The CH4/CO2Gas Mixture Separation Using the Graphene, SiC, and BN Nanochannels: A Comprehensive Computational Approach

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Abstract

This study presents a comprehensive computational investigation into the separation of CH4/CO2gas mixtures using nanochannels based on graphene, silicon carbide (SiC), and boron nitride (BN). Molecular dynamics (MD) simulations were employed to evaluate the adsorption dynamics, permeation rates, and separation efficiency of these two-dimensional materials under varying pressures and configurations. Graphene exhibited superior CH4permeability due to its atomic thickness and high surface energy, though selectivity was limited by weak interaction with CO2. SiC demonstrated moderate gas permeability with enhanced CO2selectivity, attributed to its stronger adsorption sites and balanced transport dynamics. BN displayed exceptional impermeability, effectively acting as a molecular sieve for CO2, driven by its high surface polarity and robust barrier properties. The diffusion coefficients and interaction energies revealed a strong material dependence, with CO2exhibiting higher diffusion and adsorption on polar surfaces. At the same time, CH4showed reduced mobility due to weaker van der Waals interactions. These findings underscore the significance of nanoscale structural control and surface engineering in optimizing gas separation performance. The insights provided by this study lay a robust foundation for designing hybrid nanochannel architectures, which leverage the unique properties of each material to achieve advanced separation systems. This work holds promise for developing scalable, energy-efficient membranes for clean energy applications, carbon capture, and industrial gas processing.

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Azamat, J., Alizadeh, M., & Ajalli, N. (2025). The CH4/CO2Gas Mixture Separation Using the Graphene, SiC, and BN Nanochannels: A Comprehensive Computational Approach. ACS Omega, 10(30), 33295–33305. https://doi.org/10.1021/acsomega.5c03400

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