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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Phase II Final Technical Report: Dynamic Gamma-ray Imaging for In Vivo Tracking of Microelement Transport Across Plant-Microbial Systems

The Department of Energy Office of Biological and Environmental Research (DOE BER) Mesoscale to Molecules Bioimaging Technology Program aims to develop new imaging and measurement technology to enable in situ and dynamic imaging across a range of spatial and temporal scales. Various imaging modalities are required to span the complete spatiotemporal landscape for bioenergy and environmental bioimaging needs. The high-resolution gamma-ray spectroscopy, imaging, and sensitivity of new high-purity germanium (HPGe) instruments provide a unique opportunity to complement and enhance these research goals. The HPGe-based Gamma-ray Imager for Plant Research (GIPR) developed here provides non-invasive, in vivo measurements to dynamically track the uptake and distribution of multiple gamma-emitting radioactive elements simultaneously as they move from the soil microbiome into living plants. The hand portable GIPR utilizes commercially available radioisotopes to provide spatial and temporal imaging of plant microelement exchange for the broader scientific community.

Kiser, Matthew↗
DOE OSTI2025

Developing New Fuels for High Performance Research Reactors

The National Nuclear Security Administration (NNSA) Material Management and Minimization (M3) program works globally to minimize the civilian use of highly enriched uranium (HEU), a weapon-usable nuclear material. Supporting this effort, M3’s Office of Reactor Conversion and Uranium Supply is developing new fuels capable of converting research reactors from HEU fuel to high-assay low-enriched uranium (HALEU) fuel. Some of the remaining research and test reactors (RTRs) operating on HEU today have unique designs, fuel configurations, and demanding performance requirements that cannot be met with an existing regulatory-approved low-enriched uranium (LEU) fuel. M3, DOE’s national laboratories, and other industry partners are qualifying new high-density LEU fuels to convert these RTRs while maintaining their unique capabilities supporting a wide variety of science and technology research in areas such as medicine, industry, defense, education, and training. Current efforts are focused on two options for the remaining US high-performance research reactor conversions: a monolithic uranium 10wt% molybdenum (U-10Mo) fuel form and a dispersion uranium silicide fuel form. This paper reviews the history and status of M3’s fuel qualification efforts for the U-10Mo LEU fuel form.

Montgomery, Rose [ORNL] (ORCID:0000000286038936)↗
DOE OSTI2024

SRNL Nuclear Material Management Strategy

Savannah River National Laboratory (SRNL) is a multidisciplinary laboratory located on the Savannah River Site (SRS) that specializes in applying state-of-the-art science to provide practical solutions to complex technical problems. In 2021 SRNL went through a contract transition to become an independent Federally Funded Research and Development center which kicked off a period of rapid growth in research and an increased demand for the limited nuclear material capacity. A systematic process was developed for analyzing nuclear material holdings to optimize retention and streamline efforts to disposition legacy material without jeopardizing program execution. This process focused on utilizing the expertise of researchers to identify materials for disposition and retention while creating the visibility of tracking metrics for management to monitor material utilization. This resulted in a ~20% reduction in the powder Material At Risk (MAR) and identified additional candidates that could reduce transuranic holdings by an additional ~30% without endangering future program growth.

Ramsey, Catherine M.↗
DOE OSTI2024

Fusion Energy Sciences Network Requirements Review: Mild-cycle Update

The US Department of Energy (DOE) Office of Science (SC) world-class research infrastructure provides the research community with premier observational, experimental, computational, and network capabilities. Each user facility is designed to provide unique capabilities to advance core DOE mission science for its sponsor SC program and to stimulate a rich discovery and innovation ecosystem. Research communities gather and flourish around each user facility, bringing together diverse perspectives. The continual reinvention of the practice of science — as users and staff forge novel approaches expressed in research workflows — unlocks new discoveries and propels scientific progress.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Augmented Reality Technologies for Radiation Safety Training: A Systematic Review of Sensor Integration and Visualization Approaches

