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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A stable atmospheric-pressure plasma for extreme-temperature synthesis

Plasmas can generate ultra-high-temperature reactive environments that can be used for the synthesis and processing of a wide range of materials. However, the limited volume, instability and non-uniformity of plasmas have made it challenging to scalably manufacture bulk, high-temperature materials. Here we present a plasma set-up consisting of a pair of carbon-fibre-tip-enhanced electrodes that enable the generation of a uniform, ultra-high temperature and stable plasma (up to 8,000 K) at atmospheric pressure using a combination of vertically oriented long and short carbon fibres. The long carbon fibres initiate the plasma by micro-spark discharge at a low breakdown voltage, whereas the short carbon fibres coalesce the discharge into a volumetric and stable ultra-high-temperature plasma. As a proof of concept, we used this process to synthesize various extreme materials in seconds, including ultra-high-temperature ceramics (for example, hafnium carbonitride) and refractory metal alloys. Moreover, the carbon-fibre electrodes are highly flexible and can be shaped for various syntheses. In conclusion, this simple and practical plasma technology may help overcome the challenges in high-temperature synthesis and enable large-scale electrified plasma manufacturing powered by renewable electricity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Quantifying mean, variability, and uncertainty in indoor radon exposure in Pennsylvania using random forest and quantile regression forest models

Radon is a naturally occurring radioactive gas that poses a serious health risk as the primary cause of lung cancer in non-smokers. Despite the well-known adverse association with health outcomes, current radon exposure assessments are limited to county-level or average-level estimates, which fail to capture regional variability. This study uses Machine Learning models, including Random Forest (RF) and Quantile Regression Forest (QRF), to estimate the indoor radon concentrations at the ZCTA (Zip code tabulation area)-level and characterize uncertainties in model estimates. Incorporating geological, meteorological, and building-specific data, the models aim to improve radon risk assessment by capturing mean exposure, variability, and extreme concentration levels. Processed radon test data (n = 718,111) were analyzed using average, variability, and quantile prediction methods. Models that estimate the average radon exposure at the ZCTA-level can yield promising model-fit results, but they do not capture the underlying variability of indoor radon exposure within a ZCTA. We utilize volatility analyses to identify characteristics indicative of high variability of indoor radon exposure. We also show that a QRF model can be used to estimate upper quantiles of residential radon exposure, thereby uncovering localized areas of elevated exposure that were not apparent in mean estimates. The results highlighted the need for a deep characterization of exposure risk and show that regions with moderate average exposure levels could still harbor extreme outliers with implications for evaluating health risks. Utilizing multiple radon exposure models allows for a deeper characterization of radon risk within a geographic area and can better identify high-risk areas. The results from this study provide a foundation for developing mitigation strategies and examining associations between radon exposure and health outcomes at fine scales. Future research should extend the geographic scope and incorporate additional environmental risk factors to establish a comprehensive framework for risk assessment.

Lee, Heechan [ORNL]↗
DOE OSTI2023

TRACER-Uncrewed Aircraft System (TRACER-UAS) Field Campaign Report

Convective processes drive the development of clouds across a variety of scales, thereby playing a central role in governing weather and climate globally. These processes help to set the stage for circulations that redistribute heat and moisture throughout the lower atmosphere, and simultaneously develop storms that supply precipitation to regions that depend on such rain events for supporting a variety of societal needs. At the same time, extreme precipitation events can result in localized flooding of low-lying areas, posing hazards to transportation and regional inhabitants, and potentially damaging structures and infrastructure. As a result, there is an inherent need to better understand the drivers and modulators of clouds and precipitation and leverage such understanding to make projections of how these important systems may evolve with a changing climate. With nearly three billion of Earth’s human inhabitants living within 200 km of a shoreline, development of such understanding is particularly important in coastal regimes. Central drivers of convective cloud development and life cycle in coastal environments include synoptic forcing, local meso- and microscale circulation regimes, microphysical evolution, and aerosol properties. Atmospheric boundary layer (ABL) development and its evolution can help drive the formation and organization of convective clouds, which then impart their own controls through dynamic processes related to latent heating and cooling (including cold-pool formation and propagation), three-dimensional radiative effects, and background environmental conditions (Fan et al. 2016). Such clouds have been contributing to record precipitation events in southeast Texas in recent years, relative to the last several decades of data from regional precipitation gauges (Fagnant et al. 2020). The greater Houston urban area has experienced particularly large increases in the frequency of extreme rainfall events, with enhanced intensity of extreme events (stretching of distribution tails) having potentially significant implications for watershed floodplain planning and mapping in greater Houston and Harris County. While the most extreme precipitation events were associated with tropical cyclones (e.g., Tropical Storm Allison and Hurricane Harvey; Blood 2014, Kao et al. 2019), strong thunderstorms can also deliver large amounts of precipitation over the area over relatively short periods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

