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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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1,160 records · Page 22

AL-CRADA-2025-01 Final Report: American-Made Wind Turbine Materials Recycling Prize Accelerate! Phase 2

This report summarizes the Phase 2 achievements of the Wind Turbine Materials Recycling Prize project led by Critical Materials Recycling (CMR) in partnership with Ames National Laboratory. The team demonstrated the technical feasibility and economic viability of recovering and reusing rare-earth Nd-Fe-B magnets from end-of-life (EOL) wind turbine generators. Through mechanical disassembly, demagnetization, and precision processing, magnets were harvested and characterized to assess structural, compositional, and magnetic properties. Results showed that recovered magnets performed on par with commercial-grade counterparts, enabling their integration into actuator and motor prototypes without redesign. System-level modeling and finite-element simulations validated operational performance, while Life Cycle Cost (LCC) analysis revealed up to 20% material cost savings and 2–3% reductions in overall motor system costs. Life Cycle Assessment (LCA) further confirmed substantial environmental benefits, including a ~94% reduction in global warming potential relative to virgin magnet production. The project’s success was enabled by a tightly integrated partnership between industry and national lab experts, illustrating a viable path for domestic magnet-to-magnet recycling. These findings support a scalable, circular solution for rare-earth material recovery, reducing dependence on imported critical minerals and advancing sustainable clean energy technologies.

Lograsso, Thomas [Ames Laboratory (AMES), Ames, IA

The Development of Kinetic and Radiation Hydrodynamics Modeling of Thermonuclear Burn Propagation in Isochoric p - 11 B Through the Support of the INFUSE Program

The report summarizes DOE INFUSE-supported work between HB11 Energy and the University of Rochester’s TriForce Institute to improve computational modeling of advanced fusion fuels, especially proton–boron-11 (p- 11 B). The project extended the TriForce particle-in-cell/Monte Carlo collision code to include physics needed for dense, high-temperature p- 11 B burn studies, including p- 11 B fusion reactions, three-alpha-particle reaction products, relativistic Coulomb collisions, large-angle nuclear scattering, bremsstrahlung radiation, inverse bremsstrahlung absorption, and photon transport. The upgraded models were verified against focused physics tests and against known deuterium–tritium burn behavior. The study then used one-dimensional spherical simulations to estimate the conditions required for thermonuclear burn propagation in isochoric p- 11 B fuel. The calculations found that burn propagation is possible in the model, but only under very extreme hot-spot conditions, such as about 7000 g/cm 3 at 500 keV or 9000 g/cm 3 at 300 keV for a 20-micron hot spot. These conditions are much more demanding than current demonstrated inertial confinement fusion hot spots. The report concludes that the INFUSE collaboration successfully advanced kinetic and radiation modeling capabilities for p- 11 B fusion and provided useful estimates of ignition requirements. However, the simulated fuel gains remain below what would be needed for practical inertial fusion energy, and further work is needed to reconcile differences among kinetic, radiation-hydrodynamic, and analytic models and to identify more achievable target designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Bioinspired Dry‐Steam Superinsulation Straw Foam

Abstract Cellulosic materials offer sustainable advantages for building energy conservation. However, their development has been hindered by reduced thermal performance, often caused by structural collapse during the transition from solution to solid. Inspired by natural goose down, a bio‐based, lightweight insulation foam derived from agricultural waste straw is presented. Through in situ synthesis, bio‐silica fibers with branched structures capable of supporting hollow silica microspheres are fabricated. After steam‐mediated processing, the resulting foam exhibit low density (95 mg cm − 3 ), high porosity (95.5%), low thermal conductivity (0.03 ± 0.003 W mK −1 ), and a cyclic compressive strength of 90 kPa at 50% strain. Owing to the synergistic microstructure formed by branched bio‐fibers and hollow silica spheres, the bio‐silica foam exhibit outstanding thermal insulation performance relative to other bio‐based foams prepared by ambient drying. A passivated insulation panel is further developed by incorporating this material as the core component, achieving a thermal conductivity of 0.0275 W mk −1 and flexural strength of 6.85 MPa. The panel demonstrated durability with stable thermal performance throughout a 60‐day outdoor test. Moreover, the bio‐silica foam shows a carbon footprint of 7.50 kgCO₂ kg −1 at 70.2 wt.% silica, highlighting its promise as a sustainable insulation solution for green buildings.

