Improving the estimation accuracy of confined vapor-liquid equilibria by fine-tuning the pure component parameter in the PC-SAFT equation of state.

We propose a thermodynamic model that combines the Young-Laplace equation and perturbed chain-statistical associating fluid theory (PC-SAFT) equation of state to estimate capillary condensation pressure in microporous and mesoporous sorbents. We adjust the PC-SAFT dispersion-energy parameter when the pore size becomes comparable to the molecular dimension. This modelling framework is applied to diverse systems containing associating and non-associating gases, various sorbents, and a wide range of temperatures. Our simulation results show that under extreme confinement, a higher value of the dispersion-energy parameter ( ε ) is required. Furthermore, using the experimental saturation pressure data for 18 different associating and non-associating confined fluids, we find that the shift in the PC-SAFT dispersion energy correlates with the ratio of the sorbent mean pore size to the PC-SAFT segment size ( r p / σ ). By fitting to the capillary condensation data, the relative deviation between the confined and bulk PC-SAFT dispersion energy parameter is only 0.1% at r p / σ = 15; however, this deviation starts to increase exponentially as r p / σ decreases. For a sorbent with large pores, when r p / σ > 15, the capillary condensation pressure results from our model are similar to the predictions from the Kelvin equation. Using a dataset containing 235 saturation pressure data points composed of 18 pure gases and 4 binary mixtures, the overall AARD% from our model is 12.26%, which verifies the good accuracy of our model. Because the mean sorbent pore radius ( r p ), the PC-SAFT energy parameter ( ε ), and segment size ( σ ) are known a priori , our model estimates the corrected energy parameter for small pores and, thus, extends its applicability.