Novel thin-film nanocomposite (TFN) nanofiltration membranes have attracted wide attention for their generally boosted water permeability. However, the incorporation of diverse nanomaterials introduces significant uncertainty in tuning the pore size of TFN membranes, thereby complicating the regulation of solute selectivity. This challenge is further amplified by the complex interactions among the substrate, loaded nanomaterials, and interfacial polymerization (IP) for the polyamide layer format
Optimizing Ternary Preparation Parameters of Thin-Film Nanocomposite Membranes for Tailored Selectivity via Interpretable Machine Learning
Airan Hu·CP Tang·Ying Liu·Kunpeng Zhang·Xuelin Wang·Chunlin Zhai·Lien Duan·Dan Lu·Bart Van der Bruggen·Shengji Xia·Xinxin Wei
