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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Accelerating plasma and radiation surface science using transient grating spectroscopy

A facility for the investigation of in situ radiation-materials and plasma-materials interaction is demonstrated with tungsten, using transient grating spectroscopy as a probe of thermal diffusivity and surface acoustic wave speed. Helium plasma exposure at 645 °C to 1.18 × 10 18 cm −2 helium, until the growth of tungsten fuzz, showed an increase in surface acoustic wave speed at the near-surface from 2542 ± 1 m s −1 up to 2565 ± 1 m s −1 , followed by a greater drop to 2499 ± 7 m s −1 . No observable change in thermal diffusivity was present for plasma exposure alone. A separate 10.26 MeV self-ion-irradiation of tungsten to a dose of 7.92 dpa showed a reduction in both thermal diffusivity from 61.4 ± 1.4 mm 2 s −1 to 36.0 ± 0.7 mm 2 s −1 , following trends seen in existing studies, and surface acoustic wave speed from 2647.8 ± 0.6 m s −1 to 2640.0 ± 0.4 m s −1 . Facilities like these are poised to rapidly close critical knowledge gaps regarding the coupled effects of plasma and radiation damage for materials in fusion systems.

Accelerated plasmas↗
DOE OSTI2025

How transparent is graphene? A surface science perspective on remote epitaxy

Remote epitaxy is the synthesis of a single crystalline film on a graphene-covered substrate, where the film adopts epitaxial registry to the substrate as if the graphene is transparent. Despite many exciting applications for flexible electronics, strain engineering, and heterogeneous integration, an understanding of the fundamental synthesis mechanisms remains elusive. Here we offer a perspective on the synthesis mechanisms, focusing on the foundational assumption of graphene transparency. We identify challenges for quantifying the strength of the remote substrate potential that permeates through graphene, and propose Fourier and beating analysis as a bias-free method for decomposing the lattice potential contributions from the substrate, from graphene, and from surface reconstructions, each at different frequencies. We highlight the importance of graphene-induced reconstructions on epitaxial templating, drawing comparison to moiré epitaxy. We highlight the role of the remote potential in tuning surface diffusion and adatom kinetics on graphene, which are crucial for navigating the competition between remote epitaxy and defect-seeded mechanisms like pinhole epitaxy. In light of this weak remote potential, we re-evaluate the current state-of-the-art experimental evidence, highlighting why it remains challenging to experimentally validate a ‘remote’ epitaxy mechanism that cannot be explained by alternatives, such as pinhole-seeded epitaxy or serial van der Waals epitaxy. We end with one experimental example that, to out knowledge, cannot be explained by competing mechanisms: a different long-range epitaxial relationship for GdPtSb films grown on graphene/sapphire, compared to direct epitaxy on sapphire. We suggest for future experiments that directly measure the remote potential and impact of tuneable growth kinetics.

epitaxy↗
DOE OSTI2025

A kinetic-based regularization method for data science applications

We propose a physics-based regularization technique for function learning, inspired by statistical mechanics. By drawing an analogy between optimizing the parameters of an interpolator and minimizing the energy of a system, we introduce corrections that impose constraints on the lower-order moments of the data distribution. This minimizes the discrepancy between the discrete and continuum representations of the data, in turn allowing to access more favorable energy landscapes, thus improving the accuracy of the interpolator. Our approach improves performance in both interpolation and regression tasks, even in high-dimensional spaces. Unlike traditional methods, it does not require empirical parameter tuning, making it particularly effective for handling noisy data. We also show that thanks to its local nature, the method offers computational and memory efficiency advantages over Radial Basis Function interpolators, especially for large datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Expanding Access to Science Participation: A FAIR Framework for Petascale Data Visualization and Analytics

The massive data generated by scientists daily serve as both a major catalyst for new discoveries and innovations, as well as a significant roadblock that restricts access to the data. Here, our paper introduces a new approach to removing Big Data barriers and democratizing access to petascale data for the broader scientific community. Our novel data fabric abstraction layer allows user-friendly querying of scientific information while hiding the complexities of dealing with file systems or cloud services. We enable FAIR (Findable, Accessible, Interoperable, and Reusable) access to datasets such as NASA’s petascale climate datasets. Our paper presents an approach to managing, visualizing, and analyzing petabytes of data within a browser on equipment ranging from the top NASA supercomputer to commodity hardware like a laptop. Our novel data fabric abstraction utilizes state-of-the art progressive compression algorithms and machine-learning insights to power scalable visualization dashboards for petascale data. The result provides users with the ability to identify extreme events or trends dynamically, expanding access to scientific data and further enabling discoveries. We validate our approach by improving the ability of climate scientists to visually explore their data via three fully interactive dashboards. We further validate our approach by deploying the dashboards and simplified training materials in the classroom at a minority-serving institution. These dashboards, released in simplified form to the general public, contribute significantly to a broader push to democratize the access and use of climate data.

