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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7

Sequestration and release of nitrite and nitrate in alkali-activated slag: A route toward smart corrosion control

Intercalating the corrosion inhibitive ions in hydrotalcite is a promising approach to improve the long-term efficiency of inhibitors in corrosion protection of steel in reinforced concrete. In this work, the potential of autogenously generating nitrite- and nitrate-intercalated hydrotalcite in alkali-activated slag (AAS) is investigated. The results show that the added nitrite and nitrate ions are preferably uptaken in the interlayer structure of hydrotalcite in AAS, and the sequestered nitrite and nitrate are released upon chloride exposure in seawater and NaCl solution. The incorporation of nitrite and nitrate has little detrimental effects on the chloride binding capacity of AAS but slightly enhances the chloride ingress due to the pore coarsening effect. Similar to ordinary Portland cement (OPC), AAS is more permeable to the chloride in seawater than NaCl solution. However, unlike the release of bound chloride contributed by ettringite formation in seawater-exposed OPC, the enhanced chloride ingress in seawater-exposed AAS is primarily attributed to the aggravated pH reduction at the exposure front due to brucite formation. This study contributes to the design of alkali-activated binders with a smart inhibitor releasing ability for mitigating corrosion of steel in concrete.

36 MATERIALS SCIENCE↗

Co-Assembly of Carbon Nanotube Porins into Biomimetic Peptoid Membranes

Robust and cost-effective membrane-based separations are essential to solving many global crises, such as the lack of clean water. Even though the current polymer-based membranes are widely used for separations, their performance and precision can be enhanced by using a biomimetic membrane architecture that consists of highly permeable and selective channels embedded in a universal membrane matrix. Researchers have shown that artificial water and ion channels, such as carbon nanotube porins (CNTPs), embedded in lipid membranes can deliver strong separation performance. However, their applications are limited by the relative fragility and low stability of the lipid matrix. In this work, we demonstrate that CNTPs can co-assemble into two-dimension (2D) peptoid membrane nanosheets, opening up a way to produce highly programmable synthetic membranes with superior crystallinity and robustness. A combination of molecular dynamics (MD) simulations, Raman spectroscopy, X-ray diffraction (XRD), and atomic force microscopy (AFM) measurements to verify the co-assembly of CNTP and peptoids are used and show that it does not disrupt peptoid monomer packing within the membrane. In conclusion, these results provide a new option for designing affordable artificial membranes and highly robust nanoporous solids.

36 MATERIALS SCIENCE↗

Production of β-ketoadipic acid from glucose in Pseudomonas putida KT2440 for use in performance-advantaged nylons

Biomass-derived chemicals can offer unique chemical functionality relative to petroleum-derived building blocks. To this end, here we report that β-ketoadipic acid (βKA), a C6 diacid with a β-ketone group, can be used as a performance-advantaged replacement for adipic acid in a nylon-6,6 analog. Building on our previous efforts to produce shikimate-derived products from carbohydrates, Pseudomonas putida KT2440 is engineered to produce βKA from glucose, achieving a 26 g/L titer. Following purification, βKA imparts an increase of 69 degrees C above the nylon-6,6 glass transition temperature and 20% reduced water permeability, equivalent to nylon-6,10. Molecular simulations predict that the enhanced thermal properties result from rigidity introduced by the β-ketone. Process analysis predicts that βKA can be produced for US$1.94/kg from sugars, requiring 63% less energy and emitting 43% less greenhouse gases than fossil-based adipic acid. Overall, this study illustrates the potential for βKA to serve as a useful building block for bio-based polymers.

09 BIOMASS FUELS↗

NF-κB and neutrophil extracellular traps cooperate to promote breast cancer progression and metastasis

