This PDF file contains the front matter associated with SPIE Proceedings Volume 8710, including the Title Page, Copyright information, Table of Contents, Introduction, and the Conference Committee listing.

The ability of a stand-off chemical detector to distinguish two different chemical warfare agents is demonstrated in this paper. Using Negative Contrast Imaging, based upon IR absorption spectroscopy, we were able to detect 1 μl of VX, sulfur mustard and water on a subset of representative surfaces. These experiments were performed at a range of 1.3 metres and an angle of 45° to the surface. The technique employed utilises a Q-switched intracavity MgO:PPLN crystal that generated 1.4 – 1.8 μm (shortwave) and 2.6 – 3.6 μm (midwave) infrared radiation (SWIR and MWIR, respectively). The MgO:PPLN crystal has a fanned grating design which, via translation through a 1064 nm pump beam, enables tuning through the SWIR and MWIR wavelength ranges. The SWIR and MWIR beams are guided across a scene via a pair of raster scanned mirrors allowing detection of absorption features within these spectral regions. This investigation exploited MWIR signatures, as they provided sufficient molecular information to distinguish between toxic and benign chemicals in these proof-of-concept experiments.

Standoff detection and identification (D and Id) of unknown volatile chemicals such as chemical pollutants and consequences of industrial incidents has been increasingly desired for first responders and for environmental monitoring. On site gas detection sensors are commercially available and several of them can even detect more than one chemical species, however only few of them have the capabilities of detecting a wide variety of gases at long and safe distances.

The ABB Hyperspectral Imaging Spectroradiometer (MR-i), configured for gas detection detects and identifies a wide variety of chemical species including toxic industrial chemicals (TICs) and surrogates several kilometers away from the sensor. This configuration is called iCATSI for improved Compact Atmospheric Sounding Interferometer. iCATSI is a standoff passive system.

The modularity of the MR-i platform allows optimization of the detection configuration with a 256 x 256 Focal Plane Array imager or a line scanning imager both covering the long wave IR atmospheric window up to 14 μm. The uniqueness of its extended LWIR cut off enables to detect more chemicals as well as provide higher probability of detection than usual LWIR sensors.

Stand-off identification of potentially hazardous liquid surface contaminations and the visualisation of the contaminated area enable first responders to rapidly assess emergency situations. Hyperspectral imaging allows the detection and mapping of a huge variety of liquid compounds in real time even without the active illumination of the sample. The approach that is presented in this study uses the contrast of the brightness temperature of the investigated sample and of the surrounding hemisphere. The liquid compounds are identified by the comparison of the reflection spectrum that is measured and synthetic reflection spectra for various liquid compounds. These synthetic in-situ spectra are calculated using the optical properties of the various target compounds that are stored in a library and data characterizing the measurement conditions. That is the spectrum of the radiation incident to the investigated sample and the reflection spectrum of the uncontaminated background surface, both of which are acquired along with the measurement. In this work passive measurements of liquid surface contaminations are presented. The comparison to modelled spectra proves the feasibility of passive stand-off detection and mapping of liquid compounds.

We have recently constructed and tested a gas cloud imager which demonstrates the rst-ever video-rate detection (15 frames/sec) of gas leaks using an uncooled LWIR detector array. Laboratory and outdoor measurements, taken in collaboration with BP Products North America Inc. and IES Inc., show detection sensitivities comparable to existing cooled systems for detecting hydrocarbon gases. Gases imaged for these experiments include methane, propane, propylene, ethane, ethylene, butane, and iso-butylene, but any gases with absorption features in the LWIR band could potentially be detected, such as sarin and other toxic gases. These results show that practical continuous monitoring of gas leaks with uncooled imaging sensors is now possible.

Two AIRIS sensors were tested at Dugway Proving Grounds against chemical agent vapor simulants. The primary objectives of the test were to: 1) assess performance of algorithm improvements designed to reduce false alarm rates with a special emphasis on solar effects, and 3) evaluate performance in target detection at 5 km.

The tests included 66 total releases comprising alternating 120 kg glacial acetic acid (GAA) and 60 kg triethyl phosphate (TEP) events. The AIRIS sensors had common algorithms, detection thresholds, and sensor parameters. The sensors used the target set defined for the Joint Service Lightweight Chemical Agent Detector (JSLSCAD) with TEP substituted for GA and GAA substituted for VX. They were exercised at two sites located at either 3 km or 5 km from the release point.

Data from the tests will be presented showing that: 1) excellent detection capability was obtained at both ranges with significantly shorter alarm times at 5 km, 2) inter-sensor comparison revealed very comparable performance, 3) false alarm rates < 1 incident per 10 hours running time over 143 hours of sensor operations were achieved, 4) algorithm improvements eliminated both solar and cloud false alarms. The algorithms enabling the improved false alarm rejection will be discussed.

The sensor technology has recently been extended to address the problem of detection of liquid and solid chemical agents and toxic industrial chemical on surfaces. The phenomenology and applicability of passive infrared hyperspectral imaging to this problem will be discussed and demonstrated.

This work relates to standoff detection of nerve agent simulant using mid-infrared quantum cascade lasers (QCL) and photoacoustic technique. In our experiment, a mid-IR QCL with an emission wavelength near ~7.35 μm was operated under pulsed conditions. Gas phase nerve agent simulant was generated and calibrated using a vapor generator. The QCL output beam with average output power ~150 mW was focused on the gaseous sample in open-air environment. Photoacoustic signals were generated and detected by an ultra-sensitive microphone. With the help of a parabolic sound reflector, standoff detection of gas samples with calibrated concentration of 2.3 ppm was achieved at a detection distance of more than 2 feet. An extended detection distance up to 14 feet was observed for a higher gas concentration of 13.9 ppm.

All the manufacturers of stand-off CWA detectors communicate on the “same” characteristics. And one can find these parameters in the comparison table published between all the different products [1].

