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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Revealing the evolution of order in materials microstructures using multi-modal computer vision

The development of high-performance materials for microelectronics, energy storage, and extreme environments depends on our ability to describe and direct property-defining microstructural order. Our present understanding is typically derived from laborious manual analysis of imaging and spectroscopy data, which is difficult to scale, challenging to reproduce, and lacks the ability to reveal latent associations needed for mechanistic models. Here, we demonstrate a multi-modal machine learning (ML) approach to describe order from electron microscopy analysis of the complex oxide La 1−x Sr x FeO 3 . We construct a hybrid pipeline based on fully and semi-supervised classification, allowing us to evaluate both the characteristics of each data modality and the value each modality adds to the ensemble. We observe distinct differences in the performance of uni- and multi-modal models, from which we draw general lessons in describing crystal order using computer vision.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Controls for Electrified Aircraft Propulsion

Advanced electrified aircraft propulsion (EAP) concepts with integrated power, propulsion, and thermal systems require the development of equally sophisticated controllers to fly safe and efficient missions. Hybrid electric aircraft utilize electric machines mechanically coupled to the engine shafts to extract and insert power for a variety of purposes. Additionally, electric machines may drive propulsive fans pulling from a combination of on-board energy storage devices and engine extracted power. NASA’s investment in hybrid electric aircraft hardware-in-the-loop testing enables controls research on representative engine models using a novel emulation and scaling methodology. High-voltage, high-power electrical powertrain presents several technical risks at altitude. High-power requires high efficiency to minimize losses. Superconducting electric machines and power distribution research at NASA has identified key challenges with potential controls solutions. These risks necessitate the development of controllers robust to model uncertainty, disturbances, and fault conditions. System health management and fault detection schemes play an important role in a multi-layer controls approach that utilizes a supervisor which oversees inner loops for the highly coupled power, propulsion, and thermal systems. Such a supervisory controller enables coordinates energy transfer between engines, energy storage devices, electric machines, propulsors, and heat exchangers. Existing methods have shown an improvement in engine operability using the hybrid electric powertrain.

Halle E Buescher↗
NASA NTRSDate not supplied

Improvements to RANS Modeling for Aeroheating Predictions on Blunt Bodies

Accurate predictions of aeroheating are critical for designing thermal protection systems for planetary entry vehicles. For larger vehicles, turbulence in the boundary layer can substantially increase convective heating. This turbulence must be accurately modeled to ensure the thermal protection system is sufficient. The majority of hypersonic turbulence model development and validation focuses on boundary layers developing over flat-plates or sharp cones; these cases are substantially different than the boundary layer that develops over the heatshield of a blunt body traveling at hypersonic speeds. Planetary missions often use blunt body geometries, such as the 70-degree sphere-cone favored by Mars missions or the 45-degree sphere-cone planned for the upcoming DAVINCI mission. Due to smaller vehicle size and the lower velocities in the stagnation region, planetary entry vehicles have relatively low Reynolds numbers. Surface curvature and high enthalpy gradients create additional challenges. These difficulties must be addressed to obtain high accuracy needed for the ambitious planetary missions in the upcoming decade. This work focuses on both assessing and improving Reynolds-averaged Navier-Stokes (RANS) turbulence models for blunt-body geometries typical of planetary entry vehicles, with a focus on one-equation and two-equation formulations.

Mars2020↗
NASA NTRSDate not supplied

Performance of a Regenerative Fuel Cell System for the Lunar Surface

Regenerative fuel cells (RFCs) are an attractive energy storage solution for lunar missions as a technology capable of providing a higher specific energy (i.e., W∙h/kg) than state-of-the-art packaged Li-ion battery systems. An RFC consists of the (1 & 2) electrochemical stacks (chemical to electrical energy conversion to supply electricity to an external load, i.e. the fuel cell reaction, and electrical to chemical energy conversion of supplied electrical power to dissociate water into hydrogen and oxygen gases, i.e. water electrolysis), (3) fluidic conditioning, (4) reactant storage, (5) avionics, (6) power management and distribution (PMAD), and (7) thermal management. NASA’s Glenn Research Center has designed, assembled, and tested a breadboard RFC sys-tem capable of operating autonomously for multiple simulated lunar day/night cycles in a laboratory environment. The system is comprised of a non-flow through proton exchange membrane (PEM) fuel cell stack and a liquid-anode feed PEM electrolyzer (EZ) stack designed to electrochemically compress the reactants at balanced pressures up to 12.4 MPa (1800 psia). The fluidic conditioning, avionics, PMAD, and thermal management sub-systems are largely comprised of commercial-off-the-shelf components for this system-level development effort. The hardware is controlled by a CubeSat space processor running an operational program based on core flight architecture that can control the RFC hardware autonomously through a state machine with fault monitoring. The testing results highlighted here were completed with the system in an open-loop configuration such that reactants generated through water electrolysis were vented while gas cylinders supplied fuel cell operation. The breadboard operated autonomously, but there were five unplanned transitions to a safe state that required a manual restart after reviewing the data, determining a root cause, and implementing a solution. Four of the transitions were caused by the thermal management subsystem and the fifth was caused by a water management control issue in the EZ sub-system. The RFC system operated for over 550 hours with the final cycle being slightly abbreviated due to reasons unrelated to system performance.

Kerrigan Cain↗
NASA NTRSDate not supplied

Performance of a Regenerative Fuel Cell System for the Lunar Surface

Regenerative fuel cells (RFCs) are an attractive energy storage solution for lunar missions as a technology capable of providing a higher specific energy (i.e., W∙h/kg) than state-of-the-art packaged Li-ion battery systems. An RFC consists of the (1 & 2) electrochemical stacks (chemical to electrical energy conversion to supply electricity to an external load, i.e. the fuel cell reaction, and electrical to chemical energy conversion of supplied electrical power to dissociate water into hydrogen and oxygen gases, i.e. water electrolysis), (3) fluidic conditioning, (4) reactant storage, (5) avionics, (6) power management and distribution (PMAD), and (7) thermal management. NASA’s Glenn Research Center has designed, assembled, and tested a breadboard RFC sys-tem capable of operating autonomously for multiple simulated lunar day/night cycles in a laboratory environment. The system is comprised of a non-flow through proton exchange membrane (PEM) fuel cell stack and a liquid-anode feed PEM electrolyzer (EZ) stack designed to electrochemically compress the reactants at balanced pressures up to 12.4 MPa (1800 psia). The fluidic conditioning, avionics, PMAD, and thermal management sub-systems are largely comprised of commercial-off-the-shelf components for this system-level development effort. The hardware is controlled by a CubeSat space processor running an operational program based on core flight architecture that can control the RFC hardware autonomously through a state machine with fault monitoring. The testing results highlighted here were completed with the system in an open-loop configuration such that reactants generated through water electrolysis were vented while gas cylinders supplied fuel cell operation. The breadboard operated autonomously, but there were five unplanned transitions to a safe state that required a manual restart after reviewing the data, determining a root cause, and implementing a solution. Four of the transitions were caused by the thermal management subsystem and the fifth was caused by a water management control issue in the EZ sub-system. The RFC system operated for over 550 hours with the final cycle being slightly abbreviated due to reasons unrelated to system performance.

Kerrigan Cain↗
DOE OSTI2026

Predicting Band-Gap of Inorganic Materials Using Neuromorphic Graph Learning

Predicting properties of inorganic materials is a heavily researched topic, with several new prediction approaches emerging as competitors. One such competitor is graph neural networks, which leverage the structure of the graph to aid in the prediction process. In this work, we propose integration of neuromorphic computation into the graph neural network pipeline. We call this approach Neuromorphic Graph Learning (NGL). We utilize the NGL approach to leverage evolutionary algorithms and a novel Spike Pipeline for Raster Analysis (SPIRE) for the prediction of band gap in inorganic materials.

Mulet, Ian [University of Tennessee (UT)]↗
DOE OSTI2026

SENTRA: A Modular Computational Graph Framework for Critical Mineral and Materials Supply Chains: Part I: Network Construction Latent-Quantity Estimation, and Temporal Graph Forecasting

Global supply chains for critical minerals and materials are complex, evolving networks of countries, products, production stages, and trade relationships. Existing analytical approaches are limited by fragmented data and static network representations that do not capture the dynamic production dependencies linking raw materials, intermediate products, and final goods across multiple countries. Trade and production statistics provide only a partial view of domestic production, inventories, and material flows, making it difficult to identify indirect sourcing pathways, hidden dependencies, and embedded foreign exposures. This paper introduces the Supply Chain Exposure Network Tracking and Risk Assessment (SENTRA) framework, a modular graph-based computational framework for constructing, analyzing, and forecasting dynamic supply chain networks. As the first paper in a three-part methodological series, it establishes the computational foundation of SENTRA by constructing a temporal attributed multi-relational graph whose nodes represent product–country pairs and whose edges encode observed trade and within-country value-chain relationships. Statistical estimation and constrained optimization recover latent production, final demand, and product input dependency coefficients while enforcing economic accounting constraints. Graph-derived exposure measures quantify direct, transshipment, value-chain, and multi-hop supply chain dependencies independently of the forecasting model. A temporal graph forecasting architecture based on a relational graph neural network then forecasts the evolution of the graph under mass-balance constraints with distribution-free conformal uncertainty quantification. Validation on the global aluminum supply chain shows that the learned graph representations recover economically meaningful supply chain structure, accurately forecast out-of-sample trade relationships, and produce well-calibrated prediction intervals. Subsequent papers apply this computational foundation to exposure assessment, disruption analysis, and scenario-based policy analysis, and extend the framework to multimaterial supply chain modeling and decision support.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Cosmic neutrino decoupling and its observable imprints: insights from entropic-dual transport

Abstract Very different processes characterize the decoupling of neutrinos to form the cosmic neutrino background (CνB) and the much later decoupling of photons from thermal equilibrium to form the cosmic microwave background (CMB). The CνB emerges from the fuzzy, energy-dependent neutrinosphere and encodes the physics operating in the early universe in the temperature rangeT∼ 10 MeV toT∼ 10 keV. This is the epoch where beyond Standard Model (BSM) physics, especially in the neutrino sector, may be influential in setting the light element abundances, the necessarily distorted fossil neutrino energy spectra, and other light particle energy density contributions. Here we use techniques honed in extensive CMB studies to analyze the CνB as calculated in detailed neutrino energy transport and nuclear reaction simulations of the protracted weak decoupling and primordial nucleosynthesis epochs. Our moment method, relative entropy, and differential visibility approach can leverage future high precision CMB and light element primordial abundance measurements to provide new insights into the CνB and any BSM physics it encodes. We demonstrate that the evolution of the energy spectrum of the CνB throughout the weak decoupling epoch is accurately captured in the Standard Model by only three parameters per species, a non-trivial conclusion given the deviation from thermal equilibrium and the impact of the decrease of electron-positron pairs. Furthermore, we can interpret each of the three parameters as physical characteristics of a non-equilibrium system. Though the treatment presented here makes some simplifying assumptions including ignoring neutrino flavor oscillations, the success of our compact description within the Standard Model motivates its use also in BSM scenarios. We further demonstrate how observations of primordial light element abundances can be used to place constraints on the CνB energy spectrum, deriving response functions that can be applied for general deviations from a thermal spectrum. Combined with the description of those deviations that we develop here, our methods provide a convenient and powerful framework to constrain the impact of BSM physics on the CνB.

Astronomy & Astrophysics↗
NASA NTRS1990

Planning for Execution Monitoring on A Planetary Rover

A planetary rover will be traversing largely unknown and often unknowable terrain. In addition to geometric obstacles such as cliffs, rocks, and holes, it may also have to deal with non-geometric hazards such as soft soil and surface breakthroughs which often cannot be detected until rover is in imminent danger. Therefore, the rover must monitor its progress throughout a traverse, making sure to stay on course and to detect and act on any previously unseen hazards. Its onboard planning system must decide what sensors to monitor, what landmarks to take position readings from, and what actions to take if something should go wrong. The planning systems being developed for the Pathfinder Planetary Rover to perform these execution monitoring tasks are discussed. This system includes a network of planners to perform path planning, expectation generation, path analysis, sensor and reaction selection, and resource allocation.

Erann Gat↗
DOE OSTI2024

Chemical recycling of mixed textile waste

Globally, less than 0.5% of postconsumer textile waste is recycled, with the majority incinerated or ending up in landfills. Most postconsumer textiles are mixed fibers, complicating mechanical recycling due to material blends and contaminants. Here, we demonstrate the chemical conversion of postconsumer mixed textile waste using microwave-assisted glycolysis over a ZnO catalyst followed by solvent dissolution. This approach electrifies the process heat while allowing rapid depolymerization of polyester and spandex to their monomers in 15 minutes. A simple solvent dissolution enables the separation of cotton and nylon. We assess the quality of all components through extensive material characterization, discuss their potential for sustainable recycling, and provide a techno-economic analysis of the economic feasibility of the process.

Science & Technology - Other Topics↗
DOE OSTI2026

Reliability Assessment of Solid-State Circuit Breakers (CRADA CRD-21-21469, Project 4 Final Report)

Growth in power requirements and the complexity of emerging distribution systems are creating the need for new solid-state products for many applications. The qualification requirements, testing standards and life-cycle management practices of solid-state devices used in protection applications is not established. The project will leverage newly developed accelerated testing capabilities design specifically for protection applications to generate large data sets that will enable advanced digital techniques for data analysis and embedded health monitoring.

14 SOLAR ENERGY↗
NASA NTRS2026

Mechanical Design and Operation of a Novel Lunar Environment Structural Test Rig (LESTR)

The Lunar Environment Structural Test Rig (LESTR) was developed to address a critical gap in mechanical property data for metal alloy wire materials under lunar-relevant conditions down to 40 K. Conventional aerospace material databases provide thermophysical properties for bulk metals over a wide temperature range, but validated mechanical and physical property data below 77 K, particularly for small-diameter wires, remain limited and are generally the exception rather than the rule. These conditions are essential for Artemis mission hardware such as shape memory alloy (SMA) rover tires. LESTR’s design requirements were to combine a high-stiffness electrodynamic load frame with closed- cycle cryogenic cooling, high-vacuum capability (10–6 torr), and noncontact optical strain measurement to enable tensile, four-point bend, and fatigue testing of wires or other materials and geometries at temperatures from 40 to 125 K. These considerable requirements were merged with the need to lower the barrier of testing for the end user as measured in terms of cost-per-test cycle, safety improvement, and reduction in upkeep costs associated with state-of-the-art solutions associated with cryomechanical material characterization. The system incorporates modular gripping and alignment fixtures; precision thermal management using cryocoolers and embedded heaters; and integrated instrumentation for displacement, load, temperature, and vacuum control. Calibration procedures establish correlations between tooling and specimen temperature, ensuring accurate thermal conditions across the design envelope unbound by cryofluid conditions in heritage immersion-based test systems. Initial validation tests using Inconel (Special Metals Corp.) wire demonstrated accurate ultimate strength and post-yield behavior. The load frame operation was also verified under representative service conditions, including thermal cycling and prolonged fatigue loading. By generating mechanical property data at ultralow temperatures, LESTR fills a critical gap in existing materials databases and provides a scalable platform for iterative alloy development and durability assessment for planetary hardware. This capability supports NASA’s long-term objectives for surface exploration by enabling design confidence for components operating in extreme cryogenic environments.

LESTR↗
NASA NTRS1977

Reanalysis of the Apollo Cosmic Gamma-Ray Spectrum in the 0.3 to 10 MeV Energy Region

Additional data obtained from the Apollo 16 and Apollo 17 missions, together with collateral calculations on background radiation effects, have made an improved subtraction of unwanted backgrounds from the diffuse cosmic y-ray data previously reported from Apollo 15 possible. As a result, the 1 to 10 MeV spectrum is lowered significantly and connects smoothly with recent data at other energies. The inflection reported previously is much less pronounced and has no more than a 1.5 σ significance. Sky occultation by the Apollo 16 spacecraft shows the bulk of the 0.3 to 1 MeV radiation to be diffuse. The analysis of spurious backgrounds points to important improvements for future experiments designed for this spectral region.

Gamma Rays↗
DOE OSTI2026

Enhanced Preparation for Intelligent Cybermanufacturing Systems (EPICS)

Opportunities exist for realizing transformative advances in productivity and reductions in energy footprint through ubiquitous sensing in manufacturing environments. Enhanced Preparation for Intelligent Cybermanufacturing Systems (EPICS) is a 21-month (4 academic semesters, plus one summer) experience for graduate students that focuses on scaling the knowledge, understanding and leadership skills in the cyber manufacturing area. Masters students (8/year, 32 total) complete 2-year projects on industrially-driven project topics, rotating to internships in summer semester to work on scoping and implementation at project partners. Students complete academic training in embedded systems, process modeling, data science, and cloud-based systems design. Their projects are targeted toward sensor retrofit, process monitoring, root cause analysis, and sensor fusion.

Advanced Manufacturing↗
DOE OSTI2026

Structured illumination for surface-resolved grazing-incidence X-ray scattering

Grazing-incidence (GI) scattering techniques are widely used to characterize thin films, offering high surface sensitivity and insight into morphology and structure. However, these approaches typically provide statistical averaged information due to elongated footprint or limited spatial resolution due to beam size. Here we introduce a method that combines structured illumination with GI X-ray scattering and leverages our computational imaging approach to resolve local structural details. We demonstrate that our method captures local features of an organic semiconductor thin film without the need for sample rotation as in tomography. The method expands GI techniques from statistical averaging to high-resolution imaging, thereby providing the capability for detailed analysis of local material properties, such as domain shape, orientation and polymorphism, which are critical for advancing material design towards more efficient and tailored materials.

Gursoy, Doga↗
NASA NTRSDate not supplied

Use of Assistive Technology to Augment API Capabilities

Application Programming Interfaces (APIs) allow for access to data and capabilities of computer applications by developers or users with experience in computer programming. Recent development with both Thermal Desktop and ESATAN-TMS have provided APIs to allow users to develop their own capabilities that interface with the Graphical User Interfaces (GUI) or manipulate the thermal model data. However, these APIs are only as good as the breadth of features in the native code accessible through the API; if a particular code’s feature is not accessible through the API, then users have very limited options besides waiting for updates to the API that expose the necessary functionality, particularly if model data access or user action, such as a button click, is required. However, Assistive Technology features that allow for differently-abled users to more fully experience a software’s capabilities may be creatively utilized to gain further access to data and capabilities not yet exposed by the API. This paper describes the process to augment the features of the OpenTD API via assistive technology and describes how to identify the application instance, navigate GUI elements, updates values on forms, and execute actions such as selecting a listbox item or clicking a button. It concludes with identifying some of the pitfalls to avoid and describes methods to best implement this approach.

Application Programming Interface↗
NASA NTRS2003

A High Temperature Cyclic Oxidation Data Base for Selected Materials Tested at NASA Glenn Research Center

The cyclic oxidation test results for some 1000 high temperature commercial and experimental alloys have been collected in an EXCEL database. This database represents over thirty years of research at NASA Glenn Research Center in Cleveland, Ohio. The data is in the form of a series of runs of specific weight change versus time values for a set of samples tested at a given temperature, cycle time, and exposure time. Included on each run is a set of embedded plots of the critical data. The nature of the data is discussed along with analysis of the cyclic oxidation process. In addition examples are given as to how a set of results can be analyzed. The data is assembled on a read-only compact disk which is available on request from Materials Durability Branch, NASA Glenn Research Center, Cleveland, Ohio.

Scale Spalling Models↗
NASA NTRSDate not supplied

Use of Assistive Technology to Augment API Capabilities

Application Programming Interfaces (APIs) allow for access to data and capabilities of computer applications by developers or users with experience in computer programming. Recent development with both Thermal Desktop and ESATAN-TMS have provided APIs to allow users to develop their own capabilities that interface with the Graphical User Interfaces (GUI) or manipulate the thermal model data. However, these APIs are only as good as the breadth of features in the native code accessible through the API. If a particular code’s feature is not accessible through the API, then users have very limited options besides waiting for updates to the API that expose the necessary functionality, particularly if model data access or user action, such as a button click, is required. However, Assistive Technology features that allow for users with a disability to more fully experience a software’s capabilities may be creatively utilized to gain further access to data and capabilities not yet exposed by the API. This paper describes the process to augment the features of the OpenTD API via assistive technology and describes how to identify the application instance, navigate GUI elements, updates values on forms, and execute actions such as selecting a listbox item or clicking a button. It concludes with identifying some of the pitfalls to avoid and describes methods to best implement this approach.

Application Programming Interface↗