Results for “ARIEL I SATELLITE” — Page 24

DOE OSTI2026

Understanding Discharge‐Driven Growth of Cathode Impedance in Ni‐Rich NMC Cathodes

Degradation of LiNi x Mn y Co 1-x-y O 2 (NMC)-based lithium-ion batteries depends strongly on cut-off voltage ranges. In addition to the high upper cut-off voltage, a high depth of discharge (i.e., lower cut-off voltage) significantly worsens cathode impedance growth and capacity fade during long-term cycling. However, there is currently no consensus on the mechanism behind the negative role of a deep discharge. Here, this phenomenon was investigated in graphite||NMC cells with single-crystal cathodes (LiNi 0.6 Co 0.2 Mn 0.2 O 2 (NMC622) or LiNi 0.76 Co 0.14 Mn 0.10 O 2 (NMC76)) using targeted aging protocols (constant high-voltage holds vs. charge–discharge cycling), while monitoring transition-metal (TM) dissolution, cathode-electrolyte interface (CEI) impedance, and NMC surface composition. We demonstrate a correlation between discharge-driven CEI impedance growth and increased TM dissolution. Furthermore, this degradation pathway is more pronounced in lower-Ni NMC622 than in higher-Ni (NMC76) under comparable delithiation states at charge, with both compositions undergoing the H2→H3 phase transition. X-ray photoelectron spectroscopy (XPS) reveals NMC composition-dependent evolution of surface lattice oxygen and restructured surface layer composition between charged and discharged states. These findings add mechanistic depth to the role of discharge as an active driver of interfacial degradation and provide new insights into its composition dependence.

25 ENERGY STORAGE↗

DOE OSTI2026

Identifying Strain Stacking Boundaries between Multiphase Domains in Atomically Thin Two-Dimensional Magnets

Stacking engineering of van der Waals materials is an important strategy to control the materials’ properties, such as electronic correlations, ferroelectricity, and layer-dependent two-dimensional magnetism. A timely testbed for the study of the latter is atomically thin chromium trihalides (CrX 3 , X = Cl, Br, I). Notably, by understanding the sliding mechanism between different stacking sequences, control of the stacking arrangement, and thus magnetic properties in CrX 3 , can be achieved. Such insight, however, is currently lacking. Here, in this study, advanced electron microscopy methods are used to identify multiple stacking sequences corresponding to different bulk phases in atomically thin CrX 3 (X = Cl and Br) down to bilayer thickness and with lateral domain sizes as small as tens of nanometers. Indications of nanometer scale transitions and interactions at the stacking boundaries are found, including a universally preferred sliding direction that is consistent with density functional theory calculations and the strain fields at lateral heterostructure boundaries. This study demonstrates the necessity to consider local stacking structures when interpreting averaged magnetic properties measured with macroscale probes. Additionally, the preferred sliding direction insight from this study provides a strategy to control stacking sequence in atomically thin CrX 3 samples during the exfoliation and sample fabrication process.

DFT calculations↗

DOE OSTI2026

Staged Z-pinch experiment at the double-EAGLE pulsed power facility

The staged Z-pinch is a potential high-energy gain fusion concept where a high atomic number liner implodes on a deuterium target using a pulsed multi-MA current source. Over the past several years this concept has been studied on 0.5–1.0 MA facilities using Ar and Kr gas puffs injected at R = 1.2 cm. Neutron yield up to (2.5 ± 0.34) x 10 10 was measured, Ruskov et al (2023 IEEE Trans. Plasma Sci. 51 3310–6). Here, in this study, we present experimental results from the 4 MA, 110 ns current rise time Double-EAGLE facility at L3Harris (currently, Fisica Inc.) where a larger radius nozzle created gas density profiles peaked at R = 2.5 cm. Modeling with the MACH2 and FLASH codes indicates that the larger radius allows stronger acceleration of the liner plasma and generation of shock waves that preheat a target plasma layer next to the liner to temperatures $T_i >$1 keV. The resulting counter thermal pressure on the liner plasma limits the growth of the Magneto-Rayleigh–Taylor (MRT) instability at the liner-vacuum boundary and the implosion proceeds in a relatively stable manner. Near bang time the enormous target plasma thermal pressure smoothens the MRT perturbations developed during the earlier implosion stages. Time integrated x-ray pinhole images with cutoff energy of 100 eV confirm that a long (∼3 cm), stable and uniform high energy density plasma column is formed in the final implosion stage. Consistent neutron yield in the 10 10 –10 11 range was measured for both Ar and Kr liners imploding on a deuterium target.

