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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Observation of a Flat and Extended Surface State in a Topological Semimetal

A flat band structure in momentum space is considered key for the realization of novel phenomena. A topological flat band, also known as a drumhead state, is an ideal platform to drive new exotic topological quantum phases. Using angle-resolved photoemission spectroscopy experiments, we reveal the emergence of a highly localized surface state in a topological semimetal BaAl4 and provide its full energy and momentum space topology. We find that the observed surface state is localized in momentum, inside a square-shaped bulk Dirac nodal loop, and in energy, leading to a flat band and a peak in the density of state. These results imply this class of materials as an experimental realization of drumhead surface states and provide an important reference for future studies of the fundamental physics of correlated quantum effects in topological materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Observation of topological Dirac fermions and surface states in superconducting BaSn3

The interplay between topological electronic structure and superconductivity has attracted tremendous research interests recently as they could induce topological superconductivity (TSCs) which may be used to realize topological qubits for quantum computation. Among various TSC candidates, superconducting BaSn 3 (T c ~ 4.4K) has been predicted to be a topological Dirac semimetal (TDS) hosting two pairs of Dirac points along the Γ-A direction. Here, by combining the use of angle-resolved photoemission spectroscopy and ab initio calculations, we identified the predicted topological Dirac fermions and confirmed the TDS nature of the compound. In addition, we observed surface states connecting the Dirac points. Our observations demonstrate BaSn 3 as a superconductor with nontrivial topological electronic structures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

High Carrier Lifetimes in Epitaxial Germanium-Tin/Al(In)As Heterostructures with Variable Tin Compositions

Group IV-based germanium-tin (Ge1-ySny) compositional materials have recently shown great promise for infrared detection, light emission and ultra-low power transistors. High carrier lifetimes are desirable for enhancing the detection limit and efficiency of photodetectors, low threshold current density in lasers, and low tunneling barrier height by lowering defects and dislocations at the heterointerface of a source and a channel. Here, carrier lifetimes in epitaxial germanium (Ge) and variable tin (Sn) compositional Ge1-ySny materials were experimentally determined on GaAs substrates using the contactless microwave photoconductive decay (u-PCD) technique at an excitation wavelength of 1500 nm. Sharp (2 x 2) reflection high energy electron diffraction patterns and low surface roughness were observed from the surface of the Ge0.97Sn0.03 epilayer. X-ray rocking curves from Ge0.97Sn0.03 and Ge0.94Sn0.06 layers demonstrated the pseudomorphic and lattice-matched growth on AlAs and In0.12Al0.88As buffers, respectively, further substantiated by reciprocal space maps and abrupt heterointerfaces evident from the presence of Pendellosung oscillations. High effective carrier lifetimes of 150 ns to 450 ns were measured for Ge1-ySny epilayers as a function of Sn composition, surface roughness, growth temperature, and layer thickness. The observed increase in the carrier lifetime with an increasing Ge layer thickness and a reducing surface roughness, by incorporating Sn, were explained. The enhancement of the carrier lifetime with an increasing Sn concentration was achieved by controlling the defects with lattice-matched Ge0.94Sn0.06/In0.12Al0.88As heterointerfaces or the pseudomorphic growth of Ge0.94Sn0.06 on GaAs. Therefore, our monolithic integration of variable Sn alloy compositional Ge1-ySny materials with high carrier lifetimes opens avenues to realize electronic and optoelectronic devices.

carrier lifetimes↗
DOE OSTI2022

Lifting Condensation Level Height (LCL Height) Value-Added Product Report

The lifting condensation level height (LCL, m) is determined from continuous surface-air observations of relative humidity and temperature as the altitude where the surface-air moisture equals saturation following a dry-adiabatic ascent. Values are computed from surface meteorological observations for 16 facilities belonging to the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility Southern Great Plains (SGP) atmospheric observatory and for 133 Oklahoma Mesonet (OKM) stations. The LCL Height Value-Added Product (VAP) was developed for use by the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) project (Gustafson et al. 2016, 2017, 2018, 2020).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Surface deformation coupled with self-organized pattern on a liquid anode of 1 atm DC glow discharge

