Abstract

Laser-induced breakdown spectroscopy is a promising approach for explosive residue detection, but several limitations to its widespread use remain. One issue is that the emission spectra of the residues are dependent on the substrate composition because some of the substrate is usually entrained in the laser-induced plasma and the laser–material interaction can be significantly affected by the substrate type. Here, we have demonstrated that despite the strong spectral variation in cyclotrimethylenetrinitramine (RDX) residues applied to various metal substrates, classification of the RDX residue independent of substrate type is feasible. Several approaches to improving the chemometric models based on partial least squares discriminant analysis (PLS-DA) have been described: classifying the RDX residue spectra together in one class independent of substrate, using selected emission intensities and ratios to increase the true positive rate (TPR) and decrease the false positive rate (FPR), and fusing the results from two PLS-DA models generated using the full broadband spectra and selected intensities and ratios. The combination of these approaches resulted in a TPR of 97.5% and a FPR of 1.0% for RDX classification on metal substrates.

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