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At least 271 records · Page 15

Impact of inland boundary conditions on seawater intrusion modeling in stratified coastal aquifers under sea-level rise

This study systematically examines the impact of inland boundary conditions on seawater intrusion modeling in general stratified coastal aquifers under sea-level rise (SLR). We derived analytical solutions for seawater wedge toe positions in stratified aquifers with general head boundary (GHB) conditions and compiled solutions for constant head boundary (CHB), constant flux boundary (CFB), and GHB conditions in both homogeneous and stratified aquifers. Additionally, we introduced the concept of equivalent boundary conditions and developed equations to ensure consistent steady-state toe positions across different boundary types. Unlike previous studies focusing on specific layering configurations, we conducted a comprehensive sensitivity analysis of seawater intrusion in general stratified aquifers using transmissivity centroid elevation (TCE). Our results show that SLR generally exacerbates seawater intrusion, with unconfined aquifers exhibiting higher sensitivity across all boundary conditions. Among boundary types, CHB conditions were the most sensitive to SLR, CFB the least, and GHB showed an intermediate response depending on its distance from the model boundary. Furthermore, seawater intrusion increases with the TCE of the stratified aquifer under SLR, suggesting that high-permeability or preferential flow layers near the surface amplify the impact of SLR. These findings emphasize the importance of selecting appropriate boundary conditions when evaluating SLR-driven seawater intrusion in stratified coastal aquifers.

Boundary condition↗

Site specific porosity-thermal performance correlations in neutron irradiated U-10Zr fuel

In this work, we present a site-specific three-dimensional analysis of porosity evolution in neutron-irradiated U–10Zr metallic fuel using high-resolution synchrotron X-ray tomography. Focused ion beam cubic lift-outs from four radial positions—fuel center, middle, edge, and fuel-cladding interaction (FCCI) zones—were imaged, reconstructed, and segmented to quantify pore volume, density, morphology, and pore connectivity. Porosity increased modestly from 5.5% at the center to 10.5% at the edge, yet pore number density increased by over two orders of magnitude in the fuel portion near the FCCI interface (from 4.8 x 10 4 to 6.0 x 10 6 pores/mm 3 ). Morphological classification revealed a progression from small spherical pores at the center to equiaxed and tortuous networks at the periphery, with enhanced orientation along the radial direction. Connectivity and permeability analysis reveal that the FCCI region maintains dense, highly interconnected pores despite a moderate volume fraction, enabling rapid fission gas transport and lanthanide migration. Effective thermal conductivity models incorporating sodium logging confirm that these site-specific pore features critically influenced heat transport during reactor irradiation. These findings demonstrate that pore topology—not just porosity fraction—controls thermal performance and thermal pathways in U–10Zr fuels, impacting fuel thermal performance in a reactor.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Fourier-MIONet: Fourier-enhanced multiple-input neural operators for multiphase modeling of geological carbon sequestration

Geologic carbon sequestration (GCS) is a safety-critical technology that aims to reduce the amount of carbon dioxide in the atmosphere, which also places high demands on reliability. Multiphase flow in porous media is essential to understand CO 2 migration and pressure fields in the subsurface associated with GCS. However, numerical simulation for such problems in 4D is computationally challenging and expensive, due to the multiphysics and multiscale nature of the highly nonlinear governing partial differential equations (PDEs). It prevents us from considering multiple subsurface scenarios and conducting real-time optimization. Here, we develop a Fourier-enhanced multiple-input neural operator (Fourier-MIONet) to learn the solution operator of the problem of multiphase flow in porous media. Fourier-MIONet utilizes the recently developed framework of the multiple-input deep neural operators (MIONet) and incorporates the Fourier neural operator (FNO) in the network architecture. Once Fourier-MIONet is trained, it can predict the evolution of saturation and pressure of the multiphase flow under various reservoir conditions, such as permeability and porosity heterogeneity, anisotropy, injection configurations, and multiphase flow properties. Compared to the enhanced FNO (U-FNO), the proposed Fourier-MIONet has 90% fewer unknown parameters, and it can be trained in significantly less time (about 3.5 times faster) with much lower CPU memory (<15%) and GPU memory (<35%) requirements, to achieve similar prediction accuracy. In addition to the lower computational cost, Fourier-MIONet can be trained with only 6 snapshots of time to predict the PDE solutions for 30 years. Furthermore, we observed that Fourier-MIONet can maintain good accuracy when predicting out-of-distribution (OOD) data. The excellent generalizability of Fourier-MIONet is enabled by its adherence to the physical principle that the solution to a PDE is continuous over time. Furthermore, the developed Fourier-MIONet makes it possible to solve the long-time evolution of geological carbon sequestration in a large-scale three-dimensional space accurately and efficiently.

