In silico prediction of medium effects on esterification equilibrium using the COSMO-RS method

Area of Science:

• Biocatalysis
• Chemical Engineering
• Computational Chemistry

Background:

• Solvent selection is crucial for optimizing industrial esterification reactions.
• Accurate prediction of solvent effects on reaction thermodynamics is challenging.
• Biocatalysis offers sustainable routes for ester production.

Purpose of the Study:

• To present a new computational approach for predicting solvent effects on esterification reactions.
• To compare the efficacy of COSMO-RS with the traditional UNIFAC method.
• To evaluate the prediction accuracy of thermodynamic equilibrium ratios in various solvents.

Main Methods:

• Utilized the COSMO-RS method to calculate activity coefficients of chemical species.
• Applied the UNIFAC method for comparative analysis.
• Investigated three distinct lipase-catalyzed esterification reactions under diverse solvent conditions.

Main Results:

• COSMO-RS predicted thermodynamic equilibrium ratios with variations of at most 9-fold (approx. 5.5 kJ/mol), often within 2-fold (approx. 2 kJ/mol).
• UNIFAC showed weaker performance, particularly with complex molecular interactions.
• Relative deviations from mean equilibrium constants were 17-49% for COSMO-RS versus 32-65% for UNIFAC.

Conclusions:

• COSMO-RS provides a powerful and generally applicable theoretical model for solvent selection in esterification.
• The method demonstrates high accuracy in predicting thermodynamic equilibrium, comparable to experimental error.
• COSMO-RS opens new avenues for rational solvent design in biocatalysis and chemical processes.