Infinite-dilution activity coefficients (IDAC) can be used to predict, for example, the behavior of liquid−liquid equilibrium or to determine parameters for excess Gibbs free energy expressions like NRTL, Wilson, or UNIQUAC. For systems where limited (or no) experimental data are available, predictive tools as the well-known UNIFAC variations can be very helpful. An alternative approach is to use methods based on conductor-like screening model (COSMO). In this work, we have tested a modified UNIFAC model with a recent parameter set and three variations of the COSMO-SAC model. To compare the models, a database with a total of 748 IDAC experimental points was assembled with data from the literature and is available as Supporting Information. For nonaqueous solutions, the IDAC logarithm absolute average deviation for UNIFAC was 0.28, while it was 0.48 for a COSMO-SAC with parameters adjusted in this work. On the other hand, for aqueous systems, a COSMO-SAC with optimized parameters led to a deviation of 0.81 against 1.47 for the UNIFAC model tested.

-Currently, the most successful predictive models for activity coefficients are those based on functional groups such as UNIFAC. In contrast, these models require a large amount of experimental data for the determination of their parameter matrix. A more recent alternative is the models based on COSMO, for which only a small set of universal parameters must be calibrated. In this work, a recalibrated COSMO-SAC model was compared with the UNIFAC (Do) model employing experimental infinite dilution activity coefficient data for 2236 non-hydrogen-bonding binary mixtures at different temperatures. As expected, UNIFAC (Do) presented better overall performance, with a mean absolute error of 0.12 ln-units against 0.22 for our COSMO-SAC implementation. However, in cases involving molecules with several functional groups or when functional groups appear in an unusual way, the deviation for UNIFAC was 0.44 as opposed to 0.20 for COSMO-SAC. These results show that COSMO-SAC provides more reliable predictions for multifunctional or more complex molecules, reaffirming its future prospects.

At present, at least for engineering purposes, the most successful predictive models for activity coefficients are those based on functional groups such as UNIFAC and its variants. While these models require large amounts of experimental data, the ones based on COSMO-RS require the calibration of a small set of universal parameters. However, the resolution required by many engineering tasks is usually higher than that obtained by COSMO-RS models. Thus, in this work, a novel functional-segment activity coefficient (F-SAC) model is proposed. This new model is also based on the concept of functional groups, but the interaction energy between groups comes from the COSMO-RS theory. The model parameters were calibrated for 21 groups and 43 subgroups by using infinite dilution activity coefficient (IDAC) data only. Only non-hydrogen bonding mixtures were investigated while associating mixtures are studied in an accompanying paper. For the considered IDAC data set, the F-SAC fit was superior to the predictions obtained with both UNIFAC (Do) and COSMO-SAC. Finally, the predictive strength of the model was assessed by using vapor–liquid equilibrium data not considered in the model fitting process. Very good agreement with experimental data was possible over the entire composition range, as well as in the prediction of azeotropes.

In this work, the recently proposed Functional-Segment Activity Coefficient (F-SAC) model (Ind. Eng. Chem. Res., DOI: 10.1021/ie400170a) is extended for mixtures where hydrogen bonds (HB) can form. The F-SAC model is based on the concept of functional groups with the group interaction energies calculated according to the COSMO-RS theory. In the extension proposed here, hydrogen bonds are described by one additional energy parameter for each HB donor–acceptor pair. The F-SAC parameters for substances not participating in hydrogen bonds were kept unchanged. Additional parameters were calibrated for 25 HB donor–acceptor pairs by using infinite dilution activity coefficient (IDAC) data complemented by VLE data for the ethanol/water system. For the considered IDAC data set, the F-SAC fit was superior to the predictions obtained with UNIFAC (Do). Finally, the predictive strength of the model was assessed using vapor–liquid equilibrium as well as water/alkane mutual solubility data not considered in the model fitting process. Similar to the performance for nonassociating systems, good agreement with experimental data was possible for several systems over the entire composition range, as well as in the prediction of azeotropes.

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