These characteristics are for example the maximum detection range, the number of different detectable compounds, the weight, the price, etc…

All these parameters are good to compare products between them, but they omit one very important point: the reaction time in case of an unexpected incoming chemical threat, in the case of the surveillance application.

To answer this important question, we imagine a new parameter: the Field Surface Scanning Rate (FSSR). This value is a classical parameter in astronomical survey, use by astronomers to compare the performance of different telescopes, they compute the quantity of sky (in sky square degrees) analyzed per unit of time by the system.

In this paper we will compare this new figure-of-merit, the FSSR, of some commercially off the shelf stand-off detector. The comparison between classical FTIR system and gas imaging system in term of FSSR will be presented.

Standoff chemical sensing using QCL and photoacoustic techniques recently have been demonstrated at a distance of more than 40 feet. [1]. To operate such a system outdoor, the system needs to be capable of rejecting other acoustic sources in the field. In this work, we experimentally compare two different implementations of acoustic beam forming array systems. One structure uses 4 microphones placing at the 4 foci of 4 parabolic reflectors. The other structure uses an array of 16 (4x4) microphones placing at the focal point of one parabolic reflector. Two acoustic sources were used to represent the signal (at 3kHz) and noise (at 4kHz). By adjusting delays to make sure signals from each phone were added in phase, we can enhance the signal and at the same time suppress the noise source.

The measured results are processed in Fourier domain. The signal and noise spectra of the 4 microphone/4 reflector have a combined SNR of 11.48 dB, while the results of 16-microphones/1-reflector have a combined SNR of 17.82 dB. The worse SNR result of the 4-phone/4-reflector system may not simply due to the other system has more microphones. It also because of the average effect of the full reflector area, which can blur the phase of each element and the noise, cannot be cancelled more exactly.

An engineering thermodynamic approach to the plasma description associated with Laser Induced Breakdown Spectroscopy (LIBS) has been previously published. In the prior work, a non-traditional modeling approach was made to reduce the modeling system to a configuration compatible with incorporation into a TI6701. This modeling technique was necessitated by the extreme limitations that portability and robustness place on the physical size and power consumption of the computer for data processing and classification. The new modeling approach was previously reported. This presentation reports on the finalization of this and the validation of the result through comparison to more established models such as detailed balance, via the solution to a system of Boltzmann Equations. The emphasis is on the engineering modeling and its’ system implications - not a physics tutorial. Implications of the modeling approximations for the accuracy and repeatability of the complete sensor system will be presented. Possible utilization of newer, larger scale processors and the impact that would have on the model and associate sensor performance is addressed.

The standoff detection and discrimination of aerosolized biological and chemical agents has traditionally been addressed through LIDAR approaches, but sensor systems using these methods have yet to be deployed. We discuss the development and testing of an approach to detect these aerosols using the deployed base of passive infrared hyperspectral sensors used for chemical vapor detection.

The detection of aerosols requires the inclusion of down welling sky and up welling ground radiation in the description of the radiative transfer process. The wavelength and size dependent ratio of absorption to scattering provides much of the discrimination capability. The approach to the detection of aerosols utilizes much of the same phenomenology employed in vapor detection; however, the sensor system must acquire information on non-line-of-sight sources of radiation contributing to the scattering process.

We describe the general methodology developed to detect chemical or biological aerosols, including justifications for the simplifying assumptions that enable the development of a real-time sensor system. Mie scattering calculations, aerosol size distribution dependence, and the angular dependence of the scattering on the aerosol signature will be discussed.

This methodology will then be applied to two test cases: the ground level release of a biological aerosol (BG) and a nonbiological confuser (kaolin clay) as well as the debris field resulting from the intercept of a cruise missile carrying a thickened VX warhead. A field measurement, conducted at the Utah Test and Training Range will be used to illustrate the issues associated with the use of the method.

Reliable, robust, and portable technologies are needed for the rapid identification and detection of chemical, biological, and explosive (CBE) materials. A key to addressing the persistent threat to U.S. troops in the current war on terror is the rapid detection and identification of the precursor materials used in development of improvised explosive devices, homemade explosives, and bio-warfare agents. However, a universal methodology for detection and prevention of CBE materials in the use of these devices has proven difficult. Herein, we discuss our efforts towards the development of a modular, robust, inexpensive, pervasive, archival, and compact platform (android based smart phone) enabling the rapid detection of these materials.

We report the application of paper SERS substrates for the detection of trace quantities of multiple analytes in a complex sample in the form of paper chromatography. Paper chromatography facilitates the separation of different analytes from a complex sample into distinct sections in the chromatogram, which can then be uniquely identified using SERS. As an example, the separation and quantitative detection of heroin in a highly fluorescent mixture is demonstrated. Paper SERS chromatography has obvious applications, including law enforcement, food safety, and border protection, and facilitates the rapid detection of chemical and biological threats at the point of sample.

Governments often tax fuel products to generate revenues to support and stimulate their economies. They also subsidize the cost of essential fuel products. Fuel taxation and subsidization practices are both subject to fraud. Oil marketing companies also suffer from fuel fraud with loss of legitimate sales and additional quality and liability issues. The use of an advanced marking system to identify and control fraud has been shown to be effective in controlling illegal activity. DeCipher has developed surface enhanced Raman scattering (SERS) spectroscopy as its lead technology for measuring markers in fuel to identify and control malpractice. SERS has many advantages that make it highly suitable for this purpose. The SERS instruments are portable and can be used to monitor fuel at any point in the supply chain. SERS shows high specificity for the marker, with no false positives. Multiple markers can also be detected in a single SERS analysis allowing, for example, specific regional monitoring of fuel. The SERS analysis from fuel is also quick, clear and decisive, with a measurement time of less than 5 minutes. We will present results highlighting our development of the use of a highly stable silver colloid as a SERS substrate to measure the markers at ppb levels. Preliminary results from the use of a solid state SERS substrate to measure fuel markers will also be presented.

