This PDF file contains the front matter associated with SPIE Proceedings Volume 7665, including the Title Page, Copyright information, Table of Contents, Introduction, and the Conference Committee listing.

We present an initial bacterial fate study of Gram positive vegetative cells suspended in water and stored at ambient room temperature via Raman spectroscopy monitoring. Two types of cells were considered for this study: vegetative cells of Bacillus cereus, Bacillus thuringiensis which contain the polyhydroxybutyric acid (PHBA) as an energy storage compound and Bacillus subtlilis cells which do not. The cells were cultured specifically for this project. Immediately following the culturing phase, the bacteria were extracted, cleaned and at the onset of the study were suspended in de-ionized water and stored at room temperature. Aliquots of suspensions were deposited onto aluminum slides at different times and allowed to dry for Raman analysis. Spectra from multiple regions of each dried spot and each deposit time were acquired along with the bright-field and fluorescence images. Results were examined to investigate the effect of suspension time on the spectral signatures as well as the fate behavior of the three types of cells investigated. The cells were monitored daily for over a 14 period during which time the onset of starvation induced sporulation was observed.

Weaponized biological agents are as great a threat as nuclear or chemical weapons. They must be detected at the earliest stage to prevent diffusion because once these agents are dispersed into the air, the rapidly decreasing concentration makes detection more of a challenge. Polymerase chain reaction (PCR) is a common method to create copies of a specific target region of a DNA sequence and to produce large quantities of DNA molecules. A few DNA molecules are rapidly amplified by PCR into billions of copies. While PCR is a powerful technique and is capable of countering new threats relatively easily, it is plagued by the number of processes necessary. Therefore, we have developed an integrated PCR system for rapid detection of biological agents captured from the air. Each processing function is performed by a dedicated module, and reduction in the process time has been made the top priority, without loss in the signal/noise ratio of the total system. Agents can be identified within 15 min from capture. A fully automated operation protects operators from exposure to potentially highly lethal samples.

This paper presents an overview of recent work by the Edgewood Chemical Biological Center (ECBC) in algorithm development for parameter estimation and classification of localized atmospheric aerosols using data from rapidly tuned multiple-wavelength range-resolved LWIR lidar. The motivation for this work is the need to detect, locate, and discriminate biological threat aerosols in the atmosphere from interferent materials such as dust and smoke at safe standoff ranges using time-series data collected at a discrete set of CO2 laser wavelengths. The goals of the processing are to provide real-time aerosol detection, localization, and discrimination. Earlier work by the authors has produced an efficient Kalman filter-based algorithm for estimating the range-dependent aerosol concentration and wavelength-dependent backscatter signatures. The latter estimates are used as feature vectors for training support vector machines classifiers for performing the discrimination. Several years of field testing under the Joint Biological Standoff Detection System program at Dugway Proving Ground, UT, Eglin Air Force Base, FL, and other locations have produced data and backscatter estimates from a broad range of biological and interferent aerosol materials for the classifier development. The results of this work are summarized in our presentation.

This paper presents the plume tracking algorithms developed for a series of outdoor chemical-stimulant testing conducted at Dugway Proving Ground in 2008 and 2009 employing a Raven UAV equipped with a real-time chemical sensor. The flights were conducted as part of the a program under the sponsorship of the Army JPM NBC Contamination Avoidance and in conjunction with the Army PM-Unmanned Aircraft Systems, the Defense Threat Reduction Agency, and Edgewood Chemical Biological Center. This test demonstrated the Raven's ability to autonomously detect and track a chemical plume during a variety of atmospheric conditions. During the testing, the Raven conducted over a dozen flights, tracking outdoor releases of simulated chemical weapons over significant distances. The Raven was cued to the releases with standoff detection systems through Cursor on Target messages. Upon reaching the plume, the Raven used on-board sensors and on-board meteorological data to track the plume autonomously and determine the extent of the plume. Results were provided in real-time to the UAV operator.

To ensure agent optical cross sections are well understood from the UV to the LWIR, volume integrated measurements of aerosolized agent material at a few key wavelengths is required to validate existing simulations. Ultimately these simulations will be used to assess the detection performance of various classes of lidar technology spanning the entire range of the optical spectrum. The present work demonstrates an optical measurement architecture based on lidar allowing the measurement of backscatter and depolarization ratio from biological aerosols released in a refereed, 1-m cubic chamber. During 2009, various upgrades have been made to the chamber LIDAR system, which operates at 1.064 μm with sub nanosecond pulses at a 120 Hz repetition rate. The first build of the system demonstrated a sensitivity of aerosolized Bacillus atrophaeus (BG) on the order of 5×10⁵ ppl with 1 GHz InGaAs detectors. To increase the sensitivity and reduce noise, the InGaAs detectors were replaced with larger-area silicon avalanche photodiodes for the second build of the system. In addition, computer controlled step variable neutral density filters are now incorporated to facilitate calibrating the system for absolute back-scatter measurements. Calibrated hard target measurements will be combined with data from the ground truth instruments for cross-section determination of the material aerosolized in the chamber. Measured results are compared to theoretical simulations of cross-sections.

There is an urgent need to develop standoff sensing of biological agents in aerosolized clouds. In support of the Joint Biological Standoff Detection System (JBSDS) program, lidar systems have been a dominant technology and have shown significant capability in field tests conducted in the Joint Ambient Breeze Tunnel (JABT) at Dugway Proving Ground (DPG). The release of biological agents in the open air is forbidden. Therefore, indirect methods must be developed to determine agent cross-sections in order to validate sensor against biological agents. A method has been developed that begins with laboratory measurements of thin films and liquid suspensions of biological material to obtain the complex index of refraction from the ultraviolet (UV) to the long wave infrared (LWIR). Using that result and the aerosols' particle size distribution as inputs to Mie calculations yields the backscatter and extinction cross-sections as a function of wavelength. Recent efforts to model field measurements from the UV to the IR have been successful. Measurements with aerodynamic and geometric particle sizers show evidence of particle clustering. Backscatter simulations of these aerosols show these clustered particles dominate the aerosol backscatter and depolarization signals. In addition, these large particles create spectral signatures in the backscatter signal due to material absorption. Spectral signatures from the UV to the IR have been observed in simulations of field releases. This method has been demonstrated for a variety of biological simulant materials such as Ovalbumin (OV), Erwinia (EH), Bacillus atrophaeus (BG) and male specific bacteriophage (MS2). These spectral signatures may offer new methods for biological discrimination for both stand-off sensing and point detection systems.