HydroMINE: Simple, Modular and Scalable (Final Scientific/Technical Report)

Hydromine is a novel extremely versatile solution to hydrokinetics energy generation, where the external water flow facing energy sweeping area (&structure) is completely passive. One or multiple Hydromine units can easily deploy from a multitude of floating or stationary marine structures, opening a multitude of application and use cases. Proposing Hydromine, it was initially found that the concept could easily scale into all of the four areas of ARPA-E SHARKS cases, as well as other applications, this is illustrated in Figure 1. Also, the relatively aggressive cost of energy targets of the program could be met in the conceptual phase.

13 HYDRO ENERGY↗
DOE OSTI2021

Solid-State Welding of the Nanostructured Ferritic Alloy 14YWT Using a Capacitive Discharge Resistance Welding Technique

Joining nanostructured ferritic alloys (NFAs) has proved challenging, as the nano-oxides that provide superior strength, creep resistance, and radiation tolerance at high temperatures tend to agglomerate, redistribute, and coarsen during conventional fusion welding. In this study, capacitive discharge resistance welding (CDRW)—a solid-state variant of resistance welding—was used to join end caps and thin-walled cladding tubes of the NFA 14YWT. The resulting solid-state joints were found to be hermetically sealed and were characterized across the weld region using electron microscopy (macroscopic, microscopic, and nanometer scales) and nanoindentation. Microstructural evolution near the weld line was limited to narrow (~50–200 μm) thermo-mechanically affected zones (TMAZs) and to a reduction in pre-existing component textures. Dispersoid populations (i.e., nano-oxides and larger oxide particles) appeared unchanged by all but the highest energy and power CDRW condition, with this extreme producing only minor nano-oxide coarsening (~2 nm → ~5 nm Ø). Despite a minimal microstructural change, the TMAZs were found to be ~10% softer than the surrounding base material. These findings are considered in terms of past solid-state welding (SSW) efforts—cladding applications and NFA-like materials in particular—and in terms of strengthening mechanisms in NFAs and the potential impacts of localized temperature–strain conditions during SSW.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An Assessment of the Influence of Uncertainty in Temporally Evolving Streamflow Forecasts on Riverine Inundation Modeling

Continental-scale river forecasting platforms forecast streamflow at reaches that can be used as boundary conditions to drive a local-scale flood inundation model. Uncertainty accumulated during this process stems not only from any part of the forecasting chain but can also be caused by the daily variations in weather forcing that keeps evolving as the event advances. This work aims to examine the influence of the evolving forecast streamflow on predicting the maximum inundation for extreme floods. A diagnostic case study was made on the basis of a hindcast of Hurricane Matthew striking the eastern U.S. in 2016. The U.S. National Water Model was one-way coupled to a hydrodynamic inundation model through a developed automated workflow. Although the river forcing has significantly mismatched hydrographs versus observations, the simulated peak water surface elevations and maximum extents were validated to be comparable with the observations, which indicates that the inundation model may not be sensitive to the inherited uncertainty from the weather forcing. Moreover, the uncertainty of the forecast streamflow time series caused only one order of magnitude fewer variations in inundation prediction; this dampening effect may become clearer for extreme events with large areas inundated. In addition, the forecast total volume of stream discharge appears to be an important metric for assessing the performance of river forcing for inundation mapping, as a linear correlation between the total volume and the accuracy of the predicted peak water surface elevation and maximum extent was found, with the coefficients of determination all above 0.8. Extra best-practice experience of running similar operational tasks demonstrated the tradeoff between the cost and accuracy gain.