Physics - Plasma physics↗

DOE OSTI1975

Nuclear Safety [Vol. 16, No. 1, January-February 1975]

Nuclear Safety covers significant developments in the field of nuclear safety. The scope is limited to topics relevant to the analysis and control of hazards associated with nuclear energy, operations involving fissionable materials, and the products of nuclear fission and their effects on the environment. Primary emphasis is on safety in reactor design, construction, and operation; however, safety considerations in regard to the entire fuel cycle, including fuel fabrication, spent-fuel processing, nuclear waste disposal, handling of radioisotopes, and environmental effects of these operations, are also treated. Table of Contents for this issue follows. Table of Contents for this issue follows. GENERAL SAFETY CONSIDERATIONS: 1 AEC Working Paper on Population Density Around Nuclear Power-Plant Sites Adapted by J. Ft. Buchanan, 8 Water-Reactor Safety-Research Information Meeting by Wm. B. Cottrell, D. O. Hobson, and G. D. Whitman; ACCIDENT ANALYSIS: 29 Burnout in Boiling Heat Transfer. Part I: Pool-Boiling Systems by A. E. Bergles; PLANT SAFETY FEATURES: 43 Radionuclide Behavior During Normal Operation of Liquid-Metal-Cooled Fast Breeder Reactors. Part 1: Production by C. A. Erdman and A. B. Reynolds; CONSEQUENCES OF EFFLUENT RELEASE: 60 The Control, Monitoring, and Reporting of Radioactivity in Effluents. Part 1: AEC-Owned Facilities by M. B. Biles and F. E. Coffman, 71 The Control, Monitoring, and Reporting of Radioactivity in Effluents. Part 2: AEC-Licensed Facilities by L. B. Higginbotham and J. T. Collins; OPERATING EXPERIENCES: 76 Incident at the Lucens Reactor by J. M. Miller, 79 IAEA Symposium on Experience from Operating and Fueling of Nuclear Power Reactors by William A. Pryor, 87 Recent Occurrences at Nuclear Reactors and Their Causes Compiled by William R. Casto, 98 Summary of Operating U. S. Power Reactors as of Nov. 1. 1974, 101 Selected Safety-Related Occurrences Reported in September and October 1974 Compiled by William R. Casto; CURRENT EVENTS: 104 General Administrative Activities Compiled by Wm. B. Cottrell, 110 Action on Power-Reactor Projects Undergoing Regulatory Review or Consideration Compiled by Wm. B. Cottrell, 119 Action on Nonreactor Projects Undergoing Regulatory Review or Consideration Compiled by Wm. B. Cottrell, 121 Proposed Rule Changes as of Oct. 31, 1974; MISCELLANY: 97 ASTM—Euratom Symposium on Radiation Dosimetry: Developments and Standardization (Announcement), 118 Workshops on In-Pile Filter Testing (Announcement), 119 IAEA Symposium on Radiological Impacts from Releases from Nuclear Facilities into Aquatic Environments (Announcement).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRSDate not supplied

Experimental and Numerical Investigation of the NASA High Efficiency Centrifugal Compressor Vaned Stage Geometry and Aerodynamic Performance

Since its inception in the early 2010s, the NASA High Efficiency Centrifugal Compressor (HECC) has been enigmatic for the propulsion research community: experimental data and numerical simulations of the stage have generally not aligned in their quantifications of performance metrics. Typically, the fault for these disagreements is assigned to the numerical simulations as the simulations are models, and models are inherently incomplete representations of the experiment. This “incompleteness” may manifest in assumptions regarding roughness or heat transfer, simplifications of the flow path (i.e., neglecting bleed flows), or the oft-scapegoated turbulence model. In the case of HECC, recent work showed unexpected discrepancies between the intended impeller geometry defined in the design report (termed Design-Intent) and the manufactured impeller used in the experimental campaigns (termed As-Manufactured). That work used numerical simulations to establish that the geometric differences between the Design-Intent and As-Manufactured impellers were significant enough to result in drastically different performance predictions for the HECC vaneless diffuser configuration. The Design-Intent impeller simulations over predicted the performance relative to the experiment, whereas the As-Manufactured simulations better represented the experimental data, both in terms of one-dimensional performance metrics and spanwise flow profiles. This effort expands on that work by examining in detail the geometry and aerodynamic performance of the HECC vaned diffuser configuration. Further differences between the Design-Intent and As-Manufactured geometries have been discovered in the vaned diffuser and exit guide vanes, and these differences are documented herein. The summations of the geometric differences for all of the components were used to create two numerical models of HECC vaned diffuser configuration: the Design-Intent simulations which are generated from the original geometry definitions given in the design report and the As-Manufactured simulations which are the best available representation of the manufactured compressor hardware used in the experimental test campaigns. In congruence with the earlier vaneless diffuser work, the numerical predictions of the Design-Intent choked mass flow rate, total pressure ratio, and efficiency were notably greater than that of the As-Manufactured simulations. To increase confidence in the experimental dataset, measurements from a recent test campaign conducted in 2024 are used to validate the original experimental data acquired from 2012 to 2014 with good repeatability overall, especially considering the passage of time and differences in the data acquisition systems between the test campaigns. Both numerical simulations were then extensively evaluated against the experimental data. The As-Manufactured simulations provided better estimates of the stage performance than the Design-Intent cases in terms of most performance metrics. Nonetheless, more detailed results still show opportunities for improvement. Despite a more accurate representation of the physical hardware, characterization of the impeller work input remains a challenge even for rigorously developed numerical models.

