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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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1,202 records · Page 20

Revealing the Roles of CuF 2 /NiF 2 Incorporation in the Electrochemical Performance of FeF 3 Cathodes in Solid‐State Batteries

Mixed metal fluorides have been considered as a promising candidate to lower the voltage hysteresis of conversion-type iron fluoride cathodes, but their cycling stability is limited due to transition metal dissolution and interphase growth in liquid electrolyte batteries. Here, we study the role of incorporating CuF 2 and NiF 2 in the electrochemical performance of FeF 3 cathode in halide-based solid-state batteries to test whether we can transfer the kinetic benefit of low voltage hysteresis to solid-state batteries while using solid electrolyte to eliminate transition metal dissolution and stabilize the interphase. Synchrotron X-ray absorption spectroscopy results indicated the redox reactions are attributed to Cu 0 /Cu + and Fe 0 /Fe 2+ in 25CuF 2 -75FeF 3 and Ni 0 /Ni 2+ and Fe 0 /Fe 3+ in 10NiF 2 -90FeF 3 . While no apparent improvement in electrode kinetics can be observed, the incorporation of CuF 2 and NiF 2 can largely improve the cycling stability of FeF 3 cathodes. In conclusion, the results demonstrate the advantages of using solid-state concept to improve the cycling stability of conversion-type cathodes.

25 ENERGY STORAGE

Mechanical and durability properties of ultra-high-performance concrete of spent nuclear fuel dry storage systems: a review

Dry storage systems are used for interim storage of spent nuclear fuel (SNF). However, with the growing need to extend the operational periods of these systems, there are concerns about the degradation of their concrete overpacks, which could compromise the system's structural integrity and safety during hazardous events. Traditional concrete mixtures used in SNF dry storage systems have remained largely unchanged since their inception and often use conventional ingredients. These materials are susceptible to degradation mechanisms such as chemical attacks, alkali-silica reactions (ASR), and freeze–thaw cycles, which can lead to a loss of strength and durability over time. To address these challenges, this paper reviews the application of ultra-high-performance concrete (UHPC) as a promising alternative for spent nuclear fuel dry storage system overpacks. UHPC offers superior mechanical properties, exceptional durability, and reduced susceptibility to degradation mechanisms compared to conventional concrete. This paper focuses on the role of supplementary cementitious materials (SCMs) such as silica fume, fly ash, and metakaolin in enhancing UHPC performance for SNF storage applications. These SCMs have been shown to significantly improve the material’s microstructure, strength, and resistance to environmental stressors typically encountered in SNF storage environments. Moreover, incorporating SCMs supports sustainable construction by reducing cement consumption and associated carbon emissions. The review brings together existing research and experimental data, providing insights for engineers and researchers on developing UHPC mixtures that meet the rigorous demands of spent nuclear fuel dry storage systems, extending their service life and minimizing inspection intervals.

36 - MATERIALS SCIENCE

BISON analyses of TRISO fuel performance, its dependence on time-at-temperature, and possible implications for fuel design and qualification

The Advanced Gas Reactor Fuel Development and Qualification (AGR) program has established a substantial technical foundation to support private entry into the U.S. high-temperature gas-cooled reactor market. However, emerging tristructural isotropic (TRISO)-fueled reactor applications include small modular reactors and microreactors with longer fuel residence times, which may expose fuels to higher time-at-temperature (TAT) values than were explored by the AGR program. Increased TAT could affect diffusive and thermomechanical behaviors such as Pd penetration, fission gas release, creep, and fission product transport. In this work, we applied multiscale best-estimate BISON fuel performance modeling to assess these effects within a representative design space based on the AGR-5/6/7 experiment and analyzed trends in predicted particle and compact fuel performance metrics with possible implications for near-term fuel design and qualification. BISON unambiguously predicted that TRISO fuel performance is sensitive to TAT. Increasing TAT was not predicted to increase the magnitude of failure-inducing tangential stresses in particle coating layers. Predictions obtained using a mechanistic model for Pd penetration indicated that penetration depth does not depend strongly on TAT. While these observations suggest that AGR testing provides a conservative upper bound for the steady-state operation of TRISO particles at lower powers and higher residence times, BISON also predicted that the release of poorly retained Ag would increase with TAT. Because these analyses applied models to extrapolate beyond the available experimental data, the authors recommend performing targeted experiments to confirm these predictions. Nevertheless, these predictions may provide reactor developers with enough confidence to make near-term design decisions associated with the potential fuel performance trade-offs of increasing TAT.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS

Space Station battery system design and development

The Space Station Electric Power System will rely on nickel-hydrogen batteries in its photovoltaic power subsystem for energy storage to support eclipse and contingency operations. These 81-Ah batteries will be designed for a 5-year life capability and are configured as orbital replaceable units (ORUs), permitting replacement of worn-out batteries over the anticipated 30-year Station life. This paper describes the baseline design and the development plans for the battery assemblies, the battery ORUs and the battery system. Key elements reviewed are the cells, mechanical and thermal design of the assembly, the ORU approach and interfaces, and the electrical design of the battery system. The anticipated operational approach is discussed, covering expected performance as well as the processor-controlled charge management and discharge load allocation techniques. Development plans cover verification of materials, cells, assemblies and ORUs, as well as system-level test and analyses.

Haas, R. J.

The Earth Observing System (EOS) nickel-hydrogen battery

Information is given in viewgraph form on the Earth Observing System (EOS) nickel hydrogen battery. Information is given on the life evaluation test, cell characteristics, acceptance and characterization tests, and the battery system description.

Bennett, Charles W.

Thermal Design and Thermal Vacuum Testing of the StarBurst Instrument

The StarBurst Multimessenger Pioneer is a small satellite mission serving as a wide-field gamma-ray observatory designed to capture the initial emissions of short gamma-ray bursts, electromagnetic signatures of neutron star mergers. This paper presents the final thermal design and analysis of the StarBurst Instrument, comprising the bus-to-instrument interface plate, control electronics, and twelve crystal detector units, which form the core of the mission’s science capability. The passive thermal control system design requires consideration of restrictive keep-out zones, unknown orbital parameters, and narrow temperature limits of the detectors. Also summarized is the instrument level thermal vacuum cycle test, correlated model refinements, and updated model results. Following successful completion of the instrument test campaign, the hardware was integrated with the spacecraft bus for spacecraft level testing, including additional thermal vacuum testing. The results from the spacecraft level thermal vacuum test will further inform the instrument thermal model, ensuring accurate flight temperature predictions. StarBurst launches as a secondary payload in 2027 and has a mission duration of at least one year.

StarBurst

Complex-Concentrated Anion Doping Enables Ultra-Stable Lattice Oxygen and Structural Integrity in Lithium-Rich Layered Oxide Cathodes

Lithium- and manganese-rich layered oxides (LMR) stand out as next-generation lithium-ion cathode chemistries, which harness both transition-metal and lattice-oxygen redox processes to deliver exceptional capacity and energy density. However, their full potential is hindered by intrinsic oxygen instability and structural degradation, resulting in pronounced voltage fade and capacity decay. Here, we present a complex-concentrated anion-doping paradigm in which multiple anions, F, Br, and S, are incorporated into the oxygen sublattice to enhance oxygen-redox and structural stability. X-ray absorption spectroscopy and aberration-corrected scanning transmission electron microscopy confirm ultra-stable local oxygen coordination environments during long-term cycling, with detrimental phase transformations and oxygen-loss-induced cavitation dramatically inhibited. Notably, we show that the characteristic LiTM6 transition metal (TM) honeycomb ordering is preserved even after electrochemical cycling. Concurrently, this strategy yields an unprecedented volume change of only 0.63% upon charging to 4.8 V vs. Li+/Li, achieving the first zero-strain LMR cathode. The resulting LMR cathode delivers ultralow voltage fade (1 mV per cycle during the first 100 cycles and becomes negligible in subsequent cycles) and outstanding energy retention (93% after 200 cycles) in a pouch cell configuration. Our complex-concentrated anion-doping concept establishes a broadly applicable strategy for resolving chemo-mechanical failure mechanisms in ceramic intercalation electrodes for next-generation energy storage.

Li-ion batteries

A Machine Learning Framework for Error Compensation in Radiative Transfer Calculations

Radiative heat transfer influences the amount of heat flux transferred to the surface of the hypersonic vehicle, which is essential to evaluate the performance of thermal protection systems. The radiative heat flux is found to be computationally prohibitive while accounting for the variation in spatial, angular, and spectral domains. A new methodology has been recently developed to alleviate the cost of computation in the spectral domain by constructing flow-agnostic reduced-order models (ROMs). The developed spectral ROM databases provide grouping strategies that account for non-equilibrium absorption and emission as well as interaction between disparate species due to spectral overlap in associated radiative processes. However, the developed ROMs need to be optimized for a specific combination of interacting gas species and would need to re-calibrated in case individual species are added/omitted. In this work, we use various machine learning (ML) techniques to approximate the radiative intensities determined by a ROM optimized for a specific gas mixture. The ML model relies on the ROM databases developed for a single species which ignores any spectral overlap. Thus, radiation evaluation starts with a simple summation of radiative intensities predicted using these non-calibrated ROMs for the contributing species. The ML framework then provides a correction to account for the interplay in the frequency, i.e., emission of photons by one species and absorption by another, and yields mixture-specific radiation fields. Once trained on the individual ROM databases, the ML framework offers instantaneous corrections that serves as a time/cost effective alternative to the optimization of ROMs for a specific gas mixture. The ML framework is trained on both the high fidelity and ROM evaluated line of sight (LOS) data from Orion, Stardust, and FIRE II cases to obtain a general purpose correction model for earth re-entry scenarios when radiation contributions from both atomic nitrogen and atomic oxygen are considered. A geometric length scale parameter is used in the training process to account for errors introduced in the ROM databases as a consequence of high optical thickness. The efficacy of the ML framework is underscored through extensive analysis of train and test errors with respect to all the re-entry scenarios. The applicability of such an ML framework was further corroborated by embedding it in a state-of-the-art US3D - NERO system for determining the radiative heat flux transferred to the hypersonic vehicle surface.

Radiation

Future Aerospace Technology in the Service of the Alliance: Sustained Hypersonic Flight - Volume 3

Sustained Hypersonic Flight capability is envisioned for several future military and civilian applications, such as long range immediate reaction reconnaissance, high speed interception of air targets, long range precision strike against hardened or time critical targets, and access to space. The inherent reduction in time-to-target and low vulnerability will permit new operational tactics. The symposium outlined mission needs and operational scenarios for hypersonic vehicles. Addressed were: Technological issues and challenges in external hypersonic aerodynamics and design, propulsion and engine/airframe integration, military ramjet applications, overall system design including structures and materials development needs, and test facilities. Ground based test facilities cannot provide full simulation at Mach numbers above 5. Therefore, the use of Computational Fluid Dynamics design tools is essential. For routine use of the computational tools in analysis, design and optimization, it is necessary to reduce the time for the entire computational process by two orders of magnitude. Hypersonic boundary layer transition remains a critical design issue because of the important impact on engine drag and on heating, which can affect the choice of materials and thermal protection systems. In addition, reliable prediction of scramjet net thrust is an absolute must in resolving hypersonic air breathing vehicle design issues. Due to current facility and computational shortfalls, the development of future hypersonic flight systems requires research flight tests in the technology areas of boundary layer transition and air-breathing propulsion engine performance. For sustained hypersonic flight beyond Mach 6, the supersonic combustion ramjet (scramjet) engine is the only choice for the near future. Only this air-breathing concept offers a significant promise of large reductions in required propellant fractions, increased payload fractions, and reduced size vehicles, together with a foreseeable technological feasibility. Airframe/engine integration, combustor design and thermal management are the predominant engineering tasks. Fuels, hydrogen or hydrocarbon, must be matched to the operational needs of military or civil use. Experience in existing ramjet propelled missiles capable of speeds up to Mach 4 can support the development effort. The potential mission and cost benefits of sustained hypersonic flight to both military and civil applications are tremendous. From the budget point of view, the possibility of sharing development costs between military and civil programs offers a specific advantage.

Combustion chambers

A Critical Review of Heliostat Design for Concentrating Solar Thermal Technologies

Heliostat designs have undergone a widespread and eclectic development process, with many unique designs demonstrated. However, recent developments do not show the overall cohort converging toward a globally accepted universal design. Here, this study characterizes heliostats by breaking down and evaluating design traits based on emergent patterns from a comprehensive compilation of known heliostat designs spanning several decades. Four main categories for evaluation emerged: heliostat base, heliostat primary axis, heliostat drive, and facet support. Each of these four categories is further defined by four subtypes so that all heliostats fall into a single subtype within each category. The classified heliostats are ranked, yielding several view slices into the heliostat compilation or a breakdown of heliostats by type. An analysis of the breakdown shows several trends: a scale-up of established designs, new approaches at small to medium scales, and a movement toward greater adoption of linear drives. These trends reflect the most meaningful contributing factors to a proposed trajectory for a new era of heliostat designs striving to meet widely considered cost targets of $\$$50/m 2 or $\$$75/m 2 .

14 SOLAR ENERGY

Optimizing Renewable Ammonia Production for a Sustainable Fertilizer Supply Chain Transition

Local renewable ammonia production using electrolytic hydrogen is an emerging approach to alleviate emissions attributed to synthetic nitrogen fertilizer production while also insulating against fluctuations in fertilizer prices and mitigating transportation costs and emissions. However, replacing ammonia currently produced using fossil fuels will not be immediate. To this end, we develop a supply chain transition model, which first optimizes the design and hourly operation of new renewable ammonia facilities to minimize production costs and then optimizes the annual installation timing, production scale, and location of these new renewable facilities along with ammonia transportation to meet county resolution demands. The objective is to augment and eventually replace conventional ammonia market imports in an economically competitive manner. We performed a case study for Minnesota's ammonia supply chain and found that a full transition to in-state renewable production by 2032 is optimal. This is incentivized by the U.S. federal government's clean hydrogen production credits. This transition results in 99 % reduction in carbon intensity along with stable supply costs below $475 per metric tonne. New renewable production facilities are an order of magnitude smaller than existing conventional plants. They use both wind and solar resources and operate dynamically to minimize expensive battery and hydrogen storage capacities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Amphiphilic nanopores that condense undersaturated water vapor and exude water droplets

Condensation of water vapor in confined geometries, known as capillary condensation, is a fundamental phenomenon with far-reaching implications. While hydrophilic pores enable liquid formation from undersaturated vapor without energy input, the condensate typically remains confined, limiting practical utility. Here, we explore the use of amphiphilic nanoporous polymer-infiltrated nanoparticle films that condense and release liquid water under isothermal and undersaturated conditions. By tuning the polymer fraction and nanoparticle size, we optimize condensation and droplet formation. As vapor pressure increases, voids fill with condensate, which subsequently exudes onto the surface as microscopic droplets. This behavior, enabled by a balance of polymer hydrophobicity and capillarity, reveals how amphiphilic nanostructures can drive accessible water collection. Our findings provide design insights for materials supporting energy-efficient water harvesting and heat management without external input.

Science & Technology - Other Topics

Space Shuttle News Reference

A detailed description of the space shuttle vehicle and associated subsystems is given. Space transportation system propulsion, power generation, environmental control and life support system and avionics are among the topics. Also, orbiter crew accommodations and equipment, mission operations and support, and flight crew complement and crew training are addressed.

National Aeronautics and Space Administration

Thermal property characterization of phase change materials in building applications: A systematic review of fundamentals, recent progress, and future directions

Phase change materials (PCMs) can reduce building peak loads and enable demand-responsive thermal energy storage (TES), but their deployment depends on reliable measurement and interpretation of thermal properties across laboratory, intermediate, and application scales. Here, this review systematically examines characterization methods, testing protocols, and recent advances for neat PCMs and PCM composites, emphasizing thermal conductivity, enthalpy-related properties (phase change temperature, latent heat, specific heat), and cycling stability. For thermal conductivity, we compare steady-state and transient techniques and note limitations when phase transition and contact resistance affect measurements. For enthalpy–temperature characterization, we discuss differential scanning calorimetry together with intermediate- and bulk-scale methods, including T-history, heat flow meter testing, and three-layer calorimetry (3LC), to generate application-relevant enthalpy–temperature profiles. Cycling stability is organized into four experimental families: thermoelectric–air, fully thermoelectric, water-bath, and in situ chamber approaches, with attention to separating reversible supercooling from true degradation such as phase segregation. We highlight emerging noncontact diagnostics, including infrared thermography and embedded sensing, for spatially resolved validation and multiscale interpretation. Finally, we review the growing use of AI and machine learning for property prediction, inverse characterization from experimental signals, and real-time state estimation in building-integrated TES. Key needs include harmonized protocols, interlaboratory benchmarking, uncertainty reporting, and metadata-rich datasets to accelerate reproducible PCM qualification for grid-flexible buildings.

AI

Characterization of the Mechanical Trash Compactor Bag Removal Force

Managing trash accumulation is a critical challenge in human space explorations since the trash volume and mass can significantly influence launch cost and operational efficiency. This study aids the development of a Mechanical Trash Compactor (Mpactor) by testing the removal force required to remove a “trash bag” from the Mpactor. To do this, a Pneumatic Pressure Mandrel System was designed to simulate the normal force trash would exerts on the trash bag and subsequently the sidewalls of the Mpactor. For various levels of sidewall normal force, the removal force required to remove the simulated trash bag from the Mpactor compaction chamber was measured. This testing is used to identify optimal bag materials. Additionally, testing was done on both the native stainless steel walls of the compaction chamber as well as the walls after being Teflon lined. Split-plot ANOVA, simple main effects analysis, Holm’s post hoc comparisons for interaction, and sensitivity analyses were conducted to assess the influence of trash bag and sidewall materials on the required removal force. It was found that Teflon reduced the force required to remove the trash bag as well as reduced material-dependent variation in removal force. Testing showed that Teflon reduced the required removal force with a Polyvinylidene Fluoride , an unidentified Ethylene acrylate - Low Density Polyethylene copolymer, and a Polyvinyl Chloride all requiring significantly less removal force than the other materials tested.

pressure mandrel

Large language model-driven database for thermoelectric materials

Thermoelectric materials have the ability to convert waste heat into electricity, offering a valuable solution for energy harvesting. However, their widespread use is hindered by low conversion efficiency, the reliance on expensive rare earth elements, and the environmental and regulatory concerns associated with lead-based materials. A fast and cost-effective way to identify highly efficient thermoelectric materials is through data-driven methods. These approaches rely on robust and comprehensive datasets to train models. Although there are several databases on thermoelectric materials, there is still a need to collect and integrate experimental data from peer-reviewed research articles to capture diverse compositions and properties of materials. Here, in this work, we developed a comprehensive database of 7,123 thermoelectric compounds, containing key information such as chemical composition, structural detail, seebeck coefficient, electrical and thermal conductivity, power factor, and figure of merit (ZT). We used the GPTArticleExtractor workflow, powered by large language models (LLM), to extract and curate data automatically from the scientific literature published in Elsevier journals. This process enabled the creation of a structured database that addresses the challenges of manual data collection. The open access database could stimulate data-driven research and advance thermoelectric material analysis and discovery.

Database

Modeling the Potential Impact of Storage on the US Power Sector in a Multisector Dynamic Context

The electric power sector is expected to grow in size, importance, and complexity around the world as economies expand and electric supply technologies and demand patterns evolve in significant ways. At the same time the electric power sector may see substantial increases in VRE generating technologies which can add variability and uncertainty to the diurnal and seasonal profile of electric supply. With these forces in play, the emergence of modular, flexible electricity storage technologies may have profound impacts on the operation of electric power systems. Here we reduce a storage modeling gap in MSD models by incorporating grid-based electricity storage into the electric sector dynamics of the Global Change Analysis Model-USA (GCAM-USA) with improved power sector representation. We find a potentially significant role for storage technologies in the future of the U.S. power system, with storage capacity ranging from 7.7 to 14.7 GW in 2050 and 13.9 to 31.6 GW in 2100 across several techno-economic scenarios. We also find that storage can help to smooth variability in residual load arising from evolving electricity demands and the introduction of high shares of VRE to the electric grid. This reduces reliance on high-cost peaking generators, improves system-wide capacity factors, and limits curtailment of VRE.

Patel, Pralit L.

RADAI: A Large-Scale Realistic Dataset for Radiation Detection Algorithm Development

Open, realistic datasets are essential for developing and benchmarking radiation detection algorithms, yet they remain scarce. The Radiological Anomaly Detection and Identification (RADAI) project was develop to create datasets that meet the training and testing needs for sophisticated radiation detection algorithms. The RADAI dataset is a large-scale synthetic resource that integrates high-fidelity Monte Carlo simulations with realistic urban scenarios to capture both background variability and source signatures. RADAI models construction-material NORM, people and vehicles, urban clutter, and dynamic environmental effects such as cosmic-ray and rain-induced transients, and they provide list-mode detector data with motion and response modeling suitable for algorithm training and evaluation. The RADAI project resulted in three publicly-released complementary datasets together with an online scoring portal for standardized performance assessment and an open software toolkit that supports data access, augmentation, model development, and evaluation. These resources enable reproducible comparisons across methods and promote rigorous studies at the scale required by contemporary machine learning. By grounding algorithm development in realistic, well-documented conditions, RADAI supports progress toward more robust detection, identification, and localization in complex urban environments.

Ghawaly, James M. [Division of Computer Science an