97 MATHEMATICS AND COMPUTING↗

Groundwater flowpath characteristics drive variability in per- and polyfluoroalkyl substances (PFAS) loading across a stream-wetland system

Groundwater dependent ecosystems in areas with industrial and military land use are at risk of direct exposure to a wide range of contaminants, including PFAS chemicals. Glaciated terrain often has mixed high and low permeability sediments coupled with groundwater flow-through lake features. These hydrogeologic attributes create highly complex ‘source to seep’ dynamics that make spatiotemporal contaminant transport patterns difficult to predict. We investigated one such system in detail using a suite of heat-tracing and chemical methods. Numerous (n=57) preferential groundwater discharge zones (vertical flux rates ranging 0.2 to 3.2 m/d) were identified across the upper Quashnet River stream-wetland system in Mashpee, MA, USA, adjacent to an Air Force Base with several known PFAS source areas. Surface-water and groundwater samples were collected and analyzed (n=145) for precursors and terminal PFAS compounds between March and September 2022. Samples were collected at identified seeps along the Quashnet River (n=59), from wells upgradient from the stream-wetland system (n= 44), from contributing flow-through kettle lakes (n=8), and at multiple locations along the Quashnet River (n=34). Samples from seeps and wells had measured PFAS concentrations ranging from non-detect to approximate 3,500 ng/L (mean= 1,650 ng/L), and a range of deuterium excess values (3.2 to 15.9 per mil) indicative of varying degrees of groundwater-lake interaction prior to emergence at the discharge zones. Groundwater-lake interaction along flowpaths that sourced the sampled seeps was farther supported by significant correlations (p < 0.01) between deuterium excess and %PFAS precursors, and between %PFAS precursors and multiple terminal PFAS compounds (e.g., PFPeS, PFBS, PFHxS). However, some sampled seeps contributing groundwater to the stream-wetland system had much higher total PFAS concentrations (>1000 ng/L) than the upgradient kettle lakes, despite showing lake (evaporative) isotopic signatures, indicating the potential for groundwater flowpath convergence at wetland discharge zones and the influence of lakebed PFAS precursor reactions. PFAS compounds and water isotopic composition at sampled multilevel groundwater wells, rivers, lakes, and seeps suggest that a complex mixture of source groundwater and flowpath characteristics are responsible for diverse observed PFAS mixtures at preferential discharge zones across the stream-wetland system. Further, total PFAS loading patterns to the Quashnet River via groundwater discharge remained remarkably similar from winter to summer to fall conditions, despite a regional dry period in late summer 2022 with the upper river channel completely drying. This work addresses gaps in the existing PFAS literature by demonstrating the importance of subsurface fate and transport on PFAS compound concentrations in controlling contaminant mass loading in preferential groundwater discharge zones and presents a transferrable field toolkit for efficient characterization of spatially preferential PFAS transport dynamics.

Contaminant transport↗

Modeling nuclear waste disposal in crystalline rocks at the Forsmark and Olkiluoto repository sites – Evaluation of potential thermal–mechanical damage to repository excavations

