Parametrized, Transferable Classical Density Functional Theory for Alkane/Alkene Separation in Cationic Zeolites.

Area of Science:

• Materials Science
• Physical Chemistry
• Computational Chemistry

Background:

• Predicting gas adsorption in zeolites is crucial for separation and storage technologies.
• Accurate modeling of gas-solid interactions in porous materials remains a challenge.

Purpose of the Study:

• To develop an accurate and efficient computational method for predicting gas adsorption in cation-exchanged zeolites.
• To introduce and validate a transferable binary solid-fluid interaction parameter (k_si) within classical DFT.

Main Methods:

• Classical density functional theory (DFT) enhanced with a binary solid-fluid interaction parameter (k_si).
• Parameterization of k_si for specific zeolite-alkane/alkene systems using Grand Canonical Monte Carlo (GCMC) simulations.
• Validation against GCMC simulations for various zeolite structures, conditions, and mixtures.

Main Results:

• The enhanced DFT method accurately predicts adsorption isotherms for propane/propene mixtures in sodium-exchanged zeolites (FAU and LTA).
• The k_si parameter demonstrated transferability across different zeolite structures and conditions.
• Limitations were identified for calcium-exchanged zeolites due to cation mobility effects.

Conclusions:

• Classical DFT with transferable k_si parameters provides a robust, computationally efficient alternative to empirical models and molecular simulations.
• The method enables high-throughput screening and accurate prediction of adsorption in monovalent cationic zeolites.
• Potential exists for extending this approach to other porous materials and adsorbate systems.