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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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NASA NTRS2014

High Efficiency Centrifugal Compressor for Rotorcraft Applications

The report "High Efficiency Centrifugal Compressor for Rotorcraft Applications" documents the work conducted at UTRC under the NRA Contract NNC08CB03C, with cost share 2/3 NASA, and 1/3 UTRC, that has been extended to 4.5 years. The purpose of this effort was to identify key technical barriers to advancing the state-of-the-art of small centrifugal compressor stages; to delineate the measurements required to provide insight into the flow physics of the technical barriers; to design, fabricate, install, and test a state-of-the-art research compressor that is representative of the rear stage of an axial-centrifugal aero-engine; and to acquire detailed aerodynamic performance and research quality data to clarify flow physics and to establish detailed data sets for future application. The design activity centered on meeting the goal set outlined in the NASA solicitation-the design target was to increase efficiency at higher work factor, while also reducing the maximum diameter of the stage. To fit within the existing Small Engine Components Test Facility at NASA Glenn Research Center (GRC) and to facilitate component re-use, certain key design parameters were fixed by UTRC, including impeller tip diameter, impeller rotational speed, and impeller inlet hub and shroud radii. This report describes the design effort of the High Efficiency Centrifugal Compressor stage (HECC) and delineation of measurements, fabrication of the compressor, and the initial tests that were performed. A new High-Efficiency Centrifugal Compressor stage with a very challenging reduction in radius ratio was successfully designed, fabricated and installed at GRC. The testing was successful, with no mechanical problems and the running clearances were achieved without impeller rubs. Overall, measured pressure ratio of 4.68, work factor of 0.81, and at design exit corrected flow rate of 3 lbm/s met the target requirements. Polytropic efficiency of 85.5 percent and stall margin of 7.5 percent were measured at design flow rate and speed. The measured efficiency and stall margin were lower than pre-test CFD predictions by 2.4 percentage points (pt) and 4.5 pt, respectively. Initial impressions from the experimental data indicated that the loss in the efficiency and stall margin can be attributed to a design shortfall in the impeller. However, detailed investigation of experimental data and post-test CFD simulations of higher fidelity than pre-test CFD, and in particular the unsteady CFD simulations and the assessment with a wider range of turbulence models, have indicated that the loss in efficiency is most likely due to the impact of unfavorable unsteady impeller/diffuser interactions induced by diffuser vanes, an impeller/diffuser corrected flow-rate mismatch (and associated incidence levels), and, potentially, flow separation in the radial-to-axial bend. An experimental program with a vaneless diffuser is recommended to evaluate this observation. A subsequent redesign of the diffuser (and the radial-to-axial bend) is also recommended. The diffuser needs to be redesigned to eliminate the mismatching of the impeller and the diffuser, targeting a slightly higher flow capacity. Furthermore, diffuser vanes need to be adjusted to align the incidence angles, to optimize the splitter vane location (both radially and circumferentially), and to minimize the unsteady interactions with the impeller. The radial-to-axial bend needs to be redesigned to eliminate, or at least minimize, the flow separation at the inner wall, and its impact on the flow in the diffuser upstream. Lessons were also learned in terms of CFD methodology and the importance of unsteady CFD simulations for centrifugal compressors was highlighted. Inconsistencies in the implementation of a widely used two-equation turbulence model were identified and corrections are recommended. It was also observed that unsteady simulations for centrifugal compressors require significantly longer integration times than what is current practice in industry.

Gorazd Medic↗
DOE OSTI2026

Passive Confirmation of the Presence Of High-Explosive Material Via Neutron Transmission Spectroscopy