vaned diffuser↗

NASA NTRSDate not supplied

Experimental and Numerical Investigation of the NASA High Efficiency Centrifugal Compressor Vaned Stage Geometry and Aerodynamic Performance

Since its inception in the early 2010s, the NASA High Efficiency Centrifugal Compressor (HECC) has been enigmatic for the propulsion research community: experimental data and numerical simulations of the stage have generally not aligned in their quantifications of performance metrics. Typically, the fault for these disagreements is assigned to the numerical simulations as the simulations are models, and models are inherently incomplete representations of the experiment. This “incompleteness” may manifest in assumptions regarding roughness or heat transfer, simplifications of the flow path (i.e., neglecting bleed flows), or the oft-scapegoated turbulence model. In the case of HECC, recent work showed unexpected discrepancies between the intended impeller geometry defined in the design report (termed Design-Intent) and the manufactured impeller used in the experimental campaigns (termed As-Manufactured). That work used numerical simulations to establish that the geometric differences between the Design-Intent and As-Manufactured impellers were significant enough to result in drastically different performance predictions for the HECC vaneless diffuser configuration. The Design-Intent impeller simulations over predicted the performance relative to the experiment, whereas the As-Manufactured simulations better represented the experimental data, both in terms of one-dimensional performance metrics and spanwise flow profiles. This effort expands on that work by examining in detail the geometry and aerodynamic performance of the HECC vaned diffuser configuration. Further differences between the Design-Intent and As-Manufactured geometries have been discovered in the vaned diffuser and exit guide vanes, and these differences are documented herein. The summations of the geometric differences for all of the components were used to create two numerical models of HECC vaned diffuser configuration: the Design-Intent simulations which are generated from the original geometry definitions given in the design report and the As-Manufactured simulations which are the best available representation of the manufactured compressor hardware used in the experimental test campaigns. In congruence with the earlier vaneless diffuser work, the numerical predictions of the Design-Intent choked mass flow rate, total pressure ratio, and efficiency were notably greater than that of the As-Manufactured simulations. To increase confidence in the experimental dataset, measurements from a recent test campaign conducted in 2024 are used to validate the original experimental data acquired from 2012 to 2014 with good repeatability overall, especially considering the passage of time and differences in the data acquisition systems between the test campaigns. Both numerical simulations were then extensively evaluated against the experimental data. The As-Manufactured simulations provided better estimates of the stage performance than the Design-Intent cases in terms of most performance metrics. Nonetheless, more detailed results still show opportunities for improvement. Despite a more accurate representation of the physical hardware, characterization of the impeller work input remains a challenge even for rigorously developed numerical models.

centrifugal compressor↗

NASA NTRS2026

Spacecraft Radiator Protection from Ionizing Radiation, Dust, and Excessive Heat Loss

Under a Phase II SBIR project funded by NASA Johnson Space Center (Contract No. 80NSSC25C0088), Analytical Scientific Products LLC (ASP) has been developing an actively controlled louver to protect spacecraft radiators from degradation due to exposure to various types of environmental conditions. Of particular interest are ionizing radiation during spacecraft transit through the Van Allen belts, dust during spacecraft landing and surface operations on the moon, and excessive heat loss during the long lunar night especially near the poles where the local ambient temperatures can drop below -200°C. Exposure to ionizing radiation and dust can degrade the optical properties of the radiator coating that in turn reduces its ability to reject excess heat from the spacecraft into the environment. Exposure to the extremely low temperature conditions during the lunar night near the poles can freeze the radiator fluids that can compromise the integrity of the radiator. Passive louvers constructed using thick aluminum vanes are used currently to protect spacecraft radiators from some of the above effects, but they have several drawbacks: (i) their high aerial density makes it impractical to scale them to protect the much larger spacecraft radiators needed for future manned missions to the moon and beyond, (ii) the bimetallic actuators used to open and close the vanes in passive louvers rely on external temperature alone and so the louver cannot offer protection from dust and ionizing radiation when the ambient temperatures are high, and (iii) the bimetallic actuators need time scales of the order of hours to open and close. We have addressed the above limitations of passive louvers through the development of a low aerial density and rapidly actuating actively controlled louver. It is constructed from a custom alloy that offers much higher levels of protection against the ionizing radiation, dust and excessive heat loss at a fraction of weight compared to passive louvers while providing opening and closing time scales of the order of a second. Our modular design makes it easy to scale the system up or down depending on the application. We have recently constructed a 31 inch × 31 inch module of this louver and tested its functionality and effectiveness. These tests have shown that the louver can be opened and closed in less than 2 s. It reduces the transmission of ionizing radiation by 78% to 100% (depending on the radiation source), dust transmission by more than 93%, and heat loss by more than 97%. We are currently preparing to evaluate this device at the Johnson Space Center’s cryogenic vacuum chamber where it can be subjected to simulated lunar surface conditions. This paper provides a detailed discussion of the test designs as well as the data from tests that demonstrate the effectiveness in reducing the transmission of ionizing radiation, dust, and heat under laboratory conditions.