This paper presents a comprehensive systematic review examining the application of augmented reality (AR) and sensor technologies for visualizing ionizing radiation in virtual training environments. The review methodology involved systematic identification and analysis of the relevant literature based on predetermined criteria including publication type, year of publication, application domain, and technological approach. The literature search encompassed publications from 2011 to 2021 across four major academic databases: Web of Science, Google Scholar, IEEE Xplore, and Scopus. Through rigorous screening following PRISMA 2020 guidelines, 23 research articles met the inclusion criteria for detailed analysis. From 404 initial database records, 360 were excluded during title/abstract screening (primarily for lacking AR components, radiation focus, or training applications) and 4 during full-text assessment (all for lacking sensor integration). The findings reveal that AR-based ionizing radiation visualization has been successfully implemented across diverse domains, including nuclear facility operations, medical procedures, CERN research activities, and educational and monitoring applications. The analysis identified multiple dimensions of impact, encompassing distinct benefits, emerging opportunities, and implementation challenges associated with AR deployment for ionizing radiation training. Each of these dimensions is comprehensively examined and documented within this review. Additionally, this study identifies critical research gaps that currently limit the full potential of AR technology in supporting ionizing radiation training programs. These gaps are systematically analyzed and discussed to establish clear directions for future research endeavors in this emerging field.

61 - RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2026

Brochure for the DOE Office of Science Workshop on Envisioning Frontiers in AI and Computing for Biological Research

In February of 2025 a joint ASCR/BER workshop was held to identify key transformational research directions for understanding biology using artificial intelligence (AI), digital twins and high-performance (HPC) computational methods to facilitate scientific discovery and innovation in support of the Department of Energy mission. AI technologies offer exciting new groundbreaking methods to analyze large volumes of complex biological data, thereby greatly accelerating the ability to understand, predict, and design biological processes for beneficial purposes. In the laboratory, the bridging of AI-enabled automated experimental technologies, HPC and digital twins will provide potent tools for researchers to explore the fundamental nature of biology and harness its inherent metabolic potential for a variety of beneficial purposes. The focus of this workshop was on how high-performance computational methods can impact this objective by exploring digital twins, foundational models, and data-driven approaches with applications to advance automated laboratory experiments, modeling of complex living systems and engineering new functions into plants and microbial systems relevant to DOE mission. Workshop attendees with expertise in plant science, microbiology, mathematics, computer science, and AI assessed the current state of the science, trends, and AI challenges at the interface of plant and microbial systems biology and computational science to identify opportunities for high-impact research. This collaborative effort capitalized on ASCR's advancements in applied mathematics, computer science, and Exascale systems, and BER's expertise in basic genomics-enabled research on DOE relevant plant and microbial systems. The workshop culminated in four key priority research directions to guide future research and development within DOE Office of Science programs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Type 1 Diabetes Genetic Risk in 109,954 Veterans With Adult-Onset Diabetes: The Million Veteran Program (MVP)

OBJECTIVE To characterize high type 1 diabetes (T1D) genetic risk in a population where type 2 diabetes (T2D) predominates. RESEARCH DESIGN AND METHODS Characteristics typically associated with T1D were assessed in 109,594 Million Veteran Program participants with adult-onset diabetes, 2011–2021, who had T1D genetic risk scores (GRS) defined as low (0 to <45%), medium (45 to <90%), high (90 to <95%), or highest (≥95%). RESULTS T1D characteristics increased progressively with higher genetic risk (P < 0.001 for trend). A GRS ≥90% was more common with diabetes diagnoses before age 40 years, but 95% of those participants were diagnosed at age ≥40 years, and their characteristics resembled those of individuals with T2D in mean age (64.3 years) and BMI (32.3 kg/m2). Compared with the low-risk group, the highest-risk group was more likely to have diabetic ketoacidosis (low GRS 0.9% vs. highest GRS 3.7%), hypoglycemia prompting emergency visits (3.7% vs. 5.8%), outpatient plasma glucose <50 mg/dL (7.5% vs. 13.4%), a shorter median time to start insulin (3.5 vs. 1.4 years), use of a T1D diagnostic code (16.3% vs. 28.1%), low C-peptide levels if tested (1.8% vs. 32.4%), and glutamic acid decarboxylase antibodies (6.9% vs. 45.2%), all P < 0.001. CONCLUSIONS Characteristics associated with T1D were increased with higher genetic risk, and especially with the top 10% of risk. However, the age and BMI of those participants resemble those of people with T2D, and a substantial proportion did not have diagnostic testing or use of T1D diagnostic codes. T1D genetic screening could be used to aid identification of adult-onset T1D in settings in which T2D predominates.