Intricate, self-organized plasma structures observed above the surface of a liquid anode of atmospheric DC glow discharge were found to give rise to coherent, organized surface deformation and mechanical wave formation at the plasma–liquid interface. This new phenomenon indicates that the liquid is closely coupled to the plasma by the anode sheath’s electrohydrodynamic (EHD) force. A scientific question then arises: Do surface perturbations, coupled with the nonuniform surface charge distribution, enhance the electric field and induce self-organization? Using the reflective background-oriented schlieren technique, the liquid surface profile under the plasma pattern was measured for the first time. The results show that surface distortions are driven by the repulsive Coulomb force of nonuniform net-negative surface charge acted by the anode sheath field. The impacts of various operating parameters on the patterns and surface waves were examined, revealing the significance of gas heating and liquid charge relaxation time in the pattern formation mechanism. Time-resolved dynamics of a pulsed DC discharge indicated that the surface deformation only appeared after the establishment of plasma patterns. Statistically, the surface wave under the plasma has high wave numbers (8000–16000 m −1 ) and small amplitudes ($<$ 10 µm), generally found in the capillary wave regime. Yet the motion of surface deformations is in tandem with the plasma pattern and exhibits a nondispersive nature of constant phase velocity (0.1–0.4 m s −1 ), suggesting the dominant role of EHD force over the surface tension in the observed surface wave. These results indicate that the deformed liquid surface is driven by the EHD force of the plasma sheath. Although they share a similar geometry, the deformation and wave dynamics of the liquid surface do not stimulate a plasma pattern. Importantly, the complex EHD coupling in the plasma–liquid system raises awareness and new challenges for plasma control engineering, and the quantitative characteristics of the nondispersive surface wave are informative for advancing relevant theory and modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

The Shortwave Cloud-SST Feedback Amplifies Multi-Decadal Pacific Sea Surface Temperature Trends: Implications for Observed Cooling

Climate models struggle to produce sea surface temperature (SST) gradient trends in the tropical Pacific comparable to those seen recently in nature. Here, we find that the magnitude of the cloud-SST feedback in the subtropical Southeast Pacific is correlated across models with the magnitude of Eastern Pacific multi-decadal SST variability. A heat-budget analysis reveals coupling between cloud-radiative effects, circulation, and SST gradients in driving multi-decadal variability in the Eastern Pacific. Using this relationship and observed feedback estimates, we find that internal Eastern Pacific SST variability is underestimated in most models. Adjusting for model bias increases the likelihood of generating a cooling trend at least as large as observations in preindustrial control simulations by ~56% on average. If models underestimate climate “noise,” as our results suggest, this bias should be accounted for when attributing the relative importance of forced versus unforced changes in the climate.

58 GEOSCIENCES↗
DOE OSTI2025

“Godzilla,” the Extreme African Dust Event of June 2020: Origins, Transport, and Impact on Air Quality in the Greater Caribbean Basin

In June 2020, the tropical Atlantic and the Caribbean Basin were affected by a series of African dust outbreaks unprecedented in size and intensity. These events, informally named “Godzilla,” coincided with CALIMA, a large field campaign, offering a rare opportunity to assess the impact of African dust on air quality in the Greater Caribbean Basin. Network measurements of respirable particles (i.e., PM 10 and PM 2.5 ) showed that dust significantly degraded regional air quality and increased the risk to public health in the Caribbean, the southern United States, northern South America, and Central America. CALIMA examined the meteorological context of Godzilla dust events over North Africa and how these conditions might relate to the greatly increased dust emissions and enhanced transport to the Americas. Godzilla was linked to strong pressure anomalies over West Africa, resulting in a large-scale geostrophic wind anomaly at 700 hPa over North Africa. We used surface-based and columnar measurements to test the performance of two frequently used aerosol forecast models: the NASA Goddard Earth Observing System (GEOS) and Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) models. The models showed some skills but differed substantially between their forecasts, suggesting large uncertainties in these forecasts that are critical for issuing early warnings of health-threatening dust events. Our results demonstrate the value of an integrated approach in characterizing the spatial and temporal variability of African dust transport and assessing its impact on regional air quality. Future studies are needed to improve models and to track the long-term changes in dust transport from Africa under a changing climate.

