Adsorption and diffusion of methane and light gases in 3D nano-porous graphene sponge

Pengfei Xu, Farzin Rahmani, Yee C. Chiew

Research output: Contribution to journalArticlepeer-review

Abstract

Advances in graphene assembly has shown that mechanically strong 3D nano-porous graphene sponge (NGS) can potentially be used for gas separation. The objectives of this computational study are to: (i) explore the use of NGS as adsorbent for separating light gases and light hydrocarbons from methane, and (ii) assess the potential of using NGS as a membrane for methane/ethane gas separation. A 3D nano-porous graphene sponge was constructed by reacting graphene flakes in the presence of inert non-reactive particles using Reactive Force Field (ReaxFF) molecular dynamics. We performed grand canonical Monte Carlo (GCMC) simulation to determine the adsorption capacity of NGS for methane, ethane, propane, butane, carbon dioxide, and nitrogen. In addition, GCMC simulations were performed on methane/ethane, methane/carbon dioxide, and nitrogen/methane gas mixtures to determine the selectivity for these gases on NGS. Our results show that graphene sponge has high selectivity for ethane over methane and methane over nitrogen. In addition, we obtained the diffusion coefficients of methane and ethane in NGS and estimated the perm-selectivity of ethane over methane. Because of its high solubility in graphene sponge, the perm-selectivity of ethane over methane is 4.76, despite its lower diffusion coefficient, suggesting that it could potentially be used as a membrane for separating ethane from methane.

Original languageEnglish (US)
JournalMolecular Simulation
DOIs
StateAccepted/In press - 2021

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Information Systems
  • Chemical Engineering(all)
  • Modeling and Simulation
  • Materials Science(all)
  • Condensed Matter Physics

Keywords

  • 3D nano-porous graphene sponge
  • adsorption of hydrocarbon gases
  • graphene
  • molecular dynamics simulations
  • Monte Carlo simulations

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