# Chemical Analysis of Gunpowder and Gunshot Residues
## 3 Analysis of Gunpowder and Gunshot Residue
### Emerging Applications
From this procedure, using LC/time-of-flight (TOF)-MS, a statistical analysis was conducted using PCA and HCA to discriminate unburnt gunpowder based on chemical composition and to establish a correspondence between unburnt gunpowder and OGSR compounds [152]. Although good results were obtained, these tools, as any other machine learning tools, must be used with care since their outcomes are highly reliant on the quality and representativeness of the data. On the other hand, many of these tools may struggle to distinguish between samples with minor compositional variations, particularly when the differences fall within the limits of the analytical techniques employed. [PERSON] and [PERSON] (2014) also reported a novel analytical and statistical methodology for analysing GSR based on the Raman and FTIR spectra dataset. The researchers found that these two analytical techniques contributed differently to the chemometric model. However, the authors also showed this to be a robust approach in forensic investigations for ruling out particular firearm ammunition (2017). The same authors (2017) also studied the potential of near-infrared (NIR) Raman to discriminate and identify particles of GSR using PLS correlation analysis and SVM. \begin{table}
**Statistical Method** & **Experimental Procedure** & **Target Analytes** & **Conclusions** & **Ref.** \\ \hline PCA and HCA & LC-TOF/MS & SG and OSGR & \begin{tabular}{c} Discrimination of SG based on the chemical composition by matching \\ SG’s organic compounds to OSGR \\ \end{tabular} & [(152)] \\ \hline [PERSON]’s correlation & HPLC and micellar & SG & \begin{tabular}{c} The comparison of both \\ techniques showed slightly \\ different results and \\ complementary potential \\ \end{tabular} & [(127)] \\ \hline Database and analysis of the statistical impact & Raman and FTIR & GSR & \begin{tabular}{c} Creation of a database with \\ combined FTIR and Raman \\ spectra; determination of the \\ different impacts that these \\ techniques had on a chemometric \\ model \\ \end{tabular} & [(74)] \\ \hline PLS and SVM & NIR Raman & GSR & \begin{tabular}{c} Successful discrimination and \\ identification of GSR particles \\ \end{tabular} & [(76)] \\ \hline LR & SPME/GC-MS & GSR & \begin{tabular}{c} Creation of a logical approach to \\ determining the time since \\ discharge, with a successful \\ application to a hypothetical \\ scenario \\ \end{tabular} & [(33)] \\ \hline Pairwise log ratio & & & \\ normalisation & & & \\ combined with RF and & & & \\ PLS regression & & & \\ \hline \hline \end{tabular} \begin{tabular}{c c c c} \hline \hline  & & \begin{tabular}{c} Evaluation of judgment and \\ conclusions of forensic experts in \\ identification ballistics, \\ determining their results to have \\ high sensitivity and specificity \\ \end{tabular} & [(7)] \\ \hline PCA and PLS-DA & ATR-FTIR & GSR & \begin{tabular}{c} Successful discrimination of \\ ammunition calibre \\ \end{tabular} & [(121)] \\ \hline ANN & UHPLC-UV & OGSR & \
\begin{tabular}{c} Prediction of retention time of 32 \\ OGSR compounds during method \\ optimisation \\ \end{tabular} & [(54)] \\ \hline ANN & IMS & GSR &
\begin{tabular}{c} Differentiation of particles \\ collected by hand swabs, \\ discriminating between shooters \\ and non-shooters \\ \end{tabular} & [(148)] \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Summary of some emerging applications employed in GSR analysis. With a different objective, [PERSON] et al. [128] used [PERSON]'s correlation test to compare HPLC and micellar electrokinetic capillary chromatography in their capability to analyse the organic compounds of SG. The results were slightly different with each technique, and [PERSON]'s correlation test showed a good relationship between the different separations' patterns, pointing to the possibility of complementary approaches [128]. [PERSON] et al. [33] based their study on a hypothetical SPME/GC analysis of spent cartridges to create a logical approach to estimate their time since discharge.