We conduct coupled thermo-hydro-mechanical modeling of a KBS-3V repository design in crystalline rocks, using data and conditions from the Forsmark in Olkiluoto repository sites in Sweden and Finland. The study focuses on repository performance related to the impact of thermal and hydraulic evolution on the potential for thermal–mechanical damage to underground repository excavations. For the designs and conditions considered at the Forsmark and Olkiluoto repository sites, the simulations show a peak temperature well under the adopted performance target of a 100°C maximum temperature, whereas there is still a high potential for thermal–mechanical damage to the KBS-3V waste deposition holes. The thermal–mechanical damage is much more likely if rock permeability is so low that it delays saturation and swelling of bentonite-clay-based backfill beyond the time for the thermal–mechanical peak, which occurs 50 to 100 years after nuclear waste deposition. We also found that sidewalls of the KBS-3V emplacement tunnels are vulnerable to tensile fracturing due to the combined effect of thermal stressing and backfill swelling. The study highlights a strong interaction between bentonite-based backfill and host rock through capillary suction along with induced rock desaturation. A careful design and selection of the bentonite-clay-based backfill materials for KBS-3V tunnels and deposition holes can facilitate a timely saturation and backfill swelling that in turn can minimize thermal–mechanical damage.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A percolating path to green iron

About 1.9 gigatons of steel is produced every year, emitting 8% (3.6 gigatons) of global CO 2 in the process. More than 50% of the CO 2 emissions come from a single step of steel production, known as ironmaking. Hydrogen- based direct reduction (HyDR) of iron oxide to iron has emerged as an emission-free ironmaking alternative. However, multiple physical and chemical phenomena ranging from nanometers to meters inside HyDR reactors alter the microstructure and pore networks in iron oxide pellets, in ways that resist gaseous transport of H 2 /H 2 O, slow reaction rates, and disrupt continuous reactor operation. Using synchrotron nano X-ray computed tomography and percolation theory, we quantify the evolution of pores in iron oxide pellets and demonstrate how nanoscale pore connectivity influences micro- and macroscale flow properties such as permeability, diffusivity, and tortuosity. Our modeling framework connects disparate scales and offers opportunities to accelerate HyDR.

hydrogen↗

Impact of a Novel Nickel-Based Catalyst and Phenyl-Acrylate-Based Anion-Exchange Membrane in a Direct Urea Fuel Cell

Developing target-specific catalysts and anion-exchange membranes (AEMs) is crucial for direct urea fuel cell (DUFC) performance. To advance the DUFC system, we developed an anode catalyst with a nickel–iron oxyhydroxide/carbon (NiFeOOH/C) nanofibrous structure for the urea oxidation reaction (UOR), where we optimized the Ni/Fe molar ratio as 6:4. The enhanced electrocatalytic activity of the anode (Ni 6 Fe 4 OOH/C) is attributed to the hydroxide group, which responds with urea molecules to enhance the UOR in a pH-neutral system. Here, we employed a recently developed cross-linked phenyl-acrylate-based AEM (PA/M). A DUFC prepared with the anode and PA/M generates a maximum power density of 11.1 mW/cm 2 and 0.92 V open-circuit voltage under 3 M urea as fuel at 25 °C. We further analyzed the applicability of PA/M in a DUFC system by measuring the urea partition coefficients and permeabilities over a range of concentrations.

10 SYNTHETIC FUELS↗

Nondestructive In Operando Imaging of Thin Film Composite Membrane Compaction Enhanced by AI-Based Segmentation

Reverse osmosis (RO) membranes are essential for desalination and water reuse, yet their permeability declines in high-pressure applications due to membrane compaction. This study investigates the structural and functional responses of commercial brackish, seawater, and high-pressure RO membranes at applied pressures up to 120 bar using a multiscale, nondestructive in operando scanning electron microscopy (iSEM) imaging platform. The iSEM technique reveals progressive densification across the composite membrane structure, which correlates with observed declines in water and solute permeance. To quantify these structural changes with greater fidelity, we combined X-ray computed tomography with AI-based segmentation enabling precise analysis of pore size distribution and thickness of the polysulfone support layer. Compared to traditional thresholding, AI segmentation accurately delineates material phases and void spaces, enhancing the reproducibility and resolution of morphological assessments. The results demonstrate that compaction-induced reductions in porosity and thickness strongly impact membrane transport properties. These findings provide mechanistic insights into the compaction behavior of RO membranes and underscore the potential for advanced imaging and AI-driven data analysis to guide the design of next-generation membranes with improved mechanical resilience and operational longevity.

