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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Harnessing peptide–cellulose interactions to tailor the performance of self-assembled, injectable hydrogels

Taking inspiration from natural systems, such as spider silk and mollusk nacre, that employ hierarchical assembly to attain robust material performance, we leveraged matrix–filler interactions within reinforced polymer–peptide hybrids to create self-assembled hydrogels with enhanced properties. Specifically, cellulose nanocrystals (CNCs) were incorporated into peptide–polyurea (PPU) hybrid matrices to tailor key hydrogel features through matrix–filler interactions. Herein, we examined the impact of peptide repeat length and CNC loading on hydrogelation, morphology, mechanics, and thermal behavior of PPU/CNC composite hydrogels. The addition of CNCs into PPU hydrogels resulted in increased gel stiffness; however, the extent of reinforcement of the nanocomposite gels upon nanofiller inclusion also was driven by PPU architecture. Temperature-promoted stiffening transitions observed in nanocomposite PPU hydrogels were dictated by peptide segment length. Analysis of the peptide secondary structure confirmed shifts in the conformation of peptidic domains (α-helices or β-sheets) upon CNC loading. Finally, PPU/CNC hydrogels were probed for their injectability characteristics, demonstrating that nanofiller–matrix interactions were shown to aid rapid network reformation (∼10 s) upon cessation of high shear forces. Overall, this research showcases the potential of modulating matrix–filler interactions within PPU/CNC hydrogels through strategic system design, enabling the tuning of functional hydrogel characteristics for diverse applications.

42 ENGINEERING↗
DOE OSTI2025

Strong, ductile, and hierarchical hetero-lamellar-structured alloys through microstructural inheritance and refinement

The strength−ductility trade-off exists ubiquitously, especially in brittle intermetallic-containing multiple principal element alloys (MPEAs), where the intermetallic phases often induce premature failure leading to severe ductility reduction. Hierarchical heterogeneities represent a promising microstructural solution to achieve simultaneous strength−ductility enhancement. However, it remains fundamentally challenging to tailor hierarchical heterostructures using conventional methods, which often rely on costly and time-consuming processing. Here, we report a multiscale microstructural inheritance and refinement strategy to process “structural hierarchy precursors” in as-cast heterogeneous Al 0.7 CoCrFeNi MPEAs, which lead directly to a hierarchical hetero-lamellar structure (HLS) after simple rolling and annealing. Interestingly, it takes only 10 min of annealing time, two orders of magnitude less than that required to render the state-of-the-art properties during conventional processing of Al 0.7 CoCrFeNi, for us to achieve record-high strength−ductility combinations via the hierarchical HLS design that sequentially stimulates multiple unusual deformation and reinforcement mechanisms. In particular, the HLS-enabled high hetero-deformation-induced (HDI) internal stress triggers profuse <111>-type dislocations on over five independent slip systems in the supposedly brittle intermetallic phase and activates extensive stacking faults (SFs) and nanotwinning in the adjoining soft phase with a rather high SF energy. These unexpected, dynamically reinforcing hetero-deformation mechanisms across multiple length scales facilitate high sustained HDI strain hardening, along with a salient microcrack-mediated extrinsic ductilization effect, suggesting that the proposed microstructural inheritance and refinement strategy provides an efficient, fast, and low-cost approach to overcome the strength−ductility trade-off in a broad range of structural materials.

Science & Technology - Other Topics↗
DOE OSTI2024

Low-cost sensor-based damage localization for large-area monitoring of FRP composites

Abstract In recent years, there has been growing interest in self-sensing structural materials across research and industry sectors. Detecting and locating structural damage typically requires numerous sensors wired to a data acquisition (DAQ) circuit, rendering implementation impractical in real structures. This paper proposes an innovative, cost-effective sensor network for damage detection and localization in fiber-reinforced polymer composites. The innovation encompasses three key elements: (1) utilizing carbon fiber tows within the composite as piezoresistive sensors, eliminating the need for additional foreign sensor devices; (2) introducing a novel sensor layout wherein sensor tow branches with varied resistance values are connected in parallel, reducing the number of connections to the DAQ circuit and cutting manufacturing costs significantly; (3) developing a practical sensor terminal fabrication technique to minimize manufacturing expenses. The proposed design methodology for the branch resistance values is first validated using a demonstration panel. Subsequently, the overall strategy is assessed by conducting impact tests on carbon and glass fiber-reinforced composite specimens. Results validate the sensor’s ability to accurately detect and locate structural damage.