Computer science↗
DOE OSTI2024

Are Atmospheric Models Too Cold in the Mountains? The State of Science and Insights from the SAIL Field Campaign

Mountains play an outsized role in water resource availability, and the amount and timing of water they provide depend strongly on temperature. To that end, we ask the question: How well are atmospheric models capturing mountain temperatures? We synthesize results showing that high-resolution, regionally relevant climate models produce 2-m air temperature (T2m) measurements colder than what is observed (a “cold bias”), particularly in snow-covered midlatitude mountain ranges during winter. We find common cold biases in 44 studies across global mountain ranges, including single-model and multimodel ensembles. We explore the factors driving these biases and examine the physical mechanisms, data limitations, and observational uncertainties behind T2m. Our analysis suggests that the biases are genuine and not due to observation sparsity or resolution mismatches. Cold biases occur primarily on mountain peaks and ridges, whereas valleys are often warm biased. Our literature review suggests that increasing model resolution does not clearly mitigate the bias. By analyzing data from the Surface Atmosphere Integrated Field Laboratory (SAIL) field campaign in the Colorado Rocky Mountains, we test various hypotheses related to cold biases and find that local wind circulations, longwave (LW) radiation, and surface-layer parameterizations contribute to the T2m biases in this particular location. We conclude by emphasizing the value of coordinated model evaluation and development efforts in heavily instrumented mountain locations for addressing the root cause(s) of T2m biases and improving predictive understanding of mountain climates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Are Atmospheric Models Too Cold in the Mountains? The State of Science and Insights from the SAIL Field Campaign

Mountains play an outsized role in water resource availability, and the amount and timing of water they provide depend strongly on temperature. To that end, we ask the question: How well are atmospheric models capturing mountain temperatures? We synthesize results showing that high-resolution, regionally relevant climate models produce 2-m air temperature (T2m) measurements colder than what is observed (a “cold bias”), particularly in snow-covered midlatitude mountain ranges during winter. We find common cold biases in 44 studies across global mountain ranges, including single-model and multimodel ensembles. We explore the factors driving these biases and examine the physical mechanisms, data limitations, and observational uncertainties behind T2m. Our analysis suggests that the biases are genuine and not due to observation sparsity or resolution mismatches. Cold biases occur primarily on mountain peaks and ridges, whereas valleys are often warm biased. Our literature review suggests that increasing model resolution does not clearly mitigate the bias. By analyzing data from the Surface Atmosphere Integrated Field Laboratory (SAIL) field campaign in the Colorado Rocky Mountains, we test various hypotheses related to cold biases and find that local wind circulations, longwave (LW) radiation, and surface-layer parameterizations contribute to the T2m biases in this particular location. We conclude by emphasizing the value of coordinated model evaluation and development efforts in heavily instrumented mountain locations for addressing the root cause(s) of T2m biases and improving predictive understanding of mountain climates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Using data-science approaches to unravel insights for enhanced transport of lithium ions in single-ion conducting polymer electrolyte

Solid polymer electrolytes have yet to achieve the an ionic conductivity > 1 mS/cm at room temperature for realistic applications. This target implies the need to reduce the effective energy barriers of ion transport in polymer electrolytes to around 20 kJ/mol. In this work, we combine information extracted from existing experimental results with theoretical calculations to provide insights into ion transport in single-ion conductors (SICs) with a focus on lithium ion SICs. Through the analysis of temperature-dependent ionic conductivity data obtained from the literature, we evaluate different methods of extracting energy barriers for lithium transport. The traditional Arrhenius fit to the temperature-dependent ionic conductivity data indicates that the Meyer-Neldel rule holds for SICs. However, the values of the fitting parameters remain unphysical. Our modified approach based on recent work (Macromolecules, 56, 15, 6051(2023)), which incorporates a fixed pre-exponential factor, reveals that the energy barriers exhibit temperature dependence over a wide range of temperatures. Using this approach, we identify a series of anions leading to the energy barriers less than 30 kJ/mol, which include trifluoromethane sulfonimide (TFSI), fluoromethane sulfonimide (FSI), and boron-based organic anions. In our efforts to design the next generation of anions, which can exhibit the energy barriers less than 20 kJ/mol, we focused on boron-containing SICs, and performed density functional theory (DFT) based calculations to connect the chemical structures via the binding energy of cation (lithium)-anion pairs with the experimentally derived effective energy barriers for ion transport. Not only have we identified a correlation between the binding energy and the energy barriers, but we also propose a strategy to design new boron-based anions by using the correlation. This combined approach involving experiments and theoretical calculations is capable of facilitating the identification of promising new anions, which can exhibit ionic conductivity $> 1$ mS/cm near room temperature, thereby expediting the development of novel superionic single-ion conducting polymer electrolytes. The published datasets include all the temperature-dependent ionic conductivity collected from the literature with literature DOIs, DFT calculated binding energies, and python scripts to analyze data, construct statistical models, and generate plots.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Advanced Fabrication Techniques of Metal Hydrides for Science and Technology Applications (Abbreviated Final Report)

Lithium Hydride (LiH) atomic properties make it an excellent candidate for thermal energy storage, hydrogen storage, and nuclear reactor technology. High Energy Density (HED) experiments on LiH at the National Ignition Facility (NIF) can also provide critical Equation of State (EOS) and Hugoniot data. Density requirements for LiH vary per application and therefore physical and structural requirements for LiH are non-uniform. Historical production of LiH relies on casting processesthat are limited by density and grain-size control, which leads to unfavorable machinable characteristics. LiH manufacturing is further hindered due to its chemical reactivity and propensity to readily react with moisture. This work aimed at exploring advanced fabrication techniques for LiH such as 1) uniaxial powder pressing methods and 2) laser powder bed fusion (L-PBF) additive manufacturing. Uniaxial powder compaction offers advantageous tailorable mechanical and physical properties via density control, and L-PBF can produce net-shaped complex parts with unique microstructure. Uniaxial pressing proved successful in readily producing LiH with density control.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Advanced Fabrication Techniques of Metal Hydrides for Science and Technology Applications (Full Technical Report)

Lithium Hydride (LiH) atomic properties make it an excellent candidate for thermal energy storage, hydrogen storage, and nuclear reactor technology. High Energy Density (HED) experiments on LiH at the National Ignition Facility (NIF) can also provide critical Equation of State (EOS) and Hugoniot data. Density requirements for LiH vary per application and therefore physical and structural requirements for LiH are non-uniform. Historical production of LiH relies on casting processes that are limited by density and grain-size control, which leads to unfavorable machinable characteristics. LiH manufacturing is further hindered due to its chemical reactivity and propensity to readily react with moisture. This work aimed at exploring advanced fabrication techniques for LiH such as 1) uniaxial powder pressing methods and 2) laser powder bed fusion (L-PBF) additive manufacturing. Uniaxial powder compaction offers advantageous tailorable mechanical and physical properties via density control, and L-PBF can produce net-shaped complex parts with unique microstructure. Uniaxial pressing proved successful in readily producing LiH with density control.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Dynamic Mesoscale Materials Science at the Advanced Photon Source [Slides]

We are modernizing our 1980s nuclear deterrent, and moving beyond life extensions (W76, B61, W88) to systems that have more newly (differently) manufactured components (W80, W87). For the first time since the 1980s, we are doing truly new designs (W93) and there will likely be more to respond to emerging deterrence gaps.

36 MATERIALS SCIENCE↗
DOE OSTI2024

NSA Site Science: Use of ARM Observations from Northern Alaska to Evaluate and Improve Prediction Capabilities

The Arctic is warming at a rate nearly double that of the rest of the planet, leading to profound changes in atmospheric, oceanic, and ice processes. The U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) user facility has played a significant role in Arctic research, operating observatories in Alaska's North Slope for over 25 years. These observatories provide a rich, and wide-reaching dataset that offers insight into atmospheric processes in northern Alaska. This report details the results of a nine-year research project (2015–2024) supported by the DOE Atmospheric Systems Research (ASR) program, that leverages data from ARM’s deployment of observing facilities at Utqiaġvik (known as the North Slope of Alaska, or NSA, site) and Oliktok Point, Alaska. The project was conducted in two phases: - Phase 1 (2015–2019): Focused on understanding key atmospheric processes at Oliktok Point, including cloud formation, high-latitude precipitation, aerosol-cloud interactions, and cloud properties. - Phase 2 (2019–2024): Extended the research to the broader North Slope region, using data from both Oliktok Point and Utqiaġvik. Topics explored included surface energy budgets, atmospheric stability, ice nucleation processes, and microphysics in Arctic clouds. The project resulted in numerous research products, including 50 peer-reviewed publications and dissertations, 169 presentations, and 10 data products. These products cover a variety of topics, including: - Cloud Macro- and Microphysical Properties: Arctic clouds play a crucial role in energy transfer, and accurate representation in models is critical. The study explored cloud transitions, ice crystal shapes, and dual-wavelength radar data to understand ice crystal habits and size distributions. - Aerosol Properties and Processes: The team examined aerosol sources in the Arctic, including industrial emissions and natural sources. Observations showed significant spatial gradients in aerosol concentrations due to human activities and wildfire smoke. The influence of aerosols on cloud formation and the surface energy budget was also assessed. - Aerosol-Cloud Interactions: Research revealed that aerosols might suppress cloud ice production, affecting cloud radiative forcing and precipitation. The impact of local industrial emissions on cloud properties was also investigated. - Contextualizing the North Slope of Alaska in the context of the broader Arctic: To understand broader trends, the project evaluated large-scale circulation patterns and the influence of weather systems on the Arctic. Studies indicated that large-scale processes play a significant role in temperature patterns and the timing of snowmelt. - Advancing ARM Observational and Modeling Capabilities: The project developed new radar data products and advanced measurement techniques, including clutter mitigation and drizzle detection. Uncrewed aerial systems (UAS) and tethered balloon systems (TBS) were deployed to gather detailed atmospheric data. Additionally, the project supported 10 early career scientists, providing training and mentorship to undergraduate interns, graduate students, postdoctoral researchers, and early career researchers. These efforts contributed to the advancement of ARM research capabilities and fostered a new generation of scientists skilled in Arctic atmospheric research. Ultimately, this ASR-supported project has provided valuable insights into Arctic atmospheric processes and their broader climate implications. Recommendations for future work include continuing support for long-term observing at Arctic locations to foster additional research, further exploration of aerosol-cloud interactions and the potential impacts of enhanced industrialization of the Arctic, and expanded use of uncrewed systems to gather data in this remote and harsh environment. Additionally, the data products developed by this work, and the data products developed through the ARM infrastructure, leave a treasure-trove of additional information that should be explored for many years to come to gain additional insight into physical processes in the Arctic atmosphere that drive the rapid changes occurring in at high latitudes and their global impact.

58 GEOSCIENCES↗
DOE OSTI2024

Coastal-Urban-Rural Atmospheric Gradient Experiment (CoURAGE) Science Plan

Understanding the mechanisms governing the urban atmospheric environment is critical for informing urban populations regarding the impacts of climate change and associated mitigation and adaptation measures. Earth system (climate and weather) models have not yet been adapted to provide accurate predictions of climate and weather variability within cities, nor do they provide well-tested representations of the impacts of urban systems on the atmospheric environment. These limitations are largely due to limited field data available for testing and development of these models. We will deploy the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s first Mobile Facility (AMF1) to the mid-Atlantic region surrounding the city of Baltimore for the Coast-Urban-Rural Atmospheric Gradient Experiment (CoURAGE). This deployment will create a four-node regional atmospheric observatory network including Baltimore and its three primary surrounding environments – rural, urban, and bay. CoURAGE investigators will study the interactions among the Earth’s surface, the atmospheric boundary layer, aerosols and atmospheric composition, clouds, radiation, and precipitation at each site, and examine how the spatial gradients across the region interact to create the climate conditions in Baltimore. This study will determine the degree to which Baltimore’s atmospheric environment depends on interactive feedbacks in the atmospheric system and the degree to which conditions in Baltimore depend on the surrounding environment. Some topics of interest include how urban land management exacerbates heat waves, the impact of regional mesoscale winds (nocturnal jet, bay breeze) on urban air pollution and cloud cover, and the impact of the urban heat island and aerosol production on heavy precipitation events. Understanding this integrated coast-urban-rural system quantitatively and with good accuracy and precision is critical to informing climate adaptation and mitigation efforts in the city of Baltimore. The understanding gained should be applicable to many similar coastal, mid-latitude urban centers. Another important objective of CoURAGE is to improve the representation of the climate of coastal cities in Earth systems models (ESMs). CoURAGE investigators will use the observations to test current ESMs, identify weaknesses and work towards improved simulations of this complex environment. The ARM core facility will be deployed in the city of Baltimore, complementing the Baltimore Social-Environmental Collaborative (BSEC), a DOE urban integrated field laboratory (UIFL). Ancillary sites will be deployed to rural Maryland northwest of Baltimore, and to the southern end of Kent Island within Chesapeake Bay. The fourth node will be a long-term atmospheric observatory operated in Beltsville, Maryland by Howard University and the Maryland Department of the Environment. Measurements will be conducted for one year, starting in December of 2024. There will be two intensive operational periods (IOPs), one in summer and one in winter, when the ancillary sites will be enhanced with additional balloon launches, tethered balloon system (TBS) operation, and added atmospheric composition measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

2024 OES-Environmental 2024 State of the Science Report, Chapter 1: Marine Renewable Energy and Ocean Energy Systems-Environmental

For many countries, marine renewable energy (MRE) is the most recent entry into their renewable energy portfolio. MRE involves the generation of energy from the movement of seawater including tides, waves, and persistent ocean currents, as well as from the gradients of temperature and salinity in the oceans. Some countries also include energy generation from the open waters of large rivers as part of MRE. Each MRE resource requires a different type of device to harvest that energy, placed in the appropriate portion and depth of the ocean or large river and secured to the seabed either by weight or by anchors. At full scale, these devices are large; Figure 1.1 puts the size of these devices in the context of other technologies and well-known landmarks for scale. The MRE devices generally represent the largest devices available.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

2024 OES-Environmental 2024 State of the Science Report, Chapter 2: Progress in Understanding Environmental Effects of Marine Renewable Energy

Over the past two decades, researchers, in collaboration with the marine renewable energy (MRE) industry and regulatory agencies, have examined the potential effects of MRE, focusing on the stressor-receptor approach to categorize the most significant potential risks for tidal stream, riverine, persistent ocean currents, and wave energy devices (Copping et al. 2024). Recent interest in examining potential effects of ocean thermal energy conversion (OTEC) and salinity gradient energy production has initiated investigations in those areas as well.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

2024 OES-Environmental 2024 State of the Science Report, Chapter 3: Marine Renewable Energy: Stressor-Receptor Interactions

Determining the potential effects of marine renewable energy (MRE) development on the ocean requires consideration of how each component of a tidal, wave, riverine, or other MRE system might affect marine animals, habitats that support marine communities, or processes that make up essential oceanographic and ecological systems. Researchers around the world have been assessing the potential effects of MRE deployments and operations using a variety of instruments, models, analytical methods, and approaches. The most common approach, and the one followed throughout this report, is the framework of stressor-receptor interactions (Boehlert & Gill 2010), where stressors are the components of an MRE device and associated system that may cause stress, injury, or death to a marine animal, habitat, or ecosystem. The receptors are the species, their habitats, and the oceanographic and ecological processes that support them.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

2024 OES-Environmental 2024 State of the Science Report, Chapter 5: Stakeholder Engagement for Marine Renewable Energy

Stakeholder engagement is a critical piece of any new development project that affects public or private interests. Effective, thoughtful engagement and participatory activities early in the planning process of a project can help planners and project developers understand local concerns, adjust designs to avoid negative environmental impacts, select the best site for a project, answer questions, reduce delay, enhance opportunities and benefits, and build support for a project (Cuppen et al. 2016; Portman 2009; Wiersma & DevineWright 2014). On the other hand, cursory or inadequate engagement that is viewed as “checking the box” or tokenism is unlikely to be effective, and can result in project failures, diminished trust, strong opposition, or costly, drawn-out processes (Butcher & MacLennan 2020; Garard & Kowarsch 2017; Gill & Rand 2022; Jolivet & Heiskanen 2010; Pizzi et al. 2021; Sterling et al. 2017).

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

2024 OES-Environmental 2024 State of the Science Report, Chapter 6: Strategies to Aid Consenting Processes for Marine Renewable Energy

While the marine renewable energy (MRE) industry has made positive strides in the past decade, challenges remain that stall forward progress, scaling up, and commercialization. For MRE to provide a viable solution to address the effects of climate change and achieve sustainable development and renewable energy goals, identifying and understanding barriers and opportunities to deployment is key. Barriers to date have included long consenting timelines, costly in-depth baseline data collection and monitoring requirements, and hesitancy in some countries to approve device and array deployments (Copping & Hemery 2020; Kramer et al. 2020). Some of the key drivers behind these barriers are 1) uncertainty about potential effects of MRE on marine animals, habitats, and the environment; 2) lack of familiarity with MRE technologies; or 3) challenges accessing available scientific information (Copping et al. 2020a).

16 TIDAL AND WAVE POWER↗