13 HYDRO ENERGY↗

RLMolLM: Reinforcement Learning-Enhanced Language Model Framework for Inverse Molecular Design

Inverse molecular design faces significant challenges due to vast chemical space and complex property requirements. While language models show promise for molecular generation, they struggle with validity, multi-property optimization, and structural constraints. This work presents RLMolLM, a reinforcement learning framework combining Proximal Policy Optimization (PPO) with genetic algorithms to address these limitations. Our approach optimizes multiple user-specified properties including quantitative estimates of drug-likeness (QED), synthetic accessibility (SA), and ADMET (absorption, distribution, metabolism, excretion, and toxicity) endpoints without requiring complete model retraining, while maintaining capability for scaffold-constrained generation where specific substructures must be preserved. We outperform state-of-the-art methods for molecular optimization, achieving best QED scores across GDB13, Moses, and Zinc datasets with up to 31% improvement over previous methods while maintaining excellent validity, uniqueness, and novelty metrics. For simultaneous multi-property optimization, our framework achieves substantial improvements in ADMET properties including 4.5-fold reduction in hERG toxicity and enhanced Caco-2 permeability compared to Moses dataset. Under structural constraints, the framework significantly improves molecular validity while preserving scaffolds and effectively optimizing properties. In conclusion, this versatile solution advances pharmaceutical and materials molecular design through effective integration of reinforcement learning and genetic algorithms with multi-property optimization and scaffold preservation.

Genetic algorithms↗

Self-Assembled Oligomers Facilitate Amino Acid-Driven CO 2 Capture at the Air–Aqueous Interface

Direct air capture of CO 2 using amino acid absorbents, such as glycine or sarcosine, is constrained by the relatively slow mass transfer of CO 2 through the air–aqueous interface. Our recent study showed a marked improvement in CO 2 capture by introducing CO 2 -permeable oligo-dimethylsiloxane (ODMS-MIM + ) oligomers with cationic (imidazolium, MIM + ) headgroups. Here, in this work, we have employed all-atom molecular dynamics simulations in combination with subensemble analysis using network theory to provide a detailed molecular picture of the behavior of CO 2 and the glycinate anions (Gly – ) at the ODMS-MIM + decorated air–aqueous interfaces. We show that the cationic head groups of the surfactants enhance the concentration and lifetime of Gly – in the interfacial region, while ODMS tails promote the physisorption of CO 2 in the interfacial region. Together, these two factors increase the effective region of contact and the probability of interactions between CO 2 and Gly – compared to that of the pure air–aqueous interface. The fundamental insights gained in this work establish essential foundations for developing hybrid systems with oligomer-decorated interfaces to maximize the overall CO 2 capture rates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impact of Ligands on the Ion–Ion Selectivity of Ligand-Appended-Pillar[ n ]arene Channels

Ligand-appended pillar[5]arene (LAP) channels are emerging as a promising platform for ion-selective membranes. In this study, we investigated the ion selectivities of three LAP channels functionalized with distinct ligands: diglycolamine, carbamoylmethyl phosphine oxide, and propionamide phosphonic acid. These ligands were chosen based on their demonstrated affinities for lanthanides in solvent extraction studies. We examined the selectivity of each channel toward a series of monovalent, divalent, and trivalent ions: Li + , Na + , K + , Mg 2+ , Ca 2+ , La 3+ , Eu 3+ , and Yb 3+ . To quantify ion-channel interactions and the energetics of translocation, we computed the potential of mean force (PMF) profiles for each ion. These PMFs were subsequently recast into permeability coefficients, enabling a direct evaluation of ion permselectivity. Our results reveal distinct selectivity patterns governed by the chemical nature of the appended ligands. The diglycolamine-functionalized channel exhibits strong interactions with monovalent ions, leading to replication of the Li + bulk hydration shell within the channel. This promotes preferential transport Li + ions while effectively excluding divalent and trivalent species. In contrast, the carbamoylmethyl phosphine oxide-functionalized channel displays a reduced selectivity between monovalent ions while similarly exhibiting an effective rejection of divalent and trivalent ions. This arises from steric hindrance around channel-lining oxygens imposed by the ligand's bulky phenyl groups which limits heavy ion coordination and promotes retention of hydration shells effectively increasing effective ion size. The propionamide phosphonic acid-functionalized channel exhibits a different trend, favoring ions with lower hydration free energies, with K + ions showing enhanced permeation. These findings highlight the critical role of ligand-ion interactions in modulating ion selectivity within LAP channels. In particular, the strong coordination exhibited by diglycolamine and propionamide phosphonic acid ligands significantly influences the ion transport energetics and selectivity profiles.

