A group contribution method for associating chain molecules based on the statistical associating fluid theory...

Area of Science:

• Thermodynamics
• Physical Chemistry
• Chemical Engineering

Background:

• Molecular-based equations of state are crucial for predicting thermodynamic properties.
• Existing models often require extensive parameterization for complex molecules.
• Accurate prediction of fluid-phase equilibria is essential for chemical process design.

Purpose of the Study:

• To develop a predictive group-contribution method based on Statistical Associating Fluid Theory (SAFT-gamma).
• To extend SAFT to heteronuclear molecules composed of different segment types.
• To provide an algebraic description of thermodynamic properties, complementing molecular simulation.

Main Methods:

• Extended the SAFT-VR equation of state to heteronuclear molecules using fused segments.
• Modeled functional groups as united-atom spherical segments with size, energy, and shape parameters.
• Incorporated bonding sites for associating groups, specifying site types, numbers, and association parameters.
• Estimated group parameters from pure component phase equilibria for various chemical families.

Main Results:

• Achieved accurate description of vapor-liquid equilibria with low average deviations (%AAD) for vapor pressure (3.60%) and saturated liquid density (0.86%).
• Demonstrated predictive capability for larger compounds and binary mixtures not included in the optimization database.
• Showcased that binary interaction parameters can be estimated from pure component data, enabling prediction of mixture equilibria without adjustment.

Conclusions:

• The SAFT-gamma approach provides an accurate and predictive method for thermodynamic properties of heteronuclear molecules.
• It simplifies mixture property prediction by allowing estimation of binary interaction parameters from pure component data.
• This method offers an algebraic alternative to molecular simulation for thermodynamic property calculations.