  Porous materials are widely used for applications in gas storage and
separation. The diffusive properties of a variety of gases in porous media can
be modeled using molecular dynamics simulations that can be computationally
demanding depending on the pore geometry, complexity and amount of gas
adsorbed. We explore a dimensionality reduction approach for estimating the
self-diffusion coefficient of gases in simple pores using Langevin dynamics,
such that the three-dimensional (3D) atomistic interactions that determine the
diffusion properties of realistic systems can be reduced to an effective
one-dimensional (1D) diffusion problem along the pore axis. We demonstrate the
approach by modeling the transport of nitrogen molecules in single-walled
carbon nanotubes of different radii, showing that 1D Langevin models can be
parametrized with a few single-particle 3D atomistic simulations. The reduced
1D model predicts accurate diffusion coefficients over a broad range of
temperatures and gas densities. Our work paves the way for studying the
diffusion process of more general porous materials as zeolites or
metal-organics frameworks with effective models of reduced complexity.
