Modeling complex associating mixtures with [Cn-mim][Tf2N] ionic liquids: predictions from the soft-SAFT equation

Area of Science:

• Physical Chemistry
• Chemical Engineering
• Materials Science

Background:

• Previous models for ionic liquids (ILs) had limitations in predicting complex mixtures due to limited experimental data.
• The soft-SAFT equation of state provides a framework for modeling IL behavior.

Purpose of the Study:

• To reparameterize and validate a soft-SAFT based model for imidazolium-based ILs.
• To assess the model's predictive capability for ILs in binary mixtures with associating compounds.
• To evaluate the accuracy of the model across a wide temperature and pressure range.

Main Methods:

• Reparameterization of the soft-SAFT model using new experimental density data (273-473 K, up to 60 MPa).
• Prediction of pure IL properties including density, interfacial tension, and isothermal compressibility.
• Application of the model to binary mixtures of ILs with methanol, ethanol, and water without mixture-specific fitting.

Main Results:

• The reparameterized model accurately predicts IL densities over an extended temperature and pressure range.
• Predictions for interfacial tension and isothermal compressibility showed good agreement with experimental data.
• The model excellently describes binary mixtures of ILs with common associating solvents, demonstrating high predictive power.

Conclusions:

• A simple, physics-based soft-SAFT model is sufficient for describing complex associating IL mixtures.
• Accurate experimental data is crucial for developing and validating molecular-based models.
• The validated model can reliably predict IL behavior and mixture properties, reducing the need for empirical fitting.