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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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At least 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Defect detection in atomic-resolution images via unsupervised learning with translational invariance

Abstract Crystallographic defects can now be routinely imaged at atomic resolution with aberration-corrected scanning transmission electron microscopy (STEM) at high speed, with the potential for vast volumes of data to be acquired in relatively short times or through autonomous experiments that can continue over very long periods. Automatic detection and classification of defects in the STEM images are needed in order to handle the data in an efficient way. However, like many other tasks related to object detection and identification in artificial intelligence, it is challenging to detect and identify defects from STEM images. Furthermore, it is difficult to deal with crystal structures that have many atoms and low symmetries. Previous methods used for defect detection and classification were based on supervised learning, which requires human-labeled data. In this work, we develop an approach for defect detection with unsupervised machine learning based on a one-class support vector machine (OCSVM). We introduce two schemes of image segmentation and data preprocessing, both of which involve taking the Patterson function of each segment as inputs. We demonstrate that this method can be applied to various defects, such as point and line defects in 2D materials and twin boundaries in 3D nanocrystals.

36 MATERIALS SCIENCE↗
DOE OSTI2025

WorkflowHub: a registry for computational workflows

The rising popularity of computational workflows is driven by the need for repetitive and scalable data processing, sharing of processing know-how, and transparent methods. As both combined records of analysis and descriptions of processing steps, workflows should be reproducible, reusable, adaptable, and available. Workflow sharing presents opportunities to reduce unnecessary reinvention, promote reuse, increase access to best practice analyses for non-experts, and increase productivity. In reality, workflows are scattered and difficult to find, in part due to the diversity of available workflow engines and ecosystems, and because workflow sharing is not yet part of research practice. WorkflowHub provides a unified registry for all computational workflows that links to community repositories, and supports both the workflow lifecycle and making workflows findable, accessible, interoperable, and reusable (FAIR). By interoperating with diverse platforms, services, and external registries, WorkflowHub adds value by supporting workflow sharing, explicitly assigning credit, enhancing FAIRness, and promoting workflows as scholarly artefacts. The registry has a global reach, with hundreds of research organisations involved, and more than 800 workflows registered.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Structurally silent peptide anchor modifications allosterically modulate T cell recognition in a receptor-dependent manner

Presentation of peptides by class I MHC proteins underlies T cell immune responses to pathogens and cancer. The association between peptide binding affinity and immunogenicity has led to the engineering of modified peptides with improved MHC binding, with the hope that these peptides would be useful for eliciting cross-reactive immune responses directed toward their weak binding, unmodified counterparts. Increasing evidence, however, indicates that T cell receptors (TCRs) can perceive such anchor-modified peptides differently than wild-type (WT) peptides, although the scope of discrimination is unclear. We show here that even modifications at primary anchors that have no discernible structural impact can lead to substantially stronger or weaker T cell recognition depending on the TCR. Surprisingly, the effect of peptide anchor modification can be sensed by a TCR at regions distant from the site of modification, indicating a through-protein mechanism in which the anchor residue serves as an allosteric modulator for TCR binding. Our findings emphasize caution in the use and interpretation of results from anchor-modified peptides and have implications for how anchor modifications are accounted for in other circumstances, such as predicting the immunogenicity of tumor neoantigens. Our data also highlight an important need to better understand the highly tunable dynamic nature of class I MHC proteins and the impact this has on various forms of immune recognition.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

High-resolution cryo-electron microscopy structure of photosystem II from the mesophilic cyanobacterium, Synechocystis sp. PCC 6803

Significance Photosystem II (PSII) is a photo-oxidoreductase that harnesses light energy to use water to make fuel. Water oxidation occurs at a metal cluster in the active site called the oxygen-evolving complex (OEC). Understanding PSII function has provided design principles for synthetic solar fuel catalysts; however, the details of water oxidation are obscured by the multiple states through which the mechanism proceeds, differences between species, and lability of the OEC. To better understand PSII function, we solved its structure from Synechocystis sp. PCC 6803. We observe significant differences compared with PSII from thermophilic cyanobacteria that highlight the need for reexamination of previous data using this structure for interpretation. The structure also provides a platform for studies of site-directed mutations of PSII.

