Further complicating matters, synthesis of new polymeric materials and subsequent testing of permeance and selectivity is a time-consuming, expensive, and incomplete process that can miss high-performance candidates. Molecular modeling approaches, such as Monte Carlo/molecular dynamics (MC/MD) simulations, can reasonably predict a polymer membrane's gas permeabilities without costly experiments . However, even these high throughput molecular simulations are too computationally expensive to explore the vast chemical space of polymers on the order of 10 6 ~10 . By contrast, simplified approximations to predict gas permeability for a given membrane are low cost but inaccurate. Most simply, group contribution methods sum together the gas permeability contribution of each chemical moiety in a polymer, but they do not necessarily consider connectivity and cannot expand into new classes of polymers . Permeability can also be calculated via diffusivity based on the polymer's free volume and the solution-diffusion model of gas transport using various theoretical models, but these theories are incomplete . In short, there is no efficient and accurate predictive model for gas permeability based on polymer-membrane chemistry.