Femtosecond Filaments for Standoff Detection of Explosives

Abstract

In this report, we present our results from various studies to qualitatively discriminate the common military explosives viz. RDX, TNT and HMX in their pure form at a distance of ~6.5 m in standoff mode using femtosecond (fs) filament induced breakdown spectroscopy technique (fs FIBS) together with principal component analysis. A ~30 cm length fs filament obtained by a two-lens configuration was used to interrogate those energetic molecules in the form of pressed pellets (150 mg each). The plasma emissions were collected by a Schmidt-Cassegrain telescope (SCT) from a distance of ~8 m away from the investigation zone. Additionally, a few significant results obtained from the LIBS-based investigations of nitroimidazoles with respect to the standoff distance (~2 m) are discussed. Furthermore, we have also summarised a few important results from our recent investigations of bulk energetic materials in various configurations (including those with fs filaments). The results obtained from various fs FIBS configurations corroborate that the filament generation and its properties, the size and f-number of collection optics influence signal strength in the FIBS technique. These results project the fs FIBS technique as a potential technique for investigations aimed at hazardous materials and harsh environments in the standoff mode.

Laser-Induced Breakdown Spectroscopy for the Discrimination of Explosives Based on the ReliefF Algorithm and Support Vector Machines

“…Among the multivariate techniques demonstrated to be viable to classify an unknown sample as an explosive or a harmless product, the most widely used is elemental peaks ratios [35], principal component analysis (PCA) [36][37][38][39][40][41]. Several other chemometric methods, including soft independent modeling of class analogy [42], partial least squares Discriminant Analysis (PLS-DA) [43,44], support vector machines (SVMs) [45], and artificial neural network, have been applied to LIBS spectra for classification and identification [46].…”