Demo, Luke B. (ORCID:0000000208806522)↗
DOE OSTI2025

Optimizing Traffic Signal Control to Enhance Transportation Efficiency and Maximize Pedestrian Benefits in the Road Network

Increasing urban mobility requirements demand efficient transportation system strategies for both vehicular and pedestrian movement. This study enhances the Decentralized Graph-based Multi-Agent Reinforcement Learning (DGMARL) approach, originally tailored for vehicular traffic signal timing, to incorporate pedestrian traffic dynamics. The improved algorithm considers crucial metrics such as Eco_PI, assesses vehicle fuel consumption by factoring in stops and delays, and addresses pedestrian waiting time, crucial for system efficiency while acknowledging driver waiting time impact. Utilizing Digital Twin simulation along the MLK Smart Corridor in Chattanooga, Tennessee, the algorithm's performance is compared for various pedestrian control scenarios. To evaluate the effectiveness of DGMARL, this study compared DGMARL-enabled signal management with automated pedestrian traffic detection and an actuated signal management system (real-word baseline) with pedestrian recall, which predetermingly enforces a pedestrian phase every cycle. Findings indicate substantial improvements with DGMARL, showing a 28.29% enhancement in vehicle Eco_PI, a 60.55 % reduction in pedestrian waiting time, and a 55.74% decrease in driver stop delay, on average, compared to the baseline actuated signal timing plan.

Kumarasamy, Vijayalakshmi K [The University of Ten↗
DOE OSTI2024

Quantum Circuit Partitioning for Scalable Noise-Aware Quantum Circuit Re-Synthesis

Re-synthesis techniques are utilized to optimize the quantum circuit. To enable scalable re-synthesis a divide-and-conquer approach is adopted that partitions the circuit into smaller blocks, which are optimized independently. Several algorithms have been proposed to minimize the block number while maximizing the gate count of each block. However, they vary in their performance and may not yield the highest output fidelity. We propose a reinforcement learning-based quantum circuit partitioning framework that incorporates the physical properties of the quantum hardware to maximize the output fidelity post-quantum circuit optimization. To accelerate the training, we also propose a noise injection method that enables on-the-fly optimization in the reinforcement learning environment, independent of the adopted optimization/re-synthesis method at the block level. We evaluate our approach compared to different partitioning techniques using various quantum benchmarks executed on IBM Q Hanoi quantum computer.

Charrwi, Mohammad Walid↗
DOE OSTI2025

blastforge

BlastForge is a python module meant to aid reinforcement learning research for geometry optimization research projects. The code is built to use PyTorch as a backend and will contain several model architectures and reinforcement learning training loops as well as helper python functions to evaluate a model’s performance during and after training. BlastForge is meant to be a small, focused python project to study moderate-complexity geometry optimization problems

Hickmann, Kyle [Los Alamos National Laboratory]↗
DOE OSTI2024

Advanced Computational Techniques for Improving Resilience of Critical Energy Infrastructure under Cyber-Physical Attacks

In this chapter, we present recent advances in improving the resilience of cyber-physical systems, especially with regards to energy systems. We provide discussions around various types of cyber-physical events that can cause disruptions and new advances in optimization, control, and reinforcement learning (RL) to deal with the challenges posed by such cyber-physical events. The presented methods range from distributed robust optimization, autonomous and coordinated control, reinforcement learning based resilient control and topology reconfiguration in Inter-System resilient control.

Nazir, Mohammad Nawaf [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2026

Data for High Yield Production of 3-Hydroxypropionic Acid Using Issatchenkia orientalis

Biomanufacturing provides a more sustainable alternative to fossil-based chemical manufacturing. 3-Hydroxypropionic acid (3HP) is a top Department of Energy value-added chemical and precursor to bioplastics, yet cost-effective microbial production remains elusive. Here, we establish the acid-tolerant yeast Issatchenkia orientalis as a robust host for low-pH 3HP biosynthesis. Genome-scale modeling identifies the β-alanine pathway as optimal, offering the highest theoretical yield and lowest oxygen requirement. Thermodynamic analysis confirms its favorability under acidic conditions. Using sequence similarity network analysis, we discover highly active aspartate 1-decarboxylase (PAND), β-alanine-pyruvate aminotransferase (BAPAT), and 3HP dehydrogenase (YDFG), which significantly improve the pathway efficiency. Next, to further elevate the production, pathway optimization through multi-copy PAND integration, byproduct elimination (knockouts of pyruvate decarboxylase and glycerol-3-phosphate dehydrogenase), and reinforcement of aspartate flux by overexpression of pyruvate carboxylase and aspartate amino transferase improves the titer to 29 g/L in shake flasks. Fed-batch fermentation at pH 4 with low-cost corn steep liquor medium further increases the production to 92 g/L with 0.7 g/g yield and 0.55 g/L/h productivity. Techno-economic analysis indicates that such performance could potentially enable a financially viable process for sustainable acrylic acid production. This work establishes I. orientalis as a next-generation platform for cost-effective 3HP production and paves the way toward industrial commercialization.

