SAFT-DFT Modeling of Deformation During Binary Gas Adsorption

This project (Corrente et al., 2024) developed an innovative approach combining Statistical Associating Fluid Theory with Density Functional Theory (SAFT-DFT) and Grand Canonical Monte Carlo (GCMC) simulations to predict how nanoporous carbons deform during binary gas adsorption - crucial for applications in carbon capture and enhanced gas recovery.

Key Innovations

First comprehensive study combining SAFT-DFT and GCMC to model binary gas adsorption-induced deformation
Demonstrated SAFT-DFT’s accuracy matches GCMC at fraction of computational cost
Revealed complex nonmonotonic deformation behavior in nanopores

Representative 3 nm slit pore with adsorbed equimolar CO₂/CH₄ mixture at 10 MPa. Carbon atoms shown in gray, CO₂ in red/black, CH₄ in purple.

Technical Approach

We modeled adsorption in graphite slit pores using:

PC-SAFT equation of state for fluid properties
Modified SAFT-DFT code for adsorption calculations
GCMC simulations for validation
Steele 10-4-3 potential for fluid-wall interactions

The model captured key molecular-level interactions while maintaining computational efficiency.

Key Findings

Pore Size Effects
- Adsorption and deformation decrease with increasing pore width
- Strain shows nonmonotonic behavior due to molecular packing
- Bulk-like fluid behavior emerges in larger pores
Deformation Mechanisms
- Low pressure: contraction from wall attraction
- Medium pressure: expansion from molecular repulsion
- High pressure: possible secondary compression from external pressure

Adsorption Isotherms (left) and solvation pressure and volumetric strain (right) for different pore sizes and gas compositions, showing complex nonmonotonic behavior.

Computational Efficiency

SAFT-DFT proved remarkably efficient compared to GCMC:

GCMC: ~6 days per isotherm point
SAFT-DFT: ~20 minutes for entire isotherm
Similar accuracy in predictions

Impact

This work advances our ability to predict material behavior during:

Carbon capture and storage
Enhanced gas recovery
Gas separation processes
Energy storage applications

The developed framework provides a foundation for:

Modeling more complex gas mixtures
Studying functionalized carbons
Optimizing material design
Understanding geological carbon sequestration

Methods

Statistical Associating Fluid Theory (SAFT)
Density Functional Theory (DFT)
Grand Canonical Monte Carlo (GCMC)
PC-SAFT equation of state
Steele 10-4-3 potential

This research provides crucial insights for developing better carbon capture technologies and optimizing enhanced gas recovery processes while demonstrating the power of combining advanced theoretical methods with molecular simulations.