Raman microspectroscopy is used to probe the age and milieu parameters for suspensions of bacteria for their detection in water backgrounds. No studies have been reported on the fate of Raman signatures over time for biologicals stored in water matrices. A FALCON II Raman Chemical Imaging System (ChemImage, Pittsburgh, PA) and 532 nm laser excitation source acquired the Raman spectra. MATLAB principal components (PC) analysis software was employed for data reduction. Suspensions of Bacillus atrophaeus, Bacillus thuringiensis, and three strains of E. coli (EC) were prepared in distilled and recipe tap water. Aliquots at 5 min, 5 hr, and 1, 2, and 7 days at 25 C were dried on microscope slides in replicate. Adequate spectral differences were observed for all three organism species. Microscope analysis showed that freshly suspended Bacillus spores and EC vegetative cells, in both water matrices, remained as spores after seven days. Agar plate growth procedures showed that the bacteria were still viable even after seven days resting in both water matrices. All three bacterial species were separated based on PC analysis; however, the three EC strains coalesced. The water matrix parameter was inconsistent in its ability to separate the Raman spectra in PC plots of the five bacteria. Within each group, the time parameter poorly separated the bacterial resting suspensions as the aging proceeded. A Mahalanobis linkage distance analysis (dendrogram) for all three species and strains in both water matrices confirmed a random order for all five suspension times.

Lidar has been identified as a promising sensor for remote detection of biological warfare agents (BWA). Elastic IR lidar can be used for cloud detection at long ranges and UV laser induced fluorescence can be used for discrimination of BWA against naturally occurring aerosols. This paper will describe a simulation tool which enables the simulation of lidar for detection, tracking and classification of aerosol clouds. The cloud model was available from another project and has been integrated into the model. It takes into account the type of aerosol, type of release (plume or puff), amounts of BWA, winds, height above the ground and terrain roughness. The model input includes laser and receiver parameters for both the IR and UV channels as well as the optical parameters of the background, cloud and atmosphere. The wind and cloud conditions and terrain roughness are specified for the cloud simulation. The search area including the angular sampling resolution together with the IR laser pulse repetition frequency defines the search conditions. After cloud detection in the elastic mode, the cloud can be tracked using appropriate algorithms. In the tracking mode the classification using fluorescence spectral emission is simulated and tested using correlation against known spectra. Other methods for classification based on elastic backscatter are also discussed as well as the determination of particle concentration. The simulation estimates and displays the lidar response, cloud concentration as well as the goodness of fit for the classification using fluorescence.

We have developed a small, relatively lightweight and efficient short range (<100 m) LIDAR instrument for remotely detecting harmful bioagents. The system is based on a pulsed, eye-safe, 355 nm laser exciting aerosols which then fluoresce with a typical spectrum. The system makes use of a novel technology for continuously monitoring for the presence of unusual concentrations of bioaerosols at a precise remote location within the monitored area, with response within seconds. Fluorescence is spectrally resolved over 32 channels capable of photon counting. Results show a sensitivity level of 40 ACPLA of Bacillus Globigii, an anthrax simulant, at a distance of 100 m (assumed worst case where 1 ppl = 1 ACPLA) considering particle sizes between 0.5 and 10 μm, with a geometric mean at 1 um. The apparatus has been tested in the field during three test and evaluation campaigns with multiple bioagents and public security products. Preliminary results show that the system is able to distinguish between harmful bioagents and naturally occurring ones. A classification algorithm was successfully tested with a single type of bioagent; experiments for daytime measurements are discussed.

This paper discusses selected aspects of an MIT Lincoln Laboratory effort developing information fusion techniques for biodefense decision-support tasks, involving biological standoff (lidar - light detection and ranging) sensors, meteorology, as well as point sensors and potentially other battlespace sensing and contextual information. The Spatiotemporal Coherence (STC) fusion approach developed in this effort combines phenomenology aspects with approximate uncertainty measures to quantify corroboration between the information elements. The results indicate that STC can significantly reduce false alarm rates. Meandering Plume and Background Simulation is one of two techniques developed for ground-truth data generation. Beyond the detection realm, developed techniques include information-fusion based plume mapping and propagation prediction.

Stand-off Laser-Induced-Thermal-Emission (LITE), Laser-Induced-Breakdown Spectroscopy (LIBS), and remote Raman Lidar are being studied for the remote sensing of a wide range of target substances, including explosive and chemical species. Each of these techniques use a transmitted laser beam to remotely excite a spectral emission process at a distant target, have some optical and detection characteristics in common, but also have several other excitation and delivery aspects that are unique to each technique. In order to better understand these techniques, we are developing a computer program to model and simulate a LITE, LIBS, and Raman lidar system for the stand-off detection and spectral identification of close to moderate range target species. In particular, a modified lidar equation has been used for the LIBS technique, in which the influence of the transmission of the atmosphere is also computed to determine its influence on the backscattered spectral information as a function of wavelength and range. The standard Lidar equation was modified to take into account the emission of a laser induced source at a range r, and the subsequent transmission of the emission back toward the (Lidar) telescope receiver. Applications for LITE and Raman lidar analysis are planned.

We present findings of the DYCE project, which addresses the needs of military and blue light responders in providing a rapid, reliable on-scene analysis of the dispersion of toxic airborne contaminants following their malicious or accidental release into a rural, urban or industrial environment. We describe the development of a small network of ad-hoc deployable chemical and meteorological sensors capable of identifying and locating the source of the contaminant release, as well as monitoring and estimating the dispersion characteristics of the plume. We further present deployment planning methodologies to optimize the data gathering mission given a constrained asset base.