Radiator↗

NASA NTRSDate not supplied

Spacecraft Radiator Protection from Ionizing Radiation, Dust, and Excessive Heat Loss

Under a Phase II SBIR project funded by NASA Johnson Space Center (Contract No. 80NSSC25C0088), Analytical Scientific Products LLC (ASP) has been developing an actively controlled louver to protect spacecraft radiators from degradation due to exposure to various types of environmental conditions. Of particular interest are ionizing radiation during spacecraft transit through the Van Allen belts, dust during spacecraft landing and surface operations on the moon, and excessive heat loss during the long lunar night especially near the poles where the local ambient temperatures can drop below -200°C. Exposure to ionizing radiation and dust can degrade the optical properties of the radiator coating that in turn reduces its ability to reject excess heat from the spacecraft into the environment. Exposure to the extremely low temperature conditions during the lunar night near the poles can freeze the radiator fluids that can compromise the integrity of the radiator. Passive louvers constructed using thick aluminum vanes are used currently to protect spacecraft radiators from some of the above effects, but they have several drawbacks: (i) their high aerial density makes it impractical to scale them to protect the much larger spacecraft radiators needed for future manned missions to the moon and beyond, (ii) the bimetallic actuators used to open and close the vanes in passive louvers rely on external temperature alone and so the louver cannot offer protection from dust and ionizing radiation when the ambient temperatures are high, and (iii) the bimetallic actuators need time scales of the order of hours to open and close. We have addressed the above limitations of passive louvers through the development of a low aerial density and rapidly actuating actively controlled louver. It is constructed from a custom alloy that offers much higher levels of protection against the ionizing radiation, dust and excessive heat loss at a fraction of weight compared to passive louvers while providing opening and closing time scales of the order of a second. Our modular design makes it easy to scale the system up or down depending on the application. We have recently constructed a 31 inch × 31 inch module of this louver and tested its functionality and effectiveness. These tests have shown that the louver can be opened and closed in less than 2 s. It reduces the transmission of ionizing radiation by 78% to 100% (depending on the radiation source), dust transmission by more than 93%, and heat loss by more than 97%. We are currently preparing to evaluate this device at the Johnson Space Center’s cryogenic vacuum chamber where it can be subjected to simulated lunar surface conditions. This paper provides a detailed discussion of the test designs as well as the data from tests that demonstrate the effectiveness in reducing the transmission of ionizing radiation, dust, and heat under laboratory conditions.

Radiator↗

DOE OSTI2026

UCB-GLOBES: An open-access mass spectral database of identified and unidentified atmospheric organic compounds

Chemical characterization of atmospheric organic aerosols using gas chromatography with 70 eV electron ionization mass spectrometry (GC/EI-MS) has been used for decades in advancing molecular marker detection and identification, though primarily through suspect screening and/or targeted analyses. To advance non-targeted analyses of environmental samples, we have catalogued approximately 27 000 mass spectra (MS) of the trimethylsilyl derivatives of semi-volatile organic aerosol (OA) analytes in the open-access University of California Berkeley Goldstein Library of Organic Biogenic Environmental Spectra (UCB-GLOBES). Analytes were observed in ambient samples from the U.S. and the Central Amazon and/or laboratory simulations of secondary OA (SOA) formation. These samples are representative of OA under urban and biomass burning influences as well as SOA derived from biogenic precursors (e.g., isoprene, monoterpenes, sesquiterpenes) and biomass burning intermediates. MS are documented in UCB-GLOBES without regard to known chemical identity, annotated with extensive metadata such as sample source/experimental conditions, any structural information gained from MS analyses, and predicted chemical properties such as average carbon oxidation state and carbon number. UCB-GLOBES MS are compatible for importing into the NIST MS Search program, and we have also provided a Jupyter Notebook for MS visualization and comparisons. We demonstrate the utility of UCB-GLOBES through MS reanalyses of prior analytes observed in ambient data, finding a 20 % reduction in the number of analytes assigned to OA source categories reliant solely on time series correlation and an overall 11 % increase in new MS-based OA source categorization for the Southeast U.S. For 1513 analytes observed previously in the Central Amazon, we found 375 MS matches using UCB-GLOBES vs. 136 MS matches during prior analyses, representing a 14 % gain in newly confirmed or newly categorized OA species. While OA from laboratory oxidation experiments in UCB-GLOBES are highly diverse chemically, on average only 29 % of UCB-GLOBES MS have a mass spectral match to another MS entry in UCB-GLOBES and/or in databases of known compounds (i.e. NIST MS Database, Adams Essential Oil, MANE Flavor and Fragrance Company). This indicates that roughly 70 % of UCB-GLOBES MS are unique thus far, not observed more than once among the laboratory oxidation samples and ambient data in UCB-GLOBES MS. Further, only 18 % can be positively identified using these databases or known authentic standards. This points to a large gap between these laboratory simulations and ambient OA. Overall, the UCB-GLOBES database can be utilized for improving confidence in OA source categorization and/or identification, novel chemical marker discovery, tracking chemical diversity, de novo structure and properties prediction, and improving MS search and matching algorithms. This can ultimately inform future research priorities for the chemical characterization of atmospheric organic samples.

