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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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681 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

SQUID Readout of a High-$Q$ Superconducting $LC$ Resonator

We demonstrate the readout of a superconducting $LC$ resonator, with $Q \approx 2 \times 10^{6}$ at approximately 250 kHz, using a dc SQUID followed by a SQUID series-array amplifier readout chain. We find that $Q$ depends on the SQUID flux-bias point, increasing near the shallow-slope point of the SQUID modulation curve and decreasing near the steep-slope point, consistent with the previously observed SQUID damping effects. From this variation, we infer the SQUID effective input impedance. We further infer the effective temperature of the resonator circuit from the resonance peak in the noise spectrum and show that it also depends on the SQUID flux-bias point, suggesting a possible contribution from SQUID back-action noise. This system provides a working prototype for future experiments based on lumped-element resonators with SQUID readout, in particular low-mass axion searches within the DMRadio program.

FOS: Physical sciences↗
NASA NTRS1985

Preliminary Plan for A Shuttle Coherent Atmospheric Lidar Experiment (SCALE)

A study has been completed to define a Shuttle experiment that solves the most crucial scientific and engineering problems involved in building a satellite Doppler wind profiler for making global wind measurements. The study includes: (1) a laser study to determine the feasibility of using the existing NOAA Windvan laser in the Space Shuttle spacecraft; (2) a preliminary optics and telescope design; (3) an accommodations study including power, weight, thermal, and control system requirements; and (4) a flight trajectory and operations plan designed to accomplish the required scientific and engineering goals. The experiment will provide much-needed data on the global distribution of atmospheric aerosols and demonstrate the technique of making wind measurements from space, including scanning the laser beam and interpreting the data. Engineering accomplishments will include space qualification of the laser, development of signal processing and lag angle compensation hardware and software, and telescope and optics design. All of the results of this limited Spacelab experiment will be directly applicable to a complete satellite wind profiler for the Earth Observation System/Space Station or other free-flying satellite.

D Fitzjarrald↗
DOE OSTI2024

Elastic Modulus Measurement at High Temperatures for Miniature Ceramic Samples Using Laser Micro-Machining and Thermal Mechanical Analyzer

In this paper, we demonstrate a method of measuring the flexural elastic modulus of ceramics at an intermediate (~millimeter) scale at high temperatures. We used a picosecond laser to precisely cut microbeams from the location of interest in a bulk ceramic. They had a cross-section of approximately 100 μm × 300 μm and a length of ~1 cm. They were then tested in a thermal mechanical analyzer at room temperature, 500 °C, 800 °C, and 1100 °C using the four-point flexural testing method. We compared the elastic moduli of high-purity Al2O3 and AlN measured by our method with the reported values in the literature and found that the difference was less than 5% for both materials. This paper provides a new and accurate method of characterizing the high-temperature elastic modulus of miniature samples extracted from representative/selected areas of bulk materials.

Chemistry↗
DOE OSTI2026

Techno-Economic Evaluation of a 600MW Pumped Storage Hydropower Plant using the Pumped Storage Hydropower Valuation Tool

This paper presents a techno-economic evaluation of the proposed 600 MW, 8-hour Craig – Hayden pumped storage hydropower project using the U.S. Department of Energy’s Pumped Storage Hydropower Valuation Tool. The analysis integrates plant technical characteristics, regional grid conditions, and market-based operating assumptions to quantify stacked value streams from energy arbitrage, capacity, ancillary services, transmission congestion relief, and reliability. Both price taker and price influencer frameworks are applied to examine the impact of market participation and system interactions on lifecycle economic performance using Benefit - Cost Analysis and Multi - Criteria Decision Analysis. The results show that the price taker approach provides higher revenue estimates based on exogenous price signals, while the price influencer approach captures production cost savings, renewable curtailment reduction, and market price formation, yielding more conservative but system-representative outcomes. The study demonstrates the strategic value of long-duration PSH for enhancing operational flexibility, resource adequacy, and grid reliability in a high-renewable Western Interconnection.

Bhattacharyya, Arjun [ORNL] (ORCID:000900060976046↗
NASA NTRS1995

CAE for Thermal Management of Aerospace Electronic Boards Using the BETAsoft Program

Aerospace electronic boards require special attention to thermal management due to constraints such as their need to be light, small, and maintain high power densities. Also, cooling is mainly through conductive and radiative modes with minor or negligible convective cooling. Due to these particular requirements, thermal design has become an integrated part of the electronic design process in order to avoid expensive repeat prototyping and to ensure high reliability. To achieve high speed simulations, the BETAsoft code uses semi-empirical formulations and an advanced finite difference scheme that incorporates local adaptive grids. Detailed conduction, convection and radiation heat transfer is considered. Various benchmark verifications of the software simulation compared to infrared images typically prove to be within 10% of each other. The thermal analysis of a sample avionic card in a natural convection environment is shown. Then, the individual effects of attaching metal screws to the casing, increasing radiative emissivities of the casing, increasing the conductance of the wedge lock, adding an aluminum core to the board, adding metal strips in board layers, inserting conduction pads under components, and adding heat sinks to components are demonstrated.

