Developing a predictive group-contribution-based SAFT-VR equation of state

The hetero-segmented version of the statistical associating fluid theory for potentials of variable range (hetero-SAFT-VR) is used to develop a predictive molecular-based group-contribution SAFT-VR equation of state (GC-SAFT-VR). The hetero-SAFT-VR approach models molecules composed of segments of different size and/or energies of interaction enabling an accurate description of real molecules composed of different functional groups. The differences in interactions between functional groups are maintained throughout the theory in contrast to other approaches in which the parameters for functional groups are averaged in order to model a molecule as a homonuclear chain with "group-averaged" parameters. Through the GC-SAFT-VR approach we can study the effect of molecular functionality and topology on the thermodynamic properties of real fluid systems, since parameters are determined for each functional group and chain connectivity is explicitly specified. In this initial study GC-SAFT-VR parameters are developed for key organic functional groups (CH₃, CH₂, CH₂{double bond, long}CH, C{double bond, long}O, C₆H₅, OCH₃ and OCH₂) by fitting to experimental vapor pressure and saturated liquid density data for a selected group of compounds that contain these functional groups. The transferability of the parameters obtained is tested by comparing theoretical predictions with experimental data for pure fluids not included in the fitting process and binary mixtures. Using the GC-SAFT-VR approach good agreement is obtained between experimental data and the theoretical predictions for pure substances, including isomers, and their mixtures. The GC-SAFT-VR approach is able to accurately predict the effect of molecular functionality on mixture phase behavior without fitting to any experimental data for the system being studied.