Aerosols/particulates↗
DOE OSTI2022

Three-Dimensional Surface Downwelling Longwave Radiation Clear-Sky Effects in the Upper Colorado River Basin

In complex terrain, non-parallel surfaces receive emitted radiation from adjacent surfaces. Qualitatively, where surface skin temperatures and lower tropospheric temperature and humidity are not uniform, the downwelling longwave radiation (DLR) will be determined not just by radiation from the atmosphere above a given location, but also by adjacent surface temperatures. We quantify this three-dimensional longwave radiative effect over the Upper Colorado River Basin in clear-sky conditions by calculating surface DLR with observed land-surface temperatures from ECOSTRESS. We find that this effect is due to terrain-subtended sky-view and represents ~22% of the surface longwave flux, rising to ~28% and ~24% in the East and Southeast of the Basin, respectively, and can be >50% in extreme cases. The common omission of this effect in atmospheric radiation models leads to an underestimation of DLR in complex terrain, especially at higher elevations, which has significant implications for mountainous ecohydrology simulations.

3-dimensional effects↗
DOE OSTI2020

Exchange bias and quantum anomalous nomalous Hall effect in the MnBi 2 Te 4 /CrI 3 heterostructure

The layered antiferromagnetic MnBi 2 Te 4 films have been proposed to be an intrinsic quantum anomalous Hall (QAH) insulator with a large gap. It is crucial to open a magnetic gap of surface states. However, recent experiments have observed gapless surface states, indicating the absence of out-of-plane surface magnetism, and thus, the quantized Hall resistance can only be achieved at the magnetic field above 6 T. We propose to induce out-of-plane surface magnetism of MnBi 2 Te 4 films via the magnetic proximity with magnetic insulator CrI 3 . A strong exchange bias of ~40 meV originates from the long Cr- e g orbital tails that hybridize strongly with Te p orbitals. By stabilizing surface magnetism, the QAH effect can be realized in the MnBi 2 Te 4 /CrI 3 heterostructure. Moreover, the high–Chern number QAH state can be achieved by controlling external electric gates. Thus, the MnBi 2 Te 4 /CrI 3 heterostructure provides a promising platform to realize the electrically tunable zero-field QAH effect.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Surface Film Formation on Al-V Alloys with Far-From-Equilibrium Microstructure

Nanocrystalline supersaturated Al-V alloys produced by high-energy ball milling have been reported to exhibit enhanced corrosion resistance and mechanical properties compared to commercial Al alloys. Corrosion of passive alloys such as Al-V alloy relies on the characteristics of the surface film, which is studied using scanning/transmission electron microscopy and time-of-flight secondary ion mass spectrometry. The effect of microstructure and composition on the surface film has been investigated after different immersion periods (30 min, 2 h, and 1 day) in 0.1 M NaCl. The surface film was complex and composed of oxidized Al and V. The heterogeneous surface film was observed due to the presence of secondary phases and initiation of localized corrosion. The void formation was observed beneath the surface film that would potentially cause pitting corrosion. The generation of nano-sized voids was dependent on grain orientation. Compared to pure Al, the chloride penetration is suppressed in Al-V alloys. The effect of composition and microstructure on surface film formation and attendant corrosion behavior is discussed herein.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Contrasting Trends in Colorado Fire Weather Index from Reanalysis and Observations