PsbV↗
DOE OSTI2022

Measurements of the 27 Al(α,n) Thick Target Yield near Threshold

In this work, we present results from direct measurements of the 27 Al(α,n) thick-target yield from laboratory incident energies E α ≈ 3 to 5 MeV, performed with the 3 HeBF 3 Giant Barrel (HeBGB) neutron detector at the Edwards Accelerator Laboratory. Our measurements have a small energy cadence in order to address discrepancies and sparseness of thick-target-yield data sets existing for this energy region. We find general agreement with existing data sets, including yields derived from cross-section data, while resolving a discrepancy between existing thick-target-yield data sets for E α ≈ 4–5 MeV. However, for E α < 3.5 MeV, our results are substantially lower than previous thick-target-yield data and somewhat larger than yields calculated from existing cross-section data. Our data complete the energy range needed for estimates of the 27 Al(α,n) contribution to neutrino and dark matter detector backgrounds and result in increased viability of 27 Al(α,n) as a plasma diagnostic tool at fusion facilities such as the National Ignition Facility.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

OpenMDlr: parallel, open-source tools for general protein structure modeling and refinement from pairwise distances

Easy-to-use, open-source, general-purpose programs for modeling a protein structure from inter-atomic distances are needed for modeling from experimental data and refinement of predicted protein structures. OpenMDlr is an open-source Python package for modeling protein structures from pairwise distances between any atoms, and optionally, dihedral angles. Finally, we provide a user-friendly input format for harnessing modern biomolecular force fields in an easy-to-install package that can efficiently make use of multiple compute cores.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Efficacy and safety of warfarin in patients with non-valvular atrial fibrillation and CKD G3–G5D

ABSTRACT Background Observational data comparing warfarin with no treatment for patients with non-valvular atrial fibrillation (NVAF) and severely reduced glomerular filtration rate (GFR) are conflicting and randomized controlled trials (RCTs) are lacking. Most studies do not provide information on warfarin treatment quality, making them difficult to compare. Methods This national cohort study investigates the risk of ischaemic stroke and major bleeding during warfarin treatment compared with no oral anticoagulants in patients with NVAF, GFR category 3–5 (G3–G5) or on dialysis (G5D), with kidney transplant recipients excluded, between 2009 and 2018. Data extracted from high-quality Swedish national healthcare registries, including the Swedish Renal Registry, AuriculA—the Swedish national quality registry for atrial fibrillation and anticoagulation—and the Stroke Registry. Results At enrolment of 12 106 patients, 21.4% were G3, 43.5% were G4, 11.6% were G5 and 23.6% were G5D. The mean time in the therapeutic range was 70%. Warfarin compared with no treatment showed a lower risk for ischaemic stroke for G3 {hazard ratio [HR] 0.37 [95% confidence interval (CI) 0.18–0.76]}, G4 [0.53 (0.38–0.74)] and G5D [0.49 (0.30–0.79)] and an increased risk of major bleeding in G4 [HR 1.22 (1.02–1.46)], G5 [1.52 (1.15–2.01)] and G5D [1.23 (1.00–1.51)]. All-cause mortality was more than halved on warfarin compared with no treatment in all GFR categories. Conclusions Warfarin treatment is associated with a lower risk of ischaemic stroke for patients with NVAF and G3, G4 and G5D at the cost of a higher risk of major bleeding for G4–G5D. Existing observational data are conflicting, stressing the need for RCTs on warfarin compared with no treatment in G4–G5D. Awaiting RCTs, it seems reasonable to treat selected patients on dialysis and NVAF with warfarin.

