Nanofiltration (NF) membranes are an energyefficient, scalable technology for water treatment and reuse. However, they are prone to fouling and offer limited selectivity between ions, hampering their use in water recovery and reuse. This work utilizes scalable self-assembly of zwitterionic copolymers combined with a novel cross-linking approach to develop membranes distinguished by exceptional mono/divalent ion selectivity, tunable pore size, and complete resistance to irreversible fouling. Extended cross-linking reduces the pore size to ∼0.9 nm, the smallest pore size reported for self-assembled copolymer membranes to date. These membranes achieve >99.2% SO 4 2− rejection and a Cl − /SO 4 2− selectivity of 101, demonstrating their promise for energy-efficient sulfate removal and other water treatment applications.
Water filtration membranes with advanced ion selectivity are urgently needed for resource recovery and the production of clean drinking water. This work investigates the separation capabilities of cross-linked zwitterionic copolymer membranes, a self-assembled membrane system featuring subnanometer zwitterionic nanochannels. We demonstrate that selective zwitterion–anion interactions simultaneously control salt partitioning and diffusivity, with the permeabilities of NaClO4, NaI, NaBr, NaCl, NaF, and Na2SO4 spanning roughly three orders of magnitude over a wide range of feed concentrations. We model salt flux using a one-dimensional transport model based on the Maxwell–Stefan equations and show that diffusion is the dominant mode of transport for 1:1 sodium salts. Differences in zwitterion–Cl− and zwitterion–F− interactions granted these membranes with the ultrahigh Cl−/F− permselectivity (PCl-/PF- = 24), enabling high fluoride retention and high chloride passage even from saline mixtures of NaCl and NaF.
We
report membranes with ultrathin <200 nm zwitterionic copolymer
selective layers exhibiting ∼1 nm size cutoff and permeances
as high as 50 L/m2·hr·bar. The thin layer is
formed by the deposition of random zwitterionic copolymers in trifluoroethanol/ionic
liquid mixtures onto a porous support. The resultant membranes have
the same low molecular weight cutoff of ∼1000 Da and narrow
pore size distribution but fluxes up to 10 times higher than membranes
prepared without ionic liquid and 20 times higher than commercial
membranes of similar pore size, making them promising for wastewater
treatment and pharmaceutical purification.
Long-term continuous monitoring (LTCM) of water quality can provide high-fidelity datasets essential for executing swift control and enhancing system efficiency. One roadblock for LTCM using solid-state ion-selective electrode (S-ISE) sensors is biofouling on the sensor surface, which perturbs analyte mass transfer and deteriorates the sensor reading accuracy. This study advanced the anti-biofouling property of S-ISE sensors through precisely coating a self-assembled channel-type zwitterionic copolymer poly(trifluoroethyl methacrylate-random-sulfobetaine methacrylate) (PTFEMA-r-SBMA) on the sensor surface using electrospray. The PTFEMA-r-SBMA membrane exhibits exceptional permeability and selectivity to primary ions in water solutions. NH 4 + S-ISE sensors with this anti-fouling zwitterionic layer were examined in real wastewater for 55 days consecutively, exhibiting sensitivity close to the theoretical value (59.18 mV/dec) and long-term stability (error <4 mg/L). Furthermore, a denoising data processing algorithm (DDPA) was developed to further improve the sensor accuracy, reducing the S-ISE sensor error to only 1.2 mg/L after 50 days of real wastewater analysis. Based on the dynamic energy cost function and carbon footprint models, LTCM is expected to save 44.9% NH 4 + discharge, 12.8% energy consumption, and 26.7% greenhouse emission under normal operational conditions. This study unveils an innovative LTCM methodology by integrating advanced materials (anti-fouling layer coating) with sensor data processing (DDPA).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.