2 Pure Liquids: References

Wohlfarth, Ch.; Wohlfarth, B.

doi:10.1007/10522151_8

Cited by 2 publications

(8 citation statements)

References 998 publications

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“…References. (a) Lias (2023); (b) Rumble (2022); (c) Krause & Friedrich (1972); (d) Smyth & McNeight (1936); (e) this work, estimated; (f) Würflinger (1980); (g)Wohlfarth et al (1996); and (h)Kroenlein et al (2011).…”

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confidence: 92%

Material Properties of Organic Liquids, Ices, and Hazes on Titan

Garver

et al. 2023

ApJS

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Titan has a diverse range of materials in its atmosphere and on its surface: the simple organics that reside in various phases (gas, liquid, and ice) and the solid complex refractory organics that form Titan’s haze layers. These materials all actively participate in various physical processes on Titan, and many material properties are found to be important in shaping these processes. Future in situ explorations on Titan would likely encounter a range of materials, and a comprehensive database to archive the material properties of all possible material candidates will be needed. Here, we summarize several important material properties of the organic liquids, ices, and the refractory hazes on Titan that are available in the literature and/or that we have computed. These properties include thermodynamic properties (phase-change points, sublimation and vaporization saturation vapor pressure, and latent heat), and physical properties (organic liquid densities and organic ice and haze densities). We have developed a new database to provide a repository for these data and make them available to the science community. These data can be used as inputs for various theoretical models to interpret current and future remote sensing and in situ atmospheric and surface measurements on Titan. The material properties of the simple organics may also be applicable to giant planets and icy bodies in the outer solar system, interstellar medium, protoplanetary disks, and exoplanets.

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confidence: 92%

Material Properties of Organic Liquids, Ices, and Hazes on Titan

Garver

et al. 2023

ApJS

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“…Consequently, their RI was checked in the literature from at least two different sources. It turns out that the values found either in Reaxys [32], CAS [35], or Landolt [34] are concordant but in disagreement with the values listed in the CRC database. The new values are then retained for the final RMSE test calculations.…”

Section: Rectification Of the Datasetsmentioning

confidence: 91%

“…The first required step for machine learning simulation is the construction of the training set. To that end, several refractive index sources were used [20,32,34,35,40,41], the most important being the Tokyo Chemical Industry (TCI) dataset [20]. Thus, the training and test sets accessible in Bouteloup's paper, made up of 3622 and 3621 liquids, respectively, were first used in the present study.…”

Section: Methodsmentioning

confidence: 99%

“…Thus, the training and test sets accessible in Bouteloup's paper, made up of 3622 and 3621 liquids, respectively, were first used in the present study. These compounds were extracted from chemical supplier TCI's 2018 online catalog because they had a measured refractive index (RI) there and because they were in the liquid state at 20 • C. The wavelength at which the measurements were made was not specified, but comparison of numerous values with those from reliable sources [32,34] confirms that it is that of the sodium D line, i.e., 589 nm.…”

Section: Methodsmentioning

confidence: 99%

“…As the range of refractive index values is quite narrow (1.296 to 1.687), it is important to find the appropriate balance between the accuracy of the measured values for a compound and their standard deviation when several experimental values are published. Analysis of several dozen compounds for which at least five different refractive index values were measured [34] reveals a standard deviation of measurement in most cases above 0.001. Therefore, all index values from now on will be rounded off to three decimal places.…”

Section: Methodsmentioning

confidence: 99%

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Fast and Accurate Prediction of Refractive Index of Organic Liquids with Graph Machines

Duprat,

Ploix,

Aubry

et al. 2023

Molecules

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The refractive index (RI) of liquids is a key physical property of molecular compounds and materials. In addition to its ubiquitous role in physics, it is also exploited to impart specific optical properties (transparency, opacity, and gloss) to materials and various end-use products. Since few methods exist to accurately estimate this property, we have designed a graph machine model (GMM) capable of predicting the RI of liquid organic compounds containing up to 16 different types of atoms and effective in discriminating between stereoisomers. Using 8267 carefully checked RI values from the literature and the corresponding 2D organic structures, the GMM provides a training root mean square relative error of less than 0.5%, i.e., an RMSE of 0.004 for the estimation of the refractive index of the 8267 compounds. The GMM predictive ability is also compared to that obtained by several fragment-based approaches. Finally, a Docker-based tool is proposed to predict the RI of organic compounds solely from their SMILES code. The GMM developed is easy to apply, as shown by the video tutorials provided on YouTube.

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2 Pure Liquids: References

Cited by 2 publications

References 998 publications

Material Properties of Organic Liquids, Ices, and Hazes on Titan

Material Properties of Organic Liquids, Ices, and Hazes on Titan

Fast and Accurate Prediction of Refractive Index of Organic Liquids with Graph Machines

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