Raman microspectroscopic chemical mapping and chemometric classification for the identification of gunshot residue on adhesive tape.

Abstract

A novel approach utilizing automated Raman microspectroscopic mapping for gunshot residue (GSR) detection was investigated. A well-established technique for GSR recovery (tape lifting) was utilized for GSR particle collection. Uncontaminated samples of the substrate (tape), organic GSR (OGSR), and inorganic GSR (IGSR) particles were characterized to generate three respective Raman spectroscopic training sets. Automated Raman mapping was used to rapidly collect spectra over areas of the tape substrate populated with GSR particles. Raman spectra collected from the maps were classified against the training sets via partial least squares discriminant analysis (PLS-DA) to determine if GSR was present. We report the application of Raman chemical mapping as a proof of concept for the positive detection of GSR particles of varying morphologies. The estimated size of GSR particles, which could be readily detected by this method, is about 3.4 μm. The efficiency of the classification was quantitated with rates of true positives and negatives. Validation studies scrutinizing the practicality of this approach as a viable tool for potential forensics investigations are currently in progress.