Welander, Frida (ORCID:0000000311117215)↗
DOE OSTI2022

First near-threshold measurements of the 13 C($α, n$ 1 ) 16 O reaction for low-background-environment characterization

The modeling of background sources in large volume detection systems requires accurate nuclear cross sections for a variety of reactions. Among the most important are (α,n) on light nuclei, where α particles, up to ≈9 MeV, are produced from the decay of actinides present in trace amounts in detection and structural material. In order to model the neutron energy spectra and production of other secondary particles, the partial cross sections are needed. Yet very little experimental data exists for these partial cross sections because past measurements, hampered by the experimental challenges of neutron detection, have focused mostly on total reaction cross section measurements. Here, in this paper, the partial cross section of the 13 C(α,n 1 ) 16 O reaction is reported for the first time. The measurements were made near the reaction threshold using a high energy resolution helium spectrometer. The measurements show a rapidly increasing cross section, which quickly becomes a significant fraction of the total reaction cross section. Measurements are compared with previous theory estimates and differences of more than an order of magnitude are found. A comparison is made with new total cross section measurements and the current level of consistency is demonstrated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Adaptive Reinforcement Learning (ARL) Control of a Multi-port Resonant Converter in UAV Systems

This study presents an adaptive reinforcement learning (ARL) control framework for a multi-port resonant converter used in hybrid unmanned aerial vehicle (UAV) power systems. The converter integrates high-frequency half-bridge input ports connected to a rectified engine–generator set and a battery energy storage system, along with a semi-bridgeless active rectifier supplying the propulsion load. A deep RL agent is trained to dynamically regulate inter-port phase-shift commands in real time based on flight conditions and load power demand. The ARL controller autonomously identifies phase-shift combinations that maximize conversion efficiency while maintaining stable and coordinated power flow, even under rapidly varying operating scenarios. This data-driven approach eliminates the need for explicit system modeling or extensive manual tuning and enables coordinated control among multiple power ports without inter-port communication. Experimental results validate that the ARL based strategy achieves reliable power sharing and consistently high-efficiency operation across diverse UAV operating conditions.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗
DOE OSTI2025

HexWeather: Hexagonal Spatial Data Aggregation for Weather-Driven Grid Resilience Analysis

Extreme weather accounts for over 8 0 % of major U.S. power outages since 2000, highlighting the need for spatial tools that align weather data with the irregular boundaries of electric infrastructure. This paper introduces HexWeather, a modular, resolution-aware framework for aggregating historical and forecasted weather data using Uber's H3 hexagonal spatial indexing system. Unlike traditional methods that rely on state or county-level grids, HexWeather enables weather analysis across custom geographies such as utility service areas where public datasets are often unavailable or misaligned. Using Open-Meteo data, we evaluate how H3 resolution affects anomaly detection, spatial variability, and forecast uncertainty across three scales: state, county, and utility. Results show that while coarse resolutions suffice for broad trend tracking, finer resolutions are essential for identifying localized variability and operational risks. By applying metrics like Z-score standard deviation and interquartile range, HexWeather quantifies the spatial spread of both historical anomalies and forecasted conditions, allowing users to assess resolution adequacy for each analysis. This framework supports rapid weather data reuse, reproducible anomaly detection, and predictive modeling for infrastructure resilience. By bridging spatial misalignment in traditional datasets and enabling retrospective and forward-looking analysis within the same pipeline, HexWeather lays the groundwork for better post event analysis, outage prediction, and resilience planning.

Morris, Jacob [ORNL]↗
DOE OSTI2022

The future of Earth system prediction: Advances in model-data fusion

Predictions of the Earth system, such as weather forecasts and climate projections, require models informed by observations at many levels. Some methods for integrating models and observations are very systematic and comprehensive (e.g., data assimilation), and some are single purpose and customized (e.g., for model validation). We review current methods and best practices for integrating models and observations. We highlight how future developments can enable advanced heterogeneous observation networks and models to improve predictions of the Earth system (including atmosphere, land surface, oceans, cryosphere, and chemistry) across scales from weather to climate. As the community pushes to develop the next generation of models and data systems, there is a need to take a more holistic, integrated, and coordinated approach to models, observations, and their uncertainties to maximize the benefit for Earth system prediction and impacts on society.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Building water resilience in the face of cascading wildfire risks