The goal of this project was to explore a novel approach for identifying presence and potential types of high explosives (HE) in treaty-controlled items with passive neutron sources by using passive neutron transmission spectroscopy. We predominantly look to measure relative elemental abundance of Carbon, Hydrogen, Oxygen, and Nitrogen (CHON) since most relevant materials are certain mix of these elements, as shown in Table 1. Previously, most studies exploring potential identification of CHON elemental content of targets in the vicinity of passive neutron source were focused solely on gamma spectroscopy using high resolution gamma detectors. Using neutron transmission spectroscopy with pulse-shape discrimination (PSD) capable organic scintillators is not only a novel idea in of itself, but arguably necessary for accurate identification of the CHON elemental content of an interrogated target. While high resolution gamma spectroscopy in principle can determine a presence of hydrogen and nitrogen, it is effectively blind to a quantitatively measuring areal densities of C, O. The initially proposed approach, described in detail in the project proposal, was to leverage previous Monte Carlo study on neutron transmission spectroscopy using slab shaped target interrogated with well-collimated (“pencil”) neutron beam. In this study, a simulated test CO 2 target was interrogated by a pencil neutron beam and transmitted neutron spectra were measured using PSD capable organic scintillator using MLEM based unfolding technique. To establish relative elemental content of carbon and oxygen, the unfolded neutron spectrum was fit with a parametrized combination of their respective elemental spectral templates. The individual spectral template was calculated by convoluting ENDF neutron crosssection with the known resolution of the PSD detector used in the study. This approach in the studied configuration successfully quantitatively established relative elemental composition of carbon and oxygen.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

The impact of aerosol mixing state on immersion freezing: insights from classical nucleation theory and particle-resolved simulations

Immersion freezing, initiated by ice-nucleating particles (INPs) in supercooled aqueous droplets, plays an important role in the formation of ice crystals within clouds. The efficiency of immersion freezing depends strongly on INP composition and, crucially, on the mixing state – how chemical species are distributed across the particle population. Here, we quantify the impact of aerosol mixing state on immersion freezing using a combined theoretical and particle-resolved modeling approach. We derive analytical expressions for the frozen fraction of internally and externally mixed INP populations based on classical nucleation theory, showing that the frozen fraction is sensitive to whether ice-active species are present in all particles or only in a subset of the population. We introduce a multi-species immersion freezing scheme into the particle-resolved model PartMC, using the water activity-based immersion freezing model (ABIFM) to compute freezing probabilities for mixed-composition particles. To improve computational efficiency, we implement a Binned Tau-Leaping algorithm and demonstrate an order-of-magnitude speedup with minimal accuracy loss. Simulations reproduce the analytical trends in limiting cases and extend the analysis to more general aerosol populations, where mixing state continues to exert a substantial control on frozen fraction. Sensitivity analyses across particle size, species type, and cooling condition reveal that the mixing state effect is most pronounced when small amounts of highly efficient INPs are mixed with less efficient materials. These findings underscore the need to represent aerosol mixing state explicitly in models of heterogeneous ice nucleation to reduce uncertainty in cloud-phase partitioning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Integrated Simulation of Weld Residual Stress Evolution and Crack Propagation Using XFEM

Nuclear power plant components operate in environments that promote multiple degradation mecha- nisms, several of which involve crack initiation and growth. An ongoing effort in the U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program is developing a general capability within the Multiphysics Object Oriented Simulation Environment (MOOSE) framework for simulating three-dimensional crack growth under a range of driving conditions, including fatigue, stress corrosion cracking (SCC), brittle fracture, and stress-relaxation cracking. This report demonstrates an end-to-end workflow that uses this capability to model weld-residual-stress-driven SCC in the J-groove weld of a pressurized-water reactor control rod drive mechanism penetration in the vessel head. The workflow consists of a thermomechanical welding simulation with temperature-dependent plasticity, followed by cooldown to ambient conditions, and a restart of the simulation using the MOOSE extended finite element method (XFEM) module to propagate a three-dimensional crack through the residual stress field. New welding capabilities were developed to properly initialize newly activated elements in the weld region, and robustness improvements were made to the mesh-based algorithm for defining cutting planes in the 3D XFEM algorithm, allowing it to handle complex crack fronts and stress fields. Together these advances allowed the simulated SCC crack to grow from an initial elliptical flaw in the weld, across the weld, through the tube wall, and almost to the triple point (where the weld, tube, and reactor pressure vessel head intersect) over roughly 36 years of simulated service. These results demonstrate a workflow that can be extended to fully three-dimensional welding simulations and more complex crack interaction problems.