Sarin, a well-known chemical warfare agent, is toxic for concentrations as low as 0.03 ppm in the air (Immediately Dangerous to Life or Health value). A technology providing “on the field” detection could be fluorescence spectroscopy. This presentation shows a sensitive method for the detection of Diethyl Chlorophosphate (DCP), a Sarin surrogate, which provides in a few seconds a turn-off fluorescence response of the sensor for ppb levels of DCP. For instance, a I/I₀ = 0.68 (fluorescence quenching) was obtained when the sensor was exposed to 16 ppb of DCP.

In this work we demonstrate imaging standoff detection of solid traces of explosives using infrared laser backscattering spectroscopy. Our system relies on active laser illumination in the 7 μm-10 μm spectral range at fully eye-safe power levels. This spectral region comprises many characteristic absorption features of common explosives, and the atmospheric transmission is sufficiently high for stand-off detection. The key component of our system is an external cavity quantum cascade laser with a tuning range of 300 cm^-1 that enables us to scan the illumination wavelength over several of the characteristic spectral features of a large number of different explosives using a single source. We employ advanced hyperspectral image analysis to obtain fully automated detection and identification of the target substances even on substrates that interfere with the fingerprint spectrum of the explosive to be detected due to their own wavelength-dependent scattering contributions to the measured backscattering spectrum. Only the pure target spectra of the explosives have to be provided to the detection routine that nevertheless accomplishes reliable background suppression without any a-priory-information about the substrate.

Polyisobutylene is an industrial polymer that is widely used in a number of applications including the manufacture of military grade explosives. We have examined the vapor emanating from a series of different molecular weight samples of polyisobutylene using high resolution Quantum Cascade Laser FM spectroscopy. The vapor phase spectra all exhibit a rovibrational structure similar to that for the gas phase isobutylene molecule. We have assigned the structure in the 890 cm^-1 and 1380 cm^-1 regions to the isobutylene ν₂₈ and ν₇ fundamental bands respectively. These spectroscopic signatures may prove useful for infrared sensing applications. Here we will present the infrared signatures along with recent GCMS data from a sample of C4, utilizing solid-phase microextraction vapor collection fibers, which confirm the presence of isobutylene as one of the volatile bouquet species in RDX-based explosives.

The detection and identification of hazardous material is required in a wide range of application environments including military and civilian. Infrared (IR) absorption spectroscopy is a technique that can be used for material identification through comparing absorption spectra with reference data from a spectral library. The absorption spectrum of a compound is the result of light at certain wavelengths being absorbed through molecular vibrations of the compound. To build on this phenomenon, hyperspectral imaging can be used to add spatial information of the absorber. In this case, the IR source output, an optical parametric oscillator (OPO) operating at 1.5 to 1.7 μm in the short wave IR (SWIR) and 2.7 to 3.6 μm in the mid wave IR (MWIR), is raster scanned using a galvanometric mirror pair across a scene of interest. The resulting backscattered light is de-scanned through the same mirror pair and focussed onto point detectors and images in the IR are generated. This hyperspectral imaging instrument is a prototype that is currently being developed for a wide range of applications. If an absorber is present and the OPO wavelength is tuned to an absorption feature of this absorber, this interaction will appear as a dark area in the generated image. With the broad tunability of the OPO, a detailed absorption spectrum of the target compound can be recorded and used to aid material identification. This work presents a selection of results where explosive simulants and materials were investigated and analysed using the prototype instrument.

Raman and Terahertz spectroscopy are both widely used for their ability to safely and remotely identify unknown materials. Each approach has its advantages and disadvantages. Traditional Raman spectroscopy typically measures molecular energy transitions in the 200-5000cm^-1 region corresponding to sub-molecular stretching or bending transitions, while Terahertz spectroscopy measures molecular energy transitions in the 1-200cm^-1 region (30GHz - 6THz) that correspond to low energy rotational modes or vibrational modes of the entire molecule.

Many difficult to detect explosives and other hazardous chemicals are known to have multiple relatively strong transitions in this “Terahertz” (<200cm^-1, <6THz) regime, suggesting this method as a powerful complementary approach for identification. However, THz signal generation is often expensive, many THz spectroscopy systems are limited to just a few THz range, and strong water absorption bands in this region can act to mask certain transitions if great care isn't taken during sample preparation. Alternatively, low-frequency or “THz-Raman” spectroscopy, which covers the ~5cm^-1 to 200cm^-1 (150GHz - 6 THz) regions and beyond, offers a powerful, compact and economical alternative to probe these low energy transitions.

We present results from a new approach for extending the range of Raman spectroscopy into the Terahertz regime using an ultra-narrow-band volume holographic grating (VHG) based notch filter system. An integrated, compact Raman system is demonstrated utilizing a single stage spectrometer to show both Stokes and anti-Stokes measurements down to <10cm^-1 on traditionally difficult to detect explosives, as well as other chemical and biological samples.

A mid-infrared intracavity laser absorption spectrometer based on an external cavity multi-mode quantum cascade laser is combined with a scanning Fabry-Perot interferometer is used as tunable narrow band transmission filter to analyze the laser emission spectrum. Sensitivity as a trace gas detector at 8.1 micron wavelengths has been demonstrated based on a weak water vapor line at an absorption coefficient of 1 x 10^-5 cm^-1. For molecules of reasonably strong absorption cross section (10-17 cm²), this corresponds to a detection limit of 40 ppb.

ChemImage has developed a SWIR Hyperspectral Imaging (HSI) sensor which uses hyperspectral imaging for wide area surveillance and standoff detection of surface residues. Existing detection technologies often require close proximity for sensing or detecting, endangering operators and costly equipment. Furthermore, most of the existing sensors do not support autonomous, real-time, mobile platform based detection of threats.