Mass spectrometry↗

NASA NTRS2026

Machine Learning for Predicting Team Functioning in HERA Missions

Team functioning is integral to success in future long term space exploration missions. Proactively detecting declines in team functioning can mitigate conflict and ensure mission success. This project developed a speech-based artificial intelligence (AI) system that unobtrusively predicts degradation in team functioning, including performance and cohesion, in the Human Exploration Research Analog (HERA) Campaigns 4 and 5. The AI system conducted automated analysis of the prosodic (tone of voice) and linguistic (language content) components of speech, modeling interpersonal dynamics at both the turn-taking and day-wide levels. We investigated team functioning via observing structured interactions (i.e., multi-mission space exploration vehicle-extra vehicular activity [MMSEV-EVA], team interaction battery [TIB]) and unstructured interactions before the MMSEV-EVA task. We developed machine learning models to predict team functioning (objective task accuracy, self reported team efficacy and self reported team cohesion) by analyzing OpenSmile acoustic features, linguistic descriptors extracted via the linguistic inquiry and word count (LIWC) dictionary, and semantic embeddings. In the TIB, static models using logistic regression and random forests were not able to predict task accuracy, but predicted team efficacy and cohesion during both the decision making and relational tasks to a moderate level (60-70%). Majority voting on the individual turns to predict day long team efficacy further increased accuracies (70-80%). Finally, long short-term memory (LSTM) models showed the best performance across all variables (80-91%), including task performance. In the MMSEV-EVA, static models achieved an accuracy of 60% with majority voting, which increased to 80% through the incorporation of mission day as a variable, accounting for the learning effect. A key finding across both tasks was the "team-dependent" nature of these interactions; models achieved much higher accuracy when trained on prior days of the same team's data rather than attempting to generalize across entirely different teams, with even 1-2 days of prior data per team achieving 5-15% improvement over team-independent models. In addition, the incorporation of pre-task data from the same team also improves model performance, e.g., incorporating data from the decision-making task of the TIB, which preceded the relational task, improved the prediction of team efficacy and cohesion during the latter. We compared model performance when trained on machine-generated data compared to data that had been further corrected by human annotators. Overall, models trained on human-corrected data exhibited a modest improvement in performance, particularly when acoustic features were used. We found no significant correlation between word error rate (WER) and model accuracy (r(55) = -0.08, p = 0.51), but model’s accuracy was significantly higher for medium/high quality transcription (0.74 (SD = 0.48)) compared to the low-quality group (0.64 (SD = 0.36)) (t(63)=2.82, p = 0.006). Based on these, several design recommendation emerge, that could inform Standards at NASA. Models predicting team functioning should incorporate at least one to two days of historical interaction data, include brief pre-task discussions, and explicitly model temporal learning effects, especially for longer operational tasks. Minimum quality standards for automated speech-processing pipelines are needed, given the performance gains observed with manually corrected acoustic data. Finally, systems should leverage both acoustic features and language embeddings in complementary ways, with modality choices and fusion strategies tailored to mission context, task demands, and data quality requirements.