hydration↗

Quantifying Membrane Structure and Dynamics during Bioproduct Production in Zymomonas mobilis by Molecular Simulation

The conversion of lignocellulosic biomass into biofuels and bioproducts by microbial biorefineries is central to a sustainable chemical industry. Zymomonas mobilis is one such biorefinery chassis and is resistant to ethanol stress, leading to its use in biomass conversion to biofuels and bioproducts. However, Z. mobilis growth is often inhibited by organic acids, aldehydes, alcohols, ketones, and amides found in biomass hydrolysate. The resulting slow growth inhibits production and as a result drives up the price for the resulting products. One hypothesis is that these molecules interact with or disrupt the bacterial membrane, triggering stress responses and hindering growth. To test this hypothesis at the molecular level, we employ all-atom molecular dynamics (MD) simulations to investigate lignocellulose-derived small molecules and their impact on a biologically relevant Z. mobilis membrane model. Simulations were conducted across a range of inhibitor concentrations from 0 to 2.5 mol %, analyzing key membrane properties such as area per lipid (APL), membrane thickness, lipid-order parameter (−S CH ), lateral diffusion coefficient (D xy ), and permeability coefficient (Pm). From simulation, we observed altered membrane structure and dynamics at these modest small molecule concentrations commonly found in hydrolysates. Generally, the membranes become thinner, with a higher area per lipid and lower-order parameter as the small molecule concentration increases. These trends are stronger for more hydrophobic molecules with greater hydrophobic bulk, as isobutanol, propanol, and propanoic acid showed greater membrane perturbations as the concentration increased compared to other small molecules. Tracking small molecule distributions directly in our equilibrium simulations allows us to determine concentration-dependent free energy profiles for these molecules. While the trends are noisy, generally the barriers to crossing the membrane decrease as the concentration increases, indicating that the membranes become leakier as small molecule concentrations rise. Comparing between native Z. mobilis membranes with hopanoids and membranes sharing the same phospholipid composition but without hopanoids, hopanoids stabilize and order the membrane for smaller molecules to maintain membrane structure but appear insufficient for larger hydrophobic molecules like isobutanol. These findings provide a mechanistic understanding of how small molecules found in biomass degradation streams interact with the Z. mobilis membrane, offering valuable insights for future strain engineering efforts to optimize biofuel and bioproduct synthesis from biomass feedstocks by highlighting limits to small molecule tolerance. This knowledge can guide the modification of membrane composition to develop more robust microbes, thereby improving microbial survival and yields in industrial contexts.

Singh, Nitin Kumar [Michigan State Univ., East Lan↗

Microstructure, Transport, and Mechanics of Compacted Clay Simulated at the 0.1 μm Scale (1400 Smectite Clay Particles) Using a Coarse-Grained Model with Explicit Counterions

Clay-rich geomaterials play a critical role in many subsurface systems. The macroscale properties of these materials (low permeability, high ionic conductivity, high swelling pressure, etc.) are sensitive to molecular-level adsorption and hydration interactions at clay−water interfaces. Efforts to develop multiscale simulation approaches to predict these properties reveal a scale gap between atomistic simulations (typically limited to systems smaller than 10 nm) and continuum-scale models (which use computational grid elements with dimensions ≳ 10 μm). In this study, we present a coarse-grained (CG) framework that partly bridges this gap by simulating compacted smectite clay assemblages with dimensions of 0.1 μm containing 1,400 clay particles across a range of dry densities (1,050 to 1,850 kg·m −3 ) and Na/Ca counterion compositions (Na fraction ranging from 0.2 to 1). The simulated systems, along with their reconstructed binary three-dimensional pore networks, are used to evaluate the microstructure, pore size distribution, tortuosity, ion diffusivity, and swelling pressure of compacted smectite clay. Results show that our approach captures important features of the mesoscale heterogeneity of compacted clays, including tactoid formation, hierarchical porosity, and anisotropic pore networks. Results also reveal how compaction and counterion composition govern emergent behaviors, including dominant pore sizes, directional transport, and electrochemical response. This work highlights the potential of CG simulations to bridge molecular and continuum scales and to advance geotechnical and environmental applications involving clay-rich materials as well as related nanoporous media such as geopolymers and calcium-silicate-hydrate. However, the results also suggest that accurate prediction of certain microstructural and mechanical properties (e.g., swelling pressure) may require even larger-scale systems on the order of 1 μm.

