FT-IR Standoff Detection of Thermally Excited Emissions of Trinitrotoluene (TNT) Deposited on Aluminum Substrates

Abstract

A standoff detection system was assembled by coupling a reflecting telescope to a Fourier transform infrared spectrometer equipped with a cryo-cooled mercury cadmium telluride detector and used for detection of solid-phase samples deposited on substrates. Samples of highly energetic materials were deposited on aluminum substrates and detected at several collector-target distances by performing passive-mode, remote, infrared detection measurements on the heated analytes. Aluminum plates were used as support material, and 2,4,6-Trinitrotoluene (TNT) was used as the target. For standoff detection experiments, the samples were placed at different distances (4 to 55 m). Several target surface temperatures were investigated. Partial least squares regression analysis was applied to the analysis of the intensities of the spectra obtained. Overall, standoff detection in passive mode was useful for quantifying TNT deposited on the aluminum plates with high confidence up to target-collector distances of 55 m.

Open-Path FTIR Detection of Explosives on Metallic Surfaces

“…• Establishment that multivariate data analysis techniques are required to exploit all the benefits that having a wealth of spectral information immersed in a congested multicomponent spectrum as that contained in SOIR experiments, not only for gas phase measurements but also for solid phase OP/FTIR detection at a distance, as Castro and collaborators have recently demonstrated (Castro, et al, 2010).…”

“…−log10{(T(ν)} since the absorbance is a linear function of the concentration of the species absorbing, thus rendering it more amenable to use of chemometrics routines of analysis. For the current application: OP/FTIR detection of solid threat chemicals deposited on surfaces as traces, representation as the spectral difference between the sample spectrum and the background spectrum is even more critical due to the possibility of specular reflectance and scattering from the sample (Castro, et al, 2010). Multivariate calibrations make use of not only a single spectral point but take into account spectral features over a wide range.…”

Artificial Intelligence Assisted Mid-Infrared Laser Spectroscopy In Situ Detection of Petroleum in Soils

“…This is affected if the analysis is carried out in a remote sensing modality [34,35]. A quadratic decrease in the signal with distance and angular dependence is experienced [33,36,37]. A QCL emits a markedly more significant number of photons per unit wavelength in comparison to a globar source.…”

“…On the other hand, traditional multivariate analysis (MVA) pattern recognition methods such as principal component analysis (PCA) and partial least squares coupled to discriminant analysis (PLS-DA), are used in conjunction with spectroscopic methods and are widely reported in the literature [33,37,49,50]. PCA is a non-supervised MVA statistical technique.…”

“…This implies that in the optimum separation into classes, Class A should be on one side of the threshold and Class B on the other side of it. In the case where the predictions provide no clear distinction between the classes, the number of false positives increases and the model is not suitable for discrimination [33,37,49,50].…”