The lack of mechanistic insights into the water and solute transport in the thin film nanocomposite (TFN) membrane active layer posed a major challenge in the fundamental understandings and performance optimization of such membranes in water treatment. In this work, we develop a novel water and solute transport model to qualitatively and quantitatively study the influence of intrinsic permeabilities and geometric parameters of the NPs and the NPs-polymer intermediate layer on the widely observed flux enhancement of TFN membranes based on the resistance-in-series theory and Monte Carlo simulation. The simulation results demonstrate a small amount of porous or even non-porous NPs addition would result in a significant flux increase due to either high NP permeability, high intermediate layer permeability, or the combined effects of the abovementioned factors. Besides, we find that an optimized combination of NPs mass loading and NPs size, thicker intermediate layer and TFN membrane with minimized NPs aggregation are preferred to achieve high permeate flux. This simulation can be used to predict TFN membrane performance and provide guidance on engineering the next-generation TFN membranes with high flux as well as improved rejections, to tackle with the widely acknowledged problem of flux and rejection trade-off.

薄膜纳米复合材料（TFN）膜活性层中对水和溶质的迁移缺乏机械性见解，这对此类膜在水处理中的基本理解和性能优化提出了重大挑战。在这项工作中，我们开发了一种新颖的水和溶质运移模型，以定性和定量研究NPs和NPs-聚合物中间层的固有渗透率和几何参数对基于电阻-串联理论和蒙特卡洛模拟。仿真结果表明，由于高NP渗透性，高中间层渗透性，添加少量的多孔甚至无孔NP将导致通量显着增加，或上述因素的综合影响。此外，我们发现，NPs的质量负载和NPs尺寸，较厚的中间层和TFN膜以及最少的NPs聚集的优化组合对于实现高渗透通量而言是优选的。该模拟可用于预测TFN膜的性能，并为设计具有高通量和改善的阻滞性的下一代TFN膜提供指导，以解决通量和阻滞权衡问题。