Hyperspectral imaging (HSI) data cubes are typically evaluated via methods whereby the processed spectral data are matched via some algorithm to libraries of hundreds/thousands of reflectance or emittance spectra of solids, in which the reference data often consist of pure chemicals of just one morphology and are often recorded for a specific application. We introduce an approach that can conveniently account for many different sample forms. Specifically, we demonstrate that different sample morphologies can be detected with high efficacy using "synthetic" spectra generated from physical constants and fundamental laws of optics. Experimental HSI data of thin-layer analyte chemical samples were evaluated using physics-based synthetic infrared spectra calculated from the optical n and k vectors in combination with absorption and reflection models. Besides the outdoor HSI data, hemispherical reflectance spectra were also collected in the laboratory using the same sample planchets. When evaluating the HSI standoff data using the synthetic spectra from two such models, the analysis found chemical identification to be nearly perfect. Both optical models could not only detect the target analyte chemicals but were also able to estimate a layer thickness that was found to be in quite good agreement (few micrometer level or better).

The effects of light scattering and refraction make it challenging to identify aerosolized chemicals using traditional spectral methods and reference libraries. Due to an infinite number of aerosol sizes, shapes and compositions, constructing a database of laboratory-measured reference spectra is not feasible. As an alternative approach, the measured wavelength-dependent n/k can be used in combination with photon absorption / scattering theory and the Beer-Lambert law to generate a series of synthetic infrared transmission / scattered light spectra. These synthetic spectra show that aerosol particle spectral signatures, for either transmission or scattering measurements, have distinct overall shapes as well as shifted peak positions and amplitudes compared to the reference data from bulk transmission measurements. To validate our synthetic signatures based on the derived n/k values, well-characterized aerosols of dioctyl sebacate are generated, and the spectral transmittance data are recorded for comparison.

Infrared spectroscopy is a well-established method for identifying solid, liquid, and gas-phase chemicals. Accurate infrared spectroscopic analysis requires reference libraries where library endmembers reflect all optical phenomena contributing to the observed spectra. Traditional spectral libraries most often contain molecular-based absorption spectra, but these do not account for the complex scattering effects that become significant when measuring aerosols. In this work, we combine the laboratory-derived, wavelength-dependent complex optical vectors (n/k) of liquid dioctyl sebacate (DOS) with Mie scattering theory and the Beer-Lambert law to generate synthetic infrared transmission spectra of aerosolized DOS. Additionally, we record experimental infrared transmission spectra using an FTIR spectrometer coupled to a simple aerosol chamber filled with a quantified number size distribution of aerosolized DOS. The modeled and measured spectra show strong agreement, with Mie scattering effects clearly altering the overall spectral shape as well as the positions and profiles of absorption features. The results demonstrate that synthetic spectra generated from n/k values can reliably capture aerosol-specific spectral behavior and thus serve as a foundation for building scalable, physics-based aerosol reference libraries to enable infrared spectroscopic detection of aerosols.

Identification of solids via infrared reflection spectroscopy requires a spectral library of all solids likely to be encountered. A confounding factor in populating such a spectral library is that the reflectance spectra of solids vary with their form, including particle size, film thickness, and substrate. To reduce the efforts of experimentally constructing such a library, an alternate strategy is to use the wavelength-dependent optical constants, n and k, of a solid to calculate a series of reflectance spectra corresponding to each scenario or morphology. Because most n/k measurements are best performed on mm-sized crystals, however, the challenge of determining the optical constants increases when a solid is only readily available as a powder, as is often the case. Some organic solids, such as caffeine, are both unavailable in large crystals and difficult to press into pellets. In this study, the infrared optical constants, or complex refractive indices, of caffeine were determined using three different methods: single-angle reflectance, infrared spectroscopic ellipsometry, and quantitative absorbance measurements of KBr pellets. The n and k values derived through each method were used to model the hyperspectral imaging reflectance spectrum of a caffeine film on a steel planchet. Over 1,110 - 870 cm(-1), the single-angle reflectance-derived n and k had the best correlation with the experimental spectrum. These results suggest different organic solids may require different methods to determine the most accurate infrared complex refractive indices for synthetic spectral libraries.