Shrivatsa Mishra↗

NASA NTRS2003

Ultra-High-Temperature Ceramics Evaluated for Aeropropulsion Use

Ultra-high-temperature ceramics (UHTC) are a group of materials consisting of zirconium diboride (ZrB2) or hafnium diboride (HfB2) plus silicon carbide (SiC), and in some instances, carbon (C). They offer a combination of properties that make them candidates for airframe leading edges on sharp-bodied reentry vehicles. These UHTCs perform well in the environment for such applications (i.e., air at low pressures). The purpose of this study at the NASA Glenn Research Center was to examine three of these materials under conditions more representative of a propulsion environment: that is, higher oxygen partial pressure and total pressure. Relatively long, multiple-exposure cycles were emphasized. We completed an in-house study of ZrB2 plus 20 vol% SiC (abbreviated as ZS), ZrB2 plus 14 vol% SiC and 30 vol% C (ZSC), and SCS-9a SiC fiber-reinforced ZrB2 plus 20 vol% SiC (ZSS). HfB2-based compositions were not included in the study because of their high cost. The capability of UHTC for propulsion applications must be compared with that of mature, available, and commercially used ceramics such as silicon nitride (e.g., AS-800) to put things in proper perspective. In terms of mechanical properties, UHTCs fall short in terms of strength and fracture toughness. At about 1300 C, the creep resistance of ZS appears to be superior to the creep resistance reported for AS-800. However, the stress rupture life for Si3N4 under stress and temperature conditions similar to those used in this study is measured in hundreds of hours. Because of oxidation, ZS could not achieve such lives. In terms of oxidation resistance, acceptable amounts of material recession in 1 hour to thousands of hours, depending on the specific propulsion application, are on the order of 100 to 300 mm. This converts to an acceptable range of parabolic recession rate constants kp" of approximately less than or equal to 10(exp -1) to 10(exp -2) square millimeters per hour for a 1-hr application. For a 100-hr application, an acceptable range of kp" would be less than or equal to those values divided by 100. For the more oxidation resistant ZS material, measured parabolic recession rate constants were 4.7 x 10(exp -3) millimeters per hour at 1327 C, 7.8 x 10(exp -2) square millimeters per hour at 1627 C, and 1.3 millimeters per hour at 1927 C. Thus, recession rate constants for ZS are acceptable at 1327 C for a 1-hr application, but here silicon nitride is a superior material. At 1627 C, ZS oxidation is marginal for a 1-hr application, but dimensional growth would be an issue. In a 100-hr application, ZS cannot be considered at any temperature. Our cursory examination of thermal shock, both from a theoretical and experimental viewpoint, indicated that the ZS and ZSC UHTCs are inferior to AS-800 silicon nitride. On the basis of this limited study, UHTCs are not ready to be considered as aeropropulsion materials for any applications longer than a few minutes. Current materials suffer from aggressive oxidation and moisture attack (Quynhgiao Nguyen, NASA Glenn, and Raymond C. Robinson, QSS Group, Inc., Cleveland, OH, 2002, private communication), and they are susceptible to thermal shock. For long-term propulsion applications, major improvements in environmental durability are needed. Work is in progress to improve the oxidation resistance of UHTC materials.

Stanley R Levine↗

NASA NTRS2025

Erosion Results of the MISSE 9-15 Polymers and Composites Experiment 1-4 (PCE 1-4)

Polymers and other oxidizable materials on the exterior of spacecraft in the low Earth orbit (LEO) space environment can be eroded from reaction with atomic oxygen (AO). Therefore, in order to design durable spacecraft it is important to know the extent of erosion that will occur during a mission. This can be determined by knowing the LEO AO erosion yield, E y (volume loss per incident oxygen atom), of materials susceptible to AO reaction. In addition, recent flight experiments have shown that the AO E y can vary with the AO fluence and/or solar exposure. Therefore, obtaining AO E y data for materials flown on various spaceflight missions is important. NASA Glenn Research Center has flown numerous experiments as part of the Materials International Space Station Experiment (MISSE) missions on the exterior of the International Space Station (ISS) to characterize the LEO E y of polymers, composites, protective coatings, and other spacecraft materials. Recently, four Glenn experiments with 365 flight (F) samples were flown on ISS’s MISSE-Flight Facility (MISSE-FF). These experiments are the Polymers and Composites Experiment-1 (PCE-1) flown as part of the MISSE-9 mission, the PCE-2 flown as part of the MISSE-10 mission, the PCE-3 flown as part of the MISSE-12 and MISSE-15 missions, and the PCE-4 flown as part of the MISSE-13 mission. Although each experiment had numerous sample objectives, the primary objective was to determine the LEO AO E y of various spacecraft materials as a function of solar irradiation and AO fluence. This paper provides a summary of the erosion data for the PCE 1-4 AO E y samples. The AO E y for 150 samples flown in either the LEO ram, wake, zenith or nadir directions are provided. The AO ram fluence varied from 2.97×10 20 atoms/cm 2 after 0.89 years of direct space exposure (with relatively high levels of Si contamination) on MISSE 12 to 3.93×10 20 atoms/cm 2 after 1.17 years of direct space exposure on MISSE-10. The ram AO E y values for uncoated polymers range from 3.81×10 –25 cm 3 /atom for polytetrafluoroethylene (M9R-C20 F) exposed to an AO fluence of 3.44×10 20 atoms/cm 2 on MISSE-9 to 4.43×10 –23 cm 3 /atom for AO etched low density polyimide aerogel (M12R-C21 F) exposed to an AO fluence of 2.97×10 21 atoms/cm 2 on MISSE-12. Because of the low AO fluence and relatively high Si contamination, a number of PCE-3 wake samples experienced mass gain. Thus, AO E y values are not provided for these samples. Although there are calculated AO E y values for the zenith, wake and nadir samples, the ram AO E y for a particular material is a more reliable value in terms of AO exposure because the zenith, wake and nadir directions were exposed to either no or very little AO fluence and thus other space environmental factors (i.e. vacuum, thermal extremes and thermal cycling, and/or various types of radiation) are responsible for the mass loss.