Yang, Peter K. (ORCID:0000000193796981)↗
DOE OSTI2026

Daily evapotranspiration changes during heatwaves at 32 NEON sites, 2019-2021

This dataset provides partitioned evapotranspiration (ET, the combined loss of water from soil and plant surfaces) anomalies during heatwave events—soil evaporation (E) and transpiration (T)—for 268 heatwave events across 32 National Ecological Observatory Network (NEON) flux sites in the contiguous United States from 2019–2021. Using an ensemble of four high-frequency turbulence methods (Flux-variance Similarity, Conditional Eddy Covariance [CEC], CEC with Water-Use Efficiency, and Conditional Eddy Accumulation; see Zahn and Bou-Zeid 2024), half-hourly transpiration-to-evapotranspiration (T/ET) ratios were derived from 20 hertz (Hz, cycles per second) eddy covariance measurements of carbon dioxide (CO₂) and water vapor (H₂O) concentrations. The dataset spans six vegetation types including evergreen and deciduous forests, grasslands, cultivated crops, shrublands, and emergent herbaceous wetlands. Data Package Contents: The dataset includes a single CSV (comma-separated values) file containing daily anomalies (deviations from baseline conditions) for transpiration (Delta_T), evaporation (Delta_E), total evapotranspiration (Delta_ET), and T/ET ratio (Delta_T_ET) during each day of identified heatwave events. The file also includes site codes, dates, heatwave event identifiers, and day-of-heatwave indicators. The CSV file can be opened with spreadsheet software (Microsoft Excel, Google Sheets) or programming environments (Python, R, MATLAB). This resource enables researchers to investigate ecosystem-specific responses to thermal extremes, validate land surface model partitioning of ET fluxes, and examine feedbacks between water cycling and surface energy balance during heatwaves. The dataset is particularly valuable for studies linking vegetation hydraulic strategies to climate resilience, as it captures the divergent responses of shallow-rooted versus deep-rooted ecosystems. Potential applications include improving drought early warning systems, informing irrigation management strategies, and advancing our mechanistic understanding of land-atmosphere interactions under extreme heat conditions.

Day of Heatwave↗
DOE OSTI2024

Rattlesnake User's Manual (V.3)

Rattlesnake is a combined-environments, multiple input/multiple output control system for dynamic excitation of structures under test. It provides capabilities to control multiple responses on the part using multiple exciters using various control strategies. Rattlesnake is written in the Python programming language to facilitate multiple input/multiple output vibration research by allowing users to prescribe custom control laws to the controller. Rattlesnake can target multiple hardware devices, or even perform synthetic control to simulate a test virtually. Rattlesnake has been used to execute control problems with up to 200 response channels and 24 shaker drives. This document describes the functionality, architecture, and usage of the Rattlesnake controller to perform combined environments testing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

An Approach to Shared Research Systems

World-leading research requires state-of-the-art systems for research and innovation. Operational excellence is the key component of scientific excellence by implementing ubiquitous security, repeatable processes, streamlined policies, and reliable and robust infrastructure. Building a research environment to meet these needs is a complex and expensive task. In many cases, it can be financially advantageous for one or more programs, projects, and/or stakeholder(s) to pool resources to build a shared research system to meet common goals. However, such a system brings some unique challenges that need to be addressed. This document describes the process to mitigate these challenges by documenting how the interested parties contribute to the overall success of the system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Practical Probabilistic Programming

Recent advances in probabilistic programming languages (PPLs) have provided the capability for exact inference: computing a closed-form probability distribution for a given probabilistic program. In particular, the new language Roulette uses a language oriented programming (LOP) approach, wherein analysts build new programming languages on top of a set of primitives provided by Roulette, which then translates these structures into a weighted model counting problem which can be solved by automated reasoning tools. However, because Roulette provides few convenience features, developing these new languages is challenging even for expert users. We developed a standard library of common probability functions for Roulette with the goal of improved usability. This included approximation of continuous probability density functions using discrete probability mass functions. We demonstrated this approach by modeling a cosmic ray striking a RAM controller. We found that Roulette provides a powerful interface for highly expressive probabilistic programs to be generated. In collaboration with the NNSA Advanced Simulation and Computing program, which resulted in development of a tool called Circulette, we were able to model complex circuits expressed in Verilog using probabilistic programs with an expressivity not previously possible. Our research question that motivated the development of a Roulette standard library was to determine whether non-experts could use a PPL to model relevant problems regarding radiation effects on microelectronics. This standard library improved the expressivity of Roulette by implementing common probability density functions, mathematical operators on distributions, and support for empirical distributions. While Roulette is a powerful modeling language, the untyped, LOP approach makes error messages difficult to understand and requires expert aid. We recommend further research on Roulette, especially with its error messages, to enable improved usability. At the same time, this project demonstrated that for users familiar with Roulette and the LOP approach, Roulette provides powerful new capabilities that can be integrated with other Sandia modeling capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Event Classifications on DNE2 Main Experiment Data using a Convolutional Neural Network Ensemble

