Pore model for nanofiltration: History, theoretical framework, key predictions, limitations, and prospects

Optimization of carbon membrane performance in reverse osmosis systems for reducing salinity, nitrates, phosphates, and ammonia in aquaculture wastewater

This study investigates the performance of various types of carbon membranes in reverse osmosis systems aimed at reducing salinity, nitrates, phosphates, and ammonia in aquaculture wastewater. As sustainable aquaculture practices become increasingly essential, effective treatment solutions are needed to mitigate pollution from nutrient-rich effluents. The research highlights several carbon membranes types, including carbon molecular sieves, activated carbon membranes, carbon nanotube membranes, and graphene oxide membranes, all of which demonstrate exceptional filtration capabilities due to their unique structural properties. Findings reveal that these carbon membranes can achieve removal efficiencies exceeding 90 % for critical pollutants, thereby significantly improving water quality and supporting environmental sustainability. The study also explores the development of hybrid membranes and nanocomposites, which enhance performance by combining the strengths of different materials, allowing for customized solutions tailored to the specific requirements of aquaculture wastewater treatment. Additionally, operational parameters such as pH, temperature, and feed water characteristics are crucial for maximizing membrane efficiency. The integration of real-time monitoring technologies is proposed to enable prompt adjustments to treatment processes, thereby improving system performance and reliability. Overall, this research emphasizes the importance of interdisciplinary collaboration among researchers and industry stakeholders to drive innovation in advanced filtration technologies. The findings underscore the substantial potential of carbon membranes in tackling the pressing water quality challenges faced by the aquaculture sector, ultimately contributing to the sustainability of aquatic ecosystems and ensuring compliance with environmental standards for future generations.

Breaking the trade-off between lithium purity and lithium recovery: A comprehensive mathematical modeling based on membrane structure-property-performance relationships

The application of nanofiltration (NF) membranes for resource recovery, particularly lithium (Li) extraction from high magnesium (Mg) brines, is a rapidly growing research area. However, the trade-off between high Li+ purity and recovery remains challenging. In our study, we extend the widely adopted Donnan Steric Pore Model with Dielectric Exclusion (DSPM-DE) to analyze membrane structure-property-performance relationships at the process scale. For the first time, we quantify how membrane intrinsic parameters (e.g., pore size, effective thickness, and charge density) affect Li+ purity and recovery under module-scale processes. Under this framework, we demonstrate that electrically neutral and positively charged membranes outperform negatively charged membranes, albeit at the cost of slightly higher required hydraulic pressure. Notably, positively charged membranes with smaller pore size yet high water permeance (40-80 L m-2 h-1 bar-1) are preferred, which could simultaneously achieve excellent Li+ purity (∼98 %) and high Li+ recovery (∼93 %) in the single-pass process, effectively overcoming the purity-recovery trade-off correlation. We further demonstrate that negative Li+ rejection plays a crucial role in overcoming the trade-off correlation by significantly increasing Li+ recovery. Nevertheless, poor system flux distribution is inadvertently observed in the regions where strong negative rejection occurs, highlighting the need for careful consideration of the balance between system stability and lithium extraction performances. Our study identifies critical membrane parameters for achieving optimal lithium extraction performance at the process scale, offering fundamental insights for designing high-performance membranes for resource recovery.

Relating Solute-Membrane Electrostatic Interactions to Solute Permeability in Reverse Osmosis Membranes

Despite the widespread use of reverse osmosis (RO) membranes in water desalination, the role of solute-membrane interactions in solute transport remains complex and relatively not well understood. This study elucidates the relationship between solute-membrane electrostatic interactions and solute permeability in RO membranes. The transport of salt and neutral molecules through charged polyamide (PA) and uncharged cellulose triacetate (CTA) RO membranes was examined. Results show that salt rejection and salt permeability in the PA membrane are highly dependent on the solution pH due to the variations of membrane charge density and the Donnan potential at the membrane-solution interface. Specifically, a higher salt rejection (and hence lower salt permeability) of the PA membrane is observed under alkaline conditions compared to acidic conditions. This observation is attributed to the enhanced Donnan potential at higher solution pH, which hinders co-ion partitioning into the membrane. In contrast, for salt transport through the CTA membrane and neutral solute transport through both membranes, solute permeability is independent of the solution pH and solute concentration due to the negligible Donnan effect. Overall, our results demonstrate the important role of solute-membrane electrostatic interactions, combined with steric exclusion, in regulating solute permeability in RO membranes.

Machine Learning-Aided Inverse Design and Discovery of Novel Polymeric Materials for Membrane Separation

Polymeric membranes have been widely used for liquid and gas separation in various industrial applications over the past few decades because of their exceptional versatility and high tunability. Traditional trial-and-error methods for material synthesis are inadequate to meet the growing demands for high-performance membranes. Machine learning (ML) has demonstrated huge potential to accelerate design and discovery of membrane materials. In this review, we cover strengths and weaknesses of the traditional methods, followed by a discussion on the emergence of ML for developing advanced polymeric membranes. We describe methodologies for data collection, data preparation, the commonly used ML models, and the explainable artificial intelligence (XAI) tools implemented in membrane research. Furthermore, we explain the experimental and computational validation steps to verify the results provided by these ML models. Subsequently, we showcase successful case studies of polymeric membranes and emphasize inverse design methodology within a ML-driven structured framework. Finally, we conclude by highlighting the recent progress, challenges, and future research directions to advance ML research for next generation polymeric membranes. With this review, we aim to provide a comprehensive guideline to researchers, scientists, and engineers assisting in the implementation of ML to membrane research and to accelerate the membrane design and material discovery process.