Severe wildfire is altering the natural and the built environment and posing risks to environmental and societal health and well-being, including cascading impacts to water systems and built water infrastructure. Research on wildfire-resilient water systems is growing but not keeping pace with the scale and severity of wildfire impacts, despite their intensifying threat. In this study, we evaluate the state of knowledge regarding wildfire-related hazards to water systems. We propose a holistic framework to assess interactions and feedback loops between water quality, quantity, and infrastructure hazards as determinants of post-fire water availability and access. Efforts to address the evolving threat of wildfires to water systems will require more interdisciplinary research on the complex relationships shaping wildfire’s threat to water availability and access. To support this, we need reliable long-term data availability, consistent metrics, greater research in shared contexts, more extensive research beyond the burn area, and multistakeholder collaboration on wildfire risks to water systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

SSRS (Stochastic Soaring Raptor Simulator)

SSRS (Stochastic Soaring Raptor Simulator) is a generalizable, probabilistic, and predictive tool for wind energy developers, ecologists, wildlife managers and industry consultants to estimate the potential for soaring raptors to interact with operating wind turbines, without the need for site-specific data collection. Rapid expansion of wind energy development across the world has exposed the risk of turbine collisions for birds and bats. The risk to obligate soaring raptors such as golden eagles is of particular concern due to their small population and influence on ecological balance. Golden eagles rely heavily on updrafts to subsidize their flight, putting them in direct conflict with operational wind turbines that utilize the same wind resource. Understanding the behavior of soaring raptors with varying atmospheric conditions is crucial for predicting and mitigating the risk of turbine collision. This software contains a predictive movement model that simulates individual flight paths of golden eagles during updraft-subsidized long-distance flight, including migration. For a given set of atmospheric conditions, the model simulates thousands of eagles at turbine-scale spatial resolution (50m) to produce a relative presence density map. The simulated eagles rely on updrafts to pursue uninterrupted directional flight with minimal energy expenditure, following fluid-flow principles. The simulator includes a stochastic model of eagle behavior and a systematic method of accounting for spatiotemporal variations in atmospheric conditions. This framework only requires publicly available atmospheric data to estimate orographic and thermal updrafts, ensuring general usability.

Sandhu, Rimple↗
DOE OSTI2022

Advanced architectures for high-performance quantum networking

As practical quantum networks prepare to serve an ever-expanding number of nodes, there has grown a need for advanced auxiliary classical systems that support the quantum protocols and maintain compatibility with the existing fiber-optic infrastructure. We propose and demonstrate a quantum local area network design that addresses current deployment limitations in timing and security in a scalable fashion using commercial off-the-shelf components. First, we employ White Rabbit switches to synchronize three remote nodes with ultra-low timing jitter, significantly increasing the fidelities of the distributed entangled states over previous work with Global Positioning System clocks. Second, using a parallel quantum key distribution channel, we secure the classical communications needed for instrument control and data management. Therefore, the conventional network that manages our entanglement network is secured using keys generated via an underlying quantum key distribution layer, preserving the integrity of the supporting systems and the relevant data in a future-proof fashion.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

femto-PIXAR: a self-supervised neural network method for reconstructing femtosecond X-ray free electron laser pulses

X-ray Free Electron Lasers (X-FELs) operate in a wide range of lasing configurations for a broad variety of scientific applications at ultrafast time-scales such as structural biology, materials science, and atomic and molecular physics. Shot-by-shot characterization of the X-FEL pulses is crucial for analysis of many experiments as well as tuning the X-FEL performance. However, for the weak pulses found in advanced configurations, e.g. those needed for coherent, two-pulse studies of quantum materials, there is no current method for reliably resolving pulse profiles. Here we show that a physics-based U-net model can reconstruct the individual pulse power profiles for sub-picosecond pulse separation without the need for simulations. Using experimental data from weak X-FEL pulse pairs, we demonstrate we can learn the pulse characteristics on a shot-by-shot basis when conventional methods fail.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Conifer water use patterns in the East River Watershed, Colorado US, based on stable water isotopes and cellulose isotopes