02 PETROLEUM↗

Ion Transport in Self-Assembled Peptoid Membranes with Carbon Nanotube Porin Channels

Artificial membranes that combine high ionic selectivity with mechanical robustness remain a key challenge for next-generation separation technologies. Here, we report ion transport measurements in biomimetic membranes composed of crystalline peptoid nanosheets co-assembled with carbon nanotube porins (CNTPs). Pure peptoid sheets formed defect-free, ion-impermeable membranes, which were then suspended over small SiN x nanopore apertures for ion transport measurements. Incorporation of CNTPs into the peptoid sheet matrix made these membranes ion permeable, with ion conductance values consistent with ion transport through individual and multiple carbon nanotube channels. In conclusion, the modularity and molecular order of peptoid membranes, combined with the exceptional conductance properties of CNTPs, position this platform as a versatile framework for assembling programmable, selective, and robust nanofluidic membranes that can bridge the performance gap between biological and synthetic membrane materials.

Biotechnology↗

Nanorod Pair Complexes Manipulated via Magnetic Casimir Forces

Here, we demonstrate a route to modulate Casmir–Lifshitz interactions between anisotropic nanoparticles and magnetic fluids. By semiclassical quantum electrodynamics, we study ground state dispersion forces for cylindrical dielectric nanorods made of polystyrene (PS) and zinc oxide (ZnO) embedded in toluene-based host media with gold-coated magnetite nanoparticles and also predict magnetic contributions to the fully retarded excited state interaction. The variation in magnetic permeability enables tuning between repulsive and attractive interactions, and measurable magnetic Casimir traps are predicted between a pair of ZnO–PS nanoparticles whose equilibrium position can be modulated over an order of magnitude with a small variation in the size of the magnetite nanoparticle. This provides an alternative magnetic Casimir-effect pathway to reversibly tune quantum electromagnetic forces at the nanoscale for the assembly and enhancement of colloidal stability.

Excited-state interaction↗

CO 2 Capture with Capsules of Ionic Liquid/Amines

Carbon capture remains an urgent issue that has gained a great deal of attention over the past few decades. Aqueous amines have excellent selectivity, but present corrosion and volatility issues, whereas ionic liquids (ILs) have negligible volatility and tunable physical properties, but high viscosities. One approach to improve the practical performance of these liquids is encapsulating them in a CO 2 permeable polymer shell to enhance the accessibility of the liquid and the CO 2 absorption rate. In this work, we report the encapsulation of a mixture of amine and IL (i.e., monoethanolamine (MEA) and 1-butyl-3-methylimidazolium tetrafluoroborate ([BMIM][BF 4 ])) and demonstrate enhanced carbon capture performance. A soft-template approach and interfacial polymerization are used to give capsules with liquid core (64 wt %) and polyurea shell. Compared to the bulk liquid, the encapsulated liquid shows improved thermal stability over cycles of absorption at 25 °C, and desorption at 75 °C. The capsules with core of [BMIM][BF 4 ]-MEA show 0.2 mol CO 2 /kg of capsules at 1 bar CO 2 , compared to the bulk liquid, which has 0.05 mol CO 2 /kg of sorbent. This is attributed to the limited evaporation of the amines. Alternatively, the same capsules but with 5 wt % of piperazine (Pz) in the core have doubled gravimetric CO 2 capacity of the capsules (0.4 mol CO 2 /kg of capsules); performance is evaluated over 10 capture–release cycles showing minimal mass loss. Characterization of the CO 2 uptake of the polymer shell itself reveals that the shell contributes only ~10% of the observed capacity, likely attributed to amine functionalities of the polymer. Here, this facile approach to encapsulating such “active” liquids can be applied to other CO 2 selective solvents that are volatile, viscous, and corrosive.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Insights into Probing the Effect of Molecular Weight of Poly(carboxybetaine methacrylate) on the Performance of Forward Osmosis Desalination

