SEPP: Segment-Based Equation of State Parameter Prediction

The use of equations of state (EOS) requires the knowledge of model parameters for each molecule, but experimental data for parameter regression might not always be available. The physical soundness of SAFT-type EOS allows a prediction of their parameters based on quantum mechanics, as was previously shown by our group [Van Nhu et al., J. Phys. Chem. B 2008, 112, 5693]. In this work, a new prediction framework for SAFT parameters based on quantum-mechanically obtained descriptors is derived and extended to associating molecules. The prediction of association parameters requires only unimolecular calculations, even for the prediction of cross-association and induced association, making the new approach easier to use than previous methods. While having a broader applicability and yielding a higher accuracy, the number of universal model parameters is decreased compared to the model by Van Nhu et al., showing a higher physical significance. Application of our new prediction framework to PCP-SAFT and SAFT-VR Mie shows equally good results. Vapor pressures are predicted with an average RMSD of less than 40%, even for associating molecules, densities with less than 8%, and enthalpies of vaporization with less than 10% for nonassociating molecules and less than 25% for associating molecules.