Modulated-laser source induction system for remote detection of infrared emissions of high explosives using laser-induced thermal emission

In a homeland security setting, the ability to detect explosives at a distance is a top security priority. Consequently, the development of remote, noncontact detection systems continues to represent a path forward. In this vein, a remote detection system for excitation of infrared emissions using a CO2 laser for generating laser-induced thermal emission (LITE) is a possible solution. However, a LITE system using a CO2 laser has certain limitations, such as the requirement of careful alignment, interference by the CO2 signal during detection, and the power density loss due to the increase of the laser image at the sample plane with the detection distance. A remote chopped-laser induction system for LITE detection using a CO2 laser source coupled to a focusing telescope was built to solve some of these limitations. Samples of fixed surface concentration (500 μg∕cm2) of 1,3,5-trinitroperhydro-1,3,5-triazine (RDX) were used for the remote detection experiments at distances ranging between 4 and 8 m. This system was capable of thermally exciting and capturing the thermal emissions (TEs) at different times in a cyclic manner by a Fourier transform infrared (FTIR) spectrometer coupled to a gold-coated reflection optics telescope (FTIR-GT). This was done using a wheel blocking the capture of TE by the FTIR-GT chopper while heating the sample with the CO2 laser. As the wheel moved, it blocked the CO2 laser and allowed the spectroscopic system to capture the TEs of RDX. Different periods (or frequencies) of wheel spin and FTIR-GT integration times were evaluated to find dependence with observation distance of the maximum intensity detection, minimum signal-to-noise ratio, CO2 laser spot size increase, and the induced temperature incremen

Artificial intelligence assisted Mid-infrared laser spectroscopy in situ detection of petroleum in soils

A simple, remote-sensed method of detection of traces of petroleum in soil combining artificial intelligence (AI) with mid-infrared (MIR) laser spectroscopy is presented. A portable MIR quantum cascade laser (QCL) was used as an excitation source, making the technique amenable to field applications. The MIR spectral region is more informative and useful than the near IR region for the detection of pollutants in soil. Remote sensing, coupled with a support vector machine (SVM) algorithm, was used to accurately identify the presence/absence of traces of petroleum in soil mixtures. Chemometrics tools such as principal component analysis (PCA), partial least square-discriminant analysis (PLS-DA), and SVM demonstrated the e ectiveness of rapidly di erentiating between di erent soil types and detecting the presence of petroleum traces in di erent soil matrices such as sea sand, red soil, and brown soil. Comparisons between results of PLS-DA and SVM were based on sensitivity, selectivity, and areas under receiver-operator curves (ROC). An innovative statistical analysis method of calculating limits of detection (LOD) and limits of decision (LD) from fits of the probability of detection was developed. Results for QCL/PLS-DA models achieved LOD and LD of 0.2% and 0.01% for petroleum/soil, respectively. The superior performance of QCL/SVM models improved these values to 0.04% and 0.003%, respectively, providing better identification probability of soils contaminated with petroleum

Mid-Infrared Laser Spectroscopy Applications I: Detection of Traces of High Explosives on Reflective and Matte Substrates

Mid-infrared (MIR) lasers have revolutionized infrared vibrational spectroscopy, converting an already dominant spectroscopic analysis technique into an even more powerful, easier to use, and quicker turn-around cadre of versatile spectroscopic tools. A selection of applications, revisited under the umbrella of MIR laser-based properties, very high brightness, collimated beams, polarized sources, highly monochromatic tunable sources, and coherent sources, is included. Applications discussed concern enhanced detection, discrimination, and quantification of high explosives (HEs). From reflectance measurements of chemical residues on highly reflective metallic substrates to reflectance measurements of HEs deposited on non-reflective, matte substrates is discussed. Coupling with multivariate analyses (MVA) techniques of Chemometrics allowed near trace detection of HEs, with sharp discrimination from highly MIR absorbing substrates

Mid-Infrared laser spectroscopy detection and quantification of explosives in soils using multivariate analysis and artificial intelligence