42 - ENGINEERING↗
DOE OSTI2023

Fabrication of Large-Area Metal-on-Carbon Catalytic Condensers for Programmable Catalysis

Catalytic condensers stabilize charge on either side of a high-k dielectric film to modulate the electronic states of a catalytic layer for the electronic control of surface reactions. Here, carbon sputtering provided for fast, large-scale fabrication of metal–carbon catalytic condensers required for industrial application. Carbon films were sputtered on HfO 2 dielectric/p-type Si with different thicknesses (1, 3, 6, and 10 nm), and the enhancement of conductance and capacitance of carbon films was observed upon increasing the carbon thickness following thermal treatment at 400 °C. After Pt deposition on the carbon films, the Pt catalytic condenser exhibited a high capacitance of ∼210 nF/cm 2 that was maintained at a frequency ∼1000 Hz, satisfying the requirement for a dynamic catalyst to implement catalytic resonance. Temperature-programmed desorption of carbon monoxide yielded CO desorption peaks that shifted in temperature with the varying potential applied to the condenser (−6 or +6 V), indicating a shift in the binding energy of carbon monoxide on the Pt condenser surface. A substantial increase in capacitance (∼2000 nF/cm 2 ) of the Pt-on-carbon devices was observed at elevated temperatures of 400 °C that can modulate ∼10% of charge per metal atom when 10 V potential was applied. A large catalytic condenser of 42 cm 2 area Pt/C/HfO 2 /Si exhibited a high capacitance of 9393 nF with a low leakage current/capacitive current ratio (<0.1), demonstrating the practicality and versatility of the facile, large-scale fabrication method for metal–carbon catalytic condensers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2026

The Contaminant Footprint of Landed Spacecraft: Toward an Inventory and Modelling Framework

All spacecraft generate and carry contaminants, i.e., unwanted and potentially harmful material. When a spacecraft lands and operates in near-vacuum, as onto Earth’s Moon, it introduces contaminants into its environment that may compromise mission science objectives and engineering performance. Contamination of solar system bodies may irrevocably degrade targets of unique value to planetary scientists, for instance, as lunar landed spacecraft introduce propellant effluents into the otherwise pristine ice of the Moon’s permanently shadowed regions. NASA’s planetary protection discipline seeks to ensure that solar system bodies are not contaminated, for scientific purposes, by terrestrial material (i.e., forward contamination). This interest aligns with planetary science interest in mitigating the transport of terrestrial contaminants onto solar system bodies and in controlling types of contamination that could compromise the scientific value of samples or measurements. NASA, and other entities that practice planetary science, have compelling and multidisciplinary interests in the preservation of special regions and sampling sites of high scientific value – including lunar permanently shadowed regions (PSRs) – from inadvertent contamination by any spacecraft, and in understanding the contamination of such regions by all spacecraft. Organic molecular contamination here represents a primary threat. Organic molecules will be introduced to solar system bodies by nominal landed spacecraft and crew processes – including by the action of descent and ascent engines; natural materials outgassing; and crew environmental and life support system sources. Molecular contaminants can also travel in the free-molecular sense at global scale across near-vacuum bodies, including into regions where they may be permanently trapped. This presentation will address a high-level study to identify sources of contaminants – in particular, organic material – generated by landed spacecraft along with the transport vectors by which these contaminants can reach sites of scientific interest on bodies like the Moon. A vision for an integrated modeling framework for the organic contamination footprint of spacecraft missions, individually and collectively, will also be described and presented along with initial conclusions related to organic molecular transport.

Gas Dynamics↗
DOE OSTI2024

Energy conversion and transport in molecular-scale junctions

Molecular-scale junctions (MSJs) have been considered the ideal testbed for probing physical and chemical processes at the molecular scale. Due to nanometric confinement, charge and energy transport in MSJs are governed by quantum mechanically dictated energy profiles, which can be tuned chemically or physically with atomic precision, offering rich possibilities beyond conventional semiconductor devices. While charge transport in MSJs has been extensively studied over the past two decades, understanding energy conversion and transport in MSJs has only become experimentally attainable in recent years. As demonstrated recently, by tuning the quantum interplay between the electrodes, the molecular core, and the contact interfaces, energy processes can be manipulated to achieve desired functionalities, opening new avenues for molecular electronics, energy harvesting, and sensing applications. This Review provides a comprehensive overview and critical analysis of various forms of energy conversion and transport processes in MSJs and their associated applications. We elaborate on energy-related processes mediated by the interaction between the core molecular structure in MSJs and different external stimuli, such as light, heat, electric field, magnetic field, force, and other environmental cues. Key topics covered include photovoltaics, electroluminescence, thermoelectricity, heat conduction, catalysis, spin-mediated phenomena, and vibrational effects. Furthermore, the review concludes with a discussion of existing challenges and future opportunities, aiming to facilitate in-depth future investigation of promising experimental platforms, molecular design principles, control strategies, and new application scenarios.

