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The Gibbs energy of solvation measures the affinity of a solute for its solvent and isthus a key property for the selection of an appropriate solvent for a chemical synthesis ora separation process. More fundamentally, Gibbs energies of solvation are choice data fordeveloping and benchmarking molecular models predicting solvation effects.
The Comprehensive Solvation—CompSol—database was developed with the ambition topropose very large sets of new experimental solvation chemical-potential, solvationentropy, and solvation enthalpy data of pure and mixed components, covering extendedtemperature ranges. For mixed compounds, the solvation quantities were generated ininfinite-dilution conditions by combining experimental values of pure-component andbinary-mixture thermodynamic properties.
Three types of binary-mixture propertieswere considered: partition coefficients, activity coefficients at infinite dilution, and Henry’s-law constants. A rigorous methodology was implemented with the aim to selectdata at appropriate conditions of temperature, pressure, and concentration for the estimation of solvation data.
Finally, our comprehensive CompSol database contains 21671data associated with 1969 pure species and 70062 data associated with 14102 binarymixtures (including 760 solvation data related to the ionic-liquid class of solvents).
On the basis of the very large amount of experimental data contained in the CompSol database, it is finally discussed how solvation energies are influenced by hydrogen-bondingassociation effects. 2017 AIP Publishing LLC for the National Institute of Standardsand Technology.
CompSol: The Comprehensive Solvation databanque
Solvation quantities (Gibbs free energies, enthalpies and entropies of solvation) for pure compounds or binary mixtures can be found directly here by querying either the database of pure substances, that of binary mixtures (one solute and one solvent), or that of ionic liquids. For mixed compounds, the solvation quantities were generated in infinite-dilution conditions by combining experimental values of pure-component and binary-mixture thermodynamic properties.
Please cite this work as Moine et al. J. Phys. Chem. Ref. Data 46, 033102 (2017).
Article can be found here or here and the Excel version of the database i savailable as supplementary material here