flood, national water model, RIFT↗
DOE OSTI2020

Peptide Control of Electrocatalyst Surface Environment and Catalyst Structure: A Design Platform to Enable Mechanistic Understanding and Synthesis of Active and Selective N2 Reduction Catalysts

Low-temperature electrochemical ammonia synthesis with heterogeneous catalysts suffers from extremely low Faradaic efficiencies (< 1%). The hydrogen evolution reaction (HER) is predicted and experimentally demonstrated to outcompete the nitrogen reduction reaction (N2RR). Meanwhile, the nitrogenase enzymes found in nature enable selective N2RR at Fe/Mo metal centers. Montoya and co-authors suggest that a successful transition metal N2RR catalyst will deviate from or completely circumvent current linear scaling relationships. We propose an approach where short-chain peptides (3-20 amino acids) will be used to control the local surface environment of catalysts. This peptide-based design strategy will be used to overcome HER selectivity and the limitations of *NxHy adsorbate scaling.

08 HYDROGEN↗
DOE OSTI2020

Case Studies of the Economic Impacts of Power Interruptions and Damage to Electricity System Infrastructure from Extreme Events

The risks of long-duration, widespread interruptions (LDWIs) in electrical power are a concern of U.S. regulators, the electric power industry, and stakeholders. Those responsible for making decisions about increasingly costly investments to prevent such interruptions and to facilitate rapid recovery when they do occur need relevant information on which to base those decisions. Although a number of studies have examined the physical and engineering impacts of extreme weather and other precipitating events on the bulk power system, decision makers evaluating investments in preventive strategies need information on the costs of past power interruptions and the benefits of preventing them in the future. This paper contributes to addressing this need by offering six case studies that detail the economics, at the level of the utility service territory, of power interruptions caused by extreme weather and lasting from a few days to several weeks. These intermediate-duration interruptions have been, and will continue to be, the most common type of major electric power disruption. They are longer than the short-term disruptions addressed in utility reliability planning, but not as long or widespread geographically as the national-scale interruptions with durations of many weeks, months, or longer that have been examined in some recent studies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Air-sea interactions yielding rapid Beaufort Sea ice losses during the 2021 ONR THINICE Pilot Field Campaign

Seasonal sea ice coverage has declined in the Pacific Arctic region. Losses of the ice cover have modified the region’s surface heat and momentum fluxes providing weather systems more direct interaction with the upper ocean. For example, recent cyclones that have passed over these waters have initiated multiple air-sea interactions and have impacted mixed layer depth, wave properties, and sea ice mass budgets due to diabatic and/or advective processes. As a United States Office of Naval Research (ONR) Departmental Research initiative, one key component of the ONR THINICE program was to advance knowledge on Arctic cyclone coupling with the ocean surface, its ice cover, and understand how such coupling can lead to rapid ice loss. Leading up to the primary field campaign in August 2022, a pilot field campaign from 19 August to 13 September 2021 focused in Utqiagvik, Alaska and Longyearbyen, Svalbard was carried out. This period was marked by frequent Arctic cyclones, periods of strong low-level winds, and stints of extreme short-term Beaufort Sea ice area losses. Cyclones traversed these waters much more frequently than usual during this 26-day period, but did not exhibit extreme central pressures indicative of high intensity and impactful storms. Using ERA5 atmospheric reanalysis fields, CERES and AIRS surface flux retrievals, and in situ sensor data collected from ice-tethered profilers and ice mass balance buoys, we highlight air-sea-ice interactions in the Beaufort Sea during and between these cyclones leading up to extreme ice loss events. Our case study analysis is aimed at understanding how Arctic cyclones, including air-sea interactions prompted by their passage over the marginal ice zone, influence the end-of-summer ice conditions and ice loss events. This study provides an example where frequent, yet weak storms drive rather large marginal sea-scale losses albeit with heterogenous sea ice effects at local scales.