Recent wildfires in Colorado raise the question of whether rising global temperatures have increased fire weather occurrences in Colorado. The U.S. National Weather Service defines fire weather as when “forecast weather conditions will result in a significant threat for the ignition and/or spread of wildfires.” We use two datasets to address the question: “How has the occurrence of fire weather changed in Colorado?” Using 22 years of observed weather conditions from a meteorological tower at the National Renewable Energy Laboratory and 67 years of ERA5 reanalysis data, we assess changing trends in Colorado fire weather as defined by hot, dry, and windy conditions. Additionally, we explore if the difference in recorded wind speeds between observational data and reanalysis data can be explained by differences in spatial and temporal resolution and what are the implications in the context of quantifying fire weather occurrences. The observational data are limited in temporal extent and spatial representativeness, but they capture exact real-world conditions at a location in complex terrain. The reanalysis data are available for an extended period of time and for the entire state, but the data are of relatively coarse spatial and temporal resolution and may fail to capture extremes. To quantify fire risk, we calculate the hot–dry–windy index (HDWI), which relies on wind speed and vapor pressure deficit. No statistically significant trend in the HDWI appears in the observational dataset. However, according to the reanalysis data, strong increasing trends in HDWI values emerge across all of Colorado. This apparent conflict between observational and reanalysis data suggests that reanalysis data may not be representative. Further, more long-term observational datasets are required to assess fire risk.

17 WIND ENERGY↗
DOE OSTI2023

Calibrated Radar Wind Profiler (RWP) Moments

The SGP Central Facility (C1) radar wind profiler (RWP) was calibrated using nearby surface disdrometer observations. Between 2011 and 2019, the SGP C1 RWP operated in two modes. The vertically pointing mode (named the precipitation mode) transmitted a short and long pulse length to have two different range resolutions and the beam-swinging mode (named the wind mode) transmitted one pulse length into three different beam directions. The precipitation-mode observations were available and calibrated from April 2011 through mid-August 2019. The wind-mode observations were available and calibrated between April 2014 and March 2019. The RWP spectra were processed to account for Nyquist velocity aliasing and coherent integration filtering effects before calculating the spectrum moments. During intense precipitation events, the calculated signal-to-noise ratio (SNR) is biased low due to signal power being distributed across the velocity spectrum such that some signal power is erroneously included in the noise level estimate, causing the noise level to be biased high. To correct for the low SNR bias, a new noise level is estimated using observations without precipitation and the SNR is increased accordingly. The adjusted SNR was converted to radar reflectivity factor and then calibrated against a nearby surface disdrometer. The calibration methodology is fully described in: Williams, CR, J Barrio, PE Johnston, P Muradyan, and S Giangrande. 2023. “Calibrating radar wind profiler reflectivity factor using surface disdrometer observations.” Atmospheric Measurement Techniques, https://egusphere.copernicus.org/preprints/2023/egusphere-2022-1405/

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Initial Characterization of the Second A709 Commercial Heat

In fiscal year 2021, Idaho National Laboratory (INL) received the second commercial heat of A709 in the plate-product form, heat 529900. The chemistry, microstructure, and mechanical properties of this heat were characterized. Heat 529900 met the chemistry and mechanical property requirements specified for UNS S31025 in American Society for Testing and Materials (ASTM) A213 and American Society of Mechanical Engineers SA 213 for seamless tube which A709 was derived from. The microstructure of heat 529900 was comprised of equiaxed, recrystallized grains and elongated, unrecrystallized grains. The frequency of the unrecrystallized grains varied across the thickness of the plate with the highest frequency observed at the surface and none observed at the center. The equiaxed grain size of heat 529900 ranged from an ASTM grain size number 4 to an ASTM grain size number 6. The size of the equiaxed grains varied across the thickness of the plate with the coarsest grains located at the center of the plate. Additionally, the creep-fatigue properties of the second commercial heat were better than those of the first commercial heat.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Assessment of CMIP5 and CMIP6 AMIP Simulated Clouds and Surface Shortwave Radiation Using ARM Observations over Different Climate Regions

