Predicting the Relative Static Permittivity: a Group Contribution Method Based on Perturbation Theory

The computer-aided design of (bio)chemical processes requires models that predict thermodynamic properties with as little experimental effort as possible. For the important class of electrolyte systems, the relative static permittivity of the solvent is an important thermodynamic property that depends on the temperature, pressure, composition, and molecular structure of the solvent. This work presents a broadly applicable model for the temperature-dependent relative static permittivity of pure and mixed solvents based on perturbation theory, including a group contribution method. For this purpose, we extend our previous model for polar substances to nonpolar substances. The developed model is parametrized for 785 substances, where permittivity and density data are available in the Dortmund Data Bank and the ThermoML database. Subsequently, a group contribution method is developed to predict the permittivity parameters from the molecular structure. With a mean absolute deviation of 0.2 averaged over all 785 substances, the parametrized model accurately correlates the relative static permittivity over a wide range of permittivities and temperatures. Moreover, the group contribution method achieves a mean absolute deviation of 0.6 for the substances in the training set. A leave-one-out cross-validation shows that the group contribution method accurately predicts substances not included in the training set.

Automated summary

This work presents a model for predicting the temperature-dependent relative static permittivity of pure and mixed solvents, using perturbation theory and group contribution method. The model is parametrized for 785 substances and shows accurate correlation with a mean absolute deviation of 0.2. The group contribution method accurately predicts substances not included in the training set.