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Quality of Component- and Group-Interaction-Based Regression of Binary Vapor–Liquid Equilibrium Data

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journal contribution
posted on 24.08.2017, 00:00 by Brian J. Satola, Jürgen Rarey, Deresh Ramjugernath
To describe the behavior of real liquid mixtures, binary interaction parameters of component-based models like, e.g., UNIQUAC, are fitted to experimental data or estimated values from group contribution (GC) methods like UNIFAC and mod. UNIFAC. Because parameters of GC methods are based on a large number of data sets for many similar mixtures, they are typically less precise than models fitted directly to individual data sets for the binary mixture of interest. In some cases, however, it was reported that UNIFAC with group parameters independently regressed to the same data sets represents binary mixtures more accurately than UNIQUAC, which could be due to better localization of interactions. This possible advantage was analyzed using over 3700 data sets from the Dortmund Data Bank. Advantages and disadvantages of the group-based approach are identified, which could be well-explained by the change in concentration base; the results should also hold for segment-based models like NRTL-SAC and COSMO-RS.