The Journal of Chemical Thermodynamics
ISSN: 0021-9614
Datasets associated with articles published in The Journal of Chemical Thermodynamics
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- Data for: Molecular mechanism of the clathrate cage formation in structure-Ⅱ cyclopentane hydrate: an ab initio studyThe .mol files with the optimal structures selected in this paper are present in the compression package.
- Dataset
- Data for: Energetics of melting of Yb2O3 and Lu2O3 from Drop and Catch Calorimetry and First Principles ComputationsSupplementary information for manuscript "Energetics of melting of Yb2O3 and Lu2O3 from Drop and Catch Calorimetry and First Principles Computations" by Matthew Fyhrie, Qi-Jun Hong, Denys Kapush, Sergey V. Ushakov, Helena Liu, Axel van de Walle, Alexandra Navrotsky
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- Data for: Heat capacities and thermal diffusivities of some n-alkanoic acid methyl estersThe measured values of the thermal diffusivity for six n-alkanoic acid methyl esters are graphically compared with those calculated using the thermal conductivities measured by three authors.
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- Viscosities of experimental aqueous methanol mixturesIn order to make thermophysical properties of complex liquid mixtures available to a comprehensive analysis, we developed a data management and analysis platform based on the standard data exchange format ThermoML. The practicability of integrating thermophysical data from experiment and simulation was demonstrated for two binary mixtures, methanol-water and glycerol-water, by systematically studying the dependence of densities and diffusion coefficients from water content over the whole composition range and temperatures between 278.15 and 318.15 K. Experimental data was extracted manually from literature. The same parameter space was explored by comprehensive molecular dynamics simulations, whose results were directly transferred to the analysis platform. The benefit of data integration was illustrated by assessing the transferability of the force fields, which had been developed for pure compounds to different compositions and temperatures, and by analyzing the excess mixing properties as a measure of non-ideality of methanol-water and glycerol-water mixtures. The core of the data management and analysis platform is the newly developed Python library pyThermoML, which represents metadata, the parameters and the experimentally determined or simulated properties as Python data classes.
The feasibility of a seamless data flow from data acquisition to a comprehensive data analysis was demonstrated. PyThermoML enables interoperability and reusability of the datasets. The publication of ThermoML documents on the Dataverse installation of the University of Stuttgart (DaRUS) makes thermophysical data findable and accessible, and thus FAIR.
The usage of pyThermoML is demonstrated in the following example workflow and can be utilized to read the given ThermoML file.- Dataset
- CCDC 1885513: Experimental Crystal Structure DeterminationRelated Article: Carlos E.S. Bernardes, Mariana T. Donato, M. Fátima M. Piedade, Hermínio P. Diogo, José N. Canongia Lopes, Manuel E. Minas da Piedade|2019|J.Chem.Thermodynamics|133|60|doi:10.1016/j.jct.2019.01.016
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- CCDC 1885514: Experimental Crystal Structure DeterminationRelated Article: Carlos E.S. Bernardes, Mariana T. Donato, M. Fátima M. Piedade, Hermínio P. Diogo, José N. Canongia Lopes, Manuel E. Minas da Piedade|2019|J.Chem.Thermodynamics|133|60|doi:10.1016/j.jct.2019.01.016
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- CCDC 1826473: Experimental Crystal Structure DeterminationRelated Article: Wu Xiao-Hui, Ren Ning, Zhang Jian-Jun|2018|J.Chem.Thermodynamics|132|476|doi:10.1016/j.jct.2018.05.020
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- CCDC 1826474: Experimental Crystal Structure DeterminationRelated Article: Wu Xiao-Hui, Ren Ning, Zhang Jian-Jun|2018|J.Chem.Thermodynamics|132|476|doi:10.1016/j.jct.2018.05.020
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- CCDC 1876518: Experimental Crystal Structure DeterminationRelated Article: Jason J. Calvin, Peter F. Rosen, Stacey J. Smith, Brian F. Woodfield|2018|J.Chem.Thermodynamics|132|129|doi:10.1016/j.jct.2018.12.024
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- CCDC 1483923: Experimental Crystal Structure DeterminationRelated Article: Jian-Jun Zhang,Jin Cheng-Wei , Wang Ye , Ren Ning , Geng Li-Na |2017|CSD Communication|||
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