Erosion yield↗

DOE OSTI2025

Ultrafast low-temperature metal–insulator interface phonon dynamics and heat transport in a Pt/Gd 3 Fe 5 O 12 heterostructure

Interfacial thermal and acoustic phenomena have an important role in quantum science and technology, including in spintronic and spincaloritronic materials and devices. Simultaneous measurements of the low-temperature thermal and acoustic properties of a metal/insulator heterostructure reveal distinct dynamics in the characteristic phonon frequency ranges of acoustic and thermal transport. The measurements probed a heterostructure consisting of a thin film of Pt on the ferrimagnetic insulator gadolinium iron garnet (Gd 3 Fe 5 O 12 , GdIG) grown epitaxially on a gadolinium gallium garnet substrate. Ultrafast structural dynamics within the Pt layer were tracked using time-resolved ultrafast x-ray diffraction and analyzed to probe interfacial acoustic and thermal properties. The rapid heating of the Pt layer by a 400 nm wavelength femtosecond-duration optical pulse produced transient structural changes that provided the stimulus for these measurements. Rapid heating produced a broadband acoustic pulse that was partially reflected by the Pt/GdIG interface. Temporal frequencies up to 740 GHz, corresponding to angular frequencies of several THz, were detected in a wavelet analysis of the acoustic oscillations of the strain in the Pt layer. The structural results were analyzed to determine (i) the acoustic damping coefficient and phonon mean free path in Pt at frequencies of hundreds of GHz and (ii) the Grüneisen anharmonicity parameter. The thermal conductance of the Pt/GdIG interface was tracked using the slower, tens-of-picosecond-scale, dynamics of the initial cooling of the heated Pt layer. Analysis using a model based on the Boltzmann transport equation shows that the phonon transmission is lower at the phonon frequencies relevant to thermal transport than for subterahertz regime acoustics.

Acoustic phenomena↗

DOE OSTI2026

HydraGNN_Predictive_GFM_2026 - Ensemble of predictive graph foundation models for atomistic materials modeling