Large-Area Clay Composite Membranes with Enhanced Permeability for Efficient Dye/Salt Separation

The escalating discharge of textile wastewater with plenty of dye and salt has resulted in serious environmental risks. Membranes assembled from two-dimensional (2D) nanomaterials with many tunable interlayer spacings are promising materials for dye/salt separation. However, the narrow layer spacing and tortuous interlayer transport channels of 2D-material-based membranes limit the processing capacity and the permeability of small salt ions for efficient dye/salt separation. In this work, a novel sepiolite/vermiculite membrane was fabricated using Meyer rod-coating and naturally occurring clay. The intercalation of sepiolite Nanofibers between vermiculite Nanosheets provides additional transport nanochannels and forms looser permeable networks, producing composite membranes with remarkably enhanced flux. As a result, the optimized membranes with 80% sepiolite exhibit remarkable flux as high as 78.12 LMH bar-1, outstanding dye rejection (Congo Red~98.26%), and excellent selectivity of dye/salt of 10.41. In addition, this novel all-clay composite membrane demonstrates stable separation performance under acidity, alkalinity and prolonged operation conditions. The large-scale sepiolite/vermiculite membranes made by the simple proposed method using low-cost materials provide new strategies for efficient and environmentally-friendly dye/salt separation.

Dynamic ammonium retention for nutrient separation from manure digestate

Extensive nitrogen emissions with negative impact on nature and the environment urge effective valorization of manure and fractionation of nutrients to enable precision fertilization. Typically, manure is fed to a digester to produce biogas. The remaining digestate is then mechanically separated into a solid phosphorous-rich fraction and a liquid fraction containing both NH4+ and K. These ions are difficult to separate due to their very identical size and charge. We show that with smart tuning of the pH to control the NH3/NH4+ equilibrium, membranes can produce dedicated N and K-rich streams. The increased pH switches the equilibrium towards the neutrally charged solute NH3 that permeates more easily through the membrane than charged NH4+ and K+ ions. Experiments with both artificial NH4Cl/KCl mixtures as well as real liquid digestate and four different membrane types, ranging from open nanofiltration (NF) to sea water reverse osmosis (RO) membranes were performed. At neutral pH, no N/K selectivity was observed, not for single components nor for mixtures. When the pH was increased towards alkaline environment, distinct selectivity for N/K was obtained both with model solutions and real liquid digestate. At a suitable pH of 10, with >80 % of the total ammonia present as NH3, the RO BW membrane showed a large N/K selectivity of 35 in the crossflow system. Additional RO steps at low pH allows subsequent concentration of the formed NH4+ and K+ fractions. The presented dynamic pH approach proofs that in a two-step RO system both N, and K-enriched fertilizers can be produced from real liquid digestate.

Polyelectrolyte fabricated nanofiltration membrane with heterogeneously charged channels for high efficient cephalexin wastewater treatment

Nanofiltration (NF) for treatments of pharmaceutical wastewater is a promising direction for water protection and resources recovery. Herein, a novel membrane with heterogeneously charged channels was constructed by modified layer-by-layer assembly methods. Within the well-designed pores, the polyanion structure excludes the cephalexin and the cationic structure slows down its diffusion, thereby rejections for cephalexin are improved. The hydrophilic property of polyelectrolytes simultaneously guarantees the water transport. Fabricated heterogeneously charged channels are shown to strengthen the electrostatic barrier and prevent monovalent cephalexin anions penetration. Optimized nanofiltration membrane exhibits rejections of 98.9 % for 3650 ppm cephalexin, maintaining steady rejection during 69 h of continuous operations. The flux recovers to 99.3 % of the original flux after water washing. Benefiting from the separation performance of fabricated membranes, multi-stage NF processes effectively enrich the cephalexin wastewater. This work offers significant prospects for achieving high-efficiency pharmaceutical wastewater treatment and amphoteric drug recovery.

Structure and Dynamics of Water in Polysaccharide (Alginate) Solutions and Gels Explained by the Core-Shell Model

In both biological and engineered systems, polysaccharides offer a means of establishing structural stiffness without altering the availability of water. Notable examples include the extracellular matrix of prokaryotes and eukaryotes, artificial skin grafts, drug delivery materials, and gels for water harvesting. Proper design and modeling of these systems require detailed understanding of the behavior of water confined in pores narrower than about 1 nm. We use molecular dynamics simulations to investigate the properties of water in solutions and gels of the polysaccharide alginate as a function of the water content and polymer cross-linking. We find that a detailed understanding of the nanoscale dynamics of water in alginate solutions and gels requires consideration of the discrete nature of water. However, we also find that the trends in tortuosity, permeability, dielectric constant, and shear viscosity can be adequately represented using the "core-shell" conceptual model that considers the confined fluid as a continuum.

Rejection of PFAS and priority co-contaminants in semiconductor fabrication wastewater by nanofiltration membranes

Use of high-pressure membranes is an effective means for removal of per-and polyfluoroalkyl substances (PFAS) that is less sensitive than adsorption processes to variable water quality and specific PFAS structure. This study evaluated the use of nanofiltration (NF) membranes for the removal of PFAS and industry relevant co-contaminants in semiconductor fabrication (fab) wastewater. Initial experiments using a flat sheet filtration cell determined that the NF90 (tight NF) membrane provided superior performance compared to the NF270 (loose NF) membrane, with NF90 rejection values exceeding 97 % for all PFAS evaluated, including the ultrashort trifluoromethane sulfonic acid (TFMS). Cationic fab co-contaminants diaryliodonium (DIA), triphenylsulfonium (TPS), and tetramethylammonium hydroxide (TMAH) were not as highly rejected as anionic PFAS likely due to electrostatic effects. A spiral wound NF90 module was then used in a pilot system to treat a lab solution containing PFAS and co-contaminants and fab wastewater effluent. Treatment of the fab wastewater, containing high concentrations of perfluorocarboxylic acids (PFCAs), including trifluoroacetic acid (TFA: 96,413 ng/L), perfluoropropanoic acid (PFPrA: 11,796 ng/L), and perfluorobutanoic acid (PFBA: 504 ng/L), resulted in ≥92 % rejection of all PFAS while achieving 90 % water recovery in a semi-batch configuration. These findings demonstrate nanofiltration as a promising technology option for incorporation in treatment trains targeting PFAS removal from wastewater matrices.