Highlights: • Cancer cells–derived factors, such as IL-8 and G-CSF, induce NETs formation via PAD4 and NF-κB. • NETs increase the interaction of NEMO with IKKα/β and enhance NF-κB activation. • Blockade of NETs using PAD4 inhibitor decreases NF-κB and tumor metastasis. • Selective inhibition of NF-κB reduces NETs formation and tumor growth and metastasis. Aberrant NF-κB activation and neutrophil extracellular traps (NETs) are associated with breast cancer progression. How NF-κB and NETs modulate each other in breast cancer development remains unclear. Here, we found that NETs induced by phorbol 12-myristate 13-acetate promote breast cancer cell progression. In turn, cancer cells–derived factors, such as IL-8 and granulocyte colony-stimulating factor, stimulate neutrophils to form NETs. Mechanistically, NETs increased the interaction of NF-κB essential modifier (NEMO) with IκB kinase (IKK)α/β and enhanced NF-κB activation. We then employed a cell-permeable peptide corresponding to the NEMO-binding domain (NBD) of IKKα/β, termed NBD peptide, which disrupts NETs-mediated NEMO interaction with IKKα/β and abolished NF-κB activation in vitro. NBD peptide also reduced IL-8 level and NETs formation, and suppressed primary tumor growth and/or lung metastasis in human breast cancer mouse xenograft models and mouse spontaneous breast cancer model. Blockade of NET formation using a peptidylarginine deiminase 4 (PAD4) pharmacologic inhibitor decreased NF-κB activation and tumor metastasis. Collectively, these data suggest that NF-κB associates with NETs to form a positive loop facilitating breast tumor progression and metastasis, and that selective inhibition of NF-κB and PAD4-dependent NETs provides an effective therapeutic approach for treating breast cancer.

60 APPLIED LIFE SCIENCES↗

Effective Permeability of a Nuclear Fuel Assembly

This report aids in the development of models to perform characterization studies of aerosol dispersal and deposition within a spent fuel cask system. Due to the complex geometry in a spent-fuel canister, direct simulation of buoyancy-driven flow through the fuel assemblies to model aerosol deposition within the fuel canister is computationally expensive. Identification of an effective permeability as given in this work for a nuclear fuel assembly greatly simplifies the requirements for thermal hydraulic computations. The results of computations performed using OpenFOAM® to solve the Navier-Stokes Equations for laminar flow are used to determine an effective permeability by applying Darcy's Law. The computations are validated against an analytical solution for the special case of an infinite array of pins for which the numerical and analytical solutions have excellent agreement. The effective permeability of a 1717 PWR nuclear fuel assembly in a basket without spacer grids is numerically determined to be 1.85010 -6 m 2 for the range of fluid viscosities and pressure drops expected in a spent fuel storage canister. However, the flow is not uniform on the scale of multiple pins. Instead, significantly higher velocities are attained in the space between the assembly and the basket walls compared to the flow between the fuel pins within the assembly. Comparison with an analytical solution for fully developed flow through an infinite array of pins shows that the larger spacing near the basket walls results in about a 20% larger permeability compared to the analytical solution which does not include the enhanced flow in the space between the assembly and basket wall, or entrance and exit effects. A preliminary assessment of turbulence effects shows that with a k-epsilon model, significantly higher flow velocities are attained between the fuel pins within the assembly compared to the flow velocity in the space between the assembly and the basket walls. This is the opposite of what is determined for laminar flow.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Influence of Reservoir Convection on Heat Extraction with Closed-Loop Geothermal Systems

Over the past few years, advancements in closed-loop geothermal systems (CLGS), also called advanced geothermal systems (AGS), have sparked a renewed interest in these types of designs. CLGS have certain advantages over traditional and enhanced geothermal systems (EGS), including not requiring in-situ reservoir permeability, conservation of the circulating fluid, and allowing for different fluids, including working fluids directly driving a turbine at the surface. CLGS may be attractive in environments where water resources are limited, rock contaminants must be avoided, and stimulation treatments are not available (e.g., due to regulatory or technical reasons). Despite these advantages, CLGS have some challenges, including limited surface area for heat transfer and requiring long wellbores and laterals to obtain multi-MW output in conduction-only reservoirs. CLGS have been investigated in conduction-only systems. In this paper, we explore the impact of both forced and natural convection on the levels of heat extraction with a CLGS deployed in a hot wet rock reservoir. We bound potential benefits of convection by investigating liquid reservoirs over a range of natural and forced convective coefficients. Additionally, we investigate the effects of permeability, porosity, and geothermal temperature gradient in the reservoir on CLGS outputs. Reservoir simulations indicate that reservoir permeabilities of at least ~100 mD are required for natural convection to increase the heat output with respect to a conduction-only scenario. The impact increases with increasing reservoir temperature. When subject to a forced convection flow field, Darcy velocities of at least 10-7 m/s are required to obtain an increase in heat output.

advanced geothermal systems↗

Transient evolution of permeability and friction in a slowly slipping fault activated by fluid pressurization

The mechanisms of permeability and friction evolution in a natural fault are investigated in situ. During three fluid injection experiments at different places in a fault zone, we measured simultaneously the fluid pressure, fault displacements and seismic activity. Changes in fault permeability and friction are then estimated concurrently. Results show that fault permeability increases up to 1.58 order of magnitude as a result of reducing effective normal stress and cumulative dilatant slip, and 19-to-60.8% of the enhancement occurs without seismic emissions. When modeling the fault displacement, we found that a rate-and-state friction and a permeability dependent on both slip and slip velocity together reasonably fit the fault-parallel and fault-normal displacements. This leads to the conclusion that the transient evolution of fault permeability and friction caused by a pressure perturbation exerts a potentially dominant control on fault stability during fluid flow.