The SWIR HSI sensor provides real-time standoff detection of surface residues. The SWIR HSI sensor provides wide area surveillance and HSI capability enabled by liquid crystal tunable filter technology. Easy-to-use detection software with a simple, intuitive user interface produces automated alarms and real-time display of threat and type. The system has potential to be used for the detection of variety of threats including chemicals and illicit drug substances and allows for easy updates in the field for detection of new hazardous materials.

SWIR HSI technology could be used by law enforcement for standoff screening of suspicious locations and vehicles in pursuit of illegal labs or combat engineers to support route-clearance applications- ultimately to save the lives of soldiers and civilians.

In this paper, results from a SWIR HSI sensor, which include detection of various materials in bulk form, as well as residue amounts on vehicles, people and other surfaces, will be discussed.

Cavity Ring Down Spectroscopy (CRDS) has been identified as having significant potential for Department of Defense security and sensing applications. Significant factors in the development of new sensor architectures are portability, robustness and economy. A significant factor in new CRDS sensor architectures is cavity length. Prior publication has examined the role of cavity length in sensing modality both from the standpoint of the system’s design and the identification of potential difficulties presented by novel approaches. Two of interest here are new noise terms that have been designated turbulence-like and speckle-like in prior publication. In the prior publication the theoretical and some empirical data was presented. This presentation addresses the automation of the experimental apparatus, new data analysis, and implications regarding the significance of the two noise terms. This is accomplished through an Analog-to- Digital Conversion (ADC) from the output of a custom designed optical correlator. Details of the unique application of the developed instrument and implications for short cavity (portable) CRDS applications are presented.

Multiplex coherent anti-Stokes Raman spectroscopy (MCARS) is used to detect an explosive precursor material and two chemical warfare simulants. The spectral bandwidth of the femtosecond laser pulse used in these studies is sufficient to coherently and simultaneously drive all the vibrational modes in the molecule of interest. The research performed here demonstrates that MCARS has the capability to detect an explosive precursor (e.g., acetone) and hazardous materials, such as dimethyl methylphosphonate and 2-chloroethyl methyl sulfide (a sarin and a mustard gas chemical warfare simulant, respectively), with high specificity. Evidence shows that MCARS is capable of overcoming common the sensitivity limitations of spontaneous Raman scattering, thus allowing for the detection of the target material in milliseconds with standard USB spectrometers as opposed to seconds with intensified spectrometers. The exponential increase in the number of scattered photons suggests that the MCARS technique may be capable of overcoming range detection challenges common to spontaneous Raman scattering.

This paper describes how optical Kerr gating can be used for effective rejection of fluorescence from Raman spectra of explosives and explosives precursors. Several explosives are highly fluorescent, and this method enables Raman detection of explosives materials that would else be complicated or impossible to identify. Where electronic cameras (intensified charge-coupled devices, ICCDs) have showed not yet to be sufficiently fast to be used for rejection of this fluorescence, Kerr gating is here proved to be an efficient alternative, demonstrated by measurements on plastic explosives. Results were obtained using a gating time of ~30 ps. The Kerr gate was driven by the fundamental mode of an Nd:YAG laser, at 1064 nm, with pulses of ~8 mJ, 50 Hz and 30 ps. CS₂ was used as a Kerr medium and Glan polarizing prisms were important features of the system. Raman spectra were obtained using a 532 nm probe wavelength, from the same Nd:YAG laser being frequency doubled, with a ~2 mJ pulse energy. Gating times of ~30 ps were thus achieved, with a fluorescence rejection factor of more than 1300, for the first time revealing detailed characteristics in Raman spectra from highly fluorescent PETN based plastic explosive.

The spatial and temporal evolution of the CN molecular emission following laser ablation of a TNT analog (3- nitrobenzoic acid) has been studied along with ablation of targets that contain neither nitro groups nor C-N bonds. At a fluence of ~10⁴ J/cm², behavior indicative of the ablation of native CN bonds has been observed in samples containing no native CN bonds. The recorded data show significant plasma background emissions that pose difficulties for direct spectral imaging. Spatially resolved images suggest that some of the observed phenomena are simply the result of the interaction of the plasma and the observation volume of the collection optics.

Trace or residue explosives detection typically involves examining explosives found as solid particles on a solid substrate. Different optical spectroscopy techniques are being developed to detect these explosives in situ by probing how light interacts with the surface bound particles of explosives. In order to evaluate these technologies it is important to have available suitable test coupons coated with particles of explosives. When fabricating test coupons to evaluate detection performance or help train a detection algorithm, it is important to use realistic test coupons and consider how the physicochemical properties of the explosives particles, related chemicals, and substrate may affect the spectra produced or signal intensities observed. Specific features of interest include surface fill factor, particle sizes, areal density, degree of particle contact with a substrate and any other chemicals in addition to the explosives and substrate. This level of complexity highlights the need to fabricate test coupons which mimic “real world” particle coated surfaces. With respect to metrics derived from fingerprints, we compare the properties of test coupons fabricated by sieving and inkjetting for ammonium nitrate, TNT, RDX, and sucrose on stainless steel, automotive painted steel, glass and polyethylene substrates. Sieving provides a random distribution of particles, allows fractionation of relevant particle sizes and allows relevant surface fill factors to be achieved. Inkjetting provides precise control of aerial density but because of complications related to solvent-substrate interactions, relevant fill factors and particle sizes are difficult to achieve. In addition, we introduce a custom image analysis technique, NRL ParticleMath, developed to characterize and quantify particle loadings on test coupons.