Ballinger, Thomas [International Arctic Research C↗
DOE OSTI2022

Exploring the Spatial Relationship Between Demographic Indicators and the Built Environment of a City

In addition to global and regional drivers of urbanization, neighborhood development in urban areas across the United States has been shown to be influenced by various local socio-economic factors. These factors, despite varying across socio-economic groups, have large implications regarding a population’s vulnerability to extreme climate events, including heat waves resulting in adverse health impacts. Additionally, the demographics of an urban area can shape its infrastructural characteristics, causing different populations groups to face varying levels of risks and benefits. As a result, the urban morphology and socio-economic characteristics of a city are deeply intertwined; however, their interactions on a finer scale are not yet fully understood. This research aims to better understand the relationships between various socio-economic factors and the built environment of a city, considering variability in building types, and temperature patterns. This research focuses on the city of Las Vegas, NV, and uses spatial data analysis to understand the correlation between of socio-economic characteristics, building morphology, building characteristics, and temperature data to understand the correlation between these various factors. Results of these research shows there is a distinct pattern of clustering of socio-economic characteristics with the city and there is a distinct correlation between age and cost, socio-economic characteristics, and locations of high heat distribution within the city.

Singh, Ridhima↗
DOE OSTI2022

Thermoplasticity of metallic glasses: Processing and applications

Owing to their extremely low shear viscosity and fragility, bulk metallic glasses (BMGs) are envisioned as new net-shaping material replacing conventionally used crystalline metals for various applications. The first part of this review describes the general technique and kinetics of thermoplastic forming. The second part elaborates on the thermal processing capability of metallic glasses from atomic- to meter-scale. The micro-/nano-structure obtained after various quenching rates followed by temperature, time and heating rate dependent thermoplastic forming is described in the third section. The deformation behavior and flow kinetics of BMGs in terms of composition, mold features, and applied conditions are elaborated in the fourth section. The variation of volume and enthalpy at the supercooled liquid region, strength retention of metallic glasses compared to other conventional metals and alloys, and kinetics of liquid fragility are given in the fifth section. Finite element modeling and molecular dynamics simulations of high-temperature deformation in BMGs are presented in the sixth part. Finally, thermally-formed BMGs used for different applications, including energy, biomedical and micro-optics, are presented in the final part. Altogether, this review provides an overview of shaping capabilities and modifications in the macro-scale properties and short-to-medium range order of BMGs upon thermoplastic forming.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Excited-State Dynamics during Primary C–I Homolysis in Acetyl Iodide Revealed by Ultrafast Core-Level Spectroscopy

In typical carbonyl-containing molecules, bond dissociation events follow initial excitation to $nπ_{C=O}$$^*$ states. However, in acetyl iodide, the iodine atom gives rise to electronic states with mixed $nπ_{C=O}$$^*$ and $nπ_{C–I}$$^*$ character, leading to complex excited-state dynamics, ultimately resulting in dissociation. Using ultrafast extreme ultraviolet (XUV) transient absorption spectroscopy and quantum chemical calculations, we present an investigation of the primary photodissociation dynamics of acetyl iodide via time-resolved spectroscopy of core-to-valence transitions of the I atom after 266 nm excitation. The probed I 4d-to-valence transitions show features that evolve on sub-100-fs time scales, reporting on excited-state wavepacket evolution during dissociation. These features subsequently evolve to yield spectral signatures corresponding to free iodine atoms in their spin–orbit ground and excited states with a branching ratio of 1.1:1 following dissociation of the C–I bond. Calculations of the valence excitation spectrum via equation-of-motion coupled cluster with single and double substitutions (EOM-CCSD) show that initial excited states are of spin-mixed character. From the initially pumped spin-mixed state, we use a combination of time-dependent density functional theory (TDDFT)-driven nonadiabatic ab initio molecular dynamics and EOM-CCSD calculations of the N$_{4,5}$ edge to reveal a sharp inflection point in the transient XUV signal that corresponds to rapid C–I homolysis. Here, by examining the molecular orbitals involved in the core-level excitations at and around this inflection point, we are able to piece together a detailed picture of C–I bond photolysis in which d → σ* transitions give way to d → p excitations as the bond dissociates. We also report theoretical predictions of short-lived, weak 4d → 5d transitions in acetyl iodide, validated by weak bleaching in the experimental transient XUV spectra. This joint experimental–theoretical effort has thus unraveled the detailed electronic structure and dynamics of a strongly spin–orbit coupled system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Downscaling and bias-correction contribute considerable uncertainty to local climate projections in CMIP6