Charge transport↗
DOE OSTI2026

Development of large-scale, 3D Printed high temperature ceramic material

Through this collaborative effort, a new 3D printing platform for ceramics called laser-induced slip casting (LIS) was explored and developed for improving the processing and manufacture of silicon carbide (SiC), a high temperature ceramic material. This method prints layers of ceramic slips/slurries with subsequent selective-laser heating to dry each layer to build a 3D structure. The completed and dried part is then sintered. This manufacturing process is inherently lower cost than alternative ceramic printing methods such as binder jet technology or stereolithography when it comes to the feedstock material but is more expensive than robocasting or direct ink writing. However, it has the potential to make more controlled parts with less defects compared to robocasting. The largest cost is the heating source for the printer. With this technique, there is potential to make large ceramic parts in a near-net shape. Further, there is no known commercial manufacturing of 3D printed ceramics that creates a large range of different high-density ceramics at large scale. The goals and outcomes for the development of the new printing technology were: 1) assessing the technology with alumina by characterizing coupons, 2) printing and sintering of silicon carbide (SiC), and 3) characterization and properties testing of materials printed and a scale-up of SiC part(s). Through this collaborative project, it was sought to provide the best solution to achieving highly dense and near-net shaped ceramic parts at large scale and reduced cost. The goal was to produce high density sintered materials for applications in defense, energy generating systems, armor, and wear parts using 3D printing methods. Variables including powder particle sizes, dispersant molecular weights (MWs), binders, printing parameters, and post processing were explored as well as the characterization of the physical properties (add specifics here).

36 MATERIALS SCIENCE↗
NASA NTRS2016

NASA Alternative Orion Small Cell Battery Design Support

The NASA Orion Crew Module Reference Design was produced to address large scale thermal runaway (TR) hazard with specific safety controls for the Orion Spacecraft. The design presented provides the description of a full scale battery design reference for implementation as a drop in replacement to meet all spacecraft energy requirements with compatible 120 Vdc electrical and mechanical interface using small cell technology (18650) packaging. The 32V SuperBrick incorporates unique support features and an electrical bus bar arrangement that allows cells negative can insertion into heat sink that is compressively coupled to the battery enclosure to promote good thermal management. The housing design also provides an internal flame suppression "filter tray" and positive venting path internal to the enclosure to allow hot effluent ejecta to escape in the event of single cell TR. Virtual cells (14P Banks) that are supported to provide cell spacing with interstitial materials to prevent side can failures that can produce cell to cell TR propagation. These features were successfully test in four separate TR run with the full scale DTA1 test article in February 2016. Successfully Completed Test Objectives - Four separate TR test runs with Full-Scale DTA1 housing with Two SuperBricks, Two SuperBrick Emulators All Tests resulted in "clean" gas with less than 6 C rise at Battery vent All Tests resulted in less than 2 C temperature rise on cold-plate outlet All Tests resulted in less than 6 psi pressure rise in the battery housing Test Run 1 -One neighbor cell TR, highest remaining neighbor 139 C. Ejecta shorted to bus caused prolonged additional heating, One shorted cell did experience TR after 12 minutes, remaining cells had adequate thermal margin Test Run 2 - No cell to cell propagation, highest neighbor cell 112 C; Test Run 3 - No cell to cell propagation, highest neighbor cell 96 C; Test Run 4 - No cell to cell propagation, highest neighbor cell 101 C; Primary TR testing and analysis were completed and reviewed for endorsement by NASA Engineering and Safety Center team members. All Key Test Objectives were met and the small cell design alternative was demonstrated and selected to be a feasible drop in replacement for the MPCV Orion CM Battery for EM2 mission.