Chemistry

Influence of microstructure and temperature on impact toughness of H13 steel produced by binder jet additive manufacturing

Binder Jet Additive Manufacturing (BJAM) is a promising manufacturing pathway to produce H13 steel dies and tooling with complex geometries for applications in high pressure aluminum die casting, hot stamping, and injection molding. While fully dense H13 coupons produced using BJAM have been subjected to detailed microstructure characterization, properties which are critical and relevant to the aforementioned applications, such as impact toughness, have not been reported. Here, this work evaluated the influence of microstructural characteristics and test temperature on the impact toughness of H13 produced by BJAM. Coupons were produced from three different powder size distributions (PSDs), with nominal powder size ranges of −22 μm, 10-32 μm, and 15-53 μm. Coupons were printed, sintered, hot isostatically pressed (HIPed), and heat treated by quenching and tempering. After HIPing, the measured porosities of the different PSDs were all less than 0.015 vol%. The −22 μm PSD BJAM material exhibited the best impact toughness of all three PSDs across the entire test temperature range from 25 to 400 °C, and also exhibited an ambient temperature impact toughness of 10.9 J at a hardness of 46 HRC, equivalent to minimum threshold requirements for premium grade H13. However, all three BJAM PSDs exhibited moderately lower impact toughness than premium grade wrought H13 from RT to 400 °C. We attribute this in part due to the very large prior-austenite grain (PAG) sizes near 400 μm and segregation from former liquid channels leading to greater amounts of carbide precipitation on PAG boundaries. Technical pathways for optimizing processing and chemistry of BJAM H13 to further improve impact toughness are discussed.

Binder jet additive manufacturing

Conditional diffusion machine-learning framework for mapping valence electron distribution from convergent beam electron diffraction

Quantitative convergent beam electron diffraction (CBED) enables determination of aspherical valence electron distributions through refinement of low-order structure factors, which are highly sensitive to chemical bonding and charge density variations. However, conventional quantitative CBED (QCBED) requires solving a highly nonlinear inverse problem with many coupled parameters, and computationally intensive dynamical diffraction calculations, making it time-consuming and difficult to apply to complex systems. More broadly, reconstructing charge density and orbital electron distribution from diffraction data has long been a central challenge in both x-ray and electron crystallography. Here, in this study, we introduce an artificial-intelligence (AI)-based framework that replaces traditional refinement with a data-driven inverse solver. Using a large synthetic CBED dataset generated by Bloch-wave simulations, we train a conditional diffusion model to directly infer crystal structural parameters and multipole density formalism parameters, and hence valence electron distributions, from CBED patterns alone. By learning from forward simulations across realistic parameter space, the model effectively solves the inverse problem. Compared with direct regression approaches, the diffusion-based framework provides posterior parameter distributions for rigorous uncertainty quantification while preserving quantitative fidelity and reducing analysis time by orders of magnitude. By eliminating the need for external single-crystal x-ray diffraction data and complex nonlinear refinement, this approach enables practical, high-throughput, and in situ quantitative CBED, enabling real-time mapping of valence electron distributions and their correlation with functional responses in quantum and energy materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Feedstock Choices for Advancing the Bioeconomy in the US and Policy Implications

Biomass feedstocks will be critical for scaling up the bioeconomy in the United States to meet multiple demands for biofuels, sustainable aviation fuel, bioproducts, and biochemicals. There is a wide range of choices of feedstocks, including a variety of dedicated energy crops and crop residues. There are substantial differences in the yields, costs of production, and carbon intensity of these feedstocks and for each feedstock across locations. These feedstocks also differ in the trade-offs they offer among multiple environmental impacts. We discuss the economic factors that will influence the production of these feedstocks and the implications of alternative biofuel and low-carbon policies for the mix of feedstocks that will be incentivized.

Khanna, Madhu (ORCID:0000000349944451)

Biochemical approaches for synthesis of performance-advantaged polymers from lignocellulosic biomass

Lignocellulose is an abundant renewable feedstock for production of sustainable fuels, chemicals, and materials. The structural complexity of lignocellulose provides key material properties and inspires the design of advanced materials. However, this same complexity also presents challenges for conversion of lignocellulosic biomass into new materials with consistent properties. Conventional physical and chemical strategies for valorization of biomass to new materials are often limited by the technical challenges of precisely manipulating complex feedstocks, sensitivity to feedstock variability, and associated costs. In contrast, biological approaches are capable of selectively manipulating complex architectures under mild conditions. Recent advances demonstrate the potential of biological and hybrid biochemical methods to tailor biomass-derived polymers and generate new materials. This review provides an overview of biological strategies to valorize lignocellulosic biomass into novel materials, highlighting approaches for in planta engineering, biochemical modification of natural biomass polymers, microbial funneling of deconstructed biomass, and direct biosynthesis of novel polymers. In combination, these approaches open new avenues for the synthesis of performance-advantaged materials from lignocellulosic biomass.