Abstract Efforts to diagnose the risks of a changing climate often rely on downscaled and bias-corrected climate information, making it important to understand the uncertainties and potential biases of this approach. Here, we perform a variance decomposition to partition uncertainty in global climate projections and quantify the relative importance of downscaling and bias-correction. We analyze simple climate metrics such as annual temperature and precipitation averages, as well as several indices of climate extremes. We find that downscaling and bias-correction often contribute substantial uncertainty to local decision-relevant climate outcomes, though our results are strongly heterogeneous across space, time, and climate metrics. Our results can provide guidance to impact modelers and decision-makers regarding the uncertainties associated with downscaling and bias-correction when performing local-scale analyses, as neglecting to account for these uncertainties may risk overconfidence relative to the full range of possible climate futures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Spheroidization of Nd–Fe–B particles

Spherical powders are required for many advanced manufacturing techniques due to their inherent requirement of flowability, either within feed tubes or during powder spreading. As advanced manufacturing of magnets continues to develop, new production methods for feedstocks are also sought. Plasma spheroidization is a high-yield method to produce spherical Nd–Fe–B powders from irregularly shaped particles, with advantages including high throughput and a well-controlled size distribution. Highly spherical Nd–Fe–B powders with large scale production (i.e., kg) have been demonstrated using an inductively coupled thermal plasma system; however, the magnetic properties of the output powder display significant degradation. The coercivity was decreased from the initial 8 kOe (636 kA/m) of the as-received to 0.7 kOe (55 kA/m) for spheroidized powders. Microstructural investigation reveals 6% Nd depletion caused by the extreme temperatures of the plasma, leading to the formation of low-coercivity α-Fe and a subsequent decrease in energy product. In conclusion, post-spheroidization heat treatments with Nd can partially mitigate the coercivity degradation, increasing to 1.7 kOe (135 kA/m), potentially offering a pathway toward spherical powders for a range of applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The rebrightening of a ROSAT -selected tidal disruption event: repeated weak partial disruption flares from a quiescent galaxy?

The ROSAT-selected tidal disruption event (TDE) candidate RX J133157.6-324319.7 (J1331) was detected in 1993 as a bright [0.2–2 keV flux of (1.0 ± 0.1) × 10 -12 erg s -1 cm -2 ], ultra-soft (kT = 0.11 ± 0.03 keV) X-ray flare from a quiescent galaxy (z = 0.051 89). During its fifth all-sky survey (eRASS5) in 2022, Spectrum-Roentgen-Gamma (SRG)/ eROSITA detected the repeated flaring of J1331, where it had rebrightened to an observed 0.2–2 keV flux of (6.0 ± 0.7) × 10 -13 erg s -1 cm -2 , with spectral properties (kT = 0.115 ± 0.007 keV) consistent with the ROSAT-observed flare ~30 yr earlier. In this work, we report on X-ray, ultraviolet, optical, and radio observations of this system. During a pointed XMM observation ~17 d after the eRASS5 detection, J1331 was not detected in the 0.2–2 keV band, constraining the 0.2–2 keV flux to have decayed by a factor of ≳40 over this period. Given the extremely low probability (~5 × 10 -6 ) of observing two independent full TDEs from the same galaxy over a 30 yr period, we consider the variability seen in J1331 to be likely caused by two partial TDEs involving a star on an elliptical orbit around a black hole. J1331-like flares show faster rise and decay time-scales [$\mathcal {O}(\mathrm{d})$] compared to standard TDE candidates, with negligible ongoing accretion at late times post-disruption between outbursts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Meta-virus resource (MetaVR): expanding the frontiers of viral diversity with 24 million uncultivated virus genomes