Laser-induced breakdown spectroscopy (LIBS) is a powerful analytical technique to detect the elemental composition of solids, liquids, and gases in real time. For example, recent advances in UV-VIS LIBS have shown great promise for applications in chemical, biological, and explosive sensing. The extension of conventional UVVIS LIBS to the near-IR (NIR), mid-IR (MIR) and long wave infrared (LWIR) regions (~1-12 μm) offers the potential to provide additional information due to IR atomic and molecular signatures. In this work, a Q-switched Nd: YAG laser operating at 1064 nm was employed as the excitation source and focused onto several chlorate and nitrate compounds including KClO₃, NaClO₃, KNO₃, and NaNO₃ to produce intense plasma at the target surface. IR LIBS studies on background air, KCl , and NaCl were also included for comparison. All potassium and sodium containing samples revealed narrow-band, atomic-like emissions assigned to transitions of neutral alkali-metal atoms in accordance with the NIST atomic spectra database. In addition, first evidence of broad-band molecular LIBS signatures from chlorate and nitrate compounds were observed at ~10 μm and ~7.3 μm, respectively. The observed molecular emissions showed strong correlation with FTIR absorption spectra of the investigated materials.

The successful creation and operation of a neutron and X-ray combined computed tomography (NXCT) system has been demonstrated by researchers at the Missouri University of Science and Technology. The NXCT system has numerous applications in the field of material characterization and object identification in materials with a mixture of atomic numbers represented. Presently, the feasibility studies have been performed for explosive detection and homeland security applications, particularly in concealed material detection and determination of the light atomic number materials. These materials cannot be detected using traditional X-ray imaging. The new system has the capability to provide complete structural and compositional information due to the complementary nature of X-ray and neutron interactions with materials. The design of the NXCT system facilitates simultaneous and instantaneous imaging operation, promising enhanced detection capabilities of explosive materials, low atomic number materials and illicit materials for homeland security applications. In addition, a sample positioning system allowing the user to remotely and automatically manipulate the sample makes the system viable for commercial applications. Several explosives and weapon simulants have been imaged and the results are provided. The fusion algorithms which combine the data from the neutron and X-ray imaging produce superior images. This paper is a compete overview of the NXCT system for feasibility studies of explosive detection and homeland security applications. The design of the system, operation, algorithm development, and detection schemes are provided.

This is the first combined neutron and X-ray computed tomography system in operation. Furthermore, the method of fusing neutron and X-ray images together is a new approach which provides high contrast images of the desired object. The system could serve as a standardized tool in nondestructive testing of many applications, especially in explosives detection and homeland security research.

The combination or fusion of data from multiple complementary sensors can potentially improve system performance in many explosives and weapons detection applications. The motivations for fusion can include improved probability of detection; reduced false alarms; detection of an increased range of threats; higher throughput and better resilience to adversary countermeasures. This paper presents the conclusions of a study which surveyed a wide range of data fusion techniques and examples of the research, development and practical use of fusion in explosives detection. Different applications types such as aviation checkpoint, checked baggage and stand-off detection are compared and contrasted, and the degree to which sensors can be regarded as ‘orthogonal’ is explored. Whilst data fusion is frequently cited as an opportunity, there are fewer examples of its operational deployment. Blockers to the wider use of data fusion include the difficulty of predicting the performance gains that are likely to be achieved in practice, as well as a number of cost, commercial, integration, test and evaluation issues. The paper makes a number of recommendations for future research work.

Typical systems used for detection of Weapon of Mass Destruction (WMD) are based on sensing objects using gamma rays or neutrons. Nonetheless, depending on environmental conditions, current methods for detecting fissile materials have limited distance of effectiveness. Moreover, radiation related to gamma- rays can be easily shielded.

Here, detecting concealed WMD from a distance is simulated and studied based on radar, especially WideBand (WB) technology. The WB-based method capitalizes on the fact that electromagnetic waves penetrate through different materials at different rates. While low-frequency waves can pass through objects more easily, high-frequency waves have a higher rate of absorption by objects, making the object recognition easier. Measuring the penetration depth allows one to identify the sensed material.

During simulation, radar waves and propagation area including free space, and objects in the scene are modeled. In fact, each material is modeled as a layer with a certain thickness. At start of simulation, a modeled radar wave is radiated toward the layers. At the receiver side, based on the received signals from every layer, each layer can be identified. When an electromagnetic wave passes through an object, the wave’s power will be subject to a certain level of attenuation depending of the object’s characteristics. Simulation is performed using radar signals with different frequencies (ranges MHz-GHz) and powers to identify different layers.

Deep-ultraviolet resonance Raman spectroscopy (DUVRRS) is a promising approach to stand-off detection of explosive traces due to: 1) resonant enhancement of Raman cross-section, 2) λ^-4-cross-section enhancement, and 3) fluorescence and solar background free signatures. For trace detection, these signal enhancements more than offset the small penetration depth due to DUV absorption. A key challenge for stand-off sensors is to distinguish explosives, with high confidence, from a myriad of unknown background materials that may have interfering spectral peaks. To address this, we are developing a stand-off explosive sensor using DUVRRS with two simultaneous DUV excitation wavelengths. Due to complex interplay of resonant enhancement, self-absorption and laser penetration depth, significant amplitude variation is observed between corresponding Raman bands with different excitation wavelengths. These variations with excitation wavelength provide an orthogonal signature that complements the traditional Raman signature to improve specificity relative to single-excitation-wavelength techniques. As part of this effort, we are developing two novel CW DUV lasers, which have potential to be compact, and a compact dual-band high throughput DUV spectrometer, capable of simultaneous detection of Raman spectra in two spectral windows. We have also developed a highly sensitive algorithm for the detection of explosives under low signal-to-noise situations.

An infrared spectroscopy based explosives detection system using a quantum cascade laser (QCL) as excitation source was used to record mid infrared spectral signals of highly energetic materials (HEM) deposited on real world substrates such as travel baggage, cardboard and wood. The HEMs used were nitroaromatic military explosive trinitrotoluene (TNT), aliphatic nitrate ester pentaerythritol tetranitrate (PETN) and aliphatic nitramine hexahydrotrinitrotriazine (RDX). Various deposition methods including sample smearing, spin coating, spray deposition and partial immersion were evaluated for preparing samples and standards used as part of the study. Chemometrics statistical routines such as principal component analysis (PCA) regression with various preprocessing steps were applied to the recorded infrared spectra of explosives deposited as trace contaminants on target substrates. The results show that the dispersive infrared vibrational technique investigated using QCL is useful for detection of HEMs in the types of substrates studied.

