Micellization and Partition Equilibria in Mixed Nonionic/Ionic Micellar Systems: Predictions with Molecular Models

Area of Science:

• Physical Chemistry
• Computational Chemistry
• Colloid and Surface Science

Background:

• Mixed surfactant systems offer enhanced properties over single surfactants for practical applications.
• Solute partitioning in mixed micelles is less understood than in single surfactant systems.
• Accurate prediction of partition equilibria requires knowledge of mixed micelle composition.

Purpose of the Study:

• To investigate surfactant compositions within mixed micelles using molecular dynamics (MD) simulations.
• To compare the predictive capabilities of COSMO-RS and COSMOmic models for partition equilibria in mixed micelles.
• To evaluate the prediction of ionizable molecule partitioning, considering micelle structure and protolytic equilibria.

Main Methods:

• Molecular dynamics (MD) self-assembly simulations to determine micelle composition.
• Application and comparison of COSMO-RS and COSMOmic models for predicting partition coefficients.
• Thermodynamic cycle calculations using COSMOmic to determine position-dependent pKa for ionizable solutes.

Main Results:

• MD simulations successfully determined surfactant compositions in mixed micelles.
• Both COSMO-RS and COSMOmic provided reasonable predictions for neutral molecules.
• COSMOmic, incorporating micelle's 3D structure, showed better agreement with experimental data.
• COSMOmic enabled accurate prediction of ionized isovanillin partitioning by accounting for its protolytic equilibrium within micelles.

Conclusions:

• MD simulations are effective for characterizing mixed micelle composition.
• COSMOmic is a valuable tool for predicting solute partitioning in mixed surfactant systems, outperforming COSMO-RS for accuracy.
• Accounting for the solute's ionization state within the micelle is crucial for reliable partition coefficient predictions.