Bioproducts↗
DOE OSTI2026

Surrogate model for third-integer resonance extraction at the Fermilab Delivery Ring

We present an ongoing work in which a surrogate model is being developed to reproduce the response dynamics of the third-integer resonant extraction process in the Delivery Ring (DR) at Fermilab. This is in pursuit of smoothly extracting circulating beam to the Mu2e Experiment’s production target, whereby the goal is to extract a uniform slice of the circulating 1e12 protons in the DR over 25,000 turns (43 ms). The DR contains 3 harmonic sextupoles that excite a third-integer resonance and three fast, tune-ramping quadrupole magnets that drive the horizontal tune towards the 29/3 resonance. In our initial work, the surrogate model trains on a semi-analytical simulation provided in the same format as live data. Using Reinforcement Learning (and other potential ML methods), the trained surrogate acts as the “environment” in which a simple ML control agent could learn to dynamically adjust the quadrupole ramp at 430 break points within the 43 microsecond spill window. The controller will be hosted on a dedicated Arria 10 FPGA. In this work, we report the accuracy and fidelity of the surrogate model in comparison to the response dynamics of the physics simulator.

Narayanan, Aakaash [Fermilab]↗
DOE OSTI2025

Self-healable Copolymer Composites for Extended Service H 2 Dispensing Hoses

In this project, we designed, synthesized and fabricated using X-winder technologies precommercialized novel, self-healingable commodity copolymer fiber-reinforced composites to extend the H 2 hose service life beyond the current target of 1000 fills. These studies demonstrated that these composites are able to withstand over 25,000 damage-repair cycles, which was the main objective of the proposed project, in the temperature range of -40 to +80 °C under variable pressures. When micro-cracks are formed after about 1,000 cycles/fueling per hose in the inner composite layer, these micro-cracks self-heal, thus extending the lifetime of a prototype inner layer of the hose. These composites were tested by exposure to H 2 fuel and demonstrated the ability to recover from mechanical damage. Thermomechanical testing combined with analysis of the stress and strain fields across the cross-section of the inner layer composite hoses also identified the ring-like stresses on the edge of inner layers arising from changes of the fiber winding angle directions from +45° to -45°. The developed novel concept that self-healing commodity copolymers can be used in the development of prototype composites for the extended service of H 2 dispensing hoses will have major implications for other energy-related technologies, where the extended service life in harsh environments is expected. In this project, we optimized, validated, and demonstrated novel copolymer fiber-reinforced composites for H 2 dispensing hose applications, which can be utilized in future manufacturing using commodity materials. The estimated cost of materials (exluding labor) is in the range of < $1.0/ft.

08 HYDROGEN↗
DOE OSTI2025

Design and Production for Maximum Structural Efficiency With Respect to Fiber Orientation With Increased Understanding of Hybrid Fiber Flow Behavior

