Predicting concentration-gradient-driven liquid transport in 2D membranes

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This project aims to achieve a predictive understanding of liquid transport through two-dimensional (2D) membranes driven by concentration gradients by using a combination of novel theory and computation. Membranes made from 2D nanomaterials hold great promise for many applications from desalination to power generation to chemical sensing, but the concentration-gradient-driven transport processes that underlie these applications are not well understood. The expected outcome of this project is an unprecedented quantitative understanding of the parameters that control these transport processes. This will enable predictive optimisation of 2D membranes, which will reduce the time and cost of membrane development for diverse applications.