Production of the NO photofragment in the desorption of RDX and HMX from surfaces

Non-Destructive Trace Detection of Explosives Using Pushbroom Scanning Hyperspectral Imaging System

The aim of this study was to investigate the potential of the non-destructive hyperspectral imaging system (HSI) and accuracy of the model developed using Support Vector Machine (SVM) for determining trace detection of explosives. Raman spectroscopy has been used in similar studies, but no study has been published which is based on measurement of reflectance from hyperspectral sensor for trace detection of explosives. HSI used in this study has an advantage over existing techniques due to its combination of imaging system and spectroscopy, along with being contactless and non-destructive in nature. Hyperspectral images of the chemical were collected using the BaySpec hyperspectral sensor which operated in the spectral range of 400–1000 nm (144 bands). Image processing was applied on the acquired hyperspectral image to select the region of interest (ROI) and to extract the spectral reflectance of the chemicals which were stored as spectral library. Principal Component Analysis (PCA) and first derivative was applied to reduce the high dimensionality of the image and to determine the optimal wavelengths between 400 and 1000 nm. In total, 22 out of 144 wavelengths were selected by analysing the loadings of principal components (PC). SVM was used to develop the classification model. SVM model established on the whole spectrum from 400 to 1000 nm achieved an accuracy of 81.11%, whereas an accuracy of 77.17% with less computational load was achieved when SVM model was established on the optimal wavelengths selected. The results of the study demonstrate that the hyperspectral imaging system along with SVM is a promising tool for trace detection of explosives.

Spectroscopic observation of neutral carbon during photodissociation of explosive-related compounds in the vapor phase

We perform time-resolved laser-induced fluorescence measurements of mononitrotoluenes (MNTs) and dinitrotoluenes (DNTs) in nitrogen and air. We observe the multipeak emission spectrum of NO and find that the emission peak intensity in the 247-248 nm range is stronger than expected compared to the other NO emission peak intensities. This increased emission intensity is believed to be due to neutral carbon [C(I)], which has a strong emission peak at 247.85 nm. By comparing the ratios of integrated emission peak intensities with those expected from the Franck-Condon factors for NO, we are able to identify samples that exhibit C(I) emission. We show that the DNTs exhibit C(I) emission for gate delays of 1500 ns and beyond, while the MNTs exhibit C(I) emission for gate delays of only up to about 500 ns. Carbon deposits in the analysis chamber confirm the presence of C. Ambient NO in air enhances the observed NO+C(I) signal from MNTs and DNTs.