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

该项目旨在通过使用新的理论和计算相结合的方法，实现对由浓度梯度驱动的二维(2D)膜中液体传输的预测性理解。由2D纳米材料制成的膜在从海水淡化到发电再到化学传感的许多应用中都有着巨大的前景，但这些应用背后的浓度梯度驱动的传输过程还没有被很好地理解。这一项目的预期结果是对控制这些运输过程的参数有一个前所未有的定量了解。这将实现2D膜的预测性优化，从而为不同的应用减少膜开发的时间和成本。

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.