Point-and-shoot: portable Raman and SERS detection of organic gunshot residue analytes

Abstract

Raman spectroscopy is one of many tools available to verify the molecular composition of an analyte. Due to its non-destructive nature and its ability to accurately discern differences in closely related molecular structures, it has become invaluable in many fields, including its potential for forensic gunshot residue detection. Firearm-related fatalities in the United States continue to rise and many of them remain unsolved. This necessitates tools that are better equipped to aid in the investigation of firearm-related crimes, capable of high-throughput analysis yet remaining sensitive to give accurate and valuable information. The comparative downside of Raman spectroscopy to neighboring techniques like mass spectrometry and nuclear magnetic resonance is its lower sensitivity. Surface-enhanced Raman spectroscopy allows for the benefits of Raman spectroscopy alongside the added lower limit of detection with the simple application of nanoparticles, typically gold. Unfortunately, these benefits have seen little on-site application due to the difficulty of translating methods from conventional tabletop Raman spectrometers to point-and-shoot portable Raman spectrometers which have even lower sensitivities (higher limits of detection). Herein, we outline a versatile methodology for the detection of 6 organic gunshot residue components (diphenylamine (DPA), ethyl centralite (EC), 2,4-dinitrotoluene (2,4-DNT), 2-nitrodiphenylamine (2-nDPA), 4-nitrodiphenylamine (4-nDPA), and N-nitrosodiphenylamine (N-nDPA)) in liquid-phase that allows us to detect millimolar concentrations of these analytes. Furthermore, we report calculated vibrational assignments for these 6 analytes in solution, alongside detailed peak-by-peak analyses on a portable instrument. We showed signal enhancement and lower LODs through our data processing as well as a proof-of-concept SERS enhancement in a complex liquid-phase matrix, with an increased sensitivity of 700% when using SERS.