Measurement of infrared refractive indices of organic and organophosphorous compounds for optical modeling

Tonkyn, Russell G.; Danby, Tyler O.; Birnbaum, Jerome L.; Taubman, Matthew S.; Bernacki, Bruce E.; Johnson, Timothy J.; Myers, Tanya L.

doi:10.1117/12.2264384

Cited by 3 publications

(3 citation statements)

References 16 publications

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“…In some cases, the n and k optical constants data for the substrate such as the aluminum substrate have been retrieved from literature databases. 23 As has been described elsewhere, 24,25 the n and k data for liquids are generated in our laboratory using methods first developed by Bertie et al 26 whereby a series of different liquid cells with path lengths ranging from 2 to 4,000 µm are used to generate a linear response in the k component; different bands are combined in the cumulative fit, using the many path lengths to select bands that have good signal but are not saturated. The Kramers-Kronig transform (KKT) is applied to generate associated n and (iteratively) k data.…”

Section: Obtaining the Optical Constantsmentioning

confidence: 99%

Using synthetic infrared spectra derived from n/k optical constants for standoff detection of chemical deposits

Lonergan

Erickson

Kelly-Gorham

et al. 2023

Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XXIV

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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.

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Section: Obtaining the Optical Constantsmentioning

confidence: 99%

Using synthetic infrared spectra derived from n/k optical constants for standoff detection of chemical deposits

Lonergan

Erickson

Kelly-Gorham

et al. 2023

Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XXIV

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“…The results are in part validated by the high fidelity of the reference data, and we exploit these properties: For example, in the PNNL liquids and solids spectral databases, all data were recorded at higher spectral resolution than might be expected for field data, i.e., at resolutions narrower than the natural bandwidths so the reported resolutions represent intrinsic linewidths with negligible contributions from the instrumental lineshape. 3,4 That is to say, while most field data will be a convolution of instrument and intrinsic lineshapes, we emphasize that only for database data is it important that the spectra be recorded at a greater resolution than expected; while the reference data can always be de-resolved, it is important that such data not be the limiting factor in the specificity. 1,2 Recording data at lower resolution can provide significantly improved SNR and perhaps improved results, but can also sacrifice specificity.…”

Section: Introductionmentioning

confidence: 99%

“…Fourier transform (FT) methods have to some extent replaced dispersive modes of infrared (IR) spectroscopy, including for detection of gases, 1,2 liquids, 3,4 and solids, 5–7 but with the advent of charge-coupled devices, dispersive instruments are seeing a resurgence. For both FT and dispersive systems the number of sampling methods, accessories, and methodologies has become large; most sampling methods have found ways to adapt the IR beam such that in a non-invasive, non-destructive manner the IR light can interact with a sample, often for identification purposes only.…”

Section: Introductionmentioning

confidence: 99%

Optimal Spectral Resolution for Infrared Studies of Solids and Liquids

Forland,

Hughey,

Wilhelm

et al. 2024

Appl Spectrosc

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Due to a legacy originating in the limited capability of early computers, the spectroscopic resolution used in Fourier transform infrared spectroscopy and other systems has largely been implemented using only powers of two for more than 50 years. In this study, we investigate debunking the spectroscopic lore of, e.g., using only 2, 4, 8, or 16 cm−1 resolution and determine the optimal resolution in terms of both (i) a desired signal-to-noise ratio and (ii) efficient use of acquisition time. The study is facilitated by the availability of solids and liquids reference spectral data recorded at 2.0 cm−1 resolution and is based on an examination in the 4000–400 cm−1 range of 61 liquids and 70 solids spectra, with a total analysis of 4237 peaks, each of which was also examined for being singlet/multiplet in nature. Of the 1765 liquid bands examined, only 27 had widths <5 cm−1. Of the 2472 solid bands examined, only 39 peaks have widths <5 cm−1. For both the liquid and solid bands, a skewed distribution of peak widths was observed: For liquids, the mean peak width was 24.7 cm−1 but the median peak width was 13.7 cm−1, and, similarly, for solids, the mean peak width was 22.2 cm−1 but the median peak width was 11.2 cm−1. While recognizing other studies may differ in scope and limiting the analysis to only room temperature data, we have found that a resolution to resolve 95% of all bands is 5.7 cm−1 for liquids and 5.3 cm−1 for solids; such a resolution would capture the native linewidth (not accounting for instrumental broadening) for 95% of all the solids and liquid bands, respectively. After decades of measuring liquids and solids at 4, 8, or 16 cm−1 resolution, we suggest that, when accounting only for intrinsic linewidths, an optimized resolution of 6.0 cm−1 will capture 91% of all condensed-phase bands, i.e., broadening of only 9% of the narrowest of bands, but yielding a large gain in signal-to-noise with minimal loss of specificity.

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Advances in active infrared spectroscopy for trace chemical detection

DeWitt¹

2019

Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imagery XXV

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Measurement of infrared refractive indices of organic and organophosphorous compounds for optical modeling

Cited by 3 publications

References 16 publications

Using synthetic infrared spectra derived from n/k optical constants for standoff detection of chemical deposits

Using synthetic infrared spectra derived from n/k optical constants for standoff detection of chemical deposits

Optimal Spectral Resolution for Infrared Studies of Solids and Liquids

Advances in active infrared spectroscopy for trace chemical detection

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