Biomimetic Optical-Filter Sensor System for Discrimination of Infrared Chemical Signatures Against a Cold Sky Background.

Passive infrared (IR) systems enable rapid detection of chemical vapors but are limited by size, weight, cost, and power. Previously, the authors reported a novel passive sensor that utilizes multiple IR filter/detector combinations to discriminate between different chemical vapors based on their unique IR absorption spectra in the same manner the human eye uses to generate colors. This approach enables a very small, compact, and low-power sensor system with the capability to discriminate between chemical vapors of interest and background chemicals. All previous work showed the capability of this sensor system in discriminating chemical vapors against a hot blackbody in a laboratory environment. Now the authors demonstrate the ability of this sensor system to discriminate between the chemical vapor agent simulant dimethyl methylphosphonate and ethanol against the cold sky in an outdoor environment.

Evaluation of Transmission Near the Christiansen Wavelength for Dynamic Sand Samples.

Many optical applications, including free-space optical communications, lidar, and astronomical measurements, are impacted by the presence of light-scattering particles also known as obscurants. Scattering from particles consisting of sand, dust, dirt, and other substances can significantly degrade optical signals. For many obscurants, the index of refraction is dependent on the wavelength of light, and there exists a Christiansen wavelength (λc) at which scattering is at a minimum. At λc the index of refraction of the scattering particles (ns) matches that of the surrounding medium, in this case air (with refractive index na). This condition makes the scattering particulates almost invisible to the propagating light, minimizing scattering and increasing transmission at λc. Previously, the authors showed a technique for measuring the index of refraction n(λ) and the extinction coefficient k(λ) using spectroscopic ellipsometry for various sand samples. Spectroscopic measurements on static sand samples demonstrated good agreement with the predicted spectral properties and highlighted the presence of a Christiansen feature near 8 µm. However, in outdoor environments, the scattering particles are never stationary but in a constant state of motion. In this work, spectroscopic measurements on dynamic sand samples (sand that is falling through the optical beam path) show two Christiansen features seen previously in predicted and observed static sand measurements. Additionally, we characterize, for the first time, transmission around a Christiansen feature using a tunable laser and show results consistent with other spectroscopic measurements.

Measurement of the Optical Constants of Sand Samples Using Ellipsometry on Sand-Adhesive Composites.

In order to model the propagation of light through a sand cloud, it is critical to have accurate data for the optical constants of the sand particles that comprise it. The same holds true for modeling propagation through particles of any type suspended in a medium. Few methods exist, however, to measure these quantities with high accuracy. In this paper, a characterization method based on spectroscopic ellipsometry (SE) that can be applied to a particulate material is presented. In this method, a polished disc of an adhesive compound is prepared, and its optical constants are measured. Next, a mixture of the adhesive and a sand sample is prepared and processed into a polished disc, and SE is performed. By treating the mixture as a Bruggeman effective medium, the optical constants of the particulate material are extracted. For verification of the proposed method, it is first applied to pure silica powder, demonstrating good agreement between measured optical constants and literature values. It is then applied to Arizona road dust, a standard reference material, as well as real desert sand samples. The resulting optical constant data is input into a rigorous scattering model to predict extinction coefficients for various types of sand. Modeling results are compared to spectroscopic measurements on static sand samples, demonstrating good agreement between predicted and measured spectral properties including the presence of a Christiansen feature near a wavelength of 8 µm.

Spectral Considerations for Standoff Infrared Detection of RDX on Reflective Aluminum.

This paper examines infrared spectroscopic effects for the standoff detection of an explosive material, hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), inkjet printed on an aluminum surface. Results of a spectroscopic study are described, using multiple optical setups. These setups were selected to explore how variations in the angles of incidence and collection from the surface of the material result in corresponding variations in the spectral signatures. The goal of these studies is to provide an understanding of these spectral changes since it affects standoff detection of hazardous materials on a reflective substrate. We demonstrate that variations in spectral effects are dependent on the relative surface concentration of the deposited RDX. We also show that it is reasonable to use spectroscopic data collected in a standard laboratory infrared spectrometer outfitted with a variable angle reflectometer set at 0° as reference spectra for data collected in a standoff configuration. These results are important to provide a systematic approach to understanding infrared (IR) spectra collection using standoff systems in the field, and to allow for comparison between such data, and data collected in the laboratory. Although the precise results are constrained to a specific material system (thin layers on a reflective substrate), the approach and general discussion provided are applicable to a broad range of IR standoff sensing techniques and applications.

