Pore size regulation of polyamide composite membrane via a sol-gel process confined within the selective layer

Quantifying uncertainty in nanofiltration transport models for enhanced metals recovery

To decarbonize our global energy system, sustainably harvesting metals from diverse sourcewaters is essential. Membrane-based processes have recently shown great promise in meeting these needs by achieving high metal ion selectivities with relatively low water and energy use. An example is nanofiltration, which harnesses steric, dielectric, and Donnan exclusion mechanisms to perform size- and charge-based fractionation of metal ions. To further optimize nanofiltration systems, multicomponent models are needed; however, conventional methods necessitate large amounts of data for model calibration, introduce substantial uncertainty into the characterization process, and often yield poor results when extrapolated. In this work, we develop a new computational architecture to alleviate these concerns. Specifically, we develop a framework that: (1) reduces the data requirement for model calibration to only charged species measurements; (2) eliminates uncertainty propagation problems present in conventional characterization processes; (3) enables exploration of pH optimization for enhancing metal ion selectivities; and (4) enables uncertainty quantification to assess the sensitivity of partition coefficients and ion driving forces to learned pore size distributions. Our framework captures eight independent datasets comprising over 500 measurements to within ±15%. Our studies also suggest that the expectation-maximization algorithm can effectively learn pore size distributions and that optimizing pH can improve metal ion selectivities by a factor of 3-10×. Our findings also reveal that image charges appear to play a less pronounced role in dielectric exclusion under the studied conditions and that ion driving forces are more sensitive to pore size distributions than partition coefficients.

NaHCO3 addition enhances water permeance and Ca/haloacetic acids selectivity of nanofiltration membranes for drinking water treatment

The existence of disinfection by-products such as haloacetic acids (HAAs) in drinking water severely threatens water safety and public health. Nanofiltration (NF) is a promising strategy to remove HAAs for clean water production. However, NF often possesses overhigh rejection of essential minerals such as calcium. Herein, we developed highly selective NF membranes with tailored surface charge and pore size for efficient rejection of HAAs and high passage of minerals. The NF membranes were fabricated through interfacial polymerization (IP) with NaHCO3 as an additive. The NaHCO3-tailored NF membranes exhibited high water permeance up to ∼24.0 L m - 2 h - 1 bar-1 (more than doubled compared with the control membrane) thanks to the formation of stripe-like features and enlarged pore size. Meanwhile, the tailored membranes showed enhanced negative charge, which benefitted their rejection of HAAs and passage of Ca and Mg. The higher rejection of HAAs (e.g., > 90%) with the lower rejection of minerals (e.g., < 30% for Ca) allowed the NF membranes to achieve higher minerals/HAAs selectivity, which was significantly higher than those of commercially available NF membranes. The simultaneously enhanced membrane performance and higher minerals/HAAs selectivity would greatly boost water production efficiency and water quality. Our findings provide a novel insight to tailor the minerals/micropollutants selectivity of NF membranes for highly selective separation in membrane-based water treatment.

Enhancing the Antifouling Ability of a Polyamide Nanofiltration Membrane by Narrowing the Pore Size Distribution via One-Step Multiple Interfacial Polymerization

Application of nanofiltration membranes in industries still has to contend with membrane fouling that causes a significant loss of separation performance. Herein, an innovative approach to design antifouling membranes with a narrowed pore size distribution by interfacial polymerization (IP) assisted by silane coupling agents is reported. An aqueous solution of piperazine anhydrous (PIP) and γ-(2,3-epoxypropoxy) propytrimethoxysilane (KH560) is employed to perform IP with an organic solution of trimesoyl chloride and tetraethyl orthosilicate (TEOS) on a porous support. In accordance with the results of molecular dynamics and dissipative particle dynamics simulations, the reactive additive KH560 accelerates the diffusion rate of PIP to enrich at the reaction boundary. Moreover, the hydrolysis/condensation of KH560 and TEOS at the aqueous/organic interface forms an interpenetrating network with the polyamide network, which regulates the separation layer structure. The characterization results indicate that the polyamide-silica membrane has a denser, thicker, and uniform separation layer. The mean pore size of the polyamide-silica membrane and the traditional polyamide membrane is 0.62 and 0.74 nm, respectively, and these correspond to the geometric standard deviation (namely, pore size distribution) of 1.39 and 1.97, respectively. It is proved that the narrower pore size distribution endows the polyamide-silica membrane with stronger antifouling performance (flux decay ratio decreases from 18.4 to 3.8%). Such a membrane also has impressive long-term antifouling stability during cane molasses decolorization at a high temperature (50 °C). The outcomes of this study not only provide a novel one-step multiple IP strategy to prepare antifouling nanofiltration membranes but also emphasize the importance of pore size distribution in fouling control for various industrial liquid separations.