Theoretical Evaluation of Graphene Membrane Performance for Hydrogen Separation Using Molecular Dynamic Simulation

The main purposes of this study are to evaluate the performance of graphene membranes in the separation/purification of hydrogen from nitrogen from a theoretical point of view using the molecular dynamic (MD) simulation method, and to present details about molecular mechanisms of selective gas diffusion through nanoscale pores of graphene membranes at the simulated set conditions. On the other hand, permeance and perm-selectivity are two significant parameters of such a membrane that can be controlled by several variables such as pressure gradient, pore density, pore layer angles etc. Hence, in this work, the hydrogen and nitrogen permeating fluxes as well as the H₂/N₂ ideal perm-selectivity are investigated from a theoretical point of view in a two-layer nanoporous graphene (NPG) membrane through classical MD simulations, wherein the effects of pressure gradient, pore density, and pore angle on the NPG membrane performance are evaluated and discussed. Simulation outcomes suggest that hydrogen and nitrogen permeating fluxes increase as a consequence of an increment of pressure gradient across the membrane and pore density.

Molecular simulation of pressure-driven fluid flow in nanoporous membranes

An extended nonequilibrium molecular dynamics technique has been developed to investigate the transport properties of pressure-driven fluid flow in thin nanoporous membranes. Our simulation technique allows the simulation of the pressure-driven permeation of liquids through membranes while keeping a constant driving pressure using fluctuating walls. The flow of argon in the liquid state was simulated on applying an external pressure difference of 2.4x10(6) Pa through the slitlike and cylindrical pores. The volume flux and velocity distribution in the membrane pores were examined as a function of pore size, along with the interaction with the pore walls, and these were compared with values estimated using the Hagen-Poiseuille flow. The calculated velocity strongly depends on the strength of the interaction between the fluid and the atoms in the wall when the pore size is approximately<20sigma. The calculated volume flux also shows a dependence on the interaction between the fluid and the atoms in the wall. The Hagen-Poiseuille law overestimates or underestimates the flux depending on the interaction. From the analysis of calculated results, a good linear correlation between the density of the fluid in the membrane pores and the deviation of the flux estimated from the Hagen-Poiseuille flow was found. This suggests that the flux deviation in nanopore from the Hagen-Poiseuille flow can be predicted based on the fluid density in the pores.

Coarse-grained nonequilibrium approach to the molecular modeling of permeation through microporous membranes

We present a modeling technique that combines a statistical-mechanical coarse-graining scheme with a nonequilibrium molecular simulation algorithm to provide an efficient simulation of steady-state permeation across a microporous material. The coarse-graining scheme is based on the mapping of an atomistic model to a lattice using multidimensional free-energy and transition-state calculations. The nonequilibrium simulation algorithm is a stochastic, lattice version of the recently developed atomistic dual-control-volume grand canonical molecular dynamics. We demonstrate the approach on a model of methane permeating through a bulk portion of siliceous zeolite ZK4 at 300 K under imposed fugacity differences. We predict the coarse-grained (cage-level) density profiles and observe the development of nonlinearities as the magnitude of the fugacity difference is increased. From the net flux of methane we also predict a mean permeability coefficient under the various conditions. The simulation results are obtained over time scales on the order of microseconds and length scales on the order of dozens of nanometers.