Molecular kinetics modulation and fiber-templated topography: Dual-scale engineering for loose nanofiltration with enhanced permeance and antifouling

Thin-film composite polyamide (TFC PA) membranes show promise for treating salt-containing dye wastewater, yet achieving high permeance alongside robust antifouling performance through straightforward fabrication remains a persistent challenge. Herein, we present a dual-scale engineering strategy that synergistically integrates molecular-level interfacial polymerization (IP) kinetics modulation with fiber-templated surface topography to address this challenge. At the molecular scale, piperazine-2-carboxylic acid (CPIP) was introduced as a bifunctional regulator to electrostatically retard monomer diffusion and attenuate aqueous-phase reactivity, thereby decelerating IP kinetics and yielding a smooth, thin (37 nm), and loosely cross-linked active layer with enlarged molecular weight cut-off (539.4 Da). At the topographical scale, an electrospun polyacrylonitrile (PAN) nanofibrous substrate imprinted sub-micron ridged topography (ridge depth ∼300 nm) onto the polyamide surface, which generated localized vortices and elevated shear stress to mitigate fouling accumulation, as validated by computational fluid dynamics (CFD) simulations. Importantly, these two scales act in a synergistic manner: CPIP-modulated interfacial polymerization promotes formation of a smoother active layer, which couples with the fiber-templated topography to enhance hydrodynamic regulation and antifouling behavior. Benefiting from this dual-scale synergy, the resulting loose nanofiltration (LNF) membrane exhibited high pure water permeance (111.6 L m −2  h −1 bar −1 , 4.1-fold enhancement), high dye rejection (Congo red, 99.5%), and low monovalent salt rejection (NaCl, 1.6%), and markedly enhanced antifouling performance compared with the flat counterpart. This study establishes a facile yet effective framework for engineering high-flux antifouling NF membranes through molecular and topographical co-optimization.