Qian, Liangyu [ORNL] (ORCID:0009000212029938)

Improved high-gradient performance for medium-velocity superconducting half-wave resonators: Surface preparation and trapped flux mitigation

A development effort to improve the performance of superconducting radio-frequency half-wave resonators (SRF HWRs) is underway at the Facility for Rare Isotope Beams (FRIB), where 220 such resonators are in operation. Our goal was to achieve an intrinsic quality factor (𝑄 0 ) of ≥ 2 × 10 10 at an accelerating gradient (𝐸 acc ) of 12 MV/m. FRIB production resonators were prepared with buffered chemical polishing. First trials of electropolishing (EP) and post-EP low-temperature baking of FRIB HWRs allowed us to reach higher gradient (15 MV/m, limited by quench) with a higher quality factor at high gradient, but 𝑄 0 was still below our goal. Trapped magnetic flux during the Dewar test was found to be a source of 𝑄 0 reduction. Three strategies were used to reduce the trapped flux: (i) adding a local magnetic shield (LMGS) to supplement the “global” magnetic shield around the Dewar for reduction of the ambient magnetic field; (ii) performing a “uniform cooldown” (UC) to reduce the thermoelectric currents; and (iii) using a compensation coil to further reduce the ambient field with active field cancellation (AFC). The LMGS improved the 𝑄 0 , but not enough to reach our goal. With UC and AFC, we exceeded our goal, reaching 𝑄 0 = 2.8 ×10 10 at 𝐸 acc = 12 MV/m.

Cryogenics & vacuum technology

The first high-redshift cavity power measurements of cool-core galaxy clusters with the International LOFAR Telescope

Radio-mode feedback associated with the active galactic nuclei (AGNs) at the cores of galaxy clusters injects a large amount of energy into the intracluster medium (ICM), offsetting radiative losses through X-ray emission. This mechanism prevents the ICM from rapidly cooling down and fueling extreme starburst activity as it accretes onto the central galaxies, and it is therefore a key ingredient in the evolution of galaxy clusters. However, the influence and mode of feedback at high redshifts (z ∼ 1) remains largely unknown. Low-frequency sub-arcsecond-resolution radio observations taken with the International LOFAR Telescope have demonstrated their ability to assist X-ray observations with constraining the energy output from the AGNs (or “cavity power”) in galaxy clusters, thereby enabling research at higher redshifts than before. In this pilot project, we tested this hybrid method on a high-redshift (0.6 < z < 1.3) sample of 13 galaxy clusters for the first time with the aim of verifying the performance of this method at these redshifts and providing the first estimates of the cavity power associated with the central AGN for a sample of distant clusters. We were able to detect clear radio lobes in three out of 13 galaxy clusters at redshifts of 0.7 < z < 0.9, and we used these detections in combination with ICM pressures surrounding the radio lobes obtained from standard profiles to calculate the corresponding cavity powers of the AGNs. Combining our results with the literature, the current data appear to suggest that the average cavity power peaked at a redshift ofz ∼ 0.4 and slowly decreases toward higher redshifts. However, we require more and tighter constraints on the cavity volume and a better understanding of our observational systematics to confirm any deviation of the cavity power trend from a constant level.

Astronomy & Astrophysics

Induction Melter Processing Alternatives for High Level Radioactive Wastes – 26198

This work investigates the potential to vitrify nuclear fuel directly, as well as the vitrification potential associated with experimental dissolver solutions. Greater understanding of the exothermicity is needed to quantify processing risk, especially with respect to potential phase changes and associated explosion hazards present in some systems. Thermal analysis was carried out on various simulants to elucidate the exothermic reaction potential from solid metal dissolution in glass and from the drying of alternative process dissolver solutions. Results from experimental testing of simulants to demonstrate vitrification potential and compatibility indicate that alternative dissolver flowsheets suppress the heat released during processing and that common silicate- and phosphate- based glass systems are potential candidates for direct vitrification. Direct vitrification (conversion) of fuel simulants was assessed using laboratory scale glass melts to obtain qualitative information on dissolution rates and waste loadings. Initial tests were successful to dissolve and incorporate metal directly into glass, although the kinetics and limits of dissolution and incorporation into glass are not fully understood.