Zwitterionic polymers have proven to be a promising nonfouling material that can be applied in the design of selective layers of thin film composite (TFC) membranes. Extending the permeability and usage of TFC membranes have attracted increasing interest in membrane-based desalination processes since water-flux reduction associated with biofouling nowadays persists as a common challenge. By virtue of its strong hydration, this polymer category is very useful to counteract biofouling in marine and biomedical systems, but the benefits from their application in membrane technology are still emerging. The efficacy of the nonfouling property as a function of the polymer’s molecular weight remains unknown. In pursuit of that vision, this study fosters new scientific insights via probing different molecular weights of poly(carboxybetain methacrylate) (PCBMA) coated on the surface as a selective layer for the prepared TFC membranes. The coated zwitterionic membranes (zM) exhibited excellent performance in preventing water flux decay in a bench-scale forward osmosis system. The prepared zM membranes revealed enhanced hydrophilic properties and retained their operational water flux when compared to the control. Our results suggest that using an intermediate-size molecular weight (PCBMA M n 50,000) will result in the best operational performance. The intermediate size resulted in the lowest flux decline rate (R t ) of 0.01 ± 0.001 (zM-50) when compared to the unmodified control membrane 0.56 ± 0.071 (M0) after using a model BSA foulant solution. Furthermore, all coated membranes exhibited similar trends in the observed reverse salt flux profiles, as well. In conclusion, the constructed zM membranes will serve as a model to develop further selective layers in the construction of TFC membranes.

36 MATERIALS SCIENCE↗

Interconnected Nanoporous Polysulfone by the Self-Assembly of Randomly Linked Copolymer Networks and Linear Multiblocks

Porous materials have attracted considerable attention due to their versatile applications, especially in water purification. Interconnected nanoporous structures are distinguished by their high degree of porosity and resistance to clogging, as well as their insensitivity to nanostructural orientation. Previous works on randomly linked copolymer systems have shown that they can effectively produce disordered cocontinuous nanostructures, which upon removal of one component yield interconnected nanoporous materials. However, the cocontinuous nanomaterials previously developed using polystyrene (PS) and poly(d,l-lactic acid) (PLA) strands, and the resulting interconnected nanoporous PS monoliths, were far too brittle to enable practical use as membranes. Here, we study the self-assembly of randomly linked copolymer networks prepared using blocks of the engineering polymer polysulfone (PSU). A wide cocontinuous regime (spanning 40 wt %) was found for randomly end-linked copolymer networks (RECNs) constructed from PSU and PLA strands, via a combination of mechanical testing, gravimetry, small-angle X-ray scattering, and scanning electron microscopy. The PSU/PLA cocontinuous nanomaterial with symmetric composition showed 2.4 times higher Young’s modulus and ~100 times greater toughness than the corresponding PS/PLA sample. The interconnected nanoporous PSU fabricated after etching of PLA even exhibited 1.6 times greater toughness than PS/PLA prior to PLA removal. To facilitate the production of thin films of cocontinuous nanomaterials, we applied solution-processable randomly linked linear PSU/PLA multiblock polymers onto ultrafiltration membranes. Here, the interconnected nanoporous PSU thin film generated by etching PLA was found to effectively reject 50 nm diameter particles without significantly compromising permeability. This discovery presents a valuable addition to the existing techniques used to fabricate PSU membranes. In contrast to traditional methods, which are sensitive to processing conditions, produce a wide range of pore sizes, and offer limited adjustability of pore size, the current technique is anticipated to enable interconnected PSU membranes with more uniform and tailorable porosity.

36 MATERIALS SCIENCE↗