Behavior of the Reststrahlen Band in the 17-25 µm Spectral Region in the Diffuse Reflection Spectra of Sand and Silt Mixtures.

Studies on the reflectance spectra of different mixtures of sand and silt were performed in the infrared spectral region of 7-25 µm to explore the behavior of a second reststrahlen band occurring between 17 and 25 µm with respect to different mixtures of sand and silt. The reflectance spectrum of all samples exhibited reststrahlen bands within both the long wavelength infrared (LWIR) and the very long wavelength infrared (VLWIR) regions of the reflectance spectrum. Results demonstrate that both LWIR and VLWIR reststrahlen bands increase in area as the fraction of sand increases to 80%. More importantly, the data demonstrate that the VLWIR reststrahlen band, like that in LWIR, exhibits a significant and reproducible decrease in reflectivity for mixed soil versus weathered soil.

Demonstration of a Human Color Vision Mimic in the Infrared.

Color vision results from the interaction of retinal photopigments with reflected or transmitted visible light. The International Commission on Illumination (CIE) developed the CIE color-matching chart, which separates colors on the basis of the interaction of their spectral profiles with three retinal photopigments in the human eye. We report the development of an infrared chromaticity (CIE-IR) chart, which mimics the CIE chart, in order to discriminate between different chemicals on the basis of the interactions of their IR signatures with three different IR optical filters, instead of the retinal photopigments in the human eye. Our results demonstrate that the CIE-IR chart enables separation of different classes of chemicals, as the visible CIE chart does with color, except for those in the IR spectral region. Such results clearly show that the biomimetic sensing method based on human color vision is in fact a true analogue to color vision and that the proposed CIE-IR chart can be used as a classification method unique to this biomimetic sensing modality.

Discrimination Between Explosive Materials and Isomers Using a Human Color Vision-Inspired Sensing Method.

This paper describes the application of a human color vision approach to infrared (IR) chemical sensing for the discrimination between multiple explosive materials deposited on aluminum substrates. This methodology classifies chemicals using the unique response of the chemical vibrational absorption bands to three broadband overlapping IR optical filters. For this effort, Fourier transform infrared (FT-IR) spectroscopy is first used to computationally examine the ability of the human color vision sensing approach to discriminate between three similar explosive materials, 1,3,5,-Trinitro-1,3,5-triazinane (RDX), 2,2-Bis[(nitrooxy)methyl]propane-1,3,-diyldinitrate (PETN), and 1,3,5,7-Tetranitro-1,3,5,7-tetrazocane (HMX). A description of a laboratory breadboard optical sensor designed for this approach is then provided, along with the discrimination results collected for these samples using this sensor. The results of these studies demonstrate that the human color vision approach is capable of high-confidence discrimination of the examined explosive materials.

Infrared Reflectance Spectroscopic Evaluation of Inkjet Printed Standards of Cyclotrimethylenetrinitramine (RDX) on Aluminum Substrates.