Spectroscopic identification of aerosolized chemical threats is challenging due to the complex nature of the photon/particle interaction, as well as the diversity of possible particle sizes, morphologies, and compositions. Constructing a database of laboratory - measured transmittance spectra that covers each permutation is not practical. However, calculation of the spectra using the measured optical constants as a function of wavenumber, n(nu) and k(nu), for each of the liquids and/or solids composing the aerosol particles provides a viable alternative. These synthetic spectra (vis-a-vis laboratory-measured spectra) can be used to identify chemicals of interest and subtract out background interferents in field measurements. Using a well-established multiple pathlength approach, we measure the optical constants n/k for liquids that may be found as chemical species of interest or common background interferents aerosolized in plumes. These measurements are also used to generate several test case aerosol synthetic spectra.

The effects of light scattering and refraction play significantly different roles for aerosols than for bulk materials, making it challenging to identify aerosolized chemicals using traditional spectral methods or spectral reference libraries. Due to a potentially infinite number of particle morphologies, sizes, and compositions, constructing a database of laboratory-measured aerosol spectra is not a practical solution. Here, as an alternative approach, the measured n / k optical vectors of two example organic materials (diethyl phthalate and D-mannitol) are used in combination with particle absorption / scattering theory (Mie theory and FDTD) and the Beer-Lambert law to generate a series of synthetic infrared transmission / scattered light spectra. The synthetic spectra show significant differences versus simple slab transmission spectra, even for small changes in particle size (e.g., 5 vs. 10 mu m) for both single particles and ensembles, potentially serving as useful reference data for aerosol sensing. For spherical single particles with diameters of 1 to 10 mu m, FDTD simulations predict changes in the magnitudes of spectral shifts and the shapes of the peaks vs. particle size with only small deviations from Mie theory predictions, yet reliably capture the direction of the shifts. Typical spectral peak shifts in the longwave infrared correspond to triangle lambda- 0.20 mu m (-34- 34 cm-1) - 1 ) when compared to corresponding slab transmission spectra. Additionally, synthetic spectra generated from the n / k values derived using two different methods (KBr pellet transmission and single-angle reflectance) are compared using the Mie theory model. (c) 2024 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

Reflectance spectroscopy, especially at infrared wavelengths, is often used for contact, standoff, and remote sensing of solid materials. The reflectance spectra of solids, however, are complex, relying on many factors, even for the same material. Such phenomena can be modeled if the optical constants as a function of wavelength or wavenumber, n(ν) and k(ν), are known. Methods to measure the optical constants of solids, however, are challenging, particularly for powdered materials. For powdered materials, a pressed pellet of the neat material is often used when a crystalline specimen is not available. In this work, three techniques, including ellipsometry, single-angle reflectance and KBr transmission spectroscopy, are applied to an organic material, acetaminophen, for comparison, and the effects on the modeled spectra are shown.

Detection of analytes deposited on surfaces is crucial for many applications: Development of methods to prepare thin layers (e.g. ~5 to 100 μm) is important for both system design and field studies. In this work, solid and liquid analytes were deposited on painted and bare substrates including aluminum, glass, plastic, and concrete using an ExactaCoat ultrasonic spray coater. Laboratory hemispherical reflectance (HRF) spectra were collected for samples with different layer thicknesses so as to characterize both the composition and layer thickness. Preliminary results demonstrate that to prepare homogenous layers on surfaces, parameters such as substrate type, analyte solubility, vapor pressure, paint color, surface porosity, and surface roughness are all important. Liquid chemicals posed several issues during deposition: Diisopropyl methyl phosphonate evaporated from surfaces more quickly than the other chemicals and was thus not detected in the HRF experiments. Less volatile liquids, such as tributylphosphate, remained on the surface for the duration of the test, but a uniform layer thickness could not be obtained as the liquid pooled to one side when mounted at an angle. The deposition of solids (e.g., acetaminophen, caffeine and methylphosphonic acid) from volatile solvents such as chloroform also proved problematic due to streaking caused by rapid solvent evaporation. Solids deposited from ethanol, however, worked well on bare substrates. For most samples plotting the integrated infrared band strength vs. surface thicknesses showed a linear relationship, confirming that the surface loading can be controlled by programming the concentration and the number of passes on the ultrasonic sprayer.