58 GEOSCIENCES↗

Controlled Enzyme Cargo Loading in Engineered Bacterial Microcompartment Shells

Bacterial microcompartments (BMCs) are nanometer-scale organelles with a protein-based shell that serve to colocalize and encapsulate metabolic enzymes. They may provide a range of benefits to improve pathway catalysis, including substrate channeling and selective permeability. Several groups are working toward using BMC shells as a platform for enhancing engineered metabolic pathways. The microcompartment shell of Haliangium ochraceum (HO) has emerged as a versatile and modular shell system that can be expressed and assembled outside its native host and with non-native cargo. Further, the HO shell has been modified to use the engineered protein conjugation system SpyCatcher–SpyTag for non-native cargo loading. Here, we used a model enzyme, triose phosphate isomerase (Tpi), to study non-native cargo loading into four HO shell variants and begin to understand maximal shell loading levels. We also measured activity of Tpi encapsulated in the HO shell variants and found that activity was determined by the amount of cargo loaded and was not strongly impacted by the predicted permeability of the shell variant to large molecules. All shell variants tested could be used to generate active, Tpi-loaded versions, but the simplest variants assembled most robustly. We propose that the simple variant is the most promising for continued development as a metabolic engineering platform.

59 BASIC BIOLOGICAL SCIENCES↗

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↗

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↗

Porous Flow Modeling of Axial Gas Redistribution in Fragmented LWR Fuel Rods using MOOSE

Understanding how gas axially redistributes within fragmented fuel pellets is crucial for predicting the behavior of Light Water Reactor (LWR) fuel rods, particularly during transient and accidental scenarios. The time scale of this phenomenon plays a fundamental role in determining the progression and hazard of a Loss Of Coolant Accident (LOCA), especially when high burn-up fuel in a severe state of fragmentation is involved. Here, this study presents a Computational Fluid Dynamics (CFD) model developed within the Multiphysics Object-Oriented Simulation Environment (MOOSE) to predict the time-scale of plenum depressurization in Light-Water Reactor (LWR) fuel rods driven by axial gas transport through fragmented pellets. The model examines the effects of incorporating non-linearities in the friction term by comparing the results with experimental data. The experiment employed surrogate fuel rods containing pellets subjected to mechanical and/or thermal loadings to simulate various severity of cracking, and aimed at studying the influence of fuel conditions on axial gas redistribution. The results of this analysis indicate that under certain flow regime conditions - determined by the value of an equivalent Reynolds number - accounting for the non-linear friction term in Navier-Stokes equations guarantees better predictions for the time-scale of plenum depressurization. Also, the model enabled the simulation of the pressure decay by assigning distinct permeability values to each pellet instead of a single uniform value. Multiple simulations were run across all possible pellet position combinations, having each pellet assigned with values of permeability extracted from the experimental data. This allows to quantify the impact of the considering various non-uniform distributions of permeability on the dynamics of axial gas redistribution. The present work findings enhance the understanding of axial gas transport, and provide valuable insights for the integration of a model for predicting the axial gas redistribution during a LOCA scenario into the BISON fuel performance code.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Self-Sealing Mafic Sills for Carbon and Hydrogen Storage

Tabular igneous intrusions (sills) are common features in sedimentary basins and have the potential to be useful seals for fluids (e.g., CO 2 or H 2 ) in geological storage scenarios, and may be important as the need for geologic carbon sequestration and alternative fuel storage increases. This is advantageous in regions without ready access to large-volume reservoirs in depleted hydrocarbon plays and saline aquifers, like the northeastern United States. Moreover, geological H 2 storage requires more demanding conditions than typically associated with oil and gas. An enhanced seal will have the properties of a traditional seal - competent, low permeability, and laterally extensive - with the addition of being able to self-seal pre-existing and induced fractures. Self-sealing will occur along fluid pathways like fractures where CO 2 , water, and minerals like plagioclase, olivine, and pyroxene react together. Dolerite sills from the Gettysburg Basin, Pennsylvania, have remarkably low permeability and homogeneous compositions that include minerals that will readily react with CO 2 dissolved in water. Here, we characterize the physical properties and chemical gradients within several mafic sills cored in five boreholes. In addition, preliminary CO 2 -reaction experiments on dolerite samples demonstrated rapid carbonate mineralization.

