Colón Mercado, Annette Mariel

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    Quantum cascade laser-grazing angle spectroscopy detection of high explosives deposited on various substrates using air spray
    (2020-04-19) Colón Mercado, Annette Mariel; Hernández Rivera, Samuel P.; College of Arts and Sciences - Sciences; Mina, Nairmen; Torres Candelaria, Jessica; Department of Chemistry; Hernández Maldonado, Arturo J.
    The mid-infrared (MIR) laser reflectance of samples of high explosives (HEs) deposited on reflective and matte substrates using spray deposition was measured and used to generate multivariate (MVA) models for the analysis of the accurate detection and classification. A quantum cascade laser (QCL) was optically coupled to a grazing angle probe mount (QCL-GAP) to operate in reflectance mode at an incidence angle of 82 from the surface normal. The experimental conditions enabled reflection-absorption IR spectroscopy (RAIRS) of the HE/substrates. The optical arrangement allowed to obtain spectra with high signal to noise (S/N) ratios, therefore allowing the signals of the HE to be detectable even at low surface concentrations. Reflective substrate: stainless steel (SS) and partially reflective substrates: roughened aluminum (Al) and Teflon, were sprayed with HE solutions for the creation of real-world samples. The HE used for the spray deposition was pentaerythritol tetranitrate (PETN). These samples were compared to inkjet standards containing: 1,3,5-trinitroperhydro-1,3,5-triazine (RDX), and 2,4,6-trinitrophenylmethylnitramine (Tetryl). Samples were successfully classified into the classes of Al substrates and the highly interfering MIR signals from acrylonitrile butadiene styrene (ABS) substrates. Loadings plots were constructed based on the information obtained from the PCA models for each substrate, allowing us to understand the variation that contributed to the separation of the HEs by classes. Soft independent modeling by class analysis (SIMCA) was used to predict the HEs vs. PETN deposited using a spray. The results predicted a percentage of 91.7% for Teflon, 100% for Al, and 87.5% for SS. The results presented are expected to simplify the detection of hazardous chemicals and other threats to environmental, defense, and national security applications.