Viscosities of experimental aqueous glycerol mixtures


In 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.

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Metadata Access
Creator Gültig, Matthias ORCID logo; Range, Jan Peter ORCID logo; Schmitz, Benjamin ORCID logo; Pleiss, Jürgen ORCID logo
Publisher DaRUS
Contributor Gültig, Matthias; Pleiss, Jürgen
Publication Year 2022
Rights CC BY 4.0; info:eu-repo/semantics/openAccess;
OpenAccess true
Contact Gültig, Matthias; Pleiss, Jürgen (IBTB Universität Stuttgart)
Resource Type ThermoML; Dataset
Format text/xml
Size 105167
Version 1.0
Discipline Chemistry; Construction Engineering and Architecture; Engineering; Engineering Sciences; Natural Sciences; Physics