Amoroso, Jake [Savannah River National Laboratory

Neuromorphic overparameterisation and few-shot learning in multilayer physical neural networks

Abstract Physical neuromorphic computing, exploiting the complex dynamics of physical systems, has seen rapid advancements in sophistication and performance. Physical reservoir computing, a subset of neuromorphic computing, faces limitations due to its reliance on single systems. This constrains output dimensionality and dynamic range, limiting performance to a narrow range of tasks. Here, we engineer a suite of nanomagnetic array physical reservoirs and interconnect them in parallel and series to create a multilayer neural network architecture. The output of one reservoir is recorded, scaled and virtually fed as input to the next reservoir. This networked approach increases output dimensionality, internal dynamics and computational performance. We demonstrate that a physical neuromorphic system can achieve an overparameterised state, facilitating meta-learning on small training sets and yielding strong performance across a wide range of tasks. Our approach’s efficacy is further demonstrated through few-shot learning, where the system rapidly adapts to new tasks.

Science & Technology - Other Topics

Green Era Anaerobic Digester

Green Era Educational NFP constructed and commissioned the Green Era Renewable Energy & Urban Farming Campus in Chicago’s Auburn Gresham neighborhood. The project transformed a long-vacant brownfield site into a commercial-scale anaerobic digestion facility that converts food waste into renewable natural gas and nutrient-rich material for agricultural use. The facility can process up to 80,000 wet tons of food waste annually and supports approximately 15 permanent jobs while advancing food waste diversion, renewable energy production, nutrient recovery and community revitalization.

03 NATURAL GAS

Full ribosomal operon sequencing of anaerobic gut fungi (phylum Neocallimastigomycota ): insights on its markers and phylogenetic resolution

The phylogenetic affiliations of anaerobic gut fungi (Neocallimastigomycota) are typically evaluated using single-gene markers. However, this approach often fails to resolve relationships between closely related lineages. To address this issue and identify alternative markers, we created a curated database comprising the complete ribosomal operon sequences of 156 isolates, representing 20 of the 22 recognized genera and two new genus-level clades. Using long-read sequencing, we obtained ~9 kbp operon sequences and developed a robust analysis pipeline. Incorporating both coding genes and non-coding regions (excluding IGS1) improved phylogenetic resolution. This phylogenetic approach successfully resolved the Cyllamyces and Caecomyces clades (hard-to-distinguish genetically), as well as seven analysed Piromyces species. We also scanned the operon for markers that are suitable for short-read sequencing platforms, with the aim of enhancing biodiversity and phylogenetic studies. Notably, the ETS1 genetic region also enabled the distinction between these lineages, indicating its phylogenetic value within the ribosomal operon. The resulting database is a valuable resource for expanding and strengthening phylogenetic frameworks.

High-throughput sequencing

Optical Vibrational Spectroscopic Investigation of Natural and Synthetic Analogs of Uranyl Oxyhydroxyhydrate Minerals

Uranyl oxy-hydroxy-hydrate minerals are common alteration products of uraninite (UO2+x) which is chemically and structurally analogous to uranium dioxide nuclear fuel. Therefore, structural and spectroscopic investigations of these alteration minerals and their analogous anthropogenic counterparts can provide insight into the environmental behavior of nuclear fuel cycle materials. Previously, we compiled available vibrational spectroscopic data for uranyl minerals in the Compendium of Uranium Raman and Infrared Experimental Spectra (CURIES) and found that only 37% of known uranyl oxy-hydroxy-hydrate minerals had spectra readily available in the literature and existing databases for inclusion therein. Furthermore, no available infrared spectra for this mineral group were included in CURIES. To expand our understanding of the spectroscopic features of uranyl oxy-hydroxy-hydrates and the structural origins thereof, we collected, and now include in CURIES, Raman and infrared spectra for an additional 12 uranyl hydroxide phases. To better understand the impact of structural and compositional variations of these phases on their spectroscopic features, we compare Raman spectra of different anion sheet topological groups and of analogous phases hosting different counter cations. We identify spectroscopic variations related to differences in equatorial bonding and structural changes as a result of cation substitution. We also prepare a uranyl hydroxide phase via hydrolysis of uranyl fluoride (UO2F2) as an analog of hydrolysis reactions that occur in nuclear fuel cycle materials; and we find that the alteration product of UO2F2, despite chemical and structural similarities to uranyl oxy-hydroxy-hydrate minerals, is readily distinguishable from related mineral phases using Raman spectroscopy. In this work, we provide new insights into the structural origins of spectroscopic features in uranyl oxy-hydroxy-hydrate minerals, improve the average Raman spectrum for this group of minerals, and thereby improve capabilities for identifying these mineral species and related anthropogenic phases using Raman spectroscopy.

