Nanochannel Highways in Hybrid Lamellar Membranes: Computational Simulation of Electric Field-Guided CO2 Transport via Molecular Sieving for Ultra-efficient Separation

The excessive weakness and strength of the interactions between graphene and g-C₃N₄ with CO₂ pose challenges for CO₂ separation. Here, we proposed a gas separation nanochannel composed of the interlayer spacing in a two-dimensional graphene/g-C₃N₄ (Gra/CN) membrane to solve the issue by molecular dynamics simulation. Graphene is a finely tuned electrostatic interaction membrane in direct contact with CO₂ within the nanochannel. Due to the proper interaction between Gra/CN and CO₂, Gra/CN maintains high CO₂ permeance and selectivity under mixed gas conditions at different interlayer spacings, which confirms the good applicability for CO₂ separation. The nanochannel becomes a highway for CO₂ separation under an external electric field (E_field) of 1.0 × 10^–4 V·Å^–1 along the z-axis; the CO₂ permeance reaches 1.17 × 10^–3 mol·s^–1·m^–2·Pa^–1 through computational simulation, marking a substantial enhancement of approximately 60.3% relative to conditions without E_field. Simultaneously, the solubility coefficient rises to 4.48 × 10⁷ mol·m^–4·Pa as E_field in the z-axis. Moreover, the calculated energy consumption of the CO₂ separation is 0.017 GJ·ton^–1, which is below the theoretical minimum value of 0.050 GJ·ton^–1, demonstrating practical feasibility and efficiency in real-world applications. The results of this work highlight the significant role of the synergistic effect of the hybrid membrane gas separation nanochannel and E_field in enhancing CO₂ solubility and permeance, providing valuable theoretical guidance for CO₂ separation.