Detection of explosive hazards is a critical component of enabling and improving operational mobility and protection of US Forces. The Autonomous Mine Detection System (AMDS) developed by the US Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD) is addressing this challenge for dismounted soldiers. Under the AMDS program, ARA has developed a vapor sampling system that enhances the detection of explosive residues using commercial-off-the-shelf (COTS) sensors. The Explosives Hazard Trace Detection (EHTD) payload is designed for plug-and-play installation and operation on small robotic platforms, addressing critical Army needs for more safely detecting concealed or exposed explosives in areas such as culverts, walls and vehicles. In this paper, we describe the development, robotic integration and performance of the explosive vapor sampling system, which consists of a sampling “head,” a vapor transport tube and an extendable “boom.” The sampling head and transport tube are integrated with the boom, allowing samples to be collected from targeted surfaces up to 7-ft away from the robotic platform. During sample collection, an IR lamp in the sampling head is used to heat a suspected object/surface and the vapors are drawn through the heated vapor transport tube to an ion mobility spectrometer (IMS) for detection. The EHTD payload is capable of quickly (less than 30 seconds) detecting explosives such as TNT, PETN, and RDX at nanogram levels on common surfaces (brick, concrete, wood, glass, etc.).

We present our initial experimental results from the LIBS studies of pyrazole, 1-nitropyrazole, 3-nitropyrazole, 3,4- dinitropyrazole and 1-methyl- 3,4,5 trinitro pyrazole recorded with femtosecond pulses and performed in argon atmosphere. CN molecular bands in three different spectral regions of 357 nm-360 nm, 384 nm-389 nm and 414 nm -423 nm, C2 swan bands near 460 nm-475 nm, 510 nm– 520 nm and 550 nm-565 nm were observed. The C peak at 247.82 nm, H peak at 656.2 nm have also been observed along with several peaks of O and N. CN/C₂, CN/C, C₂/C and C₂/N ratios were measured from the average of 25 spectra obtained in argon. The effect of number of nitro groups on the atomic and molecular emission has been evaluated. A gate delay of 100 ns and a gate width of 800 ns were used for collecting the spectra.

Elastic backscatter LIght Detection And Ranging (LIDAR) is a promising approach for stand-off detection of biological aerosol clouds. Comprehensive models that explain the scattering behavior from the aerosol cloud are needed to understand and predict the scattering signatures of biological aerosols under varying atmospheric conditions and against different aerosol backgrounds. Elastic signatures are dependent on many parameters of the aerosol cloud, with two major components being the size distribution and refractive index of the aerosols. The Johns Hopkins University Applied Physics Laboratory (JHU/APL) has been in a unique position to measure the size distributions of released biological simulant clouds using a wide assortment of aerosol characterization systems that are available on the commercial market. In conjunction with the size distribution measurements, JHU/APL has also been making a dedicated effort to properly measure the refractive indices of the released materials using a thin-film absorption technique and laboratory characterization of the released materials. Intimate knowledge of the size distributions and refractive indices of the biological aerosols provides JHU/APL with powerful tools to build elastic scattering models, with the purpose of understanding, and ultimately, predicting the active signatures of biological clouds.

Uptake of water by biological aerosols can impact their physical and chemical characteristics. The water content in a bioaerosol can affect the backscatter cross-section as measured by LIDAR systems. Better understanding of the water content in controlled-release clouds of bioaerosols can aid in the development of improved standoff detection systems. This study includes three methods to improve understanding of how bioaerosols take up water. The laboratory method measures hygroscopic growth of biological material after it is aerosolized and dried. Hygroscopicity curves are created as the humidity is increased in small increments to observe the deliquescence point, then the humidity is decreased to observe the efflorescence point. The field component of the study measures particle size distributions of biological material disseminated into a large humidified chamber. Measurements are made with a Twin-Aerodynamic Particle Sizer (APS, TSI, Inc), -Relative Humidity apparatus where two APS units measure the same aerosol cloud side-by-side. The first operated under dry conditions by sampling downstream of desiccant dryers, the second operated under ambient conditions. Relative humidity was measured within the sampling systems to determine the difference in the aerosol water content between the two sampling trains. The water content of the bioaerosols was calculated from the twin APS units following Khlystov et al. 2005 [1]. Biological material is measured dried and wet and compared to laboratory curves of the same material. Lastly, theoretical curves are constructed from literature values for components of the bioaerosol material.

The goal of this project is to investigate correlations of polarimetric angular scattering patterns from individual aerosol particles with the particles’ physical structure and composition. Such signature patterns may be able to provide particle classification capability, such as, for example, discrimination between man-made and naturally occurring aerosols. If successful, this effort could improve current detection methods for biological warfare (BW) agent aerosols. So far, we have demonstrated an experimental arrangement to measure polarization-state resolved, multi-angle, scattering intensities from single aerosol particles on-the-fly. Our novel approach is a radical departure from conventional polarimetric measurement methods, and a key factor is the use of a multiple-order retarder to prepare different polarization states, depending on the wavelength of the incident light. This novel experimental technique uses a supercontinuum light source, an array of optical fibers, an imaging spectrometer and an EMCCD camera to simultaneously acquire wavelength and angle dependent particle light scattering data as a two-dimensional snapshot.

Mueller matrix elements were initially measured from individual particles held in an optical trap (at 405 nm). Since particles can be stably trapped for long periods (hours), we were able to change the optical configuration to acquire multiple Mueller matrix element measurements on a single particle. We have computationally modeled these measurements at specific angles, and the comparison with experimental measurements shows good agreement. Similar measurements have also been made on slowly falling particles, and our current efforts are focused on improving experimental technique sufficiently to make such measurements on flowing particles.

