Accurate optical constants for liquids in the near-infrared:Improved methods for obtaining the n and k constants from 1 to 4 µm

Myers, Tanya L.; Tonkyn, Russell G.; Loring, John S.; Oeck, Ashley M.; Banach, Catherine A.; Francis, Robert C.; Su, Yin‐Fong; Johnson, Timothy J.

doi:10.1117/12.2519499

Cited by 7 publications

(6 citation statements)

References 10 publications

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“…The nðνÞ and kðνÞ vectors that are used in the models described here were obtained from the PNNL database of optical constants. 8,19,20 This database consists of a set of n∕k spectra for a rather large collection of liquids of different chemical varieties: organics, inorganics, polar, nonpolar viscous, etc. The liquids n∕k data 8 were derived using improved methods originally developed by Bertie et al, 21,22 whereby a series of absorption spectra are recorded from liquid cells of fixed path lengths, and the scalar refractive index n is also measured using an Abbe refractometer.…”

Section: Experimental Methodsmentioning

confidence: 99%

Modeling thin layers of analytes on substrates for spectral analysis: use of solid/liquid n and k values to model reflectance spectra

2020

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Since solids are only sometimes seen en masse in a pure bulk form, and for liquids other than water almost never, a capability to model reflectance spectra from analytes deposited on various substrates would be highly advantageous. If available, the real, nðνÞ, and imaginary, kðνÞ, components of the complex refractive index, n ∼ ¼ n þ ik, can be used to simulate infrared spectra, accounting for reflection, refraction, and absorption phenomena as a function of wavelength. We focus on using the Pacific Northwest National Laboratory (PNNL) derived n∕k vectors for solid and liquid analytes deposited as thin layers on different types of substrates including conductors, such as aluminum, and inorganic dielectrics, such as glass. The model is an adaptation of the Monte Carlo ray trace modeling program, TracePro, extended through the use of its macrolanguage. The model is tested using thin films of organic liquids including silicone oil and no. 2 diesel fuel, as well as organic solids such as caffeine and acetaminophen on aluminum and glass. The predicted spectra for the solid films were compared to experimental hemispherical reflectance data measured using a Fourier transform spectrometer with an integrating sphere. The thickness of the calculated layer is a parameter for predicting the (transflectance) spectra and is obtained using the areal density measured from gravimetric methods to generate the thin-layer samples. Comparison of the calculated spectra with experimental hemispherical reflectance data shows excellent agreement, indicating promise for the use of measured n∕k data to synthesize reference spectral data. In particular, accounting for the inhomogeneity of the deposits greatly improved the match with experimental data. Finally, the theoretical modeling shows that for thicker layers (ca. 20 to 100 μm) of typical organics possessing moderately strong k values, the longwave infrared features are often saturated and better spectral contrast is obtained from the overtone/combination bands in the shortwave infrared. © The Authors.Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Section: Experimental Methodsmentioning

confidence: 99%

Modeling thin layers of analytes on substrates for spectral analysis: use of solid/liquid n and k values to model reflectance spectra

2020

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“…The datasets (Table S2, Supplemental Material) represent several different modalities and instruments. In the PNNL libraries, the liquid-phase data are provided as n and k data (real and imaginary components of the refractive index, respectively) using methods originally developed in the 1990s by Bertie and colleagues, 45,46 and later improved by Myers et al 47 to obtain both greater spectral range and greater dynamic range in the k values. It is the k vector spectra that are used in this study to measure the peak widths.…”

Section: Pnnl Spectral Librariesmentioning

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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“…near the baseline. 50 The real part of the complex index of refraction (n) was determined by first measuring the n-values for the binary mixtures at 480, 486, 546, 589, 644, 656 and 1550 nm using an ATAGO refractometer. A modified-Sellmeier equation was then used to interpolate n at 10 000 cm À1 .…”

Section: Experimentally-derived Optical Constantsmentioning

confidence: 99%

Influence of intermolecular interactions on the infrared complex indices of refraction for binary liquid mixtures

Myers

Bernacki

Wilhelm

et al. 2022

Phys. Chem. Chem. Phys.

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Accurate optical constants for liquids in the near-infrared:Improved methods for obtaining the n and k constants from 1 to 4 µm

Cited by 7 publications

References 10 publications

Modeling thin layers of analytes on substrates for spectral analysis: use of solid/liquid n and k values to model reflectance spectra

Modeling thin layers of analytes on substrates for spectral analysis: use of solid/liquid n and k values to model reflectance spectra

Optimal Spectral Resolution for Infrared Studies of Solids and Liquids

Influence of intermolecular interactions on the infrared complex indices of refraction for binary liquid mixtures

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