Haynes, Chuck↗
DOE OSTI2025

Multi-contrast machine learning improves schistosomiasis diagnostic performance

Schistosomiasis currently affects over 250 million people and remains a public health burden despite ongoing global control efforts. Conventional microscopy is a practical tool for diagnosis and screening ofSchistosoma haematobium, but identification of eggs requires a skilled microscopist. Here we present a machine learning (ML)-based strategy for automated detection ofS. haematobiumthat combines two imaging contrasts, brightfield (BF) and darkfield (DF), to improve diagnostic performance. We collected BF and DF images of urine samples, many of them containingS. haematobiumeggs, during two different field studies in Côte d’Ivoire using a mobile phone-based microscope, the SchistoScope. We then trained separate egg-detection ML models and compared the patient-level performance of BF and DF models alone to combinations of BF and DF models, using annotations from trained microscopists as the gold standard. We found that models trained on DF images, and almost all BF and DF combinations, performed significantly better than models trained on BF images only. When models were trained on images from the first field study (n = 349 patients, 748 images of each contrast), patient-level classification performance on patient images from the second study (n = 375 patients, 752 images of each contrast) met the WHO Diagnostic Target Product Profile (TPP) sensitivity and specificity for the monitoring and evaluation use case (sensitivity for all models and combinations was >75% when evaluated at a confidence score threshold that resulted in specificity >96.5%). When we used images from both field studies for the training set, performance of the models was improved. Overall, this work shows that the use of DF and BF increases the performance of ML models on images from devices with low-cost optics, while retaining the portability, power, and time-to-results of the WHO’s diagnostic TPP. DF requires no additional sample preparation and does not increase the complexity of the imaging system. It thus offers a practical means to improve performance of automated diagnostics forS. haematobiumas well as other microscopy-based diagnostics.

Infectious Diseases↗
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

36 MATERIALS SCIENCE↗
DOE OSTI2023

Four Years of Type Ia Supernovae Observed by TESS: Early-time Light-curve Shapes and Constraints on Companion Interaction Models

Abstract We present 307 type Ia supernova (SN) light curves from the first 4 yr of the Transiting Exoplanet Survey Satellite mission. We use this sample to characterize the shapes of the early-time light curves, measure the rise times from first light to peak, and search for companion star interactions. Using simulations, we show that light curves must have noise <10% of the peak flux to avoid biases in the early-time light-curve shape, restricting our quantitative analysis to 74 light curves. We find that the mean power-law index t β 1 of the early-time light curves isβ 1 = 1.93 ± 0.57, and the mean rise time to peak is 15.7 ± 3.5 days. The underlying population distribution forβ 1 may instead consist of a Gaussian component with mean 2.29, width 0.34, and a long tail extending to values less than 1.0. We find that the data can rarely distinguish between models with and without companion interaction models. Nevertheless, we find three high-quality light curves that tentatively prefer the addition of a companion interaction model, but the statistical evidence for the companion interactions is not robust. We also find two SNe that disfavor the addition of a companion interaction model to a curved power-law model. Taking the 74 SNe together, we calculate 3σupper limits on the presence of companion signatures to control for orientation effects that can hide companions in individual light curves. Our results rule out common progenitor systems with companions having Roche lobe radii >31R ⊙ (separations >5.7 × 10 12 cm, 99.9% confidence level) and disfavor companions having Roche lobe radii >10R ⊙ (separations >1.9 × 10 12 cm, 95% confidence level). Lastly, we discuss the implications of our results for the intrinsic fraction of single degenerate progenitor systems.