The Hidden Role of the Dielectric Effect in Nanofiltration: A Novel Perspective to Unravel New Ion Separation Mechanisms

Nanofiltration (NF) membranes play a critical role in separation processes, necessitating an in-depth understanding of their selective mechanisms. Existing NF models predominantly include steric and Donnan mechanisms as primary mechanisms. However, these models often fail in elucidating the NF selectivity between ions of similar dimensions and the same valence. To address this gap, an innovative methodology was proposed to unravel new selective mechanisms by quantifying the nominal dielectric effect isolated from steric and Donnan exclusion through fitted pore dielectric constants by regression analysis. We demonstrated that the nominal dielectric effect encompassed unidentified selective mechanisms of significant relevance by establishing the correlation between the fitted pore dielectric constants and these hindrance factors. Our findings revealed that dehydration-induced ion-membrane interaction, rather than ion dehydration, played a pivotal role in ion partitioning within NF membranes. This interaction was closely linked to the nondeformable fraction of hydrated ions. Further delineation of the dielectric effect showed that favorable interactions between ions and membrane functional groups contributed to entropy-driven selectivity, which is a key factor in explaining ion selectivity differences between ions sharing the same size and valence. This study deepens our understanding of NF selectivity and sheds light on the design of highly selective membranes for water and wastewater treatment.

Ion-Ion Selectivity of Synthetic Membranes with Confined Nanostructures

Synthetic membranes featuring confined nanostructures have emerged as a prominent category of leading materials that can selectively separate target ions from complex water matrices. Further advancements in these membranes will pressingly rely on the ability to elucidate the inherent connection between transmembrane ion permeation behaviors and the ion-selective nanostructures. In this review, we first abstract state-of-the-art nanostructures with a diversity of spatial confinements in current synthetic membranes. Next, the underlying mechanisms that govern ion permeation under the spatial nanoconfinement are analyzed. We then proceed to assess ion-selective membrane materials with a focus on their structural merits that allow ultrahigh selectivity for a wide range of monovalent and divalent ions. We also highlight recent advancements in experimental methodologies for measuring ionic permeability, hydration numbers, and energy barriers to transport. We conclude by putting forth the future research prospects and challenges in the realm of high-performance ion-selective membranes.

Fouling behavior of BTEX in petrochemical wastewater treated by nanofiltration (NF)

Membrane fouling generated by small molecular-weight aromatic compounds with poor biodegradability is a major barrier to advanced petrochemical wastewater treatment using nanofiltration (NF) technology. In this study, the fouling behavior of ten BTEX with different substituent existing in petrochemical wastewater on the NF membrane was systematically investigated. By examining the effect of the number, position, and type of substituents on the permeability of NF membranes and membrane resistance analysis, combined with XDLVO theory and correlation analysis, we found that stronger dipole-dipole interactions of BTEX with higher polarity and hydrogen bonding effects between substituents and the membrane surface were verified to be the main forces driving the attachment to the surface of membranes. Furthermore, by analyzing the effect of common inorganic ions in petrochemical wastewater on membrane fouling, it was found that electron-donating substituents (-CH3, -C2H5, and -NH2) enhanced the electron cloud density of the benzene ring, a process that exacerbated membrane fouling by strengthening electrostatic interactions between the benzene ring and Ca2+ ions. The fouling potential of electron-withdrawing substituted (-NO2, -OH) BTEX exhibited the opposite trend. Overall, this study provides a theoretical basis for developing effective membrane fouling control strategies in NF advanced treatment of petrochemical wastewater. ENVIRONMENTAL IMPLICATION: Aromatic chemicals in petrochemical effluent are difficult to degrade, and their accumulation will cause significant harm to humans and ecological systems. Determine the composition of small molecule BTEX in petrochemical wastewater, gain an in-depth comprehension of the membrane fouling behavior of nanofiltration membrane filtration, identify the primary forces causing irreversible membrane surface fouling using experimental data and model fitting, and propose viable anti-fouling membrane modification strategies. Establish a technical foundation for membrane fouling management in the long-term operation of petrochemical wastewater membrane treatment.

Response of Ionic Hydration Structure and Selective Transport Behavior to Aqueous Solution Chemistry during Nanofiltration

The effect of aqueous solution chemistry on the ionic hydration structure and its corresponding nanofiltration (NF) selectivity is a research gap concerning ion-selective transport. In this study, the hydration distribution of two typical monovalent anions (Cl- and NO3-) under different aqueous solution chemical conditions and the corresponding transmembrane selectivity during NF were investigated by using in situ liquid time-of-flight secondary ion mass spectrometry in combination with molecular dynamics simulations. We demonstrate the inextricable link between the ion hydration structure and the pore steric effect and further find that ionic transmembrane transport can be regulated by breaking the balance between the hydrogen bond network (i.e., water-water) and ion hydration (i.e., ion-water) interactions of hydrated ion. For strongly hydrated (H2O)nCl- with more intense ion-water interactions, a higher salt concentration and coexisting ion competition led to a larger hydrated size and, thus, a higher ion rejection by the NF membrane, whereas weakly hydrated (H2O)nNO3- takes the reverse under the same conditions. Stronger OH--anion hydration competition resulted in a smaller hydrated size of (H2O)nCl- and (H2O)nNO3-, showing a lower observed average hydration number at pH 10.5. This study deepens the long-overlooked understanding of NF separation mechanisms, concerning the hydration structure.

Multiscale modelling of transport in polymer-based reverse-osmosis/nanofiltration membranes: present and future

Nanofiltration (NF) and reverse osmosis (RO) processes are physical separation technologies used to remove contaminants from liquid streams by employing dense polymer-based membranes with nanometric voids that confine fluids at the nanoscale. At this level, physical properties such as solvent and solute permeabilities are intricately linked to molecular interactions. Initially, numerous studies focused on developing macroscopic transport models to gain insights into separation properties at the nanometer scale. However, continuum-based models have limitations in nanoconfined situations that can be overcome by force field molecular simulations. Continuum-based models heavily rely on bulk properties, often neglecting critical factors like liquid structuring, pore geometry, and molecular/chemical specifics. Molecular/mesoscale simulations, while encompassing these details, often face limitations in time and spatial scales. Therefore, achieving a comprehensive understanding of transport requires a synergistic integration of both approaches through a multiscale approach that effectively combines and merges both scales. This review aims to provide a comprehensive overview of the state-of-the-art in multiscale modeling of transport through NF/RO membranes, spanning from the nanoscale to continuum media.

