Understanding polymeric gas separation membranes using molecular simulation

Membrane-based processes are an attractive alternative to traditional distillation processes for applications such as gas separations. To develop novel polymeric structures that are suited to specific kinds of materials, the use of in silico design methods presents a possible way of accelerating materials discovery and design. We use tools such as density functional theory, classical molecular dynamics (MD), and grand canonical Monte Carlo (GCMC) methods to explore the gas permeance behaviors of several materials including ladder polymers and polyimides using fully atomistic simulations. From the solution-diffusion method we use GCMC to deduce the solubility of gas molecules with hybrid MD/GCMC to explore structural changes induced by the solute, and classical MD to evaluate gas diffusion coefficients as a function of gas loading. When combined with machine-learning based tools for predicting new structures, simulation can be used as an effective tool to speed up the development of soft materials for separations processes and other engineering applications.