Astronomy & Astrophysics↗
DOE OSTI2026

Directing Assembly of Mesoscale Multi‐Shell Morphologies of DNA Origami Crystals

Nature builds hierarchically ordered materials, such as seashells, wood, and bones, through spatially and temporally regulated growth. Mimicking such a level of control in synthetic systems remains challenging, particularly in achieving multiscale organizations with prescribed nanoscale arrangements and desired material morphologies. In this study, we introduce a DNA-based self-assembly strategy for constructing diverse multi-shell mesoscale morphologies from nanoscale lattices, enabling prescribed structural, and compositional 3D material patterns. Using DNA origami frames as modular monomers, we direct anisotropic epitaxial growth through addressable DNA frame binding motifs and encapsulate nanoparticles (NPs) in desired 3D patterns. Sequential monomer addition under thermodynamically favorable conditions enables shell growth through heterogeneous nucleation while minimizing unwanted homogeneous nucleation. Here, we demonstrate that DNA-encoded addressability enables epitaxial shell growth along specific lattice directions, yielding crystals with multilayered mesoscale organization, including tube-like (sushi roll) and plate-like (macaron) morphologies. Shell-specific NP configurations and compositions are achieved through addressable and differentiated placement of NPs within each shell, as validated by small-angle x-ray scattering and cross-sectional scanning transmission electron microscopy. We further demonstrate addressable NP release and reveal that shells modulate release kinetics. Together, these findings establish a platform for fabricating DNA origami crystals with programmable mesoscale morphologies, nanoscale structure, composition, and transport properties.

3D patterning↗
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↗
DOE OSTI2025

Dimensional Reduction Guides Electronic Structure Evolution in the A n Cu 4–n SnS 4 Semiconductor Series

The search for new functional materials with tunable properties remains a central challenge in chemistry, particularly for applications in energy and electronics. In this work, we present a framework for predictive crystal design in alkali metal chalcogenides that enables controlled dimensional reduction of a parent covalent motif, yielding a broad range of electronic structures, which systematically evolve from one parent to the other. We present 11 new members of the A n Cu 4–n SnS 4 family (A = alkali metal; n = 0–4), which reduce the three-dimensional (3D) covalent network of Cu 4 SnS 4 into various 3D, 2D, 1D, and 0D [Cu 4–n SnS 4 ] n− motifs through the substitution of Cu with alkali metals of various radii. The end members of the family set the range in achievable band gaps at 0.99 eV for fully covalent Cu 4 SnS 4 (n = 0) and 3.38 eV for K 4 SnS 4 (n = 4) with 0D [SnS 4 ] n− tetrahedra. As the dimensionality of [Cu 4–n SnS 4 ] n− systematically reduces within A n Cu 4–n SnS 4 (n = 1–3), a stepwise increase in band gap energy occurs through a gradual decrease in the energy of the valence band maximum and an increase in the conduction band minimum, with an increase in the effective masses of charge carriers. Furthermore, irrespective of the alkali metal, the thermal stability decreases with decreasing [Cu 4–n SnS 4 ] n− dimensionality within the quaternary members. Most importantly, we demonstrate that predictable crystal structure and property evolution for a given composition space is possible by deriving a general formula based on substituting the covalent metals of a parent structure with alkali metals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Robustness of pairwise kinematic Sunyaev–Zel’dovich effect to optical-cluster-selection bias

The pairwise kinematic Sunyaev–Zel’dovich (kSZ) effect measures both the pairwise motion between galaxy groups and clusters and the amount of gas within them, providing a tracer for cosmic growth. To interpret the cosmological information in the kSZ measurements, it is crucial to understand the optical-cluster-selection bias on the kSZ observables. Line-of-sight structures that contribute to both the optical observable (e.g., richness) and the cosmological signal can induce a correlation between these two quantities at a fixed cluster mass. The selection bias arising from this correlation is a key systematic effect for cosmological analyses. For cosmological observables such as cluster abundance and weak lensing, controlling this selection bias may help explain the tension between the DES-Y1 results and the Planck constraints. In order to test for a kSZ effect equivalent of such a bias, we adopted an alternative mock richness based on galaxy counts within cylindrical volumes along the line of sight. We applied the cylindrical count method to hydrodynamical simulations across a wide range of galaxy-selection criteria, assigning richness consistent with DES-Y1 to the mock clusters. When comparing optically selected clusters to mass-selected halos, we find no significant bias on pairwise kSZ signals, pairwise velocities, or optical depth within our uncertainty limits of approximately 16, 10, and 8%, respectively.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1994

