Tailoring hole density and nitriding in graphene membranes for enhanced gas separation and selectivity

Abstract

Sour gas, containing acidic gases like hydrogen sulfide and carbon dioxide, has a characteristic odor, and toxic effects, and reduces the overall energy content of the gas. Moreover, the presence of these acid gases in water leads to the formation of highly corrosive acid compounds, increasing transportation costs. Membrane technology is widely used for gas separation due to its low energy consumption, ability to operate at ambient temperatures, lightweight and compact equipment, ease of access to all separated phases, and high process flexibility. Computer simulation bridges the gap between microscopic temporal and spatial scales and the macroscopic laboratory environment. Molecular dynamics is a technique for analyzing the physical motion of atoms and molecules. By simulating the interactions between atoms and molecules over time, insights into the dynamic evolution of the system can be obtained. This research investigates the CO2/CH4 separation performance of modified graphene membranes (C3N) using molecular dynamics simulations under various operating conditions. First, cavities with different geometrical shapes and edge atoms were created, and gas separation was examined at 300 K. A cavity with a diameter of 4.9 Å exhibited the highest selectivity (infinity) and a carbon dioxide flux of 365.65 mol/m2·s, while methane molecules were completely blocked. This cavity was selected as the optimal structure. Next, the effects of pressure, and hole density on gas separation were studied. The results showed that the flux is directly proportional to the feed pressure, reaching 503.7845 mol/m2·s at a pressure of 328.0424 atm while maintaining infinite selectivity. Finally, examining the impact of cavity density on the separation process revealed that drilling four holes in the membrane area was the optimal density, achieving infinite selectivity, zero methane flux, and a carbon dioxide flux of 292.601 mol/m2·s.