Assessing the reliability of predictive activity coefficient models for molecules consisting of several functional groups

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 multi-functional or more complex molecules, reaffirming its future prospects.