In recent years, several sensing devices capable of identifying unknown chemical and biological substances have been commercialized. The success of these devices in analyzing real world samples is dependent on the ability of the on-board identification algorithm to de-convolve spectra of substances that are mixtures. To develop effective de-convolution algorithms, it is critical to characterize the relationship between the spectral features of a substance and its probability of detection within a mixture, as these features may be similar to or overlap with other substances in the mixture and in the library. While it has been recognized that these aspects pose challenges to mixture analysis, a systematic effort to quantify spectral characteristics and their impact, is generally lacking. In this paper, we propose metrics that can be used to quantify these spectral features. Some of these metrics, such as a modification of variance inflation factor, are derived from classical statistical measures used in regression diagnostics. We demonstrate that these metrics can be correlated to the accuracy of the substance's identification in a mixture. We also develop a framework for characterizing mixture analysis algorithms, using these metrics. Experimental results are then provided to show the application of this framework to the evaluation of various algorithms, including one that has been developed for a commercial device. The illustration is based on synthetic mixtures that are created from pure component Raman spectra measured on a portable device.

Large networks of disparate chemical/biological (CB) sensors, MET sensors, and intelligence, surveillance, and reconnaissance (ISR) sensors reporting to various command/display locations can lead to conflicting threat information, questions of alarm confidence, and a confused situational awareness. Sensor netting algorithms (SNA) are being developed to resolve these conflicts and to report high confidence consensus threat map data products on a common operating picture (COP) display. A phase I SBIR study to develop a conceptual design for a SNA was recently completed. Mathematical approaches for assigning uncertainty to incoming data streams, doing spatial/temporal correlation of point and standoff sensor data (via vector translation based tomography), estimating uncertainty for threat maps, and consistency checking between the consensus threat map result and the individual input data streams were developed. A set of simulation environment tools for testing the SNA, including a simple threat model, sensor models, and fused and un-fused COPs, were also prototyped during phase I. The SNA development and simulation based testing will continue during the phase II effort, which was just awarded.

We describe experimental results on the detection of explosives residues with active hyperspectral imaging by illumination of the target surface using an external cavity quantum cascade laser (ECQCL) and imaging using an uncooled microbolometer camera. Explosives have rich absorption features in the molecular fingerprint region that spans 1500 to 500 wavenumbers and is easily probed by the wavelength range of quantum cascade lasers (QCL), which can be fabricated to emit from 3300 to 400 wavenumbers. Our laboratory-built ECQCL consists of a Fabry-Pérot laser with anti-reflection coated front facet that is arranged in a Littman-Metcalf configuration. The ECQCL was operated quasi-CW with a 100 kHz repetition rate, 50% duty cycle drive signal and tuning range from 1102.95 to 983.8 wavenumbers. The active hyperspectral imaging technique forms an image hypercube by recording one image for each tuning step of the ECQCL. For the experiments reported here, each wavelength band was 2 wavenumbers wide and 60 bands of image data were acquired in 2 seconds. The resulting hyperspectral image contains the full absorption spectrum produced by the illumination laser at each pixel in the image which can then be used to identify the explosive type and relative quantity using the rich library of spectral identification approaches developed initially in the remote sensing community. These techniques include spectral feature fitting, matched filtering, and mixture tuned matched filtering. Mixtures of materials can be evaluated using linear spectral unmixing approaches and matched filtering or mixture tuned matched filtering. We provide examples of these methods using ENVI, a commercial spectral image processing software package.

We present our results on the stoichiometric analysis of ammonium nitrate (AN) and ammonium Perchlorate (AP) studied using laser induced breakdown spectroscopy (LIBS) with nanosecond pulses. The LIBS spectra collected for AP and AN, without any gating and using a high resolution spectrometer, exhibited characteristic lines corresponding to O, N, H, C, and K. The Oxygen line at 777.38 nm and three Nitrogen lines (N₁, N₂, N₃) at 742.54 nm, 744.64 nm, 747.12 nm were used for evaluating the Oxygen/Nitrogen ratios. The intensities were calculated using area under the peaks and normalized to their respective transition probabilities and statistical weights. The O/N₁ ratios estimated from the LIBS spectra were ~4.94 and ~5.11 for AP and O/N₃ ratios were ~1.64 and ~1.47 for AN obtained from two independent measurements. The intensity ratios show good agreement with the actual stoichiometric ratios - four for AP and one for AN.

A novel microfluidic/SERS platform has been developed for real time sensing of 2,4-DNT. The fundamental research is being conducted at UCSB, commercialized by SpectraFluidics, and validated at ECBC. The system leverages phenomena at multiple length scales, ranging from tens of micrometers to several nanometers. The key enabling technology is a newly developed invention termed Free-Surface Fluidics (FSF), where one or more fluidic surfaces are confined by surface tension forces, and exposed to the surrounding atmosphere. The free-surface fluidic architecture is combined with surface-enhanced Raman spectroscopy (SERS) for detection of 2,4-DNT. Once 2,4-DNT analyte molecules are absorbed into the flow, they can interact with gold or silver colloidal particles. This architecture allows for analysis and deterministic control of SERS 'hot spot' aggregation, which can increase Raman scattering signal strength by up to 10 orders in magnitude. We have successfully measured DNT vapor at concentrations as low as ~1 ppb. This sensitivity value is confirmed by orthogonal measurements using GC-mass spectroscopy at ECBC.

Wide-field Raman chemical imaging (RCI) has been used to detect and identify the presence of trace explosives in contaminated fingerprints. A background subtraction routine was developed to minimize the Raman spectral features produced by surfaces on which the fingerprint was examined. The Raman image was analyzed with a spectral angle mapping routine to detect and identify the explosives. This study shows the potential capability to identify explosives non-destructively so that the fingerprint remains intact for further biometric analysis.

The ENEA Laser Application Section has participated to the European project ISOTREX (Integrated system for on-line trace explosives detection in solid and vapor state), funded in the frame of the PASR 2006 with the main aim to exploit different laser based techniques. Standard explosive compounds and their precursors have been investigated through an atomic technique (LIBS; Laser-Induced Breakdown Spectroscopy), an absorption technique (LPAS; Laser Photoacoustic Spectroscopy) and vibrational techniques (Laser Raman and SERS; Surface-Enhanced Raman Spectroscopy). LIBS and SERS reached a sub ng level of detection, supported by a high rank of discrimination of the components via chemometric analysis. This selectivity skill is also quite evident in the LPAS technique. These results assume particular relevance due to the inclusion of interferents, such as dust, fingerprint oil and lubricant oil, into the investigated compounds. The results of the measurements are presented in view of the possible integration of the three techniques in a single device for trace detection, might contribute also to drastically limit the number of false positives.

