Prediction-based trade-off analysis of polymer membranes for organic solvent reverse osmosis of hydrocarbons

Performance trade-off analysis of polymeric membrane materials obtained via experimental studies has been used to select materials for challenging separations and to identify opportunities for innovation. These types of analyses not only highlight the potential and limitations of polymer membranes in different separation applications, but also serve as a reference for guiding the development of new membrane materials and modules. Despite the growing interest in organic solvent reverse osmosis (OSRO) using polymer membranes, a standardized separation performance trade-off curve for OSRO has yet to emerge, primarily due to the limited number of studies in this area. Therefore, there is a need for a comprehensive indicator that reflects the potential separation capabilities of polymer membranes for various organic solvent mixtures. In this study, we generate these performance trade-off curves for >800 polymer structures and three different solvent-solvent separations using a predictive model. Existing data in the literature and new data are used to validate some of the predictions in this work. As OSRO performance is often described in terms of engineering parameters such as permeance and separation factor, we also explore the impact of factors such as permeation resistance in the support layer and the impact of osmotic pressure on separation efficiency.