58 GEOSCIENCES↗

Integration and Demonstration of Monitoring, Modeling, and Prediction of DV-1 Amendment Performance at the Bench Scale: DV-1 Amendment Demonstration

During fiscal years 2024 and 2025, the U.S. Department of Energy’s Hanford Field Office commissioned Pacific Northwest National Laboratory to conduct applied research aimed at reducing the cost, time, and uncertainty associated with in situ treatment of vadose zone contaminants at the Hanford Site. This report outlines the integration of three key research efforts into a meso-scale demonstration designed to advance field-scale solutions that aim to (1) optimize the delivery of chemical amendments to contaminated soils, (2) reduce uncertainty in amendment delivery performance assessment using advanced monitoring techniques, and (3) provide real-time insights into when and where amendment-induced precipitation reactions occur in the subsurface. To achieve these objectives, the tank-scale (~ 1 cubic meter) Geophysical Imaging of Flow and Transport (GIFT) system was developed. GIFT enables experimental testing of amendment delivery while incorporating automated multi-modal monitoring approaches, including pressure measurements, direct fluid sampling, and remote time-lapse geophysical imaging. The data generated from these monitoring techniques will serve as inputs for a generative artificial-intelligence-driven digital twin – a numerical simulation model designed to honor observed data while quantifying uncertainty in simulation accuracy. Using this simulator, researchers will refine an amendment injection strategy to maximize delivery efficiency within a low-permeability soil zone. Monitoring data will be interpreted through simulated outputs to enhance understanding of the injection process. The efficacy of this integrated approach will be evaluated through direct sampling at the conclusion of the experiment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Deep learning forecasts the spatiotemporal evolution of fluid-induced microearthquakes

Microearthquakes generated by subsurface fluid injection record the evolving stress state and permeability of reservoirs. Forecasting their spatiotemporal evolution is therefore critical for applications such as enhanced geothermal systems, carbon dioxide sequestration and other geoengineering applications. Here we propose a transformer neural network model that ingests hydraulic stimulation history and prior microearthquake observations to forecast four key quantities: cumulative microearthquake count, cumulative logarithmic seismic moment, and the 50th- and 95th-percentile extents of the microearthquake cloud. Applied to the EGS Collab Experiment 1 dataset, the model achieves R2 > 0.98 for the 1-s forecast horizon and R2 > 0.88 for the 15-s forecast horizon across all targets, and supplies uncertainty estimates through a learned standard deviation term. These accurate, uncertainty-quantified forecasts enable real-time inference of fracture propagation and permeability evolution, demonstrating the strong potential of deep-learning approaches to improve seismic-risk assessment and guide mitigation strategies in future fluid-injection operations.

Chung, Jaehong↗

Hawaii Play Fairway Analysis: Lanai Resistivity and Density 3D Inversion Models

To prepare for its third phase, the Hawaii Play Fairway project conducted groundwater sampling and analyses in ten locations in the Hawaiian islands, magnetotelluric (MT) and gravity surveys, as well as calculations of 3D subsurface stress due to the weight of the rock underlying the topography of the volcano. The subsurface stresses were used to evaluate the potential for fracture-induced permeability. Inversions of the MT and gravity data produce 3D models of resistivity and density, respectively, on Lanai, across Haleakala's SW rift (Maui), and surrounding Mauna Kea (Hawaii Island). The project developed and applied a new method for incorporating depth information about resistivity, density, and potential for fracture-induced permeability into the statistical method for computing resource probability in these three focus areas. The project then incorporated the new groundwater results with the new geophysical results and the calculations of potential for fracture-induced permeability to produce updated maps of resource probability and confidence. These results were used to identify target sites for exploratory drilling. Spreadsheet information: Each sheet contains data for a particular depth in kilometers. Positive depths are above sea level, and negative below. For more information, go to the Hawaii Groundwater and Geothermal Resources Center website linked in the resources.

15 GEOTHERMAL ENERGY↗

Vacuum-assisted carbon molecular sieve membrane reactor for non-oxidative ethane dehydrogenation

Non-oxidative ethane dehydrogenation (EDH) is equilibrium-limited and endothermic. Selective hydrogen removal using a gas-permeable membrane within the EDH reaction zone can overcome the thermodynamic equilibrium, enabling higher ethane conversions. Employing vacuum as the permeation driving force, rather than a sweep gas, enhances the industrial viability of membrane reactors by eliminating additional post-reaction separation units. This study presents a membrane reactor that integrates H 2 -permeable carbon molecular sieve (CMS) hollow fiber membranes embedded in a fixed bed of cobalt in a dealuminated beta zeolite (Co@DeAl-BEA) catalyst, utilizing a vacuum to remove hydrogen efficiently. The CMS membrane exhibits high hydrogen permeance and an excellent H 2 /C 2 H 6 separation factor. The membrane reactor significantly enhanced the ethane conversion under reaction conditions comparable to those reported in the literature. A Langmuir-Hinshelwood kinetic rate expression was developed and incorporated into a one-dimensional steady-state reactor model. The experimentally validated model indicates that increasing the number of hollow fibers improves ethane conversion, although ethane loss to the permeate limits the benefit. The contact area between the catalyst and the membrane limits the reactor performance more than the catalytic throughput. Furthermore, we find that the location of the catalyst packing relative to the hollow fiber membranes influences ethane loss and conversion. Higher reactor pressures and inlet ethane flow rates improve space-time yield at the expense of lower ethane conversion. Increasing reactor temperature or packing length promotes both performance metrics. The EDH membrane reactor demonstrated durability over 200 h of continuous operation, maintaining record-low deactivation rates and high ethylene selectivity. Protocols for catalyst regeneration were developed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

In Situ Growth of Crystalline and Polymer-Incorporated Amorphous ZIFs in Polybenzimidazole Achieving Hierarchical Nanostructures for Carbon Capture

We report mixed matrix materials (MMMs) hold great potential for membrane gas separations by merging nanofillers with unique nanostructures and polymers with excellent processability. In situ growth of the nanofillers is adapted to mitigate interfacial incompatibility to avoid the selectivity loss. Surprisingly, functional polymers have not been exploited to co-grow the nanofillers for membrane applications. Herein, in situ synergistic growth of crystalline zeolite imidazole framework-8 (ZIF-8) in polybenzimidazole (PBI), creating highly porous structures with high gas permeability, is demonstrated. More importantly, PBI contains benzimidazole groups (similar to the precursor for ZIF-8, i.e., 2-methylimidazole) and induces the formation of amorphous ZIFs, enhancing interfacial compatibility and creating highly size-discriminating bottlenecks. For instance, the formation of 15 mass% ZIF-8 in PBI improves H- 2 permeability and H- 2 /CO 2 selectivity by approximate to 100% at 35 degrees C, breaking the permeability/selectivity tradeoff. This work unveils a new platform of MMMs comprising functional polymer-incorporated amorphous ZIFs with hierarchical nanostructures for various applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Creation of Self-Semi-Interpenetrating Network Structures in PIM-1 Membranes for Enhanced Physical Aging Resistance

A series of self-semi-interpenetrating network (ssIPN) thin films based on PIM-1 structure were developed by end-cross-linking telechelic PIM-1 oligomers end-capped with curable carboxylic acid groups to form model networks, which are penetrated by linear high-molecular-weight PIM-1 chains. ssIPN films with systematically varied network content ranging from 10 to 30 wt % were comprehensively examined on their microstructure and gas permeation properties. Fresh PIM-1 ssIPN films exhibited gas separation performances close to those of as-cast linear PIM-1, where the films closely followed the upper bound trade-off line, gaining as much selectivity as they lose gas permeability as the network content increases. This indicates that gas permeability is largely preserved despite cross-linking. Wide-angle X-ray scattering supported this observation, with peaks shifting toward lower d-spacing as oligomer content increased, suggesting tighter chain packing with higher cross-linkable oligomer loading. In physical aging studies over two months, all ssIPN films outperform linear PIM-1 for H 2 /CH 4 and O 2 /N 2 separations. Notably, the PIM-1 ssIPN with 10 wt % network content showed the best physical aging resistance, with negligible permeability loss even after one month. Finally, these findings highlight a promising macromolecular strategy for enhancing the physical aging resistance of microporous polymer membranes for gas separation.

PIM-1↗