Trace explosives contamination is found primarily in the form of solid particulates on surfaces, due to the low vapor pressure of most explosives materials. Today, the standard sampling procedure involves physical removal of particulate matter from surfaces of interest. A variety of collection methods have been used including air-jetting or swabbing surfaces of interest. The sampled particles are typically heated to generate vapor for analysis in hand held, bench top, or portal detection systems. These sampling methods are time-consuming (and hence costly), require a skilled technician for optimal performance, and are inherently non-selective, allowing non-explosives particles to be co-sampled and analyzed. This can adversely affect the sensitivity and selectivity of detectors, especially those with a limited dynamic range. We present a new approach to sampling solid particles on a solid surface that is targeted, non-contact, and which selectively enhances trace explosive signatures thus improving the selectivity and sensitivity of existing detectors. Our method involves the illumination of a surface of interest with infrared laser light with a wavelength that matches a distinctive vibrational mode of an explosive. The resonant coupling of laser energy results in rapid heating of explosive particles and rapid release of a vapor plume. Neighboring particles unrelated to explosives are generally not directly heated as their vibrational modes are not resonant with the laser. As a result, the generated vapor plume includes a higher concentration of explosives than if the particles were heated with a non-selective light source (e.g. heat lamp). We present results with both benchtop infrared lasers as well as miniature quantum cascade lasers.

This paper shall demonstrate the reduced lifetime of ultra-trace explosive residues when subjected to standard laboratory conditions, citing examples of flawed experimental design. The traditional view of "trace" level residue may lie within the detection limit capabilities of bench-top instrumentation. Gas chromatography / mass spectrometry, often the main stay of many trace evidence analysis laboratories can readily deliver nanogram and now potentially upper picogram detection limits. Today, emerging technologies continue to push the limits of detection, and sub-nanogram restrictions give way to picogram and femtogram opportunities. As instrument technologies become more sensitive, the need to work at continually lower detection levels is expressed. Generation of reliable, reproducible ultra-trace samples for the testing, analysis and evaluation of those technologies is challenged by the chemical properties of the very samples under investigation. Unlike testing against bulk quantities of explosives, at the picogram level unforeseen sublimation and sorption phenomena may potentially disrupt an otherwise well-planned test. While it may be valid to assume that the properties of bulk samples of most explosives are relatively constant with respect to time, it may not be safe to assume the same is true of ultra-trace level deposits of explosive residue. The vapor pressures of many common military explosives are low, but they are not zero. This fact cannot be ignored when working with trace levels of explosive residue. Failure of an inexperienced technician to consider these factors when conducting an evaluation may unnecessarily introduce bias into the data, and may result in the misrepresentation of a sensor's capabilities. The analyst is now faced with the complication of working with amounts of explosive so potentially low, that loss of a few picograms of material due to evaporation, air currents, poor laboratory technique or some other diluting factor represents a significant percentage of the total sample mass. Added to the complication are sample and substrate matrix, carry-over, and potential cross contamination effects that may now pose a significant effect rather than a slight background nuisance.

Several homemade explosives (HMEs) were manufactured and detonated at a desert test facility. Visible and infrared signatures were collected using two Fourier transformspectrometers, two thermal imaging cameras, a radiometer, and a commercial digital video camera. Spectral emissions from the post-detonation combustion fireball were dominated by continuum radiation. The events were short-lived, decaying in total intensity by an order of magnitude within approximately 300ms after detonation. The HME detonation produced a dust cloud in the immediate area that surrounded and attenuated the emitted radiation from the fireball. Visible imagery revealed a dark particulate (soot) cloud within the larger surrounding dust cloud. The ejected dust clouds attenuated much of the radiation from the post-detonation combustion fireballs, thereby reducing the signal-to-noise ratio. The poor SNR at later times made it difficult to detect selective radiation from by-product gases on the time scale (~500ms) in which they have been observed in other HME detonations.

Herein we present some of our initial experimental results obtained from the laser induced breakdown spectroscopic (LIBS) measurements of RDX and HMX using nanosecond (ns), picosecond (ps), and femtosecond (fs) laser pulses acquired without gating and delay. RDX and HMX were mixed with KBr and pellets were prepared for the spectroscopic studies. Nanosecond pulses at 532 nm, ps/fs pulses at 800 nm were used for the experiments. The spectra were collected using Ocean Optics 4000/Maya spectrometer using a UV transmitting, 400 μm core diameter fiber in one case and a combination of lenses to collect the light from plasma in the second case. Several features were observed in the spectra exclusive for each pulse domain. The differences/similarities in the spectra collected using different pulses are presented.

We present data on standoff detection of chemicals used in synthesis of homemade explosives (HME) using a compact portable standoff Raman system developed at the University of Hawaii. Data presented in this article show that good quality Raman spectra of various organic and inorganic chemicals, including hazardous chemicals such as ammonium nitrate, potassium nitrate, potassium perchlorate, sulfur, nitrobenzene, benzene, acetone, and gasoline, can be easily obtained from remote distances with a compact standoff Raman system utilizing only a regular 85 mm Nikon camera lens as collection optics. Raman spectra of various chemicals showing clear Raman fingerprints obtained from targets placed at 50 m distance in daylight with 1 to 10 second of integration time are presented in this article. A frequency-doubled mini Nd:YAG pulsed laser source (532 nm, 30 mJ/pulse, 20 Hz, pulse width 8 ns) is used in an oblique geometry to excite the target located at 50 m distance. The standoff Raman system uses a compact spectrograph of size 10 cm (length) × 8.2 cm (width) × 5.2 cm (height) with spectral coverage from 100 to 4500 cm^-1 Stokes-Raman shifted from 532 nm laser excitation and is equipped with a gated thermo-electrically cooled ICCD detector. The system is capable of detecting both the target as well as the atmospheric gases before the target. Various chemicals could be easily identified through glass, plastic, and water media. Possible applications of the standoff Raman system for homeland security and environmental monitoring are discussed.