Recent investigations have focused on the improvement of rapid and accurate methods to develop spectroscopic markers of compounds constituting microorganisms that are considered biological threats. Quantum cascade lasers (QCL) systems have revolutionized many areas of research and development in defense and security applications, including his area of research. Infrared spectroscopy detection based on QCL was employed to acquire mid infrared (MIR) spectral signatures of Bacillus thuringiensis (Bt), Escherichia coli (Ec) and Staphylococcus epidermidis (Se), which were used as biological agent simulants of biothreats. The experiments were carried out in reflection mode on various substrates such as cardboard, glass, travel baggage, wood and stainless steel. Chemometrics statistical routines such as principal component analysis (PCA) regression and partial least squares-discriminant analysis (PLS-DA) were applied to the recorded MIR spectra. The results show that the infrared vibrational techniques investigated are useful for classification/detection of the target microorganisms on the types of substrates studied.

The secreted proteins of the enterohemorrhagic and enteropathogenic E. coli (EHEC and EPEC) are the most common cause of hemorrhagic colitis, a bloody diarrhea with EHEC infection, which often can lead to life threatening hemolytic-uremic syndrome (HUS).We are employing a metaproteomic approach as an effective and complimentary technique to the current genomic based approaches. This metaproteomic approach will evaluate the secreted proteins associated with pathogenicity and utilize their signatures as differentiation biomarkers between EHEC and EPEC strains. The result showed that the identified tryptic peptides of the secreted proteins extracted from different EHEC and EPEC growths have difference in their amino acids sequences and could potentially utilized as biomarkers for the studied E. coli strains. Analysis of extract from EHEC O104:H4 resulted in identification of a multidrug efflux protein, which belongs to the family of fusion proteins that are responsible of cell transportation. Experimental peptides identified lies in the region of the HlyD haemolysin secretion protein-D that is responsible for transporting the haemolysin A toxin. Moreover, the taxonomic classification of EHEC O104:H4 showed closest match with E. coli E55989, which is in agreement with genomic sequencing studies that were done extensively on the mentioned strain. The taxonomic results showed strain level classification for the studied strains and distinctive separation among the strains. Comparative proteomic calculations showed separation between EHEC O157:H7 and O104:H4 in replicate samples using cluster analysis. There are no reported studies addressing the characterization of secreted proteins in various enhanced growth media and utilizing them as biomarkers for strain differentiation. The results of FY-2012 are promising to pursue further experimentation to statistically validate the results and to further explore the impact of environmental conditions on the nature of the secreted biomarkers in various E. coli strains that are of public health concerns in various sectors.

Bacterial display technology offers a number of advantages over competing display technologies (e.g, phage) for the rapid discovery and development of peptides with interaction targeted to materials ranging from biological hazards through inorganic metals. We have previously shown that discovery of synthetic peptide reagents utilizing bacterial display technology is relatively simple and rapid to make laboratory automation possible. This included extensive study of the protective antigen system of Bacillus anthracis, including development of discovery, characterization, and computational biology capabilities for in-silico optimization. Although the benefits towards CBD goals are evident, the impact is far-reaching due to our ability to understand and harness peptide interactions that are ultimately extendable to the hybrid biomaterials of the future. In this paper, we describe advances in peptide discovery including, new target systems (e.g. non-biological materials), advanced library development and clone analysis including integrated reporting.

MODES SNM is a collaborative project (funded under the FP7 - Security program), aimed at developing a prototype for a mobile, modular detection system for radioactive and Special Nuclear Materials (SNM). To maximize the detection capability for SNM, the prototype will combine detectors for fast and thermal neutrons, as well as for gamma-rays. The key detector technology in the development is high pressure scintillation cells filled with noble gases, as recently developed by ARKTIS. The project started officially at the beginning of 2012, for a duration of 30 months. The goal of the project is to deliver a fully integrated and field tested prototype of a modular mobile system capable of passively detecting weak or shielded radioactive sources with accuracy higher than currently available systems. We will present the status of the project, preliminary results and future prospects.

Nevada Nanotech Systems, Inc. (Nevada Nano) has developed a multi-sensor solution to Chemical, Biological, Radiological, Nuclear and Explosives (CBRNE) detection that combines the Molecular Property Spectrometer^™ (MPS^™)—a micro-electro-mechanical chip-based technology capable of measuring a variety of thermodynamic and electrostatic molecular properties of sampled vapors and particles—and a compact, high-resolution, solid-state gamma spectrometer module for identifying radioactive materials, including isotopes used in dirty bombs and nuclear weapons. By conducting multiple measurements, the system can provide a more complete characterization of an unknown sample, leading to a more accurate identification. Positive identifications of threats are communicated using an integrated wireless module. Currently, system development is focused on detection of commercial, military and improvised explosives, radioactive materials, and chemical threats. The system can be configured for a variety of CBRNE applications, including handheld wands and swab-type threat detectors requiring short sample times, and ultra-high sensitivity detectors in which longer sampling times are used. Here we provide an overview of the system design and operation and present results from preliminary testing.

For 50 years, it was assumed that unlike liquid scintillators or organic crystals, plastic scintillators were not able to discriminate fast neutrons from gamma. In this work, we will demonstrate that triplet-triplet annihilations (which are responsible of n/γ discrimination) can occur even in plastic scintillators, following certain conditions. Thus, the presentation will deal with the chemical preparation, the characterization and the comparison of n/γ pulse shape discrimination of various plastic scintillators. To this aim, scale-up of the process allowed us to prepare a Ø 100 mm × ≈ 110 mm thick.

