Application of Quantum Chemistry Insights to the Prediction of Phase Equilibria in Associating Systems

Thermodynamic models that explicitly account for association have become essential tools for correlating and predicting multiphase equilibria. These models have many adjustable parameters, which create difficulties for uniquely fitting experimental data. Reducing the number of adjustable parameters is an important pathway to increase the reliability and extrapolation power of thermodynamic models for practical applications. In this work, we revisit the relationship between the chemical and perturbation theories of association. This relationship creates a pathway for estimating association parameters using quantum chemistry calculations and statistical mechanics. Estimated parameters are applied to pure-component calculations, which demonstrate that they can be used to reduce the number of adjustable model parameters for the cubic plus association and perturbed-chain statistical associating fluid theory equations of state.