A tunable quantum cascade laser (QCL) spectrometer was used to develop methods for detecting and quantifying high explosives (HE) in soil based on multivariate analysis (MVA) and artificial intelligence (AI). For quantification, mixes of 2,4-dinitrotoluene (DNT) of concentrations from 0% to 20% w/w with soil samples were investigated. Three types of soils, bentonite, synthetic soil, and natural soil, were used. A partial least squares (PLS) regression model was generated for predicting DNT concentrations. To increase the selectivity, the model was trained and evaluated using additional analytes as interferences, including other HEs such as pentaerythritol tetranitrate (PETN), trinitrotoluene (TNT), cyclotrimethylenetrinitramine (RDX), and non-explosives such as benzoic acid and ibuprofen. For the detection experiments, mixes of different explosives with soils were used to implement two AI strategies. In the first strategy, the spectra of the samples were compared with spectra of soils stored in a database to identify the most similar soils based on QCL spectroscopy. Next, a preprocessing based on classical least squares (Pre-CLS) was applied to the spectra of soils selected from the database. The parameter obtained based on the sum of the weights of Pre-CLS was used to generate a simple binary discrimination model for distinguishing between contaminated and uncontaminated soils, achieving an accuracy of 0.877. In the second AI strategy, the same parameter was added to a principal component matrix obtained from spectral data of samples and used to generate multi-classification models based on different machine learning algorithms. A random forest model worked best with 0.996 accuracy and allowing to distinguish between soils contaminated with DNT, TNT, or RDX and uncontaminated soils

Mid-Infrared Laser Spectroscopy Applications in Process Analytical Technology: Cleaning Validation, Microorganisms, and Active Pharmaceutical Ingredients in Formulations

Mid-infrared (MIR) lasers are very high-brightness energy sources that are replacing conventional thermal sources (globars) in many infrared spectroscopy (IRS) techniques. Although not all laser properties have been exploited in depth, properties such as collimation, polarization, high brightness, and very high resolution have contributed to recast IRS tools. Applications of MIR laser spectroscopy to process analytical technology (PAT) are numerous and important. As an example, a compact grazing angle probe mount has allowed coupling to a MIR quantum cascade laser (QCL), enabling reflectance-absorbance infrared spectroscopy (RAIRS) measurements. This methodology, coupled to powerful multivariable analysis (MVA) routines of chemometrics and fast Fourier transform (FFT) preprocessing of the data resulted in very low limits of detection of active pharmaceutical ingredients (APIs) and high explosives (HEs) reaching trace levels. This methodology can be used to measure concentrations of surface contaminants for validation of cleanliness of pharmaceutical and biotechnology processing batch reactors and other manufacturing vessels. Another application discussed concerns the enhanced detection of microorganisms that can be encountered in pharmaceutical and biotechnology plants as contaminants and that could also be used as weapons of mass destruction in biological warfare. In the last application discussed, the concentration of APIs in formulations was determined by MIR laser spectroscopy and was cross validated with high-performance liquid chromatography

Recognition of 2,4-DNT, RDX and TATP in various matrices by FTIR-partial least squares - discriminant analysis and kinetics of surface sublimation

