Abstract
Competitive adsorption of water is an important issue in the adsorption-based industrial processes of bio- and flue gases separation. The dehumidification of gases prior to separation would increase process complexity and lower its economic interest. In this work, large-scale computational screening was applied to identify Metal-Organic Frameworks (MOFs) structures which exhibit high CO2/CH4 selectivity and total loading higher than 0.5 mol/kg (in the presence of water). High-throughput Grand Canonical Monte Carlo (GCMC) screening of nearly 3000 existing MOF materials was carried out. Initial selection assumed fixed values of pore limiting diameter (PLD) and Henry's constant for water and allowed one to preselect 764 structures. After GCMC simulations carried for 50/50 CO2/CH4 mixture, at ambient conditions (p = 1 bar, T = 298 K), and variable gas humidity (0%, 5%, 30% and 40%) the final selection revealed 13 most promising MOFs structures. We focused on analysis of the correlations between the properties of the selected MOFs and the separation selectivity. We show that the selectivity is a complex function of the porous materials characteristics and finding selective sorbent, performing well in dry and wet conditions requires careful analysis of available MOFs.