This release contains data and parameters of HydraGNN-based graph foundation models trained as a result of the work published in the pre-print "Exascale Multi-Task Graph Foundation Models for Imbalanced, Multi-Fidelity Atomistic Data" by M. Lupo Pasini et al. (https://arxiv.org/abs/2604.15380). We jointly train on 16 open first-principles datasets (544+ million structures covering 85+ elements) using a multi-task architecture with per-dataset heads and a scalable ADIOS2/DDStore data pipeline. On Frontier, we execute six large-scale DeepHyper hyperparameter optimization campaigns in FP64 and promote the top-performing message-passing models to sustained 2,048-node training, yielding a PaiNN-based lead model. The version of HydraGNN used to generate the outputs provided in this release is HydraGNN v5.0 (https://github.com/ORNL/HydraGNN/releases/tag/v5.0) The list of datasets used for the training of the graph foundation model is the following: 1) Alexandria [1] 2) ANI1x [2] 3) MPTrj [3] 4) Open Catalyst 2020 (OC20) [4] 5) Open Catalyst 2022 (OC22) [5] 6) Open Catalyst 2025 (OC25) [6] 7) Open Direct ir Capture 2023 (ODAC23) [7] 8) Open Materials 2024 (OMat24) [8] 9) Open Molecules 2025 (OMol25) [9] 10) OMol25-neutral (subset of OMol25 that contains only molecules with zero total charge) 11) OMol25-non-neutral (subset of OMol25 that contains only molecules with non-zero total charge) 12) Open Polymers 2026 (OPoly2026) [10] 13) Nabla2DFT [11] 14) QCML [12] 15) QM7X [reference 13] 16) transition1x [14] Dataset references: [1] J. Schmidt et al., “A dataset of 175k stable and metastable materials calculated with the PBEsol and SCAN functionals,” Scientific Data, vol. 9, p. 64, 2022. [2] J. S. Smith et al., “The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules,” Scientific Data, vol. 7, p. 134, 2020. [Online]. Available: https: //www.nature.com/articles/s41597-020-0473-z [3] A. Jain et al., “Commentary: The Materials Project: A materials genome approach to accelerating materials innovation,” APL Materials, vol. 1, no. 1, p. 011002, 07 2013. [Online]. Available: https://doi.org/10.1063/1.4812323 [4] L. Chanussot et al., “Open catalyst 2020 (oc20) dataset and community challenges,” ACS Catalysis, vol. 11, no. 10, pp. 6059–6072, 2021. [Online]. Available: https://doi.org/10.1021/acscatal.0c04525 [5] K. Tran et al., “Open catalyst 2022 (oc22) dataset and challenges for oxidation electrocatalysts,” ACS Catalysis, vol. 13, no. 5, pp. 3066–3084, 2023. [Online]. Available: https://doi.org/10.1021/acscatal.2c05426 [6] S. J. Sahoo et al., “The open catalyst 2025 (oc25) dataset and models for solid-liquid interfaces,” arXiv preprint arXiv:2509.17862, 2025. [Online]. Available: https://arxiv.org/abs/2509.17862 [7] A. Sriram et al., “The open DAC 2023 dataset and challenges for sorbent discovery in direct air capture,” ACS Central Science, vol. 10, no. 5, pp. 923–941, 2024. [8] L. Barroso-Luque et al., “Open materials 2024 (omat24) inorganic materials dataset and models,” 2024. [Online]. Available: https://arxiv.org/abs/2410.12771 [9] D. S. Levine et al., “The open molecules 2025 (OMol25) dataset, evaluations, and models,” 2025. [Online]. Available: https://arxiv.org/abs/2505.08762 [10] D. S. Levine et al., The open polymers 2026 (OPoly26) dataset and evaluations,” arXiv preprint arXiv:2512.23117, 2025. [Online]. Available: https://arxiv.org/abs/2512.23117 [11] K. Khrabrov et al., “Nabla2dft: A universal quantum chemistry dataset of drug-like molecules and a benchmark for neural network potentials,” in NeurIPS 2024 Datasets and Benchmarks Track, 2024. [Online]. Available: https://openreview.net/forum?id=ElUrNM9U8c [12] S. Ganscha et al., “The QCML dataset, quantum chemistry reference data from 33.5M DFT and 14.7B semi-empirical calculations,” Scientific Data, vol. 12, p. 406, 2025. [13] J. Hoja et al., “QM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules,” Scientific Data, vol. 8, p. 43, 2021. [Online]. Available: https://www.nature.com/articles/s41597-021-00812-2 [14] M. Schreiner et al., “Transition1x - a dataset for building generalizable reactive machine learning potentials,” Scientific Data, vol. 9, p. 779, 2022. The folder "datasets_ADIOS2_format" contains the set of pre-processed datasets in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used for the development and training of GFMs in this work. The "datasets_ADIOS2_format" directory contains 2 sub-directories, one for the version "v1" of the datasets and one for the version "v2" of the datasets. The version "v1" of the datasets provides values of the total energy as they are extracted from the original data as it was released by the respective institutions. The version "v2" of the datasets provides values of the energy that have been realigned. The realignment was performed by training a linear regression model that predicts the total energy as a function of the chemical composition of the atomistic structure, and then subtract such prediction from the original value of the total energy. Both folders "v1" and "v2" contain 16 sub-directories, each corresponding to an ADIOS2-formatted dataset The folder "DeepHyper-results" contains the configurational files and model's parameters for all the 186 HPO trials that were successfully completed by the scalable hyperparameter optimization (HPO) runs on Frontier. The content of the folder "DeepHyper-results" I structured as follows: 1) task-list.txt: list of mpnn name, jobid, and deephyper task id 2) gfm_${MPNN}_${JOBID}_0.${TASKID}: run directory with checkpoint files 3) gfm_${MPNN}: deephyper summary directory (*.csv) for each specific MPNN type 4) deephyper-experiment-${JOBID}: output and error logs for each job The file "deephyper-sorted.csv" contains the details of each HydraGNN model built and tested by HPO, obtained by merging the (*.csv) filed from each HPO run executed. Out of all the HPO trials, we selected 10 to continue the training of the respective HydraGNN models. Due to limited computational budget available in the LRN070 allocation we could not complete the training till convergence for all these 10 selected models. The folder "models" contains multiple sub-folders, one per each HydraGNN model trained. Each model sub-folder contains the parameters of each HydraGNN model, with multiple checkpoint-restarts. The list of sub-folders are as follows: 1) multidataset_hpo-BEST1-fp64 2) multidataset_hpo-BEST2-fp64 3) multidataset_hpo-BEST3-fp64 4) multidataset_hpo-BEST4-fp64 5) multidataset_hpo-BEST5-fp64 6) multidataset_hpo-BEST6-fp64 7) multidataset_hpo-BEST7-fp64 8) multidataset_hpo-BEST8-fp64 9) multidataset_hpo-BEST9-fp64 10) multidataset_hpo-BEST10-fp64 Within each one of these folders, additional auxiliary log files are provided with descriptions about how the training proceeded. The lead PaiNN-model is contained inside "multidataset_hpo-BEST6-fp64". The file "mlp_branch_weights" contains the parameters of the multi-layer perceptron (MLP) used to reconcile the predictions of the 16 output decoding heads of the HydragNN architectures. The MLP takes in input the chemical composition of the atomistic structure and predicts averaging weights to linearly mix the predictions of each output decoding head toward consolidating them into a single one. The folder "1.1billion-structure-inference" contains 1.1 billion atomistic structures randomly generated. Each structures is associated with energy and forces predicted with the lead-PaiNN model combined with the MLP model for reconciliation of the multi-branch predictions generated by the 16 output decoding heads. The folder "1.1billion-structure-inference" contains 9,300 (*.tar.gz) subdirectories, one per Frontier compute node used to execute the inference at exascale. Once uncompressed, each (*.tar.gz) subdirectory contains an ADIOS2 (*.bp) file container, where each atomistic structure is stored as a PyTorch-Geometric Data object. The file "export_dataset_environment_variables.sh" contains the environment variables that need to be set before running the HydraGNN code to reproduce the results provided in this dataset release. The code that can be used to load the ADIOS2 files, load HydraGNN models, and run inference is available at: https://github.com/ORNL/HydraGNN/releases/tag/v5.0

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