We report results from a recent field experiment to test the validity of using physics-based synthetic infrared spectra to serve as endmembers in a spectral database targeted at chemical deposits. Specifically, the optical constants n and k, (the real and imaginary part of the refractive index) were used to first model infrared reflectance spectra for different thicknesses of chemical layers (e.g. acetaminophen, methylphosphonic acid – MPA, etc.) on various conducting and insulating substrates such as aluminum, wood, and glass. In the experimental portion of the research, thin films of the solid and liquid analytes were deposited onto such substrates to form micron-thick layers of the analytes at different thicknesses: Standoff data from an imaging instrument were then recorded and analyzed to not only identify the different analytes, but also quantify the layer/deposit thickness. To gauge success, the detection results using the synthetic data were compared to the results from laboratory hemispherical reflectance (HRF) spectra that were collected for the same sample planchets measured in the field via standoff methods. Preliminary results indicate good agreement between the synthetic reference data as compared to the lab-measured HRF data in terms of their ability to quantitatively reduce longwave infrared data. Specifically, modeled IR spectra for acetaminophen on an aluminum planchet at various thicknesses (1, 2, 5, 10, 15, and 20 μm) were synthesized and compared with standoff field reflectance data as well as HRF laboratory reflectance spectra for two samples: a 5.2 μm- and 12.8 μm-thick layer of acetaminophen on aluminum. Using a first-order approximation, analysis of the field data estimates the thicknesses of the samples to be 2 and 10 μm for the two samples, respectively, while the HRF laboratory data yields thickness estimates of between 5-10 μm and 10 μm, respectively. Both yield reasonable estimates, with the uncertainty most likely due to factors yet to be accounted for in the synthetic spectra such as light scattering.

Direct comparisons are made between an active laser-based swept-wavelength ECQCL and passive LWIR hyperspectral imager for dynamic chemical plume detection at a standoff distance of 1.5 km in complex terrain.

This paper investigates the accuracy of deriving the composite optical constants of binary mixtures from only the complex indices of refraction of the neat materials. These optical constants enable the reflectance spectra of the binary mixtures to be modeled for multiple scenarios (e.g., different substrates, thicknesses, volume ratios), which is important for contact and standoff chemical detection. Using volume fractions, each mixture's complex index of refraction was approximated via three different mixing rules. To explore the impact of intermolecular interactions, these predictions are tested by experimental measurements for two representative sets of binary mixtures: (1) tributyl phosphate combined with n-dodecane, a non-polar medium, to represent mixtures which primarily interact via dispersion forces and (2) tributyl phosphate and 1-butanol to represent mixtures with polar functional groups that can also interact via dipole-dipole interactions, including hydrogen bonding. The residuals and the root-mean-square error between the experimental and calculated index values are computed and demonstrate that for miscible liquids in which the average geometry of the cross-interactions can be considered isotropic (e.g., dispersion), the refractive indices of the mixtures can be modeled using composite n and k values derived from volume fractions of the neat liquids. Conversely, in spectral regions where the geometry of the cross-interactions is more restricted and anisotropic (e.g., hydrogen bonding), the calculated n and k values vary from the measured values. The impact of these interactions on the reflectance spectra are then compared by modeling a thin film of the binary mixtures on an aluminum substrate using both the measured and the mathematically computed indices of refraction.

Recently, significant advances have been made in designing high-temperature capable nuclear fuels. In parallel, important advances have occurred in design of nanophotonic structures (coatings) with ability to shape the frequencies of light being emitted from hot surfaces. In this project, we bring these materials advances together into a design for a new direct conversion nuclear powered system with high thermodynamic efficiency, inherent safety, and unprecedented reduction in size and weight relative to current designs. The concept involves using the heat generated from nuclear fission to raise the temperature of a selective thermal emitter to >800°C. The selective emitter shifts the normal broad brand emissions of light from its hot surface into the correct near- and mid-IR bands that produce electricity with inexpensive photovoltaic cells. We have designed a new annular flow Lead Fast Reactor (LFR) that minimizes overall reactor/power conversion footprint. The results indicate that the overall microreactor/power-system design offers a 2X reduction in size over existing technology that is based on the sCO2 reverse compression Brayton cycle. Additionally, the only moving part in our design is a circulation pump to cool the PVT panels.