Energy-resolving gamma-ray detectors are of particular interest for the detection of illicit radioactive materials at border crossings and other portals because they offer fast, contactless screening that can discriminate between dangerous and benign materials. Among detector classes, scintillators offer an intriguing balance between cost and performance, but current technologies rely on single-crystal materials that are not scalable to portal-relevant detector sizes. Thus, there is a recognized need for novel, processible, high-performance scintillating materials or composites. Composites based on semiconductor nanocrystal quantum dots (QDs) are of interest because of their potentially high gamma-stopping power, high emission quantum yields, and low-cost solution synthesis and processing. Yet the performance of these and other granular nanomaterials has not met expectations. We suggest that this is due to the general lack of insight into the gamma-to-photons transduction process within these inherently more complex materials, which reduces the development and refinement of candidates to simple trial-and-error. Here, we describe the development of ultrafast transient cathodoluminescence as a unique spectroscopic tool for probing the population of excited states formed within a material during scintillation, and thus determining the major sources of energy loss. Our analysis shows that in the case of CdSe/ZnS core/shell QDs, any efficiency loss due to previously blamed factors of low-stopping power and high reabsorptive losses are likely dwarfed by the losses attributable to efficient, non-radiative Auger recombination. We examine how we reached this conclusion, and how this insight defines the characteristics needed in the next generation of scintillating QD composites.

Considerable progress has been achieved recently to enhance the thermal neutron detection efficiency of solid-state neutron detectors that incorporate neutron sensitive materials such as ¹⁰B and ⁶LiF in Si micro-structured p-n junction diode. Here, we describe the design, fabrication process optimization and characterization of an enriched boron filled honeycomb structured neutron detector with a continuous p⁺-n junction. Boron deposition and diffusion processes were carried out using a low pressure chemical vapor deposition to study the effect of diffusion temperature on current density-voltage characteristics of p⁺-n diodes. TSUPREM-4 was used to simulate the thickness and surface doping concentration of p⁺-Si layers. MEDICI was used to simulate the depletion width and the capacitance of the microstructured devices with continuous p⁺-n junction. Finally, current density-voltage and pulse height distribution of fabricated devices with 2.5×2.5 mm2 size were studied. A very low leakage current density of ~2×10^-8 A/cm² at -1 V (for both planar and honeycomb structured devices) and a bias-independent thermal neutron detection efficiency of ~26% under zero bias voltage were achieved for an enriched boron filled honeycomb structured neutron detector with a continuous p⁺-n junction.

Pulse shape discrimination (PSD) is a common method to distinguish between pulses produced by gamma rays and neutrons in scintillator detectors. This technique takes advantage of the property of many scintillators that excitations by recoil protons and electrons produce pulses with different characteristic shapes. Unfortunately, many scintillating materials with good PSD properties have other, undesirable properties such as flammability, toxicity, low availability, high cost, and/or limited size. In contrast, plastic scintillator detectors are relatively low-cost, and easily handled and mass-produced. Recent studies have demonstrated efficient PSD in plastic scintillators using a high concentration of fluorescent dyes. To further investigate the PSD properties of such systems, mixed plastic scintillator samples were produced and tested. The addition of up to 30 wt. % diphenyloxazole (DPO) and other chromophores in polyvinyltoluene (PVT) results in efficient detection with commercial detectors. These plastic scintillators are produced in large diameters up to 4 inches by melt blending directly in a container suitable for in-line detector use. This allows recycling and reuse of materials while varying the compositions. This strategy also avoids additional sample handling and polishing steps required when using removable molds. In this presentation, results will be presented for different mixed-plastic compositions and compared with known scintillating materials

We present the test results of a neutron/gamma-ray imaging spectrometer for the identification and location of radioactive and special nuclear materials. Radioactive materials that could be fashioned into a radiation dispersal device typically emit gamma rays, while fissile materials such as uranium and plutonium emit both neutrons and gamma rays via spontaneous or induced fission. The simultaneous detection of neutrons and gamma rays is a clear indication of the presence of fissile material. The instrument works as a double-scatter telescope, requiring a neutron or gamma ray to undergo an interaction in two detectors to be considered a valid event. While this requirement reduces the detector efficiency, it yields information about the direction and energy of the incident particle, which is then used to reconstruct an image of the emitting source. Because of this imaging capability background events can be rejected, decreasing the number of events required for high confidence detection and thereby greatly improving its sensitivity. The instrument is optimized for the detection of neutrons with energies from 1-20 MeV and gamma rays from 0.4 to 10 MeV. Images and energy spectra for neutron and gamma rays are reported for several sources including depleted uranium and plutonium. In addition, the effect of neutron source shielding is investigated.

We present our initial experimental results from the LIBS studies of pyrazole, 1-nitropyrazole, 3-nitropyrazole, 3,4- dinitropyrazole and 1-methyl- 3,4,5 trinitro pyrazole recorded with femtosecond pulses and performed in argon atmosphere. CN molecular bands in three different spectral regions of 357 nm-360 nm, 384 nm-389 nm and 414 nm -423 nm, C2 swan bands near 460 nm-475 nm, 510 nm– 520 nm and 550 nm-565 nm were observed. The C peak at 247.82 nm, H peak at 656.2 nm have also been observed along with several peaks of O and N. CN/C², CN/C, C₂/C and C₂/N ratios were measured from the average of 25 spectra obtained in argon. The effect of number of nitro groups on the atomic and molecular emission has been evaluated. A gate delay of 100 ns and a gate width of 800 ns were used for collecting the spectra.

Portable LIBS sensor communication bandwidth limitations favor local material classification for low power consumption. Partial Least Squares - Discriminant Analysis (PLS-DA) and Principle Component Analysis (PCA) have been implementation via general purpose computers and are accepted for some Department of Defense applications. Prior publications address the creation of a low mass, low power, robust hardware spectra classifier for a limited set of predetermined materials in an atmospheric matrix. The incorporation of a PCA or a PLS-DA classifier into a predictorcorrector implementation on a TI6701 has been developed. The performance modeling of the control system with an emphasis on further optimization needs addressing. This paper characterizes, from a control system standpoint, the predictor-corrector architecture applied to LIBS data collection. In addition, the application of this as a material classifier is presented. Updates in the model implemented on a low power multi-core DSP will be presented as well. Performance comparisons to alternative control system structures will be considered.