Understanding Rejection Mechanisms of Trace Organic Contaminants by Polyamide Membranes via Data-Knowledge Codriven Machine Learning

Data-driven machine learning (ML) provides a promising approach to understanding and predicting the rejection of trace organic contaminants (TrOCs) by polyamide (PA). However, various confounding variables, coupled with data scarcity, restrict the direct application of data-driven ML. In this study, we developed a data-knowledge codriven ML model via domain-knowledge embedding and explored its application in comprehending TrOC rejection by PA membranes. Domain-knowledge embedding enhanced both the predictive performance and the interpretability of the ML model. The contribution of key mechanisms, including size exclusion, charge effect, hydrophobic interaction, etc., that dominate the rejections of the three TrOC categories (neutral hydrophilic, neutral hydrophobic, and charged TrOCs) was quantified. Log D and molecular charge emerge as key factors contributing to the discernible variations in the rejection among the three TrOC categories. Furthermore, we quantitatively compared the TrOC rejection mechanisms between nanofiltration (NF) and reverse osmosis (RO) PA membranes. The charge effect and hydrophobic interactions possessed higher weights for NF to reject TrOCs, while the size exclusion in RO played a more important role. This study demonstrated the effectiveness of the data-knowledge codriven ML method in understanding TrOC rejection by PA membranes, providing a methodology to formulate a strategy for targeted TrOC removal.

Double charge flips of polyamide membrane by ionic liquid-decoupled bulk and interfacial diffusion for on-demand nanofiltration

Fine design of surface charge properties of polyamide membranes is crucial for selective ionic and molecular sieving. Traditional membranes face limitations due to their inherent negative charge and limited charge modification range. Herein, we report a facile ionic liquid-decoupled bulk/interfacial diffusion strategy to elaborate the double charge flips of polyamide membranes, enabling on-demand transformation from inherently negative to highly positive and near-neutral charges. The key to these flips lies in the meticulous utilization of ionic liquid that decouples intertwined bulk/interfacial diffusion, enhancing interfacial while inhibiting bulk diffusion. These charge-tunable polyamide membranes can be customized for impressive separation performance, for example, profound Cl-/SO42- selectivity above 470 in sulfate recovery, ultrahigh Li+/Mg2+ selectivity up to 68 in lithium extraction, and effective divalent ion removal in pharmaceutical purification, surpassing many reported polyamide nanofiltration membranes. This advancement adds a new dimension to in the design of advanced polymer membranes via interfacial polymerization.

Membrane Design Principles for Ion-Selective Electrodialysis: An Analysis for Li/Mg Separation

Selective electrodialysis (ED) is a promising membrane-based process to separate Li+ from Mg2+, which is the most critical step for Li extraction from brine lakes. This study theoretically compares the ED-based Li/Mg separation performance of different monovalent selective cation exchange membranes (CEMs) and nanofiltration (NF) membranes at the coupon scale using a unified mass transport model, i.e., a solution-friction model. We demonstrated that monovalent selective CEMs with a dense surface thin film like a polyamide film are more effective in enhancing the Li/Mg separation performance than those with a loose but highly charged thin film. Polyamide film-coated CEMs when used in ED have a performance similar to that of polyamide-based NF membranes when used in NF. NF membranes, when expected to replace monovalent selective CEMs in ED for Li/Mg separation, will require a thin support layer with low tortuosity and high porosity to reduce the internal concentration polarization. The coupon-scale performance analysis and comparison provide new insights into the design of composite membranes used for ED-based selective ion-ion separation.

Ion Selectivity in Multilayered Stacked Nanoporous Graphene

Nanoporous graphene is an ideal candidate for molecular filtration as it can potentially combine high permeability with high selectivity at molecular levels. To make use of graphene in filtration setups, the defects formed during its growth and during the transfer of graphene to the carrier support pose a challenge. These uncontrolled pores can be avoided by stacking graphene layers, and then, controlled pores can be initiated with oxygen plasma. Here, we show that two-layer stacks provide the best balance of defect coverage and high selectivity compared with other stacks. Using the electrical characterization of ionic solutions in the standard diffusion cell, we compare the ionic transport and ionic selectivity of up to three-layered stacks of graphene that have been plasma-treated. We find that there is a decrease in the ionic selectivity of a two-layered stack as one more layer of graphene is added. We provide a model for this occurrence. Our results will be helpful for making practical and high-performance filtration systems from two-dimensional materials.

Exploring the Knowledge Attained by Machine Learning on Ion Transport across Polyamide Membranes Using Explainable Artificial Intelligence

Recent studies have increasingly applied machine learning (ML) to aid in performance and material design associated with membrane separation. However, whether the knowledge attained by ML with a limited number of available data is enough to capture and validate the fundamental principles of membrane science remains elusive. Herein, we applied explainable artificial intelligence (XAI) to thoroughly investigate the knowledge learned by ML on the mechanisms of ion transport across polyamide reverse osmosis (RO) and nanofiltration (NF) membranes by leveraging 1,585 data from 26 membrane types. The Shapley additive explanation method based on cooperative game theory was used to unveil the influences of various ion and membrane properties on the model predictions. XAI shows that the ML can capture the important roles of size exclusion and electrostatic interaction in regulating membrane separation properly. XAI also identifies that the mechanisms governing ion transport possess different relative importance to cation and anion rejections during RO and NF filtration. Overall, we provide a framework to evaluate the knowledge underlying the ML model prediction and demonstrate that ML is able to learn fundamental mechanisms of ion transport across polyamide membranes, highlighting the importance of elucidating model interpretability for more reliable and explainable ML applications to membrane selection and design.

