The separation of CO₂ from a mixture of CO₂ and N₂ using a porous graphene membrane was investigated using molecular dynamics (MD) simulations. The effects of chemical functionalization of the graphene sheet and pore rim on the gas separation performance of porous graphene membranes were examined. It was found that chemical functionalization of the graphene sheet can increase the absorption ability of CO₂, while chemical functionalization of the pore rim can significantly improve the selectivity of CO₂ over N₂. The results show that the porous graphene membrane with all-N modified pore-16 exhibits a higher CO₂ selectivity over N₂ (∼11) due to the enhanced electrostatic interactions compared to the unmodified graphene membrane. This demonstrates the potential use of functionalized porous graphene as single-atom-thick membrane for CO₂ and N₂ separation. We provide an effective way to improve the gas separation performance of porous graphene membranes, which may be useful for designing new concept membranes for other gases.

First-principle density functional theory (DFT) calculation and molecular dynamic (MD) simulation are employed to investigate the hydrogen purification performance of two-dimensional porous graphene material (PG-ESX). First, the pore size of PG-ES1 (3.2775 Å) is expected to show high selectivity of H2 by DFT calculation. Then MD simulations demonstrate the hydrogen purification process of the PG-ESX membrane. The results indicate that the selectivity of H2 over several other gas molecules that often accompany H2 in industrial steam methane reforming or dehydrogenation of alkanes (such as N2, CO, and CH4) is sensitive to the pore size of the membrane. PG-ES and PG-ES1 membranes both exhibit high selectivity for H2 over other gases, but the permeability of the PG-ES membrane is much lower than the PG-ES1 membrane because of the smaller pore size. The PG-ES2 membrane with bigger pores demonstrates low selectivity for H2 over other gases. Energy barrier and electron density have been used to explain the difference of selectivity and permeability of PG-ESX membranes by DFT calculations. The energy barrier for gas molecules passing through the membrane generally increase with the decreasing of pore sizes or increasing of molecule kinetic diameter, due to the different electron overlap between gas and a membrane. The PG-ES1 membrane is far superior to other carbon membranes and has great potential applications in hydrogen purification, energy clean combustion, and making new concept membrane for gas separation.

Mixed-matrix membranes (MMMs) comprising Matrimid and a microporous azine-linked covalent organic frameworks (ACOF-1) were prepared and tested in the separation of CO2 from an equimolar CO2 /CH4 mixture. The COF-based MMMs show a more than doubling of the CO2 permeability upon 16 wt % ACOF-1 loading together with a slight increase in selectivity compared to the bare polymer. These results show the potential of COFs in the preparation of MMMs.

During the last decade, the synthesis and application of metal-organic framework (MOF) nanosheets has received growing interest, showing unique performances for different technological applications. Despite the potential of this type of nanolamellar materials, the synthetic routes developed so far are restricted to MOFs possessing layered structures, limiting further development in this field. Here, a bottom-up surfactant-assisted synthetic approach is presented for the fabrication of nanosheets of various nonlayered MOFs, broadening the scope of MOF nanosheets application. Surfactant-assisted preorganization of the metallic precursor prior to MOF synthesis enables the manufacture of nonlayered Al-containing MOF lamellae. These MOF nanosheets are shown to exhibit a superior performance over other crystal morphologies for both chemical sensing and gas separation. As revealed by electron microscopy and diffraction, this superior performance arises from the shorter diffusion pathway in the MOF nanosheets, whose 1D channels are oriented along the shortest particle dimension.

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