The COSMO-SAC modeling approach has found wide application in science as well as in a range of industries due to its good predictive capabilities. While other models for liquid phases, as for example UNIFAC, are in general more accurate than COSMO-SAC, these models typically contain many adjustable parameters and can be limited in their applicability. In contrast, the COSMO-SAC model only contains a few universal parameters and subdivides the molecular surface area into charged segments that interact with each other. In recent years, additional improvements to the construction of the sigma profiles and evaluation of activity coefficients have been made. In this work, we present a comprehensive description how to postprocess the results of a COSMO calculation through to the evaluation of thermodynamic properties. We also assembled a large database of COSMO files, consisting of 2261 compounds, freely available to academic and noncommercial users. We especially focus on the documentation of the implementation and provide the optimized source code in C++, wrappers in Python, sample sigma profiles calculated from each approach, as well as tests and validation results. The misunderstandings in the literature relating to COSMO-SAC are described and corrected. The computational efficiency of the implementation is demonstrated.

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.

No abstract

The PR+COSMOSAC EOS has been shown to be able to utilize quantum mechanical calculation results to predict the thermodynamic properties and fluid phase equilibrium with the only input of molecular structure. In this study, two modifications are introduced to further improve its accuracy in predicting vapor pressures of pure fluids. The average logarithmic deviation in vapor pressure (ALD-P) from the triple-point temperature to the normal boiling temperature for 1124 substances is reduced from 0.321 to 0.256 (or from 109.4% to 80.2%) (a reduction of 20% in ALD-P), while ALD-P from the normal boiling temperature to the critical temperature remains similar. The average absolute deviation (AAD) in the normal boiling temperature for 1405 substances is reduced from 16.32 to 14.25 K. Furthermore, its accuracy in predicting the critical properties and sublimation pressures (1140 substances) of pure fluids and vapor–liquid equilibrium of binary mixtures (1118 systems) is investigated and compared with the previous versions of PR+COSMOSAC. The accuracy of the revised PR+COSMOSAC EOS is generally improved, and the effect of each modification on the accuracy is discussed. This model is particularly useful when no experimental data are available.