Barth, Brodie [ORNL] (ORCID:0000000256142601)

Development of a high fidelity CFD model for solvent evaporation and transport in porous structure during battery electrode drying

An efficient battery manufacturing process is the key to the mass production of Electric Vehicles (EV), in which drying is one of the most energy-intensive steps significantly influencing the battery cell performance. An accurate 3D CFD model for drying is essential for predicting the drying mechanism and optimizing its parameters. By optimizing the drying process, it is possible to reduce energy consumption and cost during battery manufacturing, minimize binder loading and maximize active material loading to achieve superior electrochemical performances and facilitate wider and faster public adoption of EV. This project aims to optimize the drying process during electrode manufacturing by leveraging high-fidelity, porous electrode simulations for solvent evaporation. By optimizing this process, we seek to reduce energy consumption during battery manufacturing, while minimizing binder loading and maximizing active material loading, with the overall goal of enhancing electrical vehicle performance.

Horner, Jeffrey Scott [Sandia National Laboratorie

Characterization of lateral amorphous selenium photodetectors for low-photon and VUV detection at cryogenic temperatures

The performance of amorphous selenium (a-Se) as a cryogenic photodetector material is evaluated through a series of experiments using laterally structured devices operated in a custom optical test stand. These studies investigate the response of a-Se detectors to low-photon fluxes at high electric fields near avalanche conditions, the linearity of the photoconductive response over a wide dynamic range and the direct detection of narrowband 130 nm vacuum ultraviolet (VUV) illumination. At 87 K, matched-filter analysis shows reliable single-shot detection with efficiencies ≥80% and area under the curve (AUC) ≥ 0.85 using as few as ∼ 6800 incident 401 nm photons, corresponding to ∼ 3400 photons within field-active regions after accounting for geometric constraints. Measurements are performed at cryogenic temperatures using calibrated photon fluxes derived from a silicon photomultiplier reference and a characterized optical filter stack. Additional experiments using a tellurium-doped a-Se (a-SeTe) device explore the material's behavior under identical test conditions and demonstrate that avalanche is achievable in a-SeTe at cryogenic temperatures. The results demonstrate reproducible low-noise operation, VUV sensitivity and field-dependent gain behavior in a lateral a-Se architecture, representing the first reported observation of avalanche multiplication in laterally structured a-Se and a-SeTe devices at cryogenic temperatures. These findings support the potential integration of laterally structured a-Se devices into next-generation pixelated liquid-argon time projection chambers (TPCs) requiring scalable, high-field-compatible photon detection systems.

Amorphous selenium

All-Polyester Multilayer Plastics (‘All-Polyester MLPs’): A Redesign for Inherently Recyclable Plastics

Multilayer plastics (MLPs) are widely used in modern packaging because they combine multiple functions such as oxygen and moisture barriers, mechanical strength, puncture resistance, and heat sealability into lightweight and cost-effective packaging solutions. These attributes are essential for food, beverage, pharmaceutical, and consumer goods packaging. However, conventional commercial MLPs typically consist of five to twelve layers made from chemically incompatible materials, including polyolefins, polyethylene terephthalate, nylon, ethylene-vinyl alcohol (EVOH), adhesives, and tie layers. This complexity makes MLPs extremely difficult to recycle. As a result, the vast majority of multilayer plastics (MLPs) are disposed of through landfilling or incineration. This disposal pathway perpetuates demand for virgin material production, thereby driving high industrial energy consumption, increasing greenhouse gas (GHG) emissions, and contributing to the long-term accumulation of plastic waste. The scope of work included: (1) Design and fabrication of all-polyester multilayer structures using commercially relevant processing methods; (2) Experimental validation of barrier, mechanical, and sealing performance; (3) Demonstration of both mechanical and chemical recycling pathways; and (4) Comprehensive techno-economic analysis (TEA) and life-cycle assessment (LCA) to quantify cost, energy, and environmental impacts.

36 MATERIALS SCIENCE