Two recent and fully open source COSMO-SAC models are assessed for the first time on the basis of very large experimental data sets. The model performance of COSMO-SAC 2010 and COSMO-SAC-dsp (2013) is studied for vapor−liquid equilibrium (VLE) and infinite dilution activity coefficient (γ i ∞) predictions, and it is benchmarked with respect to the group contribution models UNIFAC and mod. UNIFAC(DO). For this purpose, binary mixture combinations of 2 295 components are investigated. This leads to 10 897 γ i ∞ and 6 940 VLE mixtures, which correspond to 29 173 γ i ∞ and 139 921 VLE data points. The model performance is analyzed in terms of chemical families. A MATLAB program is provided for the interested reader to study the models in detail. The comprehensive assessment shows that there is a clear improvement from COSMO-SAC 2010 to COSMO-SAC-dsp and from UNIFAC to mod. UNIFAC(DO). The mean absolute deviation of γ i ∞ predictions is reduced from 95% to 86% (COSMO-SAC 2010 to COSMO-SAC-dsp) and from 73% to 58% (UNIFAC to mod. UNIFAC(DO)). A combined mean absolute deviation is introduced to study the temperature, pressure, and vapor mole fraction errors of VLE predictions, and it is reduced from 4.77% to 4.63% (COSMO-SAC 2010 to COSMO-SAC-dsp) and from 4.47% to 3.51% (UNIFAC to mod. UNIFAC(DO)). Detailed error analyses show that the accuracy of COSMO-SAC models mainly depends on chemical family types, but not on the molecular size asymmetry or polarity. The present results may serve as a reference for the reliability of predictions with COSMO-SAC methods and provide direction for future developments.

The performance of two versions of the COSMO-SAC activity coefficient model is carefully examined based on eight sets of quantum chemical computations [VWN-BP/DNP, b3lyp/6-31G(d,p), b3lyp/6-31G(2d,p), b3lyp/6-31+G(d,p), b3lyp/6-311G(d,p), wb97xd/6-31G(d,p), wb97xd/6-31G(2d,p), and wb97xd/6-31+G(d,p)] and one semiempirical calculation (PM6). Furthermore, the effect of the molecular geometry is examined based on equilibrium structures determined both in a vacuum, representing a nonpolar environment, and in a conductor, representing a highly polar environment. The model parameters are reoptimized for each quantum chemical calculation method, and the performance is evaluated using a large set of databases covering the vapor−liquid equilibrium, liquid−liquid equilibrium, infinite-dilution activity coefficient of binary mixtures, and octanol−water partition coefficient (K ow ; containing over 22000 data points). It is found that the original COSMO-SAC model is sensitive to the quantum chemical method used, whereas the revised COSMO-SAC model is not. For the original COSMO-SAC, a method that gives higher molecular polarity often results in a better prediction accuracy. The modifications introduced in the revised COSMO-SAC model not only improve the accuracy but also allow for the use of a lower-quality quantum computational theory without much loss of accuracy.

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Der vorliegende Übersichtsartikel berichtet über Fortschritte in der molekularen Modellierung und Simulation mittels massiv‐paralleler Hoch‐ und Höchstleistungsrechner (HPC). Im SkaSim‐Projekt arbeiteten dazu Partner aus der HPC‐Community mit Anwendern aus Wissenschaft und Industrie zusammen. Ziel dabei war es mittels HPC‐Methoden die Vorhersage von thermodynamischen Stoffdaten in Bezug auf Effizienz, Qualität und Zuverlässigkeit weiter zu optimieren. In diesem Zusammenhang wurden verschiedene Themen bearbeitet: Atomistische Simulation der homogenen Gasblasenbildung, Oberflächenspannung klassischer Fluide und ionischer Flüssigkeiten, multikriterielle Optimierung molekularer Modelle, Weiterentwicklung der Simulationscodes ls1 mardyn und ms2, atomistische Simulation von Gastrennprozessen, molekulare Membran‐Strukturgeneratoren, Transportwiderstände und gemischtypenspezifische Bewertung prädiktiver Stoffdatenmodelle.