In order to realize a compact instrument for detection of explosive at trace levels, LIBS was applied on residues from different explosives and potentially interfering materials. The residues were simply placed on aluminum support and the measurements were performed in air. Spectral line intensities from the characteristic atoms/molecules and their ratios, are strongly varying from one sampling point to another. The reasons for such variations were studied and explained, allowing establishing a suitable procedure for material recognition. Correct classification was always obtained for five types of explosives, while for TATP, nitroglycerine, DNT and EGDN this occurred only for very thin residues. In all the cases, the estimated detection threshold is between 0.1 ng and 1 ng.

Molecularly imprinted polymers (MIPs) can be utilized as artificial recognition elements for target chemical analytes of interest. Molecular imprinting involves arranging polymerizable functional monomers around a template followed by polymerization and template removal. The selectivity for the target analyte is based on the spatial orientation of the binding site and covalent or noncovalent interactions between the functional monomer and the analyte. The polymer materials of particular interest are sol-gel-derived xerogels. To allow for increased target recognition, the xerogel has specific functional groups, which allow for polymer interactions with the template molecule (and target analyte). In a sensor format, the recognition event is monitored with some form of transduction. MIP technology is still in its infancy and limitations such as non-specific binding may be overcome utilizing surface enhanced Raman scattering (SERS) as an integrated transduction method for enhanced sensor performance. The objective of the present work is to create a sensitive and selective MIP-SERS sensing platform for 2,4,6-trinitrotoluene (TNT).

Recent progress has been made on an explosive laser standoff detection system called TREDS-2 constructed from COTS components. The TREDS-2 system utilizes combination of Laser Induced Breakdown (LIBS), Townsend Effect Plasma Spectroscopy (TEPS) and Raman spectroscopy techniques with chemometric algorithms to detect hazardous materials. Extension of the detection capability of the TREDS-2 system on the real-time point detection of chemical, biological, radioactive, and nuclear threats has been tested and presented in this report. System performance of surface detection of a variety of CBRNE materials is shown. An overview of improvements to the explosives detection capabilities is given first. Challenges to sensing some specific CBRN threats are then discussed, along with the initial testing of TREDS-2 on CBRN surrogates on a limited number of surfaces. Signal processing using chemometric algorithms are shown as a demonstration of the system's capabilities. A path forward for using the specific technologies is also provided, as well as a discussion of the advantages that each technology brings to the CBRNE detection effort.

Laser Induced Breakdown Spectroscopy (LIBS) is dependent on the interaction between the initiating Laser sequence, the sampled material and the intermediate plasma states. Pulse shaping and timing have been empirically demonstrated to have significant impact on the signal available for active/passive detection and identification. The transient nature of empirical LIBS work makes data collection for optimization an expensive process. Guidance from effective computer simulation represents an alternative. This computational method for CBRNE sensing applications models the Laser, material and plasma interaction for the purpose of performance prediction and enhancement. This paper emphasizes the aspects of light, plasma, and material interaction relevant to portable sensor development for LIBS. The modeling structure emphasizes energy balances and empirical fit descriptions with limited detailed-balance and finite element approaches where required. Dusty plasma from partially decomposed material sample interaction with pulse dynamics is considered. This heuristic is used to reduce run times and computer loads. Computer simulations and some data for validation are presented. A new University of Memphis HPC/super-computer (~15 TFLOPS) is used to enhance simulation. Results coordinated with related effort at Arkansas State University. Implications for ongoing empirical work are presented with special attention paid to the application of compressive sensing for signal processing, feature extraction, and classification.

Photoacoustic spectroscopy (PAS) is a useful monitoring technique that is well suited for trace gas detection. This method routinely exhibits detection limits at the parts-per-million (ppm) or parts-per-billion (ppb) level for gaseous samples. PAS also possesses favorable detection characteristics when the system dimensions are scaled to a microsystem design. Current research utilizes quantum cascade lasers (QCLs) in combination with micro-electromechanical systems (MEMS)-scale photoacoustic cell designs. This sensing platform has provided favorable detection limits for a standard nerve agent simulant. The objective of the present work is to demonstrate an extremely versatile MEMS-scale photoacoustic sensor system that is able to discriminate between different analytes of interest.

An effective method to create fear in the populace is to endanger the water supply. Homeland Security places significant importance on ensuring drinking water integrity. Beyond terrorism, accidental supply contamination from a spill or chemical residual increases is a concern. A prominent class of toxic industrial chemicals (TICs) is pesticides, which are prevalent in agricultural use and can be very toxic in minute concentrations. Detection of TICs or warfare agents must be aggressive; the contaminant needs to be rapidly detected and identified to enable isolation and remediation of the contaminated water while continuing a clean water supply for the population. Awaiting laboratory analysis is unacceptable as delay in identification and remediation increases the likelihood of infection. Therefore, a portable or online water quality sensor is required that can produce rapid results. In this presentation, Surface-Enhanced Raman Spectroscopy (SERS) is discussed as a viable fieldable sensor that can be immersed directly into the water supply and can provide results in <5 minutes from the time the instrument is turned on until analysis is complete. The ability of SERS to detect several chemical warfare agent degradation products, simulants and toxic industrial chemicals in distilled water, tap water and untreated water will be shown. In addition, results for chemical warfare agent degradation products and simulants will be presented. Receiver operator characteristic (ROC) curves will also be presented.

The standoff detection of energetic materials via laser-induced fluorescence of vapors has received relatively little attention due to spectrally broad fluorescence emission from aerosols and unwanted background molecules. This unwanted broad emission can obscure fluorescence from the molecule of interest. When multiphoton excitation is used, the problem can be avoided by blue-shifting the emission from the target molecule relative to the unwanted broad emission. As a precursor to the detection of explosives, we demonstrate coherent multiphoton excitation via stimulated Raman adiabatic passage (STIRAP) on sodium vapor in an argon buffer gas as a function of argon pressure. Results indicate that STIRAP can be performed in a buffer gas at atmospheric pressure with a minimal eduction in STIRAP efficiency. The 15 ps long light pulses used for the pump and Stokes pulses were produced by two synchronously pumped OPO/OPAs tuned to the 3p (²P_1/2) ← 3s (²S_1/2) transition for the pump pulse and the 5s (²S_1/2) ← 3p (²P_1/2) for the Stokes pulse.