Chemical plume detection and modeling in complex terrain present numerous challenges. We present experimental results from outdoor releases of two chemical tracers (sulfur hexafluoride and Freon-152a) from different locations in mountainous terrain. Chemical plumes were detected using two standoff instruments collocated at a distance of 1.5 km from the plume releases. A passive long-wave infrared hyperspectral imaging system was used to show time- and space-resolved plume transport in regions near the source. An active infrared swept-wavelength external cavity quantum cascade laser system was used in a standoff configuration to measure quantitative chemical column densities with high time resolution and high sensitivity along a single measurement path. Both instruments provided chemical-specific detection of the plumes and provided complementary information over different temporal and spatial scales. The results show highly variable plume propagation dynamics near the release points, strongly dependent on the local topography and winds. Effects of plume stagnation, plume splitting, and plume mixing were all observed and are explained based on local topographic and wind conditions. Measured plume column densities at distances ~100 m from the release point show temporal fluctuations over ~1 s time scales and spatial variations over ~1 m length scales. The results highlight the need for high-speed and spatially resolved measurement techniques to provide validation data at the relevant spatial and temporal scales required for high-fidelity terrain-aware microscale plume propagation models.

To support stand-off detection, spectral libraries are being developed that include the optical constants, n(ν) and k(ν). Variable angle spectroscopic ellipsometry and single-angle reflectance are used to derive these data, enabling the reference spectra to be modeled for different parameters.

This report describes a preliminary analysis on the utility of modern capabilities to localize radiological sources in a marine environment. This study analyzed expected background sources and identified possible approaches based on modeling and simulation analyses. The effort culminated in the design and fabrication of validation experiments which provided favorable supporting data. The conclusions of this effort are not conclusive as to the viability of the approach, but neither is the underlining hypothesis disproved. Continuation of the experimental approach is recommended with a focus on open-water experimentation.

This paper updates recent work to populate spectral databases for (near-) infrared sensing of solids in different modalities including passive and active sensing of minerals, ores and other mining chemicals and minerals.

Binary mixtures of liquids may be encountered in industrial or remote sensing scenarios and present challenges to positive identification compared to neat single-component liquids. Our investigation examines whether one can predict the optical properties of the mixture, i.e. its complex index of refraction, by assuming a linear superposition of the real and imaginary components of the index of refraction in proportion to the ratio of each constituent. To investigate this hypothesis various liquid mixtures were created using mass ratios. The mixtures were then characterized as to their complex index of refraction and used in numerical modeling calculations of thin liquid mixture films on surfaces and compared with composed mixtures using linear n and k synthetic mixtures where the n and k components of the complex index of refraction were combined in similar ratios. The comparison of modeling and experimental results is presented with recommendations for further investigation.

This paper presents the methods for developing synthetic spectral libraries using the real n(λ) and imaginary k(λ) parts of the complex refractive index for sensors, including hyperspectral sensors, and presents results for solid materials.

Knowledge of the bulk optical constants n and k of solids or liquids allows researchers to accurately predict the absorption, reflection, and scattering properties of materials for different physical forms. Indeed, chemically complex materials such as minerals can have an almost limitless variety of morphologies, particle sizes, shapes, and compositions, and the optical properties of such species can be predicted if the optical constants are known. For species such as minerals, there can be additional challenges due to e.g. hydration or dehydration during the course of the optical constants measurement. Here, we describe the protocols to obtain the bulk optical constants n and k of uranium-bearing minerals and ores such as uraninite or autunite. If quality n and k data are at hand, the (infrared) reflectance spectra can be predicted for different particle sizes and morphologies and the modeling results for various scenarios can be derived.