Orbital Processing of High-Quality CdTe Compound Semiconductors

CdZnTe crystals were grown in one-g and in micro-g for comparative analysis. The two micro-g crystals were grown in the Crystal Growth Furnace during the First United States Microgravity Laboratory mission (USML-1). The samples were analyzed for chemical homogeneity, structural perfection, and optoelectronic performance (infrared transmission). Fourier Transform Infrared (FTIR) transmission of both ground and flight materials showed that the infrared transmission was close to theoretical, 63% versus 66%, suggesting that the material was close to the stochiometric composition during both the ground and flight experiments. Infrared microscopy confirmed that the principal precipitates were Te and their size (1-10 microns) and density suggested that the primary flight and ground base samples experienced similar cooling rates. Macrosegregation was predicted, using scaling analysis, to be low even in one-g crystals and this was confirmed experimentally, with nearly diffusion controlled growth achieved even in the partial mixing regime on the ground. Radial segregation was monitored in the flight samples and was found to vary with fraction solidified, but was disturbed due to the asymmetric grvitational and thermal fields experienced by the flight samples. The flight samples, however, were found to be much higher in structural perfection than the ground samples produced in the same furnace under identical growth conditions except for the gravitational level. Rocking curve widths were found to be substantially reduced, from 20/35 (one-g) to 9/20 (micro-g) for the best regions of the crystals. The full width at half maximum (FWHM) of 9 arc seconds is as good as the best reported terrestrially for this material. The ground samples were found to have a fully developed mosaic structure consisting of subgrains, whereas the flight sample dislocations were discrete and no mosaic substructure was evident. The defect density was reduced from 50-100,000 (one-g) to 500-25000 EPD (micro-g). These results were confirmed using rocking curve analysis, synchrotron topography, and etch pit analysis. The low dislocation density is thought to have resulted from the near-absence of hydrostatic pressure which allowed the melt to solidify with minimum or no wall contact, resulting in very low stress being exerted on the crystal during growth or during post-solidification cooling.

D J Larson, Jr.↗
NASA NTRSDate not supplied

First N 2 Profile for Venus’ Deep Lower Atmosphere

We present the first N 2 profile for Venus’ deep lower atmosphere (<15 km) and a constrained isotopic composition for cloud N 2 [1]. This work directly addresses unresolved questions for Venus using legacy observations. Prior to this work, there were no reported measurements for N 2 abundances at <15 km and the isotopic composition remained unconstrained [2]. The N 2 parameters are critical to understanding the evolution and thermal properties of the atmosphere [3-7]. Our N 2 results were obtained by re-analysis of data acquired in 1978 by the Pioneer Venus Large Probe Neutral Mass Spectrometer (LNMS) [8]. The archived mass spectra from 64.2 to 0.2 km were treated using the analytical procedures specifically developed for the LNMS [9-11]. Judicious peak fitting permitted disambiguation of (A) N 2 + and CO + at 28 u and (B) 14 N 15 N+, 13 CO + , and C 2 H 5 + at 29 u. Quality controls included comparing the (A) LNMS CO + /CO 2 + ratios to the NIST database and literature and (B) fitted counts for CO + to the expected counts of CO + calculated from C 18 O + and 13 CO + using the LNMS 16 O/ 18 O and 12 C/ 13 C ratios (obtained from CO 2 ). Our results show that N 2 is uniformly mixed across the deep lower atmosphere between ~0.2 and 15 km (2.49 ± 0.10 v%). In contrast, N 2 is non-uniformly mixed across the sub-cloud atmosphere and clouds (~15–59 km), where N 2 abundances increase by ~ 2-fold between ~15 km (2.45 ± 0.32 v%) and ~59-51 km (5.21 ± 0.18 v%). Using the cloud data, we also obtained a constrained 15 N/ 14 N ratio (2.93×10 -3 ± 0.13×10 -3 ) and δ 15 N value (-204 ± 35‰). Thus, the LNMS results [1] suggest that (A) the atmosphere is unstable at <15 km, (B) N 2 is not well-mixed >15 km, and (C) the cloud δ 15 N falls between Earth and the solar wind [12, 13]. Comparisons of the N 2 abundances and isotopic compositions for nitrogen, carbon, and oxygen to other Venus measurements will be discussed.

deep lower atmosphere↗