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.