A methodology useful for processing spectroscopic information using pattern recognition was designed, developed and implemented in detection of energetic materials at trace level in air, sand and surfaces. Partial Least Squares-1 (PLS) was used to generate vectors to be used with pattern recognition. These vectors were then coupled to Discriminant Analysis by adjusting to a discriminating function. Fourier Transform Infrared (FTIR) spectra of traces of 2,4-dinitro-toluene (2,4-DNT) in air, triacetone triperoxide (TATP) in air and air free of those explosives were recorded and used for generated the vectors. Short wave infrared (Near IR) and Long wave infrared (Mid IR) regions were studied and used for the model. Two vectors were necessary for good discrimination for TATP and four vectors for 2,4-DNT; but, when the regions were weighted from the response of detector, the model was improved and less vectors were needed for all discrimination in the prediction of new samples. Traces of 2,2,4,4,6,6-hexa-hydro-1,3,5-trinitro-1,3,5-triazine (RDX) in sand were detected for microscopy FT-IR. By means of the methodologies PLS and Discriminant analysis, we are found that spectra infrared of the sand can be affected by the presence of traces of RDX. The traces of RDX is created perturbation or patter in the spectra of sand, and this patter is utilized for the detection of RDX. In addition, the kinetics of surface sublimation for 4 explosives was studied. For TATP two minutes were necessary for the half of the explosive on the surface be to transported to air. For 2,4-DNT one hour were necessary. RDX and TNT was not good candidate for detection in gas phase, specially RDX, because its half life is very long, approximately 2 years.Una metodología útil para procesar la información espectroscópica es mediante reconocimiento de patrón, esta fue diseñada, desarrollada y puesta en ejecución en la detección de materiales explosivos a niveles de trazas en aire, arena y superficies. Mínimos cuadrados parciales fue utilizado para generar los vectores que se utilizarán en el reconocimiento de patrones. Estos vectores entonces fueron utilizados en para un análisis discriminante y con ellos se hallaron una función discriminatoria. Espectros de (FTIR) de trazas de 2,4- dinitro-tolueno (2,4-DNT) en aire, Triacetona triperoxido (TATP) en el aire y de aire libres de esos explosivo fueron registrados y utilizado para generar los vectores. Las regiones infrarrojas de onda corta (cercano de IR) y de onda larga (IR medio) fueron estudiadas y utilizadas para el modelo. Dos vectores eran necesarios para la buena discriminación para TATP y cuatro vectores para 2,4-DNT; pero, cuando las regiones fueron ponderadas de la respuesta del detector, el modelo fue mejorado y menos vectores eran necesarios para toda la discriminación in la predicción de nuevas muestras. Trazas de 2,2,4,4,6,6-hexa-hidro-1,3,5-trinitro-1,3,5-triazina (RDX) en arena fueron detectadas por microscopia FT-IR. Por medio de las metodologías PLS y análisis discriminante, los espectros de infrarrojo arena son afectados por la presencia de trazas de RDX, las trazas de RDX producen perturbación en el espectro de arena, y esta perturbación se utiliza para la detección de RDX. También se estudio la cinética de la sublimación superficial 4 explosivos. En TATP en dos que el minuto es necesario para que la mitad del explosivo en el superficial pase al ventilar al aire. Para 2,4-DNT una hora es necesaria. RDX y TNT no son buenos candidato a la detección en fase de gaseosa, en especial RDX, porque su media vida es muy larga, aproximadamente 2 años.Grant from Center for Pharmaceutical Processing Research (CPPR), Collaboration with the Center for Chemical Sensors Development of the University of Puerto Rico–Mayagüez sponsored by the Department of Defense, University Research Initiative–Multidisciplinary University Research Initiative (URI–MURI) Program, under grant no. DAAD19–02–1–0257.200