The Dynamic Networks (DN) Experiment for FY24 (DNE2) is an experiment within DN with the goal of quantitatively evaluating the effectiveness of solutions developed so far by various researchers under the Low Yield Nuclear Monitoring (LYNM) program using a shared set of metrics and datasets. A key component of this experiment is the mimicking of a signature processing pipeline, and comparing currently accepted and standard-use processing methods to more state-of-the-art processes developed under DN. In this work, we focus specifically on the Event Characterization (EC) Focus Area (FA) of the pipeline, where a seismic event’s magnitude, yield and class are identified. We use Deep Learning (DL) to classify the type of events being processed as either earthquakes (EQs) or explosions (EXs) for three iterations of experiment datasets. The model is noticeably more confident and accurate in classifying explosions than earthquakes, reflecting a known shortcoming of the model, that being of a bias towards predicting explosions over earthquakes in the west coast due to training data biases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

NorthWest Cleantech Innovation Network

To help overcome these barriers for clean tech/climate tech entrepreneurs in the Pacific Northwest, the Northwest Cleantech Innovation Network (NWCIN) was established in October 2021 with support from the Department of Energy. Launched as a consortium of three organizations: VertueLab, the CleanTech Alliance (CTA) and University of Washington Clean Energy Testbeds (WCET), the NWCIN successfully leveraged the strengths and expertise of each organization to deliver four assistance programs: Cascadia Cleantech Accelerator (CCA), an 18-week yearly cohort-based virtual program providing business and technical mentorship Lab2Launch (L2L), a program to educate and connect entrepreneurs to regional research institution resources and technologies available to license Federal Funding Assistance (FFA), to provide support to companies from Washington, Oregon, Idaho and Alaska that are applying for SBIR/STTR and other federal grants Cleantech Hardware Innovation Prototyping (CHIP) to provide access to facilities and lab/office space at the Washington

25 ENERGY STORAGE↗
DOE OSTI2024

Instrumentation for the In-Core Real-Time Mechanical Testing of Structural Materials (INCREASE) Project

Idaho National Laboratory (INL), in collaboration with the Electric Power Research Institute (EPRI), the Nuclear Regulatory Commission (NRC), the French Atomic and Alternative Energies Commission (CEA), the Joint Research Center (JRC), the Nuclear Research and Consultancy Group (NRG), and the Research Center Rez (CVR), started a Joint Experimental Program (JEEP) project that operates within the Nuclear Energy Agency’s Framework for Irradiation Experiments (FIDES II) program in order to develop capabilities for the in-core real-time mechanical testing of structural materials. This effort will focus on designing a shared capsule capable of housing a variety of in-core mechanical testing instrumentation allowing enhanced experiments for the material science community. The outcome of the project would be high-priority, stress relaxation data for stainless-steel-based materials provided by EPRI and CEA. Stress relaxation is a major phenomenon that contributes to material degradation in nuclear reactor components. Currently, nuclear material stress relaxation is assessed both before and after irradiation, using complex and costly post-irradiation examination (PIE) activities. In-situ data would support the development of precision modeling and simulation of this degradation phenomena and would provide validation and benchmarking for existing models using the PIE data. As part of the U.S. Department of Energy Advanced Sensor and Instrumentation (ASI) program, INL has fabricated and tested out-of-core mechanical test instrumentation. This instrumentation was designed for easy adaptation to the irradiation capsule proposed under this JEEP, and can be deployed to measure real-time stress relaxation under pressurized-water reactor (PWR) conditions. This initial effort will partially serve to replace the testing capabilities lost because of shutting down the Halden Boiling Water Reactor (HBWR). The project would provide these capabilities to the international community via a shared capsule design that is easily adaptable to additional material test reactors. The design features will incorporate expansion to PWR and non-light-water reactor (LWR) environments that will be developed in future work. The capsule and instrumentation will be demonstrated in the Massachusetts Institute of Technology Reactor (MITR) for phase I and the Petten High Flux Reactor (HFR) for phase II irradiations to deliver real-time stress relaxation data on high priority stainless steel structural materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

