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We presented the first demonstration of stand-off Fourier transform infrared (FTIR) spectroscopy using a broadband mid-infrared optical parametric oscillator, with spectral coverage over 2700-3200  cm⁻¹. For vapor-phase water and nitromethane (NM), stand-off spectra was recorded using a concrete target at from 1-m to 2-m range and showed good agreement with reference spectra, and in NM a normalized detection sensitivity of 15  ppm·m·Hz(-1/2) was obtained. Spectra from 50-μL droplets of liquid thiodiglycol were detected at a stand-off distance of 2 m from aluminum, concrete and painted metal surfaces. Our results imply that OPO-based active FTIR stand-off spectroscopy is a promising new technique for the detection of industrial pollutants and the identification of chemical agents, explosives or other hazardous materials.

Raman spectroscopy is a well-established spectroscopic method for the detection of condensed phase chemicals. It is based on scattered light from exposure of a target material to a narrowband laser beam. The information generated enables presumptive identification from measuring correlation with library spectra. Whilst this approach is successful in identification of chemical information of samples with one component, it is more difficult to apply to spectral mixtures. The capability of handling spectral mixtures is crucial for defence and security applications as hazardous materials may be present as mixtures due to the presence of degradation, interferents or precursors. A novel method for spectral unmixing is proposed here. Most modern decomposition techniques are based on the sparse decomposition of mixture and the application of extra constraints to preserve the sum of concentrations. These methods have often been proposed for passive spectroscopy, where spectral baseline correction is not required. Most successful methods are computationally expensive, e.g. convex optimisation and Bayesian approaches.We present a novel low complexity sparsity based method to decompose the spectra using a reference library of spectra. It can be implemented on a hand-held spectrometer in near to real-time. The algorithm is based on iteratively subtracting the contribution of selected spectra and updating the contribution of each spectrum. The core algorithm is called fast non-negative orthogonal matching pursuit, which has been proposed by the authors in the context of nonnegative sparse representations. The iteration terminates when the maximum number of expected chemicals has been found or the residual spectrum has a negligible energy, i.e. in the order of the noise level. A backtracking step removes the least contributing spectrum from the list of detected chemicals and reports it as an alternative component. This feature is particularly useful in detection of chemicals with small contributions, which are normally not detected. The proposed algorithm is easily reconfigurable to include new library entries and optional preferential threat searches in the presence of predetermined threat indicators.Under Ministry of Defence funding, we have demonstrated the algorithm for fingerprinting and rough quantification of the concentration of chemical mixtures using a set of reference spectral mixtures. In our experiments, the algorithm successfully managed to detect the chemicals with concentrations below 10 percent. The running time of the algorithm is in the order of one second, using a single core of a desktop computer.

This article presents new spectroscopic results in standoff chemical detection that are enabled by monolithic arrays of Distributed Feedback (DFB) Quantum Cascade Lasers (QCLs), with each array element at a slightly different wavelength than its neighbor. The standoff analysis of analyte/substrate pairs requires a laser source with characteristics offered uniquely by a QCL Array. This is particularly true for time-evolving liquid chemical warfare agent (CWA) analysis. In addition to describing the QCL array source developed for long wave infrared coverage, a description of an integrated prototype standoff detection system is provided. Experimental standoff detection results using the man-portable system for droplet examination from 1.3 meters are presented using the CWAs VX and T-mustard as test cases. Finally, we consider three significant challenges to working with droplets and liquid films in standoff spectroscopy: substrate uptake of the analyte, time-dependent droplet spread of the analyte, and variable substrate contributions to retrieved signals.

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