Laser-Induced growth of nanoparticles and nanostructures

The preparation of nanostructures assisted by laser action was studied and successfully accomplished from solution and on surfaces. The synthesized nanostructures were characterized by several microscopy techniques. Silver, gold, copper and platinum nanoparticles were grown on surfaces in the form of patterns by the exposure of laser radiation onto droplets of metal ion solutions and the aid of a reducing agent. The generation of patterns from metallic nanoparticles (NPs) was achieved by combining induced growth of nanoparticles and nanostructures by laser incidence directly on surfaces (LIDS) and optical image formation techniques for transferring the patterns. Near-ultraviolet (363.8 nm) and visible (532 nm) laser wavelengths were used for the laser induced growth of NPs into microstructures on glass, quartz, stainless steel, silicon and gold-on-silicon substrates. The sizes of the patterns formed were on the micrometer scale and the sizes of the transferred patterns were on the millimeter scale. The patterns formed were generated by optical transference of image and interference of laser beams. Ag and Au substrates were highly active in surface enhanced Raman spectroscopy (SERS). The enhanced Raman activity was measured for SERS probe molecules: 9H-purin-6-amine (adenine) and 1,2-bis(4-pyridyl)-ethane (BPE) analytes on Ag and Au substrates, respectively. The enhancement factor obtained were 1.8×105 and 6.2×106 respectively. The growth Ag nanoparticles in solution and their conversion to nanoprisms induced by laser radiation action were studied and the kinetics of growth and conversion processes was measured. A mechanism for the growth and conversion from nanoparticle seeds to nanostructures consisting of two processes was proposed. The kinetics for the two processes was measured and the dependence of rate of growth and conversion with laser power was obtained. The quantum efficiency for the processes was also measured. The first process consisting of agglomeration was found to depend on the probability of excitation of plasmon the initial nanoparticles (seeds). This first process is necessary for the second process (growth process) to occur and controls it in an indirect way. Nucleation and crystallization of nanoprisms and the growth of crystal are produced by the NP excited by light. The size of the crystals obtained is controlled by the wavelength of the incident light in the second process. The growth begins by an agglomeration process followed by fusion of the nanoparticles to produce small crystals and finally the growth of relatively large crystals. SERS activity was measured for three different analytes, several types of nanoprisms and various Raman excitation lines. Enhanced Raman activity was measured for nanoprisms in aqueous suspensions and on surfaces. The activity SERS for the nanoprisms is better when those are on substrate surfaces. It is possible have a considerable repeatability when a gold surface is treated with a solution of S2− anions.La preparación de nanoestructuras asistida por acción de láseres se estudió y fue exitosamente llevada a cabo en solución y sobre superficies. Las nanoestructuras sintetizadas fueron caracterizadas fue realizada por varias técnicas de microscopía. Nanopartículas de plata, oro, cobre y platino fueron sintetizadas sobre superficies por exposición de la radiación láser sobre una gotita de solución de iones metálicos y un agente reductor. Laser of ultravioleta cercano (363.8 nm) y visible (532 nm) se utilizaron para el crecimiento inducido de las nanopartículas sobre vidrio, cuarzo, acero inoxidable y sobre silicio cubierto de oro. Los tamaños de los patrones formados fueron de escala de micrómetros y los tamaños de los patrones transferidos eran en la escala de milímetros. El tamaño de los patrones obtenidos está limitado por la longitud de onda de la luz, el tamaño del objeto que acta como la imagen del patrón para generar la imagen transferida y el diseño de ópticas empleadas. La falta de nitidez cuando la imagen del patrón es ópticamente transferido está limitada por la configuración óptica debido a que el proceso de deposición es al azar en el sitio irradiado. Un efecto de penumbra también puede inducir el crecimiento de nanopartículas en los alrededores de la imagen, disminuyendo la nitidez de la imagen en las fronteras. Los super-substratos de Ag y Au fueron activos para espectroscopia Raman aumentada sobre ficie. La actividad fue medida para 9H-purina-6 amina (adenina) y 1,2-bis(4-piridil)-etano (BPE) como analitos sobre los substratos de Ag y Au respectivamente. El factor de au- mento fue 1.8x103 y 6.2x 108 respectivamente. El crecimiento de nanopartículas de Ag en solución y su conversión a nanoprismas inducidos por acción de radiación láser se estudió y la cinética de los procesos de crecimiento y conversión se midió. Un mecanismo para el crecimiento y conversión de semillas de nanopartículas a nanoestructuras se propuso. La cinética de los dos procesos se midió y la dependencia de la rapidez de crecimiento con la potencia del láser se obtuvo. La eficiencia cuántica para los procesos también se midió. El primer proceso consistente de aglomeración se encontró que tiene una dependencia en la babilidad de la excitación de las oscilaciones colectivas de electrones de en la banda de pro conducción del metal o plasmón de las nanopartículas iniciales (semillas) utilizadas para el crecimiento inducido por radiación láser. Este primer proceso es necesario para que se de paso al segundo proceso (de conversión) y controla el mismo en forma indirecta. La nucleación y cristalización de nanoprismas y el crecimiento cristalino se producen mediante la excitación de las nanopartículas por luz. El tamaño de los cristales obtenidos se controla con la longitud de onda de la luz incidente en el segundo proceso. El crecimiento comienza con un proceso de aglomeración seguido por la fusión de nanopartículas para producir pequeños cristales y finalmente crecimiento de cristales relativamente grandes. Act ividad SERS se midió para tres analitos diferentes, varios tipos de nanoprimas y varias longitudes de onda de excitación Raman. Actividad Raman realzada por superficies se midió para nanoprismas en suspensiones acuosas y en superficies de sustratos. La actividad SERS de los nanoprismas fue mayor cuando las nanoestructuras se depositaron sobre superficies y se enlazaron fuertemente al sustrato de oro. Se demostró que es posible conseguir buena reproducibilidad cuando se utiliza una superficie de oro tratada con una solución de aniones S2-.U.S. Department of Defense, University Research Initiative Multidisciplinary University Research Initiative (URI)-MURI Program, U.S. Department of Homeland SecuritySpring201