be detected easier since they are typically much larger in size than IGSR particles. In addition, the chemical composition of OGSR is quite complex and includes partially burned and unburned smokeless powder, stabilizers, plasticizers, etc. Application of AI allows for a confirmatory identification of OGSR particles using Raman spectroscopy. Generating additional datasets for the same GSR particles by applying laser induced breakdown spectroscopy (LIBS) and attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy opens new opportunities for the identification of an ammunition and ammunition manufacturer based on GSR analysis.