DRDC Valcartier recently completed the development of the CATSI EDM (Compact Atmospheric Sounding Interferometer Engineering Development Model) for the Canadian Forces (CF). It is a militarized sensor designed to meet the needs of the CF in the development of area surveillance capabilities for the detection and identification of chemical Warfare Agents (CWA) and toxic industrial chemicals (TIC). CATSI EDM is a passive infrared double-beam Fourier spectrometer system designed for real-time stand-off detection and identification of chemical vapours at distances up to 5 km. It is based on the successful passive differential detection technology. This technique known as optical subtraction, results in a target gas spectrum which is almost free of background, thus making possible detection of weak infrared emission in strong background emission. This paper summarizes the system requirements, achievements, hardware and software characteristics and test results.

The MR-CATSI combines the latest ABB Bomem MR spectro-radiometer technology and software with the concepts used in the design of the ABB and DRDC CATSI instrument twelve years ago. This instrument is a Fourier transform spectro-radiometer with dual input beams. It is a passive, stand-off sensor. One input port can be directed to the area to be interrogated while the other input beam can be pointed at the background. The instrument automatically measures the difference of spectral radiance between the target and the background, hence achieving a suppression of the background signal. The resulting measurement is the unique spectral signature of the target. The system includes a software module to control the instrument and the acquisition parameters, a module for the radiometric calibration and a module to perform the identification and quantification, in real time, of various gases. Overview of the design and results from field trials will be presented. This includes recent measurements of a number of gas plumes.

This presentation describes the use of an FTIR (Fourier Transform Infrared)-based spectrometer designed to continuously monitor ambient air for the presence of chemical warfare agents (CWAs) and toxic industrial chemicals (TICs). The necessity of a reliable system capable of quickly and accurately detecting very low levels of CWAs and TICs while simultaneously retaining a negligible false alarm rate will be explored. Technological advancements in FTIR sensing have reduced noise while increasing selectivity and speed of detection. These novel analyzer design characteristics are discussed in detail and descriptions are provided which show how optical throughput, gas cell form factor, and detector response are optimized. The hardware and algorithms described here will explain why this FTIR system is very effective for the simultaneous detection and speciation of a wide variety of toxic compounds at ppb concentrations. Analytical test data will be reviewed demonstrating the system's sensitivity to and selectivity for specific CWAs and TICs; this will include recent data acquired as part of the DHS ARFCAM (Autonomous Rapid Facility Chemical Agent Monitor) project. These results include analyses of the data from live agent testing for the determination of CWA detection limits, immunity to interferences, detection times, residual noise analysis and false alarm rates. Sensing systems such as this are critical for effective chemical hazard identification which is directly relevant to the CBRNE community.

Airborne hyperspectral ground mapping is being used in an ever-increasing extent for numerous applications in the military, geology and environmental fields. The different regions of the electromagnetic spectrum help produce information of differing nature. The visible, near-infrared and short-wave infrared radiation (400 nm to 2.5 μm) has been mostly used to analyze reflected solar light, while the mid-wave (3 to 5 μm) and long-wave (8 to 12 μm or thermal) infrared senses the self-emission of molecules directly, enabling the acquisition of data during night time. The Telops Hyper-Cam is a rugged and compact infrared hyperspectral imager based on the Fourier-transform technology. It has been used on the ground in several field campaigns, including the demonstration of standoff chemical agent detection. More recently, the Hyper-Cam has been integrated into an airplane to provide airborne measurement capabilities. The technology offers fine spectral resolution (up to 0.25 cm^-1) and high accuracy radiometric calibration (better than 1 degree Celsius). Furthermore, the spectral resolution, spatial resolution, swath width, integration time and sensitivity are all flexible parameters that can be selected and optimized to best address the specific objectives of each mission. The system performance and a few measurements have been presented in previous publications. This paper focuses on analyzing additional measurements in which detection of fertilizer and Freon gas has been demonstrated.

OPTRA has developed an imaging open-path Fourier transform infrared (I-OP-FTIR) spectrometer for 3D profiling of chemical and biological agent simulant plumes released into test ranges and chambers. An array of I-OP-FTIR instruments positioned around the perimeter of the test site, in concert with advanced spectroscopic algorithms, enables real time tomographic reconstruction of the plume. The approach is intended as a referee measurement for test ranges and chambers. This Small Business Technology Transfer (STTR) effort combines the instrumentation and spectroscopic capabilities of OPTRA, Inc. with the computed tomographic expertise of the University of North Carolina, Chapel Hill. In this paper, we summarize the design and build and detail system characterization and test of a prototype I-OP-FTIR instrument. System characterization includes radiometric performance and spectral resolution. Results from a series of tomographic reconstructions of sulfur hexafluoride plumes in a laboratory setting are also presented.

The concentration of Ammonia excreted through human skin has recently been measured using a gas chromatograph equipped with a flame ionization detector (GC-FID) by a group from Nagoya, Japan. These emissions, referred to as ammonia skin gas, were determined to be 1.7±.4 ng/cm³ for healthy subjects in the study. To achieve greater molecule specificity, sensitivity, as well as add a real time capability, we are investigating the potential of a mid IR laser spectrometer, consisting of a Pb-salt diode laser coupled with a low volume 75 meter Herriott gas sample cell, to perform real time ammonia diagnostic measurements. Here we will present a series of preliminary ammonia skin gas measurements obtained with this mid IR laser system.

Raman spectroscopy has proven to be a powerful technique for the standoff identification of surface-deposited chemical agents. In the supervised detection framework, the measured Raman spectrum is compared to a reference library of known spectra. A well-known shortcoming of the supervised approach is that no comprehensive library exists, and when chemicals are present that are not contained in the reference library, the supervised algorithms may confuse those chemicals with library members. One way to deal with this problem is to use an unsupervised method such as nonnegative matrix factorization (NMF) to estimate both the constituent spectra and their relative quantities directly from a block of measured spectra. Chemical identification may then be performed by associating the extracted spectra with the reference library spectra. This two-stage NMF approach often fails because knowledge of the reference library was not used in extracting the spectra. We present a novel modification of NMF in which a subset of the extracted spectra are constrained to be equal to the known reference library. This method is shown to outperform the standard NMF approach and the common supervised identification algorithms when there are chemicals present that are not in the library. This algorithm is applicable to any problem in which a target is identified by comparing a block of measured data to a library of known constituent signatures.