Enhancing the removal of organic micropollutants by nanofiltration membrane with Fe (III)-tannic acid interlayer: Mechanisms and environmental implications

Nanofiltration technology has been applied in a variety of water treatment scenarios. However, conventional thin-film composite (TFC) membranes fail to remove emerging organic micropollutants (OMPs) efficiently. Here we applied thin-film nanocomposite membrane with an interlayer (TFNi) of Fe (III)-tannic acid to remove various types of OMPs, such as endocrine disrupting chemicals (EDCs), pharmaceutically active compounds (PhACs), and perfluoroalkyl substances (PFASs). Compared to the pristine TFC membrane, TFNi membrane exhibited crumpled morphology and its rejection layer was denser, better cross-linked and possessed smaller average pore size with narrower distribution. Significant enhancement in water-OMPs selectivity of PhACs and PFASs was observed. The mechanism lies in the effects of interlayer in improving the membrane permeance to water and meanwhile reducing the permeance to some OMPs by enhancing size exclusion effects. This work confirms the effectiveness of using TFNi membrane to simultaneously enhance the OMPs rejection and water permeance. The unraveled mechanism might inspire the future development of high-performance nanofiltration membranes targeting OMPs removal.

Sustainable Lithium Recovery from Hypersaline Salt-Lakes by Selective Electrodialysis: Transport and Thermodynamics

Evaporative technology for lithium mining from salt-lakes exacerbates freshwater scarcity and wetland destruction, and suffers from protracted production cycles. Electrodialysis (ED) offers an environmentally benign alternative for continuous lithium extraction and is amenable to renewable energy usage. Salt-lake brines, however, are hypersaline multicomponent mixtures, and the impact of the complex brine-membrane interactions remains poorly understood. Here, we quantify the influence of the solution composition, salinity, and acidity on the counterion selectivity and thermodynamic efficiency of electrodialysis, leveraging 1250 original measurements with salt-lake brines that span four feed salinities, three pH levels, and five current densities. Our experiments reveal that commonly used binary cation solutions, which neglect Na+ and K+ transport, may overestimate the Li+/Mg2+ selectivity by 250% and underpredict the specific energy consumption (SEC) by a factor of 54.8. As a result of the hypersaline conditions, exposure to salt-lake brine weakens the efficacy of Donnan exclusion, amplifying Mg2+ leakage. Higher current densities enhance the Donnan potential across the solution-membrane interface and ameliorate the selectivity degradation with hypersaline brines. However, a steep trade-off between counterion selectivity and thermodynamic efficiency governs ED's performance: a 6.25 times enhancement in Li+/Mg2+ selectivity is accompanied by a 71.6% increase in the SEC. Lastly, our analysis suggests that an industrial-scale ED module can meet existing salt-lake production capacities, while being powered by a photovoltaic farm that utilizes <1% of the salt-flat area.

Evaluating the potential of nanofiltration membranes for removing ammonium, nitrate, and nitrite in drinking water sources

Advanced drinking water treatment process using nanofiltration (NF) membranes has gained attention recently because it removes many challenging constituents in contaminated surface waters, such as dissolved organics and heavy metals. However, much literature has reported high variations and uncertainties of NF membranes for removing nitrogen compounds in the contaminated water-ammonium (NH4+), nitrates (NO3-), and nitrites (NO2-). This study aimed to identify the ability of commercial NF membranes to remove NH4+, NO2-, and NO3- and clarify the mechanisms underlying their transport through NF membranes. This was examined by evaluating their rejection by three commercial NF membranes using artificial and actual river waters under various conditions (variable permeate flux, temperature, pH, and ionic strength). Ammonium commonly showed the highest removal among the three nitrogen compounds, followed by nitrites and nitrates. Interestingly, ammonium removal varied considerably from 6% to 86%, depending on the membrane type and operating conditions. The results indicated that the selected nitrogen compounds (NH4+, NO2-, and NO3-) could be highly rejected depending on the clearance between their hydrated radius and the membrane's pore walls. Further, the rejection of the lowest molecular-weight nitrogen compound (NH4+) could be higher than NO2- and NO3- due to its highest energy barrier and larger hydrated radius. This study suggests that compliance with the drinking water regulations of NH4+, NO2-, and NO3- can be reliably achieved by selecting appropriate membrane types and predicting the range of their removal under various feed water quality and operating conditions.

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.

Facile Preparation of Dense Polysulfone UF Membranes with Enhanced Salt Rejection by Post-Heating

Polysulfone (PSf) membranes typically have a negligible rejection of salts due to the intrinsic larger pore size and wide pore size distribution. In this work, a facile and scalable heat treatment was proposed to increase the salt rejection. The influence of heat treatment on the structure and performance of PSf membranes was systematically investigated. The average pore size decreased from 9.94 ± 5.5 nm for pristine membranes to 1.18 ± 0.19 nm with the increase in temperature to 50 °C, while the corresponding porosity decreased from 2.07% to 0.13%. Meanwhile, the thickness of the sponge structure decreased from 20.20 to 11.5 μm as the heat treatment temperature increased to 50 °C. The MWCO of PSf decreased from 290,000 Da to 120 Da, whereas the membrane pore size decreased from 5.5 to 0.19 nm. Correspondingly, the water flux decreased from 1545 to 27.24 L·m-2·h-1, while the rejection ratio increased from 3.1% to 74.0% for Na2SO4, from 1.3% to 48.2% for MgSO4, and from 0.6% to 23.8% for NaCl. Meanwhile, mechanism analysis indicated that the water evaporation in the membranes resulted in the shrinkage of the membrane pores and decrease in the average pore size, thus improving the separation performance. In addition, the desalting performance of the heat-treated membranes for real actual industrial wastewater was improved. This provides a facile and scalable route for PSf membrane applications for enhanced desalination.