Viruses are ubiquitous in all environments and impact host metabolism, evolution, and ecology, although our knowledge of their biodiversity is still extremely limited. Viral diversity from genomic and metagenomic datasets has led to an explosion of uncultivated virus genomes (UViGs) and the development of specialized databases to catalog this viral diversity, though many lack comprehensive integration. Here, we introduce meta-virus resource (MetaVR), the successor of the IMG/VR database, designed to overcome previous limitations such as large-scale querying and programmatic access. Drawing on the increase of publicly available genomes and metagenomes, MetaVR significantly expands viral diversity, now comprising 24,435,662 UViGs, a 57.6% increase from its predecessor, organized into over 12 million viral operational taxonomic units. Key enhancements include the integration of curated eukaryotic host information, the integration of protein clusters and predicted structures for comparative studies, and an API for programmatic data access. Furthermore, MetaVR features an updated taxonomic framework based on ICTV release 39, assignment to Baltimore classes, and enhanced host assignment through novel computational tools like iPHoP. These advancements position MetaVR as a unique resource for exploring viral diversity, evolution, and host interactions across diverse environments. MetaVR can be freely accessed at https://www.meta-virome.org/.

Fiamenghi, Mateus B↗
DOE OSTI2020

Ultrasonic Measurements of Temperature Distribution in Extreme Environments: Results of Power Plant Testing

The most hardened insertion sensors do not perform reliably in extreme environmental conditions. We address this problem by developing an ultrasonic thermometry system for the measurements of segmental temperature distributions (MSTD) in solid materials and, specifically, across containments of energy conversion processes. The MSTD approach uses an echogenically segmented ultrasound propagation path, structured to contain engineered or naturally occurring echogenic features. In pulse-echo mode, these features produce a train of echoes in response to an external pulse of ultrasonic excitation created and acquired by a transducer located outside the extreme environment. The delays between the echoes encode the information on the temperature distribution in the corresponding segments of the ultrasonic propagation path, which we use to reconstruct an unknown temperature profile. This note describes the preliminary results and initial experience in applying the developed MSTD ultrasonic thermometry system to the measurements of temperatures in a utility-scale 500MW coal-fired boiler.

John, Mason↗
DOE OSTI2025

Graph-based Simulation Framework for Power Resilience Estimation and Enhancement

The increasing frequency of extreme weather events poses significant risks to power distribution systems, leading to widespread outages and severe economic and social consequences. This paper presents a novel simulation framework for assessing and enhancing the resilience of power distribution networks under such conditions. Resilience is estimated through Monte Carlo simulations, which simulate extreme weather scenarios and evaluate the impact on infrastructure fragility. Due to the proprietary nature of power network topology, a distribution network is synthesized using publicly available data. To generate the weather scenarios, an extreme weather generation method is developed. To enhance resilience, renewable resources such as solar panels and energy storage systems (batteries in this study) are incorporated. A customized Genetic Algorithm is proposed to determine the optimal locations and capacities for solar panels and battery installations, maximizing resilience while balancing cost constraints. Experiment results demonstrate that on a large-scale synthetic distribution network with more than 300,000 nodes and 300,000 edges, the proposed framework can efficiently evaluate the resilience, and enhance the resilience through the installations of distributed energy resources (DERs), providing utilities with valuable insights for community-level power system resilience estimation and enhancement.

Wang, Xuesong [Wayne State Univ., Detroit, MI (Uni↗