The simulations of clouds and surface radiation from 10 CMIP6 models and their CMIP5 predecessors are compared to the ARM ground-based observations over different climate regions. Compared to the ARM radar-lidar derived total cloud fractions (CFT) and cloud fraction vertical distributions over the six selected sites, both CMIP5 and CMIP6 significantly underestimated CFT and low-level CF over the Northern Hemispheric midlatitude sites (SGPC1 and ENAC1), although the biases are generally smaller in CMIP6. Over the tropical oceanic site (TWPC2), 5 out of 10 CMIP6 models better simulated low-level CF than their CMIP5 predecessors. CMIP6 simulations generally agreed well with the ARM observations in CFT and cloud fraction vertical distributions over the tropical continental (MAOM1) and coastal (TWPC3) sites but missed the transitions between dry and wet seasons, similar to CMIP5 simulations. The improvements in downwelling shortwave fluxes (SWdn) at the surface from the majority of CMIP6 compared to CMIP5 primarily resulted from the improved cloud fraction simulations, especially over the SGPC1, ENAC1, and TWPC3 sites. By contrast, both CMIP5 and CMIP6 models exhibited diverse performances of clouds and shortwave radiation over the Arctic site (NSAC1), where CMIP6 models produced more clouds than CMIP5 models, especially for the low-level clouds. The comparisons between observations and CMIP5 and CMIP6 simulations provide valuable quantitative assessments of the accuracy of mean states and variabilities in the model simulations and shed light on general directions to improve climate models in different regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A Hybrid Biophysical‐Machine Learning Framework for Diurnal Surface Energy Flux Estimation Using Proximal Sensing

Thermal infrared-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy ( LE ) and sensible heat ( H ) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal infrared data sets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of a ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R 2 = 0.81–0.94) and H (R 2 = 0.46–0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical-machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.

evapotranspiration↗
DOE OSTI2026

Data for: A hybrid biophysical-machine learning framework for diurnal surface energy flux estimation using proximal sensing

Thermal-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy (LE) and sensible heat (H) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal datasets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for specific surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of an ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R2 = 0.81-0.94) and H (R2 = 0.46-0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical – machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.

Agricultural Sciences↗
DOE OSTI2024

Urbanization exacerbates continental- to regional-scale warming

Urbanization is usually ignored when estimating past changes in large-scale climate and for future climate projections since cities historically covered a small fraction of the Earth’s surface. Here, by combining global land surface temperature observations with historical estimates of urban area, we demonstrate that the urban contribution to continental- to regional-scale warming has become non-negligible, especially for rapidly urbanizing regions and countries in Asia. Consequently, expected urban expansion over the next century suggests further increased urban influence on large-scale surface climate in the future (approximately 0.16 K for North America and Europe for high-emission scenario in 2100). Based on these results, also seen for air temperature, we argue that, in line with other forms of land use/land cover change, urbanization should be explicitly included in climate change assessments. This requires incorporation of dynamic urban extent and biophysics in current-generation Earth system models to quantify potential urban feedback on the climate system across scales.

Chakraborty, TC↗
DOE OSTI2023

Designing an Observing System to Study the Surface Biology and Geology (SBG) of the Earth in the 2020s

Abstract Observations of planet Earth from space are a critical resource for science and society. Satellite measurements represent very large investments and United States (US) agencies organize their effort to maximize the return on that investment. The US National Research Council conducts a survey of Earth science and applications to prioritize observations for the coming decade. The most recent survey prioritized a visible to shortwave infrared imaging spectrometer and a multispectral thermal infrared imager to meet a range of needs for studying Surface Biology and Geology (SBG). SBG will be the premier integrated observatory for observing the emerging impacts of climate change by characterizing the diversity of plant life and resolving chemical and physiological signatures. It will address wildfire risk, behavior, and recovery as well as responses to hazards such as oil spills, toxic minerals in minelands, harmful algal blooms, landslides, and other geological hazards. The SBG team analyzed needed instrument characteristics (spatial, temporal, and spectral resolutions, measurement uncertainty) and assessed the cost, mass, power, volume, and risk of different architectures. We present an overview of the Research and Applications trade‐study analysis of algorithms, calibration and validation needs, and societal applications with specifics of substudies detailed in other articles in this special collection. We provide a value framework to converