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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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1,950 records · Page 103

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NASA NTRSDate not supplied

Battery Failure Databank

The Battery Failure Databank contains thermal runaway results gathered from nearly 300 small format fractional thermal runaway calorimetry (S-FTRC) experiments. A majority of these experiments were conducted at synchrotron facilities where high-speed x-ray videography was conducted of the cell while tested inside of the S-FTRC. The databank is a two-component system which consists of a Microsoft ExcelTM spreadsheet which provides S-FTRC results in tabular format and a radiographic video library containing the high-speed x-ray videos. Overall, the databank provides thermal results from S-FTRC experiments conducted on a mixture of commercially available lithium-ion (Li-ion) cells and specialized Li-ion test cells with varying cell format (18650, 21700, and D-cell) and trigger mechanism (heaters, heaters plus internal short circuiting device, and nail penetration). The radiography video component provides insight into the initiation and propagation of TR in the cells, in addition to consequences of TR measured by the FTRC. Fractions of mass ejected for the cell types are separated into regimes based on the different failure modes of the cells, such as purely venting, partial ejection, and total ejection. With knowledge of the rate and characterization of the internal degradation of the cells during TR, and the amounts of mass ejected and unrecovered, the extent of TR, and therefore the mitigation of TR, is revealed relative to cell types and failure modes.

Lithium-ion battery↗

DOE OSTI2026

A Data-Driven Method for Modeling Creep-Fatigue Stress- Strain Behavior Using Neural ODEs

In this paper, we introduce a data-driven machine learning approach for modeling one-dimensional stress–strain behavior under cyclic loading, utilizing experimental data from the nickel-based Alloy 617. The study employs uniaxial creep–fatigue test data acquired under various loading histories and compares two distinct neural network-based ODE models. The first model, known as the black-box model, comprehensively describes the strain–stress relationship using a Neural ODE equation. To interpret this black-box model, we apply the Sparse Identification of Nonlinear Dynamical Systems (SINDy) technique, transforming the black-box model into an equation-based model using symbolic regression. The second model, the Neural flow rule model, incorporates Hooke’s Law for the linear elastic component, with the nonlinear part characterized by a Neural ODE. Both models are trained with experimental data to accurately reflect the observed stress–strain behavior. We conduct a detailed comparison with the standard Chaboche model, which includes three back stresses. Our results demonstrate that the neural network-based ODE models precisely capture the experimental creep–fatigue mechanical behavior, exceeding the standard Chaboche model’s accuracy. Furthermore, an interpretable model derived from the black-box neural ODE model through symbolic regression achieves accuracy comparable to the Chaboche model, enhancing its interpretability. The results highlight the potential of neural network-based ODE models to depict complex creep–fatigue behavior, eliminating the necessity for experts to define a specific, material-focused model form.

creep-fatigue↗

NASA NTRSDate not supplied

Hot Water, Cold Reality: Experimental Analysis of Sorption Constraints in Iodine Filtration Media Under Heated-Water Conditions

Iodine has been widely employed as a residual biocide in potable water applications during crewed missions. Unlike other biocides, it is essential to remove iodine from drinking water prior to consumption, as its biocidal concentration raises health concerns. Consequently, effectively removing iodine species from water is a critical step in potable water processing. Although the non-biocided heated leg has not violated microbial specifications on the International Space Station, any wetted volume lacking biocide presents potential risks for long‑duration exploration missions and for systems that are sensitive to microbial growth/contamination. Recent assessments indicate, however, that iodine‑removal performance may degrade under elevated temperature conditions, such as those required for dispensing hot water for food preparation. This reduction in efficacy appears to stem from both the potential physical degradation of filtration media and the temperature‑dependent behavior of adsorption processes. To investigate the influence of water temperature on the efficacy of filtration media for iodine removal, a series of adsorption capacity tests were conducted at both room temperature and elevated temperatures (90 °C). These experiments aimed to benchmark the performance of the adsorbents that constitute the ACTEX filter in the ISS’s potable water dispenser. The findings of this study provide critical insights into the iodine filtration process, verify the potential performance shortfall under elevated temperature conditions, and establish the basis for defining new absorbent requirements to ensure reliable iodine removal in future mission architectures.

drinking water↗

DOE OSTI2025

Keldysh tuning of photoluminescence in a lead halide perovskite crystal

In 1964, Keldysh laid the groundwork for strong-field physics in atomic, molecular, and solid-state systems by delineating a ubiquitous transition from multiphoton absorption to quantum electron tunneling under intense AC driving forces. While both processes in semiconductors can generate carriers and result in photon emission through electron-hole recombination, the low quantum yields in most materials have hindered direct observation of the Keldysh crossover. Leveraging the large quantum yields of photoluminescence in lead halide perovskites, we show that we can not only induce bright light emission from extreme sub-bandgap light excitation but also distinguish between photon-induced and electric-field-induced processes. Our results are rationalized by the Landau-Dykhne formalism, providing insights into the non-equilibrium dynamics of strong-field light-matter interactions. These findings open new avenues for light upconversion and sub-bandgap photon detection, highlighting the potential of lead halide perovskites in advanced optoelectronic applications.

FOS: Physical sciences↗

DOE OSTI2025

From PINNs to PIKANs: recent advances in physics-informed machine learning

Physics-Informed Neural Networks (PINNs) have emerged as a key tool in Scientific Machine Learning since their introduction in 2017, enabling the efficient solution of ordinary and partial differential equations using sparse measurements. Over the past few years, significant advancements have been made in the training and optimization of PINNs, covering aspects such as network architectures, adaptive refinement, domain decomposition, and the use of adaptive weights and activation functions. A notable recent development is the Physics-Informed Kolmogorov-Arnold Networks (PIKANS), which leverage a representation model originally proposed by Kolmogorov in 1957, offering a promising alternative to traditional PINNs. In this review, we provide a comprehensive overview of the latest advancements in PINNs, focusing on improvements in network design, feature expansion, optimization techniques, uncertainty quantification, and theoretical insights. We also survey key applications across a range of fields, including biomedicine, fluid and solid mechanics, geophysics, dynamical systems, heat transfer, chemical engineering, and beyond. Lastly, we review computational frameworks and software tools developed by both academia and industry to support PINN research and applications.

Kolmogorov-Arnold networks↗

NASA NTRS1996

Planetary and Deep Space Requirements for Photovoltaic Solar Arrays

In the past 25 years, the majority of interplanetary spacecraft have been powered by nuclear sources. However, as the emphasis on smaller, low cost missions gains momentum, more deep space missions now being planned have baselined photovoltaic solar arrays due to the low power requirements (usually significantly less than 100 W) needed for engineering and science payloads. This will present challenges to the solar array builders, inasmuch as planetary requirements usually differ from earth orbital requirements. In addition, these requirements often differ greatly, depending on the specific mission; for example, inner planets vs. outer planets, orbiters vs. flybys, spacecraft vs. landers, and so on. Also, the likelihood of electric propulsion missions will influence the requirements placed on solar array developers. This paper will discuss representative requirements for a range of planetary and deep space science missions now in the planning stages. We have divided the requirements into three categories: Inner planets and the sun; outer planets (greater than 3 AU); and Mars, cometary, and asteroid landers and probes. Requirements for Mercury and Ganymede landers will be covered in the Inner and Outer Planets sections with their respective orbiters. We will also discuss special requirements associated with solar electric propulsion (SEP). New technology developments will be needed to meet the demanding environments presented by these future applications as many of the technologies envisioned have not yet been demonstrated. In addition, new technologies that will be needed reside not only in the photovoltaic solar array, but also in other spacecraft systems that are key to operating the spacecraft reliably with the photovoltaics.

C P Bankston↗

NASA NTRSDate not supplied

Hot Water, Cold Reality: Experimental Analysis of Sorption Constraints in Iodine Filtration Media Under Heated-Water Conditions

iodine↗

DOE OSTI2025

Multiscale aperture synthesis imager

Synthetic aperture imaging has enabled breakthrough observations from radar to astronomy. However, optical implementation remains challenging due to stringent wavefield synchronization requirements among multiple receivers. Here we present the multiscale aperture synthesis imager (MASI), which utilizes parallelism to break complex optical challenges into tractable sub-problems. MASI employs a distributed array of coded sensors that operate independently yet coherently to surpass the diffraction limit of single receiver. It combines the propagated wavefields from individual sensors through a computational phase synchronization scheme, eliminating the need for overlapping measurement regions to establish phase coherence. Light diffraction in MASI naturally expands the imaging field, generating phase-contrast visualizations that are substantially larger than sensor dimensions. Without using lenses, MASI resolves sub-micron features at ultralong working distances and reconstructs 3D shapes over centimeter-scale fields. MASI transforms the intractable optical synchronization problem into a computational one, enabling practical deployment of scalable synthetic aperture systems at optical wavelengths.

electrical and electronic engineering↗

DOE OSTI2025

Observation of deuteron and antideuteron formation from resonance-decay nucleons

High-energy hadronic collisions generate environments characterized by temperatures above 100 MeV (refs.), about 100,000 times hotter than the centre of the Sun. At present, it is therefore unclear how light (anti)nuclei with mass number A of a few units, such as the deuteron, 3 He or 4 He, each bound by only a few MeV, can emerge from these collisions. Here, the ALICE Collaboration reports that deuteron–pion momentum correlations in proton–proton (pp) collisions provide model-independent evidence that about 90% of the observed (anti)deuterons are produced in nuclear reactions following the decay of short-lived resonances, such as the Δ(1232). These findings, obtained by the ALICE Collaboration at the Large Hadron Collider, resolve a gap in our understanding of nucleosynthesis in ultrarelativistic hadronic collisions. Apart from offering insights on how (anti)nuclei are formed in hadronic collisions, the results can be used in the modelling of the production of light and heavy nuclei in cosmic rays and dark-matter decays.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Spinel high-entropy oxides (FeNiCrMnZnX) 3 O 4 (X = Al, mg) as anode materials for high-performance lithium-ion batteries

To address the high cost, cobalt dependency, and resource constraints typical of conventional high-entropy oxide (HEO) anodes, this study reports the successful synthesis of two Co-free, six-component spinel-type HEOs(FeNiCrMnZnAl) 3 O 4 (HEO-Al) and (FeNiCrMnZnMg) 3 O 4 (HEO-Mg), via a sol-gel method. The distinct effects of Al 3+ and Mg 2+ incorporation on the electrochemical performance and lithium storage kinetics were systematically investigated. XRD, Raman, and TEM characterizations confirm that both materials possess a pure spinel phase, uniform particle size, and homogeneous elemental distribution. Notably, electrochemical evaluations reveal that HEO-Al delivers a superior reversible capacity of 480.7 mAh g −1 after 100 cycles at 0.1 A g −1 , and maintains 354.5 mAh g −1 after 1000 long-term cycles at 1 A g −1 , significantly outperforming HEO-Mg. Kinetic analysis indicates that HEO-Al exhibits lower charge transfer resistance, a higher Li + diffusion coefficient, and a pseudocapacitive contribution of up to 82%. Furthermore, these findings demonstrate that Al substitution effectively optimizes the structural stability and lithium storage kinetics of Co-free HEOs, providing a viable strategy for designing low-cost, highly stable HEO anode systems.

Anode materials↗

DOE OSTI2026

Electron temperature relations and the direct N, O, Ne, S, and Ar abundances of 49 959 star-forming galaxies in DESI data release 2

We present the largest direct-method abundance catalogue of galaxies to date, containing measurements of 49 959 star-forming galaxies at z<0.96 from DESI (Dark Energy Spectroscopic Instrument) data release 2. By directly measuring electron temperatures across multiple ionization zones, we provide constraints on a number of electron temperature relations. Using the temperature measurements, we derive reliable abundances for N, O, Ne, S, and Ar, and measure the evolution of abundances and abundance ratios of as a function of metallicity and other galaxy properties. Our measurements include direct oxygen abundances for 49 507 galaxies, leading to the discovery of the two most metal-poor galaxies in the nearby Universe, with oxygen abundances of 12+log⁡(O/H)=6.77−0.03+0.03 dex (1.2 per cent Z⊙⁠) and 12+log⁡(O/H)=6.81−0.04+0.04 dex (1.3 per cent Z⊙⁠). We identify a rare outlier population of 24 galaxies with high-N/O ratios at low metallicity, reminiscent of galaxy abundances observed in the early Universe. We find the Ne/O ratio is constant at low metallicity but increases gradually at 12+log(O/H)>8.105±0.004 dex. We show that the S/O and Ar/O abundance ratios are strongly correlated, consistent with the expected additional Type Ia enrichment channel for S and Ar. In this work, we present an initial survey of the key properties of the sample, with this data set serving as a foundation for extensive future work on galaxy abundances at low redshift.

Scholte, D. [Edinburgh U., Inst. Astron.] (ORCID:0↗

DOE OSTI2026

Insights into elevated temperature tensile deformation mechanisms and kink banding in additively manufactured tungsten

Additive manufacturing (AM) potentially enables fabrication and repair of plasma facing components (PFCs) of tungsten. However, deformation mechanisms in AM-fabricated tungsten under service-relevant thermomechanical conditions remain unknown majorly due to challenges in achieving crack-free W. This study reveals the deformation mechanisms operative under tension at 800 °C and 1200 °C in the electron beam melting powder bed fusion (EBM-PBF) fabricated W. Textured columnar grains with mixed <001 >/<111 >|| build-direction were observed. Strong anisotropy in tensile properties persisted across test temperatures, and all specimens exhibited extensive deformation-induced banding phenomena. Grain boundary character analysis of the deformed specimens indicated that these deformation bands were kink bands with tilt grain boundaries prominently present at the band-matrix interface. Interestingly, the material within the kink bands rotated toward higher resolved shear stress, providing insights into the origins of kink band formation in body-centered cubic refractory metals. Intragranular misorientation axis analysis revealed that plasticity was dominated by {110} <111 > slip at 800 °C, whereas additional (213)[11⁢̄1] and (112)[11⁢̄1] slip systems activated at 1200 °C. A dense low-angle boundary networks observed near fractured surface indicated the onset of dynamic recrystallization. Results reveal plasticity governing mechanisms in AM-fabricated W under power plant-relevant conditions, and provide insights into kink band attributes in refractory metals.

Mayes, Riley [ORNL] (ORCID:000900089307010X)↗

NASA NTRSDate not supplied

The NASA Turbulent Heat Flux (THX) Experiments: Summary and Lessons Learned

The Turbulent Heat Flux (THX) experiments were conducted at NASA Glenn Research Center (GRC) in order to collect measurements of velocities and temperatures for computational fluid dynamics (CFD) validation of heated flows, with a focus on propulsion system components. The experiments spanned 5 phases; four of which were conducted in the GRC AeroAcoustic Propulsion Laboratory (AAPL) using the Small Hot Jet Flow Rig (SHJAR). In addition to making velocity measurements with Particle Image Velocimetry (PIV), the THX experiments introduced a new Raman-scattering based capability to measure temperatures. Computational studies were also conducted for each of the experimental configurations, in order to provide a baseline of expected CFD results and conduct an assessment of the capability of various CFD approaches for calculating flows where the turbulent transport of heat was important. Two of the collected sets of data were used for American Institute of Aeronautics and Astronautics (AIAA) Propulsion Aerodynamic Workshops (PAWs). The data set from the 5th phase, collected for heated supersonic jets, was also used to construct new validation cases for the NASA Turbulence Model Resource (TMR). This paper provides an overview of the experiments and associated computations for each of the 5 test phases. Key experimental findings are presented. Lessons learned are provided concerning the effect of computational modeling choice on accuracy of predicting turbulent flows where thermal transport is important. Emphasis is placed on comparing Reynolds-averaged Navier-Stokes approaches with large-eddy simulation approaches. The benefits of utilizing a conjugate heat transfer method in conjunction with CFD solver for film cooling is demonstrated.

RANS↗

NASA NTRS2026

Influence of Processing Parameters on the Mechanical Properties of 3D Printed Borosilicate Particulate Reinforced Polymer Composites

Emerging composite materials are expanding the potential of additive manufacturing and enabling applications previously restricted by traditional manufacturing methods. The multi-phase nature of these composite materials combined with the complex in-ternal geometry of additively manufactured parts have enabled unique behavior, and potentially new applications. Additionally, these materials can be pyrolyzed to create dense metal, ceramic, and glass parts with geometries typically not achievable by tra-ditional processes. Additive manufacturing of borosilicate glass-based systems can open new applications in nuclear engineering, astronomy, and bone regrowth therapy. To elucidate the process-parameter relationship of borosilicate-polylactic acid (PLA) composites, mechanical testing was conducted and compared with a pure polylactic acid polymer baseline. Test specimens were fabricated by fused-filament fabrication with minimal post-processing. Yield strength, ultimate strength, and elastic modulus were calculated from stress-strain curves. Optical and scanning electron microscopy were conducted to observe the specimen microstructure before and after testing. The highest compressive yield strength for the composite was 28.22 MPa, and the highest compressive yield strength for PLA was 49.30 MPa. Print orientation was found to benefit the composite material but have a detrimental effect on the pure matrix material. An elastic modulus of 2.66 GPa was recorded for the borosilicate-PLA composite at 100% infill, 1 shell wall, and layer lines parallel to compression axis. Microscopy revealed that lower modulus composite specimens had the particulates re-distributed within the matrix. Tensile testing was done according to a polymer testing standard, which caused difficulties obtaining consistent fracture within the gauge length.

mechanical testing↗

DOE OSTI2024

Understanding the origin of early-type dwarfs: the spectrophotometric study of CGCG014−074

ABSTRACT Early-type dwarf galaxies constitute a prevalent population in the central regions of rich groups and clusters in the local Universe. These low-luminosity and low-mass stellar systems play a fundamental role in the assembly of the luminous galaxies observed today, according to the Lambda cold dark matter hierarchical theory. The origin of early-type dwarfs has been linked to the transformation of disc galaxies interacting with the intracluster medium, especially in dense environments. However, the existence of low-luminosity early-type galaxies in low-density environments presents a challenge to this scenario. This study presents a comprehensive photometric and spectroscopic analysis of the early-type dwarf galaxy CGCG014−074 using deep Gemini GMOS (Gemini Multi-Object Spectrograph) data, focusing on its peculiarities and evolutionary implications. CGCG014−074 exhibits distinct features, including a rotating inner disc, an extended stellar formation with a quiescent phase since about 2 Gyr ago, and the presence of boxy isophotes. From the kinematic analysis, we confirm CGCG014−074 as a nucleated early-type dwarf galaxy with embedded disc. The study of its stellar population parameters using different methods provides significant insights into the galaxy’s evolutionary history. These results show an old and metal-poor nucleus (${\sim}9.3$ Gyr and $\mathrm{[Z/H]}\sim -0.84$ dex), while the stellar disc is younger (${\sim}4.4$ Gyr) with a higher metallicity ($\mathrm{[Z/H]}\sim -0.40$ dex). These distinctive features collectively position CGCG014−074 as a likely building block galaxy that has evolved passively throughout its history.

Astronomy & Astrophysics↗

NASA NTRSDate not supplied

The NASA Turbulent Heat Flux Experiments: Summary and Lessons Learned

The Turbulent Heat Flux (THX) experiments were conducted at NASA Glenn Research Center (GRC) in order to collect measurements of velocities and temperatures for computational fluid dynamics (CFD) validation of heated flows, with a focus on propulsion system components. The experiments spanned 5 phases; four of which were conducted in the GRC AeroAcoustic Propulsion Laboratory (AAPL) using the Small Hot Jet Flow Rig (SHJAR). In addition to making velocity measurements with Particle Image Velocimetry (PIV), the THX experiments introduced a new Raman-scattering based capability to measure temperatures. Computational studies were also conducted for each of the experimental configurations, in order to provide a baseline of expected CFD results and conduct an assessment of the capability of various CFD approaches for calculating flows where the turbulent transport of heat was important. Two of the collected sets of data were used for American Institute of Aeronautics and Astronautics (AIAA) Propulsion Aerodynamic Workshops (PAWs). The data set from the 5th phase, collected for heated supersonic jets, was also used to construct new validation cases for the NASA Turbulence Model Resource (TMR). This paper provides an overview of the experiments and associated computations for each of the 5 test phases. Key experimental findings are presented. Lessons learned are provided concerning the effect of computational modeling choice on accuracy of predicting turbulent flows where thermal transport is important. Emphasis is placed on comparing Reynolds- averaged Navier-Stokes approaches with large-eddy simulation approaches. The benefits of utilizing a conjugate heat transfer method in conjunction with CFD solver for film cooling is demonstrated.

RANS↗

NASA NTRS2025

Improving Adhesive Bondline Time of Flight Predictions During Autoclave Cure Utilizing Machine Learning

Composite materials are increasingly being used in aerospace applications due to their superior strength-to-weight ratio compared to commonly used metals. A current limitation to widespread adoption is the certification of adhesively bonded joints. One approach to improving adhesive bonding in composites is accurately measuring the thickness of adhesive bondlines in composite laminates. Precise bondline thickness control is essential for aerospace applications where adhesive layer thickness directly affects joint fracture properties and structural performance. This study focused on implementing machine learning techniques to determine the ultrasonic time of flight (directly correlated to thickness) in adhesive bondlines throughout autoclave cure cycles. A high-temperature (use up to 180°C) ultrasonic scanning system was deployed in an autoclave to provide time of flight data through composite panels. Three experiments were conducted on the curing of 305 mm × 305 mm unidirectional composite panels. In the first experiment, a piecewise function was fit for the temperature correction factor to account for changing autoclave temperatures. Due to deficiencies in the first calibration experiment, a second experiment was run, and the results were used to train a machine learning model. The revised experiment, in combination with the machine learning model, significantly increased the accuracy of the bondline time of flight predictions (~14% error reduced to <1%). Data was processed using the Regression Learner Application in MATLAB®, with a Support Vector Machine selected for the model. The result was a machine learning algorithm capable of reliably quantifying ultrasonic time of flight through adhesive bondlines. The third experiment provided independent test data for the machine learning model, demonstrating that the model produces accurate predictions from data beyond its training set.

Machine Learning↗

NASA NTRS2026

Uranus Orbiter and Probe: Mission Challenges and Concept Updates Since the Origins, Worlds, and Life Decadal Survey

Origins, Worlds, and Life: Planetary Science and Astrobiology in the Next Decade identified a Uranus Orbiter and Probe as the highest-priority strategic mission for the decade 2023–2032, as it enables broad cross-disciplinary science in the largely unexplored Uranian system. The mission architecture evaluated by the Decadal Survey was a singular proof of concept demonstrating that a moderately instrumented mission could deliver Decadal-priority science with a reduced cost and risk posture by leveraging existing technologies to the maximum extent possible. With revised assumptions since the Decadal, we have explored a large trade space including launch vehicles, propulsion options, cruise trajectories, available power sources, viable concept of operations, and science data return for later launch dates without a Jupiter gravity assist. The most repeatable trajectory solutions employ either a commercially derived solar electric propulsion (SEP) transfer stage or the availability of a more capable launch vehicle under development, such as the SpaceX Starship. Orbit insertion has been moved farther from Uranus to acknowledge the remaining uncertainty in Uranian ring structure. A streamlined, SEP-adaptable, orbiter design was developed using two Next Gen Radioisotope Thermoelectric Generators, and the probe design was matured, reducing the entry gravitational acceleration, and assuming the largest Decadal-recommended payload to provide margin for future instrument selections. With this updated design, we also constructed a detailed concept of operations for three representative science cases, returning 13–15 Gbit of science data and spacecraft telemetry per ∼34 day orbit.

Amy A Simon↗