IBR Digital Supply Chain Gap Analysis and Recommendations

The adoption of clean energy technologies, including solar photovoltaics, continues to introduce non-traditional stakeholders to the operations and planning of the electric system. Stakeholders such as manufacturers, vendors, owners, aggregators, and others are enabling the adoption, integration, and optimum operations of solar technologies at accelerated rates. Inverters form the foundation of many digitally controlled energy sources for clean energy technologies, including Solar, Battery Energy Storage Systems, Hybrid Systems, and Hydrogen Fuel Cells. Their supply chain is complex, a series of microchips, electronic switches and other components making up its primary functions. The complexity of this space and the growing digitization associated with these components can create supply chain cyber risks. One measure to mitigate cybersecurity attacks is proper digital supply chain security. The U.S. Department of Energy (DOE) Solar Energy Technologies Office (SETO), in partnership with the Cybersecurity, Energy, Security, and Emergency Response (CESER) office, is hosting a workshop to bring together solar vendors and services providers to discuss digital supply chain security for solar systems and challenges and opportunities in the transitioning to a fully domestic supply chain for solar energy in the U.S. This workshop will support the Securing Solar for the Grid (S2G) and Energy Cyber Sense program activities. During the workshop, industry experts and researchers from DOE National Laboratories will discuss the current solar supply chain landscape and the transition to domestic manufacturing of solar components in the U.S. Tools and techniques to better manage and secure the digital supply chain of solar devices and systems will be discussed.

cybersecurity↗
DOE OSTI2025

Open Energy Data Initiative (OEDI) FY22-24 (Final Technical Report)

Final technical report for the Open Energy Data Initiative (OEDI) project covering fiscal years FY22 through FY24. The DOE Open Energy Data Initiative (OEDI) is a partnership between the National Renewable Energy Laboratory (NREL), the U.S. Department of Energy (DOE), and major cloud providers including Amazon, Microsoft, and Google to provide universal access to big data in the cloud. At the heart of OEDI is a centralized repository of high-value energy research datasets aggregated from the U.S. Department of Energy's Program Offices, National Laboratories and other collaborators. It aggregates smaller, domain-specific repositories, allows direct data submissions, and includes support for big data through its energy data lakes. OEDI's data lakes make high-value data universally accessible and help researchers, collaborators and the general public overcome many of the obstacles to accessing and using big data.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Physics Flash: Summer 2024

Each year, the Lab’s Partnerships and Pipeline Office's Postdoc Program honors outstanding efforts made by postdocs and mentors that have led to a positive impact on the Lab and its missions. For such contributions, Applied and Fundamental Physics (P-2) researchers David Rivera and Sowjanya Gollapinni have been recognized by the program.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Best Practices for Equitable Solar Workforce Development

The Midwest Renewable Energy Association (MREA) was selected to serve as a lead organization for the U.S. Department of Energy Solar Energy Technology Office’s Equitable Solar Communities of Practice initiative. This project, facilitated through a partnership with ENERGYWERX, aimed to develop strategies to support the expansion of equitable benefits in solar adoption across the U.S. Specifically, the MREA was chosen to lead the solar workforce development community of practice, focusing on scaling the U.S. solar workforce, to meet growing industry demands and ensure that these opportunities are accessible and beneficial to all communities. For the purpose of this initiative, we define the solar workforce in line with the National Solar Jobs Census, which defines a solar worker as someone who spends a majority of their time on solar-related work. This also includes workers who spend a plurality of their time on solar tasks. It’s important to note that manufacturing jobs were not included in this research, as the focus is primarily on solar installation, development, and related roles. To achieve the goals of the Equitable Solar Communities of Practice initiative, the MREA leveraged existing resources and engaged a diverse core team and group of stakeholders including industry professionals, educators, policymakers, and community leaders. The MREA began with a literature review and gap analysis to identify existing best practices and gaps in the solar workforce. This was followed by a community convening to gather insights from a wide range of stakeholders. The findings informed the best practices and pathways to scale the benefits of solar workforce development, focusing on training programs, workforce services, apprenticeship, and justice, inclusion, and sustainability. This report outlines the background, methodology, findings, and conclusions drawn from the landscape and gap analysis, providing valuable insights into workforce needs and training program capacities across the U.S. The outcomes of this research are presented in this report and contain recommendations for optimizing workforce development and training funding to support the equitable growth of the solar industry, ensuring that the transition to solar energy is inclusive and beneficial for all communities.

14 SOLAR ENERGY↗