Discontinuous fiber-reinforced thermoplastic composites have gained considerable attention in automotive, aerospace, and other industries, due to their high-rate of production combined with their ability to attain complex and intricate shapes. Among other high-rate thermoplastic manufacturing processes, injection-molding is one of the most common manufacturing methods due to fast production and high surface finishing of complex geometries. Fiber orientation in discontinuous fiber composites plays a pivotal role in determining the mechanical, electrical, and thermomechanical properties, underscoring the necessity to comprehend fiber orientation in injection molded parts. Among different fiber types, glass and carbon fibers are most common in the composite industries. The recent trend of hybrid composites comprising both glass fiber (GF) and carbon fiber (CF) is also gaining importance in the automotive industry. Hybrid fiber options allow designers to optimize the balance between glass and carbon fibers by leveraging the high durability and low cost of GF while the strength and lightweight properties of CF. Consequently, comparing the fiber oriented distribution (FOD) of injection molded composites containing GF, CF, and a hybrid of GF/CF is critical to investigating the local mechanical properties of intricate structures for high-end applications. In Phase I of this project, FOD in injection-molded panels with respect to distance from the gate was analyzed using X-ray computed tomography (X-CT) for GF, CF, and hybrid CF/GF (CGF) reinforced nylon 66. To understand the reason behind the FOD with different fiber types, computational fluid dynamics (CFD) and rheology were performed. Samples were extracted at three locations: near the gate, center, and opposite end. Thickness of the layers of typical skin-shell-core type FOD varies with fiber type and location. GF achieved flow direction alignment (in shell) earlier than viscous CF and CGF near the gate, whereas CF showed the highest flow-direction alignment at the center due to shear induced orientation. At the opposite end, GF experienced more backflow than others indicating faster mold filling owing to its lower viscosity. Hybrid CGF exhibited GF-dominated center and CF-dominated end region. The numerical model used to obtain FOD and rheological predictions for the CF and GF composites served to corroborate the trends observed in the experimental trials. The FOD responses across fiber types and location were reflected in their longitudinal and transverse properties. Only GF showed higher longitudinal modulus over transverse modulus near the gate attributed to rapid alignment, whereas CF and CGF exhibited opposite trend. However, fountain flow enhanced the longitudinal modulus over transverse modulus with the distance for all, particularly for CF. This study offers insights into mold filling behavior of different fibers which are critical in optimizing injection molding conditions for tailored final properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Fully Recyclable CFRP Particles (CRADA 519)

The proposed resin-enhanced materials, which utilize fully recycled CFRP (carbon-fiber-reinforced polymer) particles, are enabled by PARC's proprietary Chemically Linked Particles Networks (13 granted patents and patent applications). PNNL and PARC have collaborated to develop manufacturing methods, such as vacuum-assisted wet compression molding and filament winding, for fabricating fiber-reinforced composites with the PARC matrix. PNNL has conducted various mechanical, physical, and thermal characterizations to compare their differences between the composites with baseline and PARC matrices. Those characterizations include density, void volume fraction, optical micrography, uniaxial tension, four-point bending/flexure, interlaminar shear, coefficient of thermal expansion, glass transition temperature, and curing kinetics.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Low-Cost Highly Recyclable Structural Composites Utilizing Vitrimers and Natural Fibers (Basalt) Manufactured via a Novel Pultrusion Method for High-Volume Applications

The project’s overall goal is to explore and demonstrate as proof-of-concept that a highly recyclable and repairable composite material system, that is reinforced with natural fibers, can be used to produce lightweight structural components using a low-cost manufacturing process for high-volume automotive applications. More specifically, the project’s objectives will focus on vitrimer resins (which are a hybrid polymeric system of thermoplastics and thermosets) reinforced with basalt fibers and manufactured using pultrusion technologies. Pultrusion, as a method, is well-known to be one of the lowest-cost manufacturing processes for high-volume applications. However, to date, the validity and viability of such attractive objectives have not been demonstrated in support of the automotive industry.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Cathodic Protection Modeling for Hanford Underground Double-Shell Tank Farms