Kimberly Bobish↗
DOE OSTI2026

Ultrafast Nanoimaging of Carrier Funneling in Composition-Graded Semiconductor Nanowires

Recent advances in bandgap engineering of low-dimensional semiconductors have enabled high-efficiency carrier transport in miniaturized electronic and optoelectronic devices. The physical properties and functionalities of these materials are governed by complex carrier dynamics coupled with multiple transport mechanisms in tailored band structures. Here, we report ultrafast nanoimaging of carrier funneling and recombination in composition-grade CdSxSe1-x nanowires using pump-probe near-field nanoscopy. Leveraging the high resolution of this technique in both space and time, we resolve nanoscale local carrier dynamics along composition-graded nanowires, revealing the local variation of composition-dependent carrier mobilities and lifetimes that significantly differ from their uniform composition counterparts. Furthermore, we demonstrate a length-dependent behavior wherein shorter nanowires exhibit enhanced funneling effects, accelerating carrier transport by up to 33%. Our findings provide direct visualization of nanoscale carrier transport while supporting an effective approach for investigating complex carrier interactions in inhomogeneous semiconductor nanostructures, with implications for optimizing next-generation optoelectronic devices.

Yang, Rundi↗
DOE OSTI2026

Nanohybrid of Cu2O-Ti3C2Tx as a Silver-Free MXene Sorbent for Iodine Gas Capture from Nuclear Waste

The capture of volatile radioiodine from nuclear fuel reprocessing off-gas streams remains a critical challenge due to the high volatility, long half-life of 129I, and biological uptake of iodide from the environment. Although silver-based sorbents provide strong iodine chemisorption, their high cost and regulatory classification as mixed radioactive-hazardous waste motivate the development of alternative materials. Here, we report a silver-free Cu2O-Ti3C2Tx MXene hybrid for iodine gas capture at 150 °C. Structural and compositional analyses confirm the formation of Cu2O nanoparticles on Ti3C2Tx nanosheets and their subsequent conversion to thermodynamically stable CuI upon static iodine gas exposure, achieving an iodine mass loading of up to 1115 mg/g. These results demonstrate the potential of Cu2O-Ti3C2Tx MXene as a copper-based alternative to silver sorbents for elevated-temperature iodine gas capture.

iodine gas capture↗
NASA NTRS1958

High Mach Number, Low-Cowl-Drag, External-Compression Inlet With Subsonic Dump Diffuser

A zero-cowl-drag, all-external-compression inlet with an abrupt area discontinuity or subsonic dump diffuser has been proposed and demonstrated for high Mach number application. Isentropic compression was focused at the lip of a cylindrical cowl and limited by the requirements for shock attachment. Theoretical calculations of the performance of such an inlet showed that it may be suited for application at Mach numbers of 4 and above. In an experimental investigation at Mach 3.85, a 4.75-inch-diameter inlet attained a total-pressure recovery of 0.41 at a corresponding mass-flow ratio of 0.92. Subsonic diffusion over an area ratio of about 3.5 to 1.0 was accomplished in 1.25 inlet diameters. Essentially no difference in performance was obtained in a comparison of the dump and a conventional subsonic diffuser. On a range basis, the over-all performance of this inlet was at least comparable with that of the best on-design isentropic external-compression inlet previously reported. A variable Mach number configuration utilizing a telescoping spike with a subsonic dump diffuser is also included.

James F Connors↗
NASA NTRSDate not supplied

MEAD In-situ Sampling and Testing at Haughton Crater

The Mars Exploration through Analog-site Drilling (MEAD) project is designed to demonstrate the feasibility and scientific value of robotic drilling missions to Mars in the search for evidence of past or extant life. MEAD conducts high-fidelity field simulations integrating drilling, autonomous operations, and in-situ life-detection and mineralogical instruments. The project tests the Signs of Life Detector (SOLID), proposed for the 2019 Discovery Mars Icebreaker mission, and ARIA (Astronaut Raman Instrument for ISRU and Astrobiology), which provides mineral identification and detects trace organics and volatiles, including indicators of organic thermal maturity. Because current and planned Mars drilling missions operate largely “blind,” MEAD also evaluates the use of drill-induced vibrations recorded by deployed geophones to enable local subsurface mapping for improved targeting of drilling and sampling. In August 2025, MEAD completed its first-year field deployment to Haughton Crater in the Canadian High Arctic, an established Mars impact-crater terrestrial analog site, bringing a Honeybee Robotics TRIDENT drill with applied automation, alongside ARIA, SOLID, and FleetSpace geophones.

Haughton Crater↗
DOE OSTI2026

Limited proteolysis of pea protein to promote aggregation/gelation: role of enzyme concentration and molecular characteristics

Limited proteolysis promotes aggregation/gelation of plant proteins, but its relationship with the molecular characteristics of hydrolysates remains poorly understood. In here, response surface methodology was employed to evaluate the effects of protein concentration, Alcalase level, and hydrolysis time on the storage modulus (G′) of pea protein hydrolysates (PPH). 7.5% protein, 1.65% Alcalase, and a 6-min reaction time resulted in the highest relative increase in G′ upon heating PPH, whereas both higher (3.55%) and lower (0.3%) Alcalase levels led to less increment. Increasing the Alcalase level increased the degree of hydrolysis while decreasing the molecular weight, surface hydrophobicity, and total sulfhydryl and disulfide bond contents of PPH. Confocal laser scanning microscopy and X-ray scattering analyses found PPH produced with 1.65% Alcalase formed interconnected aggregates with dual structural domains, but not at other Alcalase conditions. These results demonstrate the role of controlled proteolysis in governing the aggregation/gelation behavior of PPH.

X-ray scattering↗
DOE OSTI2026

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 ↗
DOE OSTI2026

Feedback, physics, and forecasts: The emerging paradigm of machine learning-driven battery research

Machine learning (ML) is reshaping how we understand, predict, and optimize electrochemical systems. In batteries, ML accelerates discovery across chemistry, design, and operation by transforming massive experimental and simulated datasets into predictive, interpretable models. This review consolidates a decade of progress in ML-driven battery innovation, from early-cycle feature extraction to operando image analysis and physics-informed modeling. We categorize approaches by data domain and physical fidelity, emphasizing interpretable ML for diagnostics, reinforcement learning for control, and multi-objective optimization for lifetime extension strategies. Additionally, we demonstrate how integrated models accelerate discovery, reduce testing time, and guide sustainable design. Economic analyses furthermore illustrate how these advances can lower cost per cycle and improve circularity. Together, these developments chart a path toward self-optimizing, sustainable battery technologies.

artificial intelligence↗
DOE OSTI2024

Light–Material Interactions Using Laser and Flash Sources for Energy Conversion and Storage Applications

Abstract This review provides a comprehensive overview of the progress in light–material interactions (LMIs), focusing on lasers and flash lights for energy conversion and storage applications. We discuss intricate LMI parameters such as light sources, interaction time, and fluence to elucidate their importance in material processing. In addition, this study covers various light-induced photothermal and photochemical processes ranging from melting, crystallization, and ablation to doping and synthesis, which are essential for developing energy materials and devices. Finally, we present extensive energy conversion and storage applications demonstrated by LMI technologies, including energy harvesters, sensors, capacitors, and batteries. Despite the several challenges associated with LMIs, such as complex mechanisms, and high-degrees of freedom, we believe that substantial contributions and potential for the commercialization of future energy systems can be achieved by advancing optical technologies through comprehensive academic research and multidisciplinary collaborations.

Materials Science↗
DOE OSTI2026

Additively manufactured refractory high-entropy alloys with superior radiation resistance

Refractory high-entropy alloys (RHEAs) are promising candidates for next-generation nuclear and high-temperature applications. Among many approaches to manufacture RHEAs, additive manufacturing (AM) represents the most recent and advanced metal manufacturing method which allows near-net-shape manufacturing to reduce material waste and post-processing time. However, performance of AM RHEAs under complex irradiation conditions remains largely unexplored. Here, in this study, we demonstrate for the first time the response of directed energy deposition (DED) AM quaternary RHEAs (HfTaVW, CrTaVW) subjected to sequential dual-beam ion irradiation, consisting of helium pre-implantation followed by high-dose heavy ion bombardment. Compositions of DED AM RHEAs were selected using Monte Carlo (MC) simulations based on a cluster expansion (CE) Hamiltonian parameterized by density functional theory (DFT). Post-irradiation microstructural characterization revealed that the AM RHEA maintained remarkable stability, with suppressed helium bubble growth and reduced defect accumulation compared to conventional alloys. Even at high doses (∼100 dpa), the alloy exhibited no void swelling, a low density of dislocation loops, and no evidence of severe degradation. These results highlight the intrinsic ability of AM-derived microstructures and multicomponent chemistry to synergistically mitigate irradiation effects. Our findings establish AM RHEAs as a class of materials with superior resistance to radiation damage under conditions relevant to advanced fusion and fission environments and demonstrate the importance of sequential ion beam studies in evaluating their long-term performance.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Design of monolithic piezoelectric bimorph mirrors made from lithium niobate

Recent advances in deformable mirrors based on monolithic piezoelectric substrates, such as lithium niobate, have the potential to improve the image quality of X-ray optical systems on synchrotron and free-electron laser beamlines and microscopes. However, the quantitative relationship between design parameters and the deformed shape has not been readily available in the literature. We present an analytical model, validated through finite element analysis, enabling calculation of tangential and sagittal curvatures based on mirror dimensions, crystallographic orientation, and applied voltage. We demonstrate that through the selection of material orientation, it is possible to achieve different deformed shapes (sphere, cylinder, or hyperbolic paraboloid). This methodology can be generalized to other piezoelectric materials and substrate-integrated actuator systems.

Marzari, Francesco [University of Trento (Italy); ↗
DOE OSTI2026

Mesh-based multiphysics coupling acceleration for fusion neutronics through clustering for fusion blanket applications

Accurate modeling of particle transport within fusion blankets is essential for predicting performance metrics such as heat deposition and the tritium breeding ratio (TBR). However, high-fidelity coupling of thermal fluids from computational fluid dynamics (CFD) to neutronics simulations often incurs significant computational costs due to the complexity of surface intersection calculations in Monte Carlo codes. This paper presents an accelerated multiphysics coupling method for neutronics that utilizes hierarchical agglomerative clustering to map complex material property distributions to a neutronics model. Implemented within the fusion reactor design and assessment (FREDA) framework, the method leverages existing Python packages to automate the creation of clustered geometries for OpenMC. The approach is demonstrated on a sector model of an ARC-class tokamak with an immersion molten salt blanket, and an simple geometry with varying isotopic concentrations. Results show that the clustering method significantly reduces computational burden without compromising fidelity, providing a foundation for agile iteration of neutronics simulations involving multiple coupled material properties.

Bae, Jin Whan [ORNL] (ORCID:0000000326548907)↗
NASA NTRS2026

Diamond-Loaded Polyimide Aerogel Scattering Filters and Their Applications in Astrophysical and Planetary Science Observations

Infrared-blocking, aerogel-based scattering filters have a broad range of potential applications in astrophysics and planetary science instruments in the far-infrared, sub-millimeter, and microwave regimes. This paper demonstrates the ability of conductively-loaded, polyimide aerogel filters to meet the mechanical and science instrument requirements for several experiments, including the Cosmology Large Angular Scale Surveyor (CLASS), the Experiment for Cryogenic Large-Aperture Intensity Mapping (EXCLAIM), and the Sub-millimeter Solar Observation Lunar Volatiles Experiment (SSOLVE). Thermal multi-physics simulations of the filters predict their performance when integrated into a cryogenic receiver. Prototype filters have survived cryogenic cycling to 4 K with no degradation in mechanical properties. Measurement of total hemispherical reflectance and transmittance, as well as cryogenic tests of the aerogel filters in a full receiver context, allow estimates of the integrated infrared emissivity of the filters. Knowledge of the emissivity will help instrument designers incorporate the filters into future experiments in planetary science, astrophysics, and cosmology.

Kyle R Helson↗
DOE OSTI2026

Resolving root causes of experiment discrepancies guided by machine learning

Abstract Scientists rely on accurate experimental data to explain nature and then harness this knowledge for applications addressing human needs. However, discrepancies between experiments of the same observable can impede scientific progress if one does not understand the underlying causes. Here, we developed a process that unravels data discrepancies by first using Bayesian machine learning to relate discrepancies to few of many, potentially biasing metadata features that encode experiment procedures. This machine learning output guides human experts to study discrepancy causes by simulating suspicious aspects of historical experiments or designing modern ones to address open questions. The study findings then lead to rejecting or correcting historical data on firm scientific bases. This process is demonstrated for the energy spectrum of neutrons emitted promptly (<1 ns) after fission of 252 Cf, a trusted nuclear physics Standard. It reduces the spread in experimental 252 Cf spectra by up to a factor of 6.

Neudecker, D. (ORCID:0000000339200627)↗