The Department of Defense (DOD) and first responder communities are evaluating and developing optical systems for the detection and identification of explosives and components used for assembling homemade explosives (HMEs). Emerging detection technologies must be evaluated with authentic hazard material concentrations to ensure their accurate and reliable use in the field. In this work, infrared (IR) reflectance spectra over the spectral rage of 1000-1700 cm-1 were collected for different concentrations of inkjet-printed RDX (cyclotrimethylenetrinitramine) samples deposited onto aluminum substrates. A plot of the integrated area of both the symmetric and asymmetric NO2 vibrational bands for RDX on aluminum exhibited good linearity over the concentration range 20-500 µg/cm2. Detection limits for RDX on an aluminum surface were calculated to be 10.7 µg/cm2 for the symmetric NO2 vibrational band and 1.4 µg/cm2 for the asymmetric NO2 vibrational band. Evaluation of the NO2 vibrational band areas at different locations of the RDX array demonstrated that the samples exhibited good homogeneity across the surface. The concentration of an unknown sample of RDX on aluminum was determined using the fitted equations; results showed good agreement between the calculated and actual RDX surface concentration. The lot-to-lot variation of RDX on the aluminum surface was compared using the long wavelength infrared (LWIR) spectral band areas for two different lots of standards printed at the same RDX surface concentration. Results showed excellent lot-to-lot agreement indicating good reproducibility of the standards for RDX.

Analytical procedure to assess the performance characteristics of a non-spectroscopic infrared optical sensor for discrimination of chemical vapors.

An optical-filter-based sensor that was designed to mimic human color vision was recently developed. This sensor uses three mid-infrared optical filters to discriminate between chemicals with similar, strongly overlapping mid-infrared absorption bands. This non-spectroscopic technique requires no spectral scanning. This paper defines the selectivity and specificity of this biomimetic sensor. Receiver operating characteristic curves are presented for each target chemical. These results demonstrate that the sensor is highly selective and can provide discrimination with no false positives for three similar target chemicals-acetone, hexane, and fuel oil-while rejecting potential interferents.

Optical filter selection for high confidence discrimination of strongly overlapping infrared chemical spectra.

Optical filter-based chemical sensing techniques provide a new avenue to develop low-cost infrared sensors. These methods utilize multiple infrared optical filters to selectively measure different response functions for various chemicals, dependent on each chemical's infrared absorption. Rather than identifying distinct spectral features, which can then be used to determine the identity of a target chemical, optical filter-based approaches rely on measuring differences in the ensemble response between a given filter set and specific chemicals of interest. Therefore, the results of such methods are highly dependent on the original optical filter choice, which will dictate the selectivity, sensitivity, and stability of any filter-based sensing method. Recently, a method has been developed that utilizes unique detection vector operations defined by optical multifilter responses, to discriminate between volatile chemical vapors. This method, comparative-discrimination spectral detection (CDSD), is a technique which employs broadband optical filters to selectively discriminate between chemicals with highly overlapping infrared absorption spectra. CDSD has been shown to correctly distinguish between similar chemicals in the carbon-hydrogen stretch region of the infrared absorption spectra from 2800-3100 cm(-1). A key challenge to this approach is how to determine which optical filter sets should be utilized to achieve the greatest discrimination between target chemicals. Previous studies used empirical approaches to select the optical filter set; however this is insufficient to determine the optimum selectivity between strongly overlapping chemical spectra. Here we present a numerical approach to systematically study the effects of filter positioning and bandwidth on a number of three-chemical systems. We describe how both the filter properties, as well as the chemicals in each set, affect the CDSD results and subsequent discrimination. These results demonstrate the importance of choosing the proper filter set and chemicals for comparative discrimination, in order to identify the target chemical of interest in the presence of closely matched chemical interferents. These findings are an integral step in the development of experimental prototype sensors, which will utilize CDSD.

Comparative discrimination spectral detection method for the identification of vapors using overlapping broad spectral filters.

We present a comparative discrimination spectral detection approach for the identification of chemical vapors using broad spectral filters. We applied the method to flowing vapors of as-received and non-interacting mixtures for the detection of the volatile components of a target chemical in the presence of interferents. The method is based on measurements of the overall spectral signature of the vapors, where the interferent spectrum largely overlaps the target spectrum. In this work we outline the construction of a set of abstract configuration-space vectors, generated by the broadband spectral components from sampled chemical vapors, and the subsequent vector-space operations between them, which enable the detection of a target chemical by comparative discrimination from interferents. The method was applied to the C-H vibrational band from 2500 to 3500 cm(-1), where there is large spectral signal overlap between the chosen target chemical and two interferents. Our results show clear detection and distinction of the target vapors without ambiguity.