Hanford stores millions of gallons of radioactive and chemically hazardous waste from the production of weapon materials in tank farms consisting of underground carbon-steel storage tanks surrounded by reinforced concrete. Six of these Hanford tank farms use double-shell storage tanks (DSTs). The DST farms were constructed from 1968 to 1986 with a planned 40–50 year design life, so some are already operating beyond their initial life expectancy. Ultrasonic testing (UT) has indicated significant thinning on the bottom of the secondary (outer) liner of these tanks, believed to arise from groundwater intrusion driving concrete side corrosion. There is no direct access to the steel/concrete interface between the tank and the concrete pad, making it difficult to apply a chemical-based mitigation strategy or to conduct repairs, but cathodic protection (CP) is a possible method to inhibit further concrete-side corrosion. Hanford already uses CP to protect below grade steel piping within the tank farms and connected to the tanks, but this system was not designed to protect the tank bottoms. CP design must account for the structures surrounding the DSTs, including the steel reinforcing bars (rebar) within the concrete pad and vault, various process lines, and the existing CP system. In this study, finite element analysis (FEA) modeling was carried out to simulate CP protection of 1) a single tank and CP anode to develop options for modeling the rebar and to compare to a simpler circuit model and 2) the entire Hanford AN tank farm as a representative example consisting of seven tanks, associated piping, and both existing and new CP anodes. Both circuit and FEA models predict that significant protective current could be delivered to the bottoms of the tanks with the addition of tank-protection anodes below the depth of the tanks. Simulations with only the existing pipe-protection anodes active confirmed that only a very small current to the tank bottoms is predicted under present conditions. Multiple simplified representations of the dome and wall rebar were tested to reduce the computational complexity of the tank-farm simulations, resulting in modeling the rebar as edge elements with a prescribed effective circumference that matches the real rebar surface area. The geometry of the rebar is also simplified into horizontal hoops around the tank walls and radial rebar over the dome with increased effective circumference to retain the target surface area. This simplification was found to greatly reduce the complexity and solution time of the models without large changes in current distributions, especially to the tank bottom. A range of values were tested for model parameters such as soil and concrete resistivities and polarization resistance to investigate their impact on the current and electric potential distributions. Depending on the parameters used, FEA simulations predict some risk of overprotection, particularly on the piping system; since overprotection can also lead to surface damage associated with hydrogen gas generation at the interface (e.g. hydrogen embrittlement or damage to coatings), this needs to be considered when refining the design of the new CP system. Comparison between the FEA models and the circuit model representation demonstrated that the circuit model could not match the predicted FEA current distribution, even when using the exact same surface areas. This discrepancy appeared to be at least partly attributable to the impact of the relative positions of the tank components and anodes to each other and to the ground surface. The FEA model accounts for the relative positions since it solves the governing equations in three dimensions, but the circuit model cannot account for the positioning. In particular, the circuit model underpredicts the current to the tank bottom and overpredicts the current to the dome compared to FEA for the baseline geometry. The FEA models omitted the electrically isolated rebar in the bottom concrete slab. However, a circuit based stray current model estimated that only 2.1% of the total current through the slab would stray into the rebar, corresponding to ~0.21 A for a target current density of 2 mA/ft2 to the tank bottom. The estimated corrosion driven by this amount of stray current is predicted to yield a lifetime of >400 years for the minimum rebar diameter, assuming an acceptable cross-section area loss of 10%.

d'Entremont, Anna [Savannah River National Laborat↗
DOE OSTI2024

Multiscale Modeling of Silicon Carbide Cladding for Nuclear Applications: Thermal Performance Modeling

The complex multiscale and anisotropic nature of silicon carbide (SiC) ceramic matrix composite (CMC) makes it difficult to accurately model its performance in nuclear applications. The existing models for nuclear grade composite SiC do not account for the microstructural features and how these features can affect the thermal and structural behavior of the cladding and its anisotropic properties. In addition to the microstructural features, the properties of individual constituents of the composites and fiber tow architecture determine the bulk properties. Models for determining the relationship between the individual constituents’ properties and the bulk properties of SiC composites for nuclear applications are absent, although empirical relationships exist in the literature. Here, a hierarchical multiscale modeling approach was presented to address this challenge. This modular approach addressed this difficulty by dividing the various aspects of the composite material into separate models at different length scales, with the evaluated property from the lower-length-scale model serving as an input to the higher-length-scale model. The multiscale model considered the properties of various individual constituents of the composite material (fiber, matrix, and interphase), the porosity in the matrix, the fiber volume fraction, the composite architecture, the tow thickness, etc. By considering inhomogeneous and anisotropic contributions intrinsically, our bottom-up multiscale modeling strategy is naturally physics-informed, bridging constitutive law from micromechanics to meso-mechanics and structural mechanics. The effects that these various physical attributes and thermo-physical properties have on the composite’s bulk thermal properties were easily evaluated and demonstrated through the various analyses presented herein. Since silicon carbide fiber-reinforced SiC CMCs are also promising thermal–structural materials with a broad range of high-end technology applications beyond nuclear applications, we envision that the multiscale modeling method we present here may prove helpful in future efforts to develop and construct reinforced CMCs and other advanced composite nuclear materials, such as MAX phase materials, that can service under harsh environments of ultrahigh temperatures, oxidation, corrosion, and/or irradiation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Hygrothermal Aging and Thermomechanical Characterization of As-Manufactured Tidal Turbine Blade Composites