Raman spectroscopy is a very powerful technique for molecular identification, and small Raman instruments have been used successfully to identify toxic substances. The sensitivity of the technique, however, can be limited by fluorescence interference arising from the analyte itself or sample impurities. In the case of surface detection, the Raman signature and/or fluorescence from the surface can also interfere with identification of the target chemical. We take advantage of the polarization characteristics of the Raman scattering to reduce the broadband fluorescence background and surface Raman features. Using a custom fiber optic probe with excitation at 785 nm, we have demonstrated real-time polarization analysis. The spectrum obtained by ratioing the parallel and perpendicular polarization components of the Raman scattering, reduces the surface signature and has a better spectral correlation to the target analyte.

Non-contact chemical warfare agent detection has been demonstrated on military painted surfaces using polarization modulation infrared reflection-absorption spectroscopy (PMIRRAS). Notably, VX has been detected on chemical agent resistance coating (CARC) paint at a distance of approximately 10 cm. PMIRRAS does not rely on the presence of chemical vapors and is not affected by many common battlefield interferants such as aerosolized dust, water and diesel vapors, etc., making it highly suitable for use in operational environments.

Recently, researchers at the Naval Research Laboratory have developed the SWORrD system for measuring two-dimensional Raman Spectra. The device consists of a tunable 2d ultraviolet laser that illuminates the sample at various wavelengths (210-300 nm) and collects a single Raman spectrum at each laser wavelength. The single spectra are combined to form a two-dimensional spectrum (laser wavelength by scattered wavenumber). In this paper we introduce a novel method for the detection of known agents ('targets') within measured 2d spectra. Our method is bases on 'linear mixed pixel' techniques from hyperspectral imagery; in particular, we generalize the Adaptive Subspace Detector (ASD) to a form suitable for SWORrD samples. Our detector uses the individual laser runs to define a set of points within wavenumber space; the set of points corresponding to a 2d spectra defines a particular subspace that contains each material. These subspaces are then used with ASD to identify targets. We include experimental results using real-world data to illustrate our results.

We are designing a Compton imager for use in security investigations and in radiological incident remediation. Previously, results from simulations of a system consisting of several layers of pixellated solid scintillator for both the scatter and absorber detectors were reported. We have now established a two-pixel test stand for validation of the simulations. The stand consists of a single scatter pixel fixed in space, and a single absorber pixel affixed to a two-dimensional translator. Automated translation of the absorber pixel to different positions allows for the acquisition of data at multiple Compton scattering angles, thereby building up a dataset from an effectively multi-channel Compton imager. Here we present performance characteristics for an imager composed of a single 1 cm³ pixel of NaI(Tl) for the scatter detector, and a single 1 cm³ pixel of LaBr₃ for the absorber detector.

A novel concept for detection of thermal neutrons based on lanthanide halide nanocrystals containing gadolinium, an element with by far the highest thermal neutron capture cross section among all stable isotopes, is presented. Colloidal synthesis of GdF₃ nanocrystals, GdF₃ nanocrystals doped with Ce, and LaF₃ nanocrystals doped with Gd is reported. The nanocrystals were characterized by transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDS), dynamic light scattering (DLS) analysis, and steady state UV-VIS optical absorption and photoluminescence spectroscopy. Neutron detection has been confirmed in experiments with Gd-containing nanocrystalline material irradiated with ²⁵²Cf neutron source.

Radiation-induced malfunction and degradation of electronic modules in certain operating conditions are described in this report. The cumulative radiation effects on Atmel AVR microcontrollers, and 2.4 GHz and 303 MHz wireless network devices were evaluated under gamma ray irradiation with dose rates of 100, 10 and 3 Gy/h. The radiation-induced malfunctions occurred at doses of 510±22 Gy for AVR microcontrollers, and 484±111 and 429±14 Gy for 2.4 GHz and 303 MHz wireless network devices, respectively, under a 100 Gy/h equivalent dose rate. The degradation of microcontrollers occurred for total ionizing doses between 400 and 600 Gy under X-ray irradiation. In addition, we evaluated the reliability of neutron dosimeters using a standard neutron field. One of the neutron dosimeters gave a reading that was half of the standard field value.

A new nanoparticle loaded plastic scintillator embedded in a glass substrate detects and discriminates all species of radiation emitted from fissionable bomb making materials. The fast electron scintillating resin is doped with tailored charge conversion nanoparticles to produce characteristic optical pulses. The created optical pulses exit the detector, since the nanoparticles are appreciably smaller than the wavelength of light. Microsandblasting is used to etch deep cavities in the glass substrate forming independent optical paths. The doped resin is injected into the cavities and cured. A separate off-the-shelf PM tube linearly amplifies the created light pulse into a usable electrical signal. By using tailored nanoparticles, the physical mechanisms for converting different species of radiation into lower energy electrons allows for pulse height spectroscopy to discriminate between alpha, beta, gamma, and neutron radiation. A ⁹⁰Sr source was used to test the beta detector, which is loaded with W. The drop in count rates versus distance was found to be similar to traditional detectors. The gamma detector loaded with Pb nanoparticles was tested with a ⁶⁰Co source. The addition of Pb provided greater sensitivity to the gamma radiation. A ²¹⁰Pl source was used to test the glass doped scintillator. The count rates remained fairly constant for varying distances since alpha particles tend to travel in straight paths until losing most of their initial energy. The ¹⁵⁷Gd loaded scintillator was tested with an Am/Be source. ¹⁵⁷Gd has the largest thermal neutron absorption cross section at 255,000 barns and releases a usable characteristic 72keV electron in 39% of the capture reactions.

The use of radiation sensors as portal monitors is increasing due to heightened concerns over the smuggling of fissile material. Transportable systems that can detect significant quantities of fissile material that might be present in vehicular traffic are of particular interest, especially if they can be rapidly deployed to different locations. To serve this application, we have constructed a rapid-deployment portal monitor that uses visible-light and gamma-ray imaging to allow simultaneous monitoring of multiple lanes of traffic from the side of a roadway. The system operation uses machine vision methods on the visible-light images to detect vehicles as they enter and exit the field of view and to measure their position in each frame. The visible-light and gamma-ray cameras are synchronized which allows the gamma-ray imager to harvest gamma-ray data specific to each vehicle, integrating its radiation signature for the entire time that it is in the field of view. Thus our system creates vehicle-specific radiation signatures and avoids source confusion problems that plague non-imaging approaches to the same problem. Our current prototype instrument was designed for measurement of upto five lanes of freeway traffic with a pair of instruments, one on either side of the roadway. Stereoscopic cameras are used with a third "alignment" camera for motion compensation and are mounted on a 50' deployable mast. In this paper we discuss the design considerations for the machine-vision system, the algorithms used for vehicle detection and position estimates, and the overall architecture of the system. We also discuss system calibration for rapid deployment. We conclude with notes on preliminary performance and deployment.

Termed Special Nuclear Material (SNM) by the Atomic Energy Act of 1954, fissile materials, such as ²³⁵U and ²³⁹Pu, are the primary components used to construct modern nuclear weapons. Detecting the clandestine presence of SNM represents an important capability for Homeland Security. An ideal SNM sensor must be able to detect fissile materials present at ppb levels, be able to distinguish between the source of the detected fissile material, i.e., ²³⁵U, ²³⁹Pu, ²³³U or other fission source, and be able to perform the discrimination in near real time. A sensor with such capabilities would provide not only rapid identification of a threat but, ultimately, information on the potential source of the threat. For example, current detection schemes for monitoring clandestine nuclear testing and nuclear fuel reprocessing to provide weapons grade fissile material rely largely on passive air sampling combined with a subsequent instrumental analysis or some type of wet chemical analysis of the collected material. It would be highly useful to have a noncontact method of measuring isotopes capable of providing forensic information rapidly at ppb levels of detection. Here we compare the use of Kr, Xe and I as "canary" species for distinguishing between ²³⁵U and ²³⁹Pu fission sources by spectroscopic methods.

The spectral post-processing algorithm Advanced Synthetically Enhanced Detector Resolution Algorithm (ASEDRA (patent pending)) has shown to be a powerful tool for deconvolving full energy peaks from scintillation spectrometeracquired gamma-ray spectra, effectively improving obtainable data-synthesized energy resolutions by a factor of four to six times over what is rendered from the detector. An isotope attribution algorithm, SmartID, was developed to augment ASEDRA in order to improve radionuclide identification accuracy. SmartID utilizes a novel, physics-based method of importance weighting the ASEDRA-identified peaks and the emissions of a candidate isotope. This methodology enhances the screening of potential false peaks and prevents isotope mismatches. As a final step, SmartID assigns a physical matching attribution score to each possible isotope match to reflect goodness-of-fit. A test suite of 105 gammaray spectra acquired with a 2"×2" NaI:Tl spectrometer under varying shielding conditions and various single and multisource configurations were recorded for testing the accuracy of ASEDRA+SmartID. The sources utilized in the tests included ¹³³Ba, ¹⁰⁹Cd, ⁵⁷Co, ⁶⁰Co, ¹³⁷Cs, ¹⁵²Eu, ⁵⁴Mn, ²²Na, ²³²Th, natural uranium rods and a PuBe source. Shielding configurations varied widely, ranging from none to more than 2.5cm Pb. Overall, SmartID proved to be more than 95% accurate in attributing the correct isotope(s) to the spectra.

Our team at the United States army research laboratory (ARL) has implemented the design and development of a low-power, compact, wireless-networked radiation sensor array. The sensor system was developed to provide high sensitivity event detection and remote warning for a broad range of radioactive materials. The sensor can identify the presence of 1μCi Cs¹³⁷ at a distance of 1.5m. The networked array operates well as a facility sensor however the architecture is designed to be operated outside the laboratory environment as well. The performance of the facility radiation measurement system is described and benchmarked to readily available check sources such as Cs¹³⁷.

The World Health Organization has reported that each year approximately 3 million people are poised by organophosphate substances (pesticides and nerve agents) resulting in 220,000 deaths. Organophosphates (OP) are toxic compounds which cause rapid and severe inhibition of serine proteases, most markedly acetylcholinesterase, which is vital to nerve function. This inhibition is often fatal. OP nerve agents are generally stable, easy to disperse, and highly toxic. They can be absorbed through the skin, by ingestion, or by respiration. A release of a nerve agent has the potential to rapidly affect a large number of people. The ease of manufacturing and dispensability of nerve agents, as well as available, inexpensive starting materials make these agents a weapon of choice for criminal terrorist attacks. One of the major steps toward protection against dangerous substances is to develop sensor devices that can act as an early warning system to the endangered people.

Arrays of atmospheric discharge cold plasma jets have been used to decontaminate surfaces of a wide range of microorganisms quickly, yet not damage that surface. Its effectiveness in decomposing simulated chemical warfare agents has also been demonstrated, and may also find use in assisting in the cleanup of radiological weapons. Large area jet arrays, with short dwell times, are necessary for practical applications. Realistic situations will also require jet arrays that are flexible to adapt to contoured or irregular surfaces. Various large area jet array prototypes, both planar and flexible, are described, as is the application to atmospheric decontamination.

Both real events and models have proven that drinking water systems are vulnerable to deliberate and/or accidental contamination. Additionally, homeland security initiatives and modeling efforts have determined that it is relatively easy to orchestrate the contamination of potable water supplies. Such contamination can be accomplished with classic and non-traditional chemical agents, toxic industrial chemicals (TICs), and/or toxic industrial materials (TIMs). Subsequent research and testing has developed a proven network for detection and response to these threats. The method uses offthe- shelf, broad-spectrum analytical instruments coupled with advanced interpretive algorithms. The system detects and characterizes any backflow events involving toxic contaminants by employing unique chemical signature (fingerprint) response data. This instrumentation has been certified by the Office of Homeland Security for detecting deliberate and/or accidental contamination of critical water infrastructure. The system involves integration of several mature technologies (sensors, SCADA, dynamic models, and the HACH HST Guardian Blue instrumentation) into a complete, real-time, management system that also can be used to address other water distribution concerns, such as corrosion. This paper summarizes the reasons and results for installing such a distribution-based detection and protection system.