This data package contains a series of datasets aimed at understanding the seasonal origins of water used by the dominant conifer species, Abies lasiocarpa and Picea engelmannii, in the East River Watershed. There is a distinct difference in the stable isotopic ratio of summer rain and snowpack and thus by tracking the isotopic ratio of the xylem water in trees, it is possible to separate when a tree is using snow vs. summer rain. Following typical protocols, we sampled and extracted water from soils in the "Research Meadow" near Gothic, CO within the East River Watershed through the 2016 growing season. The stable isotopic ratio of these waters were then measured. Using values of the isotopic ratio of precipitation and snowpack from that season, we develop a mixing model to show how the trees transitioned from use of snowpack to summer in late July. We extended the information on the seasonal origins of water from 2016 back until 1980 by using measurements of the isotopic ratio of cellulose from trees in the Research Meadow. The isotopic ratio of tree ring cellulose records a signal both of the Vapor Pressure Deficit at the leaf-atmosphere boundary and also the source water for the trees. We concluded from this extended analysis that the trees underwent transitions between periods where snow was the dominant water source and summer rain was the dominant water source. More details on this analysis can be found in the publication: Persistence and Plasticity in Conifer Water Use Strategies. JGR Biogeoscience. DOI 10.1029/2018JG004845. The dataset specifically includes stable isotope measurements of xylem and soil water for Spruce and Fir trees at the Rocky Mountain Biological Lab's Research Meadow as well as snowpack and precipitation stable isotopes from nearby National Atmospheric Deposition Program sites. Associated meteorological data is included, which is needed to understand the source water for the trees based on the cellulose measurements.This dataset was updated in June 2021 also include intra-ring measurements of the d18O and d13C of cellulose these same species of trees at the Ziegler Reservoir site in Snowmass, CO. These are listed as files: "Interglaciald18OCellulose.csv", "Interglaciald13OCellulose.csv" and "Modernd13CCellulose.csv". The intent of these measurements was to assess whether common conifers (abies and picea) had undergone ecophysiological or ecohydrological changes during the last period in Earth's history was warmer than today, i.e. the last Interglacial (116,000 to 130,000 years ago). This site was chosen because it is a location where subfossil wood from this critical warm period was discovered. We measured the d18O and d13C of the subfossil trees following the same protocol as the modern samples which included chemical extraction of cellulose and isotope ratio mass spectrometry. We found that the trees showed little difference in water use efficiency but utilized more summer rain during the interglacial period. This analysis and detailed methods are provided in the following manuscript: Wetter summers mitigated temperature stress on Rocky Mountain forests during the last interglacial warm period which is in revision at GRL but is available as a preprint here: 10.1002/essoar.10506740.2

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Developing Sample Management Tools for the Irradiation Test Area (ITA)

The ITA Data Manager (IDM) has been ported from CERN’s Proton Irradiation Facility (IRRAD), where it was used previously as the IRRAD Data Manager (IDM), in order to meet the data management and sample tracking needs of the Irradiation Test Area (ITA), a newly developed facility at Fermilab (launching Fall 2020) operating under the Fermilab Test Beam Facility.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Cold Testing for Characterization of Oxide Feed Impurities in Support of the ARIES Program

The Advanced Recovery and Integrated Extraction System (ARIES) Program converts surplus plutonium metal components into an oxide powder form and packages the material for final disposition. In support of the ARIES program, over a metric ton (MT) of plutonium has been removed from surplus nuclear weapons since 1998 and packaged for long-term storage in 3013 cans. The oxide production rate is anticipated to increase substantially over the next decade in support of dilute and dispose goals. Analytical chemistry data from destructive analysis of the resulting 70+ blend lots to date has been reported for contaminants in the product oxide. Changes in the Pu product specification for Pu oxide product, induced by a different pit mix, the LANL swap program and processing Alternate (non-Pit Pu) Feed Stock (AFS) metals, will affect the level and the mix of these contaminants in the upcoming years. With these changes in feed material, it will be important to provide fast and efficient measurement of elemental impurities in the oxide to be certain that the process is under control and to monitor the anticipated changes from the historical blend lot data. Non-destructive methods need to be evaluated for the characterization of the plutonium oxide product and the quantification of the impurities at the current and anticipated levels. A feasibility study has begun to investigate the applicability of new spectroscopic methods for oxide impurity characterization. To this end, here we describe the preparation of surrogate materials to support these investigations, and the results of a feasibility study investigating the use of LIBS (Laser Induced Breakdown Spectroscopy) to characterize the surrogate materials as calibration standards.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