This study investigates the hygrothermal aging behavior and thermomechanical properties of as-manufactured glass fiber-reinforced epoxy and thermoplastic composite tidal turbine blades. The blades were previously deployed in a marine environment and subsequently analyzed through a comprehensive suite of material characterization techniques, including hygrothermal aging, dynamic mechanical analysis (DMA), tensile testing and X-ray computed tomography (XCT). Hygrothermal aging experiments revealed that while thermoplastic composites exhibited lower overall water absorption (0.78% vs. 0.47%), they had significantly higher diffusion coefficients than epoxy (2.1 vs. 12.1 × 10 −13 m 2 s −1 ), suggesting faster saturation in operational environments. DMA results demonstrated that water ingress caused plasticization in epoxy matrices, reducing the glass transition temperature and increasing damping (112 °C to 104 °C), while thermoplastic composites showed more stable thermal behavior (87 °C glass transition temperature). Tensile testing revealed substantial reductions in ultimate strength (>40%) for both materials after prolonged water exposure, with minimal change in elastic modulus, highlighting the role of matrix degradation over fiber reinforcement. XCT image analysis showed that both composites were manufactured with high quality: no large voids or cracks were present, and the degree of misalignment was low. These findings inform future marine renewable energy composite designs by emphasizing the critical influence of moisture on long-term structural integrity and the need for optimized material systems in harsh marine environments. This work provides a rare real-world comparison of epoxy and recyclable thermoplastic tidal turbine blades, showing how laboratory aging tests and advanced imaging reveal the influence of material and manufacturing choices on long-term marine durability.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Quality Investigation of Pultruded Carbon Fiber Panels Subjected to Four-Point Flexure via Fiber Optic Sensing

Pultruded carbon fiber-reinforced composites are attractive to the wind energy industry due to the rapid production of highly aligned unidirectional composites with enhanced fiber volume fractions and increased specific strength and stiffness. However, high volume carbon fiber manufacturing remains cost-prohibitive. This study investigates the feasibility of a pultruded low-cost textile carbon fiber-reinforced epoxy composite as a promising material in spar cap production was undertaken based on mechanical response to four-point flexure loading. As spar caps are primarily subjected to flexural loading, large-span four-point flexure was considered, and coupon testing was restricted to tensile modulus and compression strength assessment. High-resolution spatial fiber optic strain sensing was utilized to determine spatial strain distribution during four-point flexure, revealing consistent strain along the length of the part and proved to be an excellent option for process manufacturing quality examination. Additionally, holes with diameters of 2.49 mm, 5.08 mm, and 1.93 mm were drilled through the thickness of full-width parts to determine the feasibility of structural health monitoring of pultruding parts internal to wind blades via fiber optic strain sensing.

Chemistry↗
DOE OSTI2024

Monolithic Polyepoxide Membranes for Nanofiltration Applications and Sustainable Membrane Manufacture

The present work details the development of carbon fiber-reinforced epoxy membranes with excellent rejection of small-molecule dyes. It is a proof-of-concept for a more sustainable membrane design incorporating carbon fibers, and their recycling and reuse. 4,4′-methylenebis(cyclohexylamine) (MBCHA) polymerized with either bisphenol-A-diglycidyl ether (BADGE) or tetraphenolethane tetraglycidylether (EPON Resin 1031) in polyethylene glycol (PEG) were used to make monolithic membranes reinforced by nonwoven carbon fibers. Membrane pore sizes were tuned by adjusting the molecular weight of the PEG used in the initial polymerization. Membranes made of BADGE-MBCHA showed rejection of Rose Bengal approaching 100%, while tuning the pore sizes substantially increased the rejection of Methylene Blue from ~65% to nearly 100%. The membrane with the best permselectivity was made of EPON-MBCHA polymerized in PEG 300. It has an average DI flux of 4.48 LMH/bar and an average rejection of 99.6% and 99.8% for Rose Bengal and Methylene Blue dyes, respectively. Degradation in 1.1 M sodium hypochlorite enabled the retrieval of the carbon fiber from the epoxy matrix, suggesting that the monolithic membranes could be recycled to retrieve high-value products rather than downcycled for incineration or used as a lower selectivity membrane. The mechanism for epoxy degradation is hypothesized to be part chemical and part physical due to intense swelling stress leading to erosion that leaves behind undamaged carbon fibers. The retrieved fibers were successfully used to make another membrane exhibiting similar performance to those made with pristine fibers.

Polymer Science↗