Pressure-driven distillation using air-trapping membranes for fast and selective water purification

Membrane technologies that enable the efficient purification of impaired water sources are needed to address growing water scarcity. However, state-of-the-art engineered membranes are constrained by a universal, deleterious trade-off where membranes with high water permeability lack selectivity. Current membranes also poorly remove low-molecular weight neutral solutes and are vulnerable to degradation from oxidants used in water treatment. We report a water desalination technology that uses applied pressure to drive vapor transport through membranes with an entrapped air layer. Since separation occurs due to a gas-liquid phase change, near-complete rejection of dissolved solutes including sodium chloride, boron, urea, and N-nitrosodimethylamine is observed. Membranes fabricated with sub-200-nm-thick air layers showed water permeabilities that exceed those of commercial membranes without sacrificing salt rejection. We also find the air-trapping membranes tolerate exposure to chlorine and ozone oxidants. The results advance our understanding of evaporation behavior and facilitate high-throughput ultraselective separations.

Experimental and Modeling Study of the Nanofiltration of Alcohol-Based Molecules and Amino Acids by Commercial Membranes

The nanofiltration performance of three commercial membranes was analyzed by the Steric Pore Model (SPM) and the extended Nernst-Planck diffusion equation inside membrane pores. The model was completed with the equation to predict the concentration polarization, and the mass transfer coefficient was determined by considering the presence of a feed spacer. The model parameters that characterized the performance of the membrane were the hydrodynamic coefficient, which accounts for the possible variations in solute size and membrane pore radius, the effective membrane thickness, and the water permeability coefficient. All experiments were conducted at fixed feed pH of 6. The rejections of uncharged solutes (glucose for membranes with a high molecular weight cut-off (MWCO) and glycerol and ethylene glycol for membranes with a low MWCO) allowed the model parameters to be determined. We found that glycerol and ethylene glycol overestimate the membrane pore radius due to their ability to interact with the membrane matrix. Therefore, the rejection of glycine as a small amino acid was explored to characterize the membranes with low MWCO since these molecules do not interact with the membrane matrix and have an almost zero charge at pH values between 4.5 and 6.5. Based on the experimental rejections, it was stated that glucose and glycine could be separated by these membranes operating in continuous diafiltration mode.

Modelling the Performance of Electrically Conductive Nanofiltration Membranes

Electrically conductive membranes are a class of stimuli-responsive materials, which allow the adjustment of selectivity for and the rejection of charged species by varying the surface potential. The electrical assistance provides a powerful tool for overcoming the selectivity-permeability trade-off due to its interaction with charged solutes, allowing the passage of neutral solvent molecules. In this work, a mathematical model for the nanofiltration of binary aqueous electrolytes by an electrically conductive membrane is proposed. The model takes into account the steric as well as Donnan exclusion of charged species due to the simultaneous presence of chemical and electronic surface charges. It is shown that the rejection reaches its minimum at the potential of zero charge (PZC), where the electronic and chemical charges compensate for each other. The rejection increases when the surface potential varies in positive and negative directions with respect to the PZC. The proposed model is successfully applied to a description of experimental data on the rejection of salts and anionic dyes by PANi-PSS/CNT and MXene/CNT nanofiltration membranes. The results provide new insights into the selectivity mechanisms of conductive membranes and can be employed to describe electrically enhanced nanofiltration processes.

Regulation of molecular transport in polymer membranes with voltage-controlled pore size at the angstrom scale

Polymer membranes have been used extensively for Angstrom-scale separation of solutes and molecules. However, the pore size of most polymer membranes has been considered an intrinsic membrane property that cannot be adjusted in operation by applied stimuli. In this work, we show that the pore size of an electrically conductive polyamide membrane can be modulated by an applied voltage in the presence of electrolyte via a mechanism called electrically induced osmotic swelling. Under applied voltage, the highly charged polyamide layer concentrates counter ions in the polymer network via Donnan equilibrium and creates a sizeable osmotic pressure to enlarge the free volume and the effective pore size. The relation between membrane potential and pore size can be quantitatively described using the extended Flory-Rehner theory with Donnan equilibrium. The ability to regulate pore size via applied voltage enables operando modulation of precise molecular separation in-situ. This study demonstrates the amazing capability of electro-regulation of membrane pore size at the Angstrom scale and unveils an important but previously overlooked mechanism of membrane-water-solute interactions.

Lithium Concentration from Salt-Lake Brine by Donnan-Enhanced Nanofiltration

Membranes offer a scalable and cost-effective approach to ion separations for lithium recovery. In the case of salt-lake brines, however, the high feed salinity and low pH of the post-treated feed have an uncertain impact on nanofiltration's selectivity. Here, we adopt experimental and computational approaches to analyze the effect of pH and feed salinity and elucidate key selectivity mechanisms. Our data set comprises over 750 original ion rejection measurements, spanning five salinities and two pH levels, collected using brine solutions that model three salt-lake compositions. Our results demonstrate that the Li⁺/Mg²⁺ selectivity of polyamide membranes can be enhanced by 13 times with acid-pretreated feed solutions. This selectivity enhancement is attributed to the amplified Donnan potential from the ionization of carboxyl and amino moieties under low solution pH. As feed salinities increase from 10 to 250 g L^-1, the Li⁺/Mg²⁺ selectivity decreases by ∼43%, a consequence of weakening exclusion mechanisms. Further, our analysis accentuates the importance of measuring separation factors using representative solution compositions to replicate the ion-transport behaviors with salt-lake brine. Consequently, our results reveal that predictions of ion rejection and Li⁺/Mg²⁺ separation factors can be improved by up to 80% when feed solutions with the appropriate Cl^-/SO₄^2- molar ratios are used.

Unlocking the potential of polymeric desalination membranes by understanding molecular-level interactions and transport mechanisms

Polyamide reverse osmosis (PA-RO) membranes achieve remarkably high water permeability and salt rejection, making them a key technology for addressing water shortages through processes including seawater desalination and wastewater reuse. However, current state-of-the-art membranes suffer from challenges related to inadequate selectivity, fouling, and a poor ability of existing models to predict performance. In this Perspective, we assert that a molecular understanding of the mechanisms that govern selectivity and transport of PA-RO and other polymer membranes is crucial to both guide future membrane development efforts and improve the predictive capability of transport models. We summarize the current understanding of ion, water, and polymer interactions in PA-RO membranes, drawing insights from nanofiltration and ion exchange membranes. Building on this knowledge, we explore how these interactions impact the transport properties of membranes, highlighting assumptions of transport models that warrant further investigation to improve predictive capabilities and elucidate underlying transport mechanisms. We then underscore recent advances in in situ characterization techniques that allow for direct measurements of previously difficult-to-obtain information on hydrated polymer membrane properties, hydrated ion properties, and ion-water-membrane interactions as well as powerful computational and electrochemical methods that facilitate systematic studies of transport phenomena.

Prediction of single salt rejection in PES/CMS based membranes

This study explains the modeling of synthesized membranes using the Donnan Steric Pore model (DSPM) based on the Extended Nernst Planck Equation (ENP). Conventionally, structural parameters required to predict the performance of the membranes were determined through tedious experimentation, which in this study are found using a new MATLAB technique. A MATLAB program is used to determine the unknown structural parameters such as effective charge density (X_d), effective pore radius (r_p), and effective membrane thickness to porosity ratio (Δx/A_k) by using the single solute rejection and permeation data. It was found that the model predicted the rejection of studied membranes accurately, with the E5C1 membrane exceeding the others (E5, E5C5) for rejection of single and divalent salt's aqueous solutions. The rejection of 100 ppm aqueous solution of NaCl for E5C1 was around 60%, whereas, for an aqueous solution of 100 ppm, CaCl₂ rejection reached up to 80% at 10 bar feed pressure. The trend of salt rejection for all three membranes was found to be in the following order: E5C1 > E5C5 > E5, confirming that their structural parameters-controlled ion transport in these membranes. The structural parameters, such as effective pore radius, effective membrane thickness to porosity ratio, and effective charge density for the best performing membrane, i.e., E5C1, were determined to be 0.5 nm, 16 μm, and -6.04 mol/m^3,respectively. Finally, it can be asserted that this method can be used to predict the real performance of membranes by significantly reducing the number of experiments previously required for the predictive modeling of nanofiltration-type membranes.

N-Oxide Zwitterion Functionalized Positively Charged Polyamide Composite Membranes for Nanofiltration

N-Oxide zwitterionic polyethyleneimine (ZPEI), a new kind of aqueous phase monomer synthesized by commercially branched polyethyleneimine (PEI) via oxidation reaction, was prepared for fabrication of thin-film composite (TFC) polyamide membranes via interfacial polymerization. The main factors, including the monomer concentration and immersion time of the aqueous phase and organic phase, were investigated. Compared with PEI-TFC membranes, the obtained optimal defect-free ZPEI-TFC membranes exhibited a lower roughness (3.3 ± 0.3 nm), a better surface hydrophilicity, and a smaller pore size (238 Da of MWCO). The positively charged ZPEI-TFC membranes (isoelectric point at pH 8.05) showed higher rejections toward both divalent cationic (MgCl₂, 93.0%) and anionic (Na₂SO₄, 96.1%) salts with a water permeation flux of up to 81.0 L·m^-2·h^-1 at 6 bar, which surpassed currently reported membranes. More importantly, mainly owing to N-oxide zwitterion with strong hydration capability, ZPEI-TFC membranes displayed a high flux recovery ratio (97.0%) toward a model protein contaminant (bovine serum albumin), indicating good anti-fouling properties. Therefore, the novel N-oxide zwitterion functionalized positively charged nanofiltration membranes provide an alternative for water desalination and sewage reclamation.

Molecular Design of the Polyamide Layer Structure of Nanofiltration Membranes by Sacrificing Hydrolyzable Groups toward Enhanced Separation Performance

Nanofiltration (NF) is an effective technology for removing trace organic contaminants (TrOCs), while the inherent trade-off effect between water permeance and solute rejections hinders its widespread application in water treatment. Herein, we propose a novel scheme of "monomers with sacrificial groups" to regulate the microstructure of the polyamide active layer via introducing a hydrolyzable ester group onto piperazine to control the diffusion and interfacial polymerization process. The achieved benefits include narrowing the pore size, improving the interpore connectivity, enhancing the microporosity, and reducing the active layer thickness, which collectively realized the simultaneous improvement of water permeance and enhancement of TrOCs rejection performance. The resulting membranes were superior to both the control and commercial membranes, especially in water-TrOCs selectivity. The effects of using the new monomers on the membrane physicochemical properties were systematically studied, and underlying mechanisms for the enhanced separation performance were further revealed by simulating the polymerization process through density functional theory calculation and measuring the trans-interface diffusion rate of monomers. This study demonstrates a novel promising NF membrane synthesis strategy by designing the structure of reaction monomers for achieving excellent rejection of TrOCs with a low energy input in water treatment.

Modeling micropollutant removal by nanofiltration and reverse osmosis membranes: considerations and challenges

Organic micropollutants (OMPs) in drinking water constitute a potential risk to human health; therefore, effective removal of these pollutants is required. Nanofiltration (NF) and reverse osmosis (RO) are promising membrane-based technologies to remove OMPs. In NF and RO, the rejection of OMPs depends on the properties and characteristics of the membrane, the solute, and the solution. In this review, we discuss how these properties can be included in models to study and predict the rejection of OMPs. Initially, an OMP classification is proposed to capture the relevant properties of 58 OMPs. Following the methodology described in this study, more and new OMPs can be easily included in this classification. The classification aims to increase the comprehension and mechanistic understanding of OMP removal. Based on the physicochemical principles used to classify the 58 OMPs, it is expected that other OMPs in the same groups will be similarly rejected. From this classification, we present an overview of the rejection mechanisms involved in the removal of specific OMP groups. For instance, we discuss the removal of OMPs classified as perfluoroalkyl substances (e.g., perfluorooctanoic acid, PFOA). These substances are highly relevant due to their human toxicity at extremely low concentration as well as their persistence and omnipresence in the environment. Finally, we discuss how the rejection of OMPs can be predicted by describing both the membrane-solution interface and calculating the transport of solutes inside the membrane. We illustrate the importance and impact of different rejection mechanisms and interfacial phenomena on OMP removal and propose an extended Nernst-Plank equation to calculate the transport of solutes across the membrane due to convection, diffusion, and electromigration. Finally, we show how the theory discussed in this review leads to improved predictions of OMP rejection by the membranes.

Roles of Anion-Cation Coupling Transport and Dehydration-Induced Ion-Membrane Interaction in Precise Separation of Ions by Nanofiltration Membranes

Nanofiltration (NF) membranes are playing increasingly crucial roles in addressing emerging environmental challenges by precise separation, yet understanding of the selective transport mechanism is still limited. In this work, the underlying mechanisms governing precise selectivity of the polyamide NF membrane were elucidated using a series of monovalent cations with minor hydrated radius difference. The observed selectivity of a single cation was neither correlated with the hydrated radius nor hydration energy, which could not be explained by the widely accepted NF model or ion dehydration theory. Herein, we employed an Arrhenius approach combined with Monte Carlo simulation to unravel that the transmembrane process of the cation would be dominated by its pairing anion, if the anion has a greater transmembrane energy barrier, due to the constraint of anion-cation coupling transport. Molecular dynamics simulations further revealed that the distinct hydration structure was the primary origin of the energy barrier difference of cations. The cation having a larger incompressible structure after partial dehydration through subnanopores would induce a more significant ion-membrane interaction and consequently a higher energy barrier. Moreover, to validate our proposed mechanisms, a membrane grafting modification toward enlarging the energy barrier difference of dominant ions achieved a 3-fold enhancement in ion separation efficiency. Our work provides insights into the precise separation of ionic species by NF membranes.

Applying Transition-State Theory to Explore Transport and Selectivity in Salt-Rejecting Membranes: A Critical Review

Membrane technologies using reverse osmosis (RO) and nanofiltration (NF) have been widely implemented in water purification and desalination processes. Separation between species at the molecular level is achievable in RO and NF membranes due to a complex and poorly understood combination of transport mechanisms that have attracted the attention of researchers within and beyond the membrane community for many years. Minimizing existing knowledge gaps in transport through these membranes can improve the sustainability of current water-treatment processes and expand the use of RO and NF membranes to other applications that require high selectivity between species. Since its establishment in 1949, and with growing popularity in recent years, Eyring's transition-state theory (TST) for transmembrane permeation has been applied in numerous studies to mechanistically explore molecular transport in membranes including RO and NF. In this review, we critically assess TST applied to transmembrane permeation in salt-rejecting membranes, focusing on mechanistic insights into transport under confinement that can be gained from this framework and the key limitations associated with the method. We first demonstrate and discuss the limited ability of the commonly used solution-diffusion model to mechanistically explain transport and selectivity trends observed in RO and NF membranes. Next, we review important milestones in the development of TST, introduce its underlying principles and equations, and establish the connection to transmembrane permeation with a focus on molecular-level enthalpic and entropic barriers that govern water and solute transport under confinement. We then critically review the application of TST to explore transport in RO and NF membranes, analyzing trends in measured enthalpic and entropic barriers and synthesizing new data to highlight important phenomena associated with the temperature-dependent measurement of the activation parameters. We also discuss major limitations of the experimental application of TST and propose specific solutions to minimize the uncertainties surrounding the current approach. We conclude with identifying future research needs to enhance the implementation and maximize the benefit of TST application to transmembrane permeation.

Valorization of UWWTP effluents for ammonium recovery and MC elimination by advanced AOPs

The main objective of this study was to generate ready-to-use revalorized irrigation water for fertilization from urban wastewater treatment plant (UWWTP) effluents. The focus was on controlled retention of NH₄⁺ and microcontaminants (MC), using nanofiltration. Retentates generated were treated by solar photo-Fenton at circumneutral pH using Ethylenediamine-N, N'-disuccinic acid (EDDS) iron complexing agent. Solar photo-Fenton degradation efficacy was compared with electrooxidation processes as anodic oxidation, solar-assisted anodic oxidation, electro-Fenton and solar photoelectro Fenton. Finally, phytotoxicity and acute toxicity tests were performed to demonstrate the potentially safe reuse of treated wastewater for crop irrigation. Nanofiltration was able to produce a ready-to-use permeate stream containing recovered NH₄⁺. (valuable nutrient). Solar photo-Fenton treatment at circumneutral pH would only be of interest for rapid degradation of contaminants at less than 1 mg/L in nanofiltration retentates. Other alternative tertiary treatments, such as electrooxidation processes, are a promising alternative when a high concentration of MC requires longer process times. Anodic oxidation was demonstrated to be able to eliminate >80% of microcontaminants and solar-assisted anodic oxidation significantly reduced the electricity consumption. Electro-Fenton processes were the least efficient of the processes tested. Phytotoxicity results showed that irrigation with the permeates reduced germination, root development was mainly promoted and shoot development was positive only at low retention rate (concentration factor = 2). Acute and chronic Daphnia magna toxicity studies demonstrated that the permeate volumes should be diluted at least 50% before direct reuse for crop irrigation.

Azo-Dye-Functionalized Polycarbonate Membranes for Textile Dye and Nitrate Ion Removal

Challenges exist in the wastewater treatment of dyes produced by the world’s growing textiles industry. Common problems facing traditional wastewater treatments include low retention values and breaking the chemical bonds of some dye molecules, which in some cases can release byproducts that can be more harmful than the original dye. This research illustrates that track-etched polycarbonate filtration membranes with 100-nanometer diameter holes can be functionalized with azo dye direct red 80 at 1000 µM, creating a filter that can then be used to remove the entire negatively charged azo dye molecule for a 50 µM solution of the same dye, with a rejection value of 96.4 ± 1.4%, at a stable flow rate of 114 ± 5 µL/min post-functionalization. Post-functionalization, Na⁺ and NO3⁻ ions had on average 17.9%, 26.0%, and 31.1% rejection for 750, 500, and 250 µM sodium nitrate solutions, respectively, at an average flow rate of 177 ± 5 µL/min. Post-functionalization, similar 50 µM azo dyes had increases in rejection from 26.3% to 53.2%. Rejection measurements were made using ultraviolet visible-light spectroscopy for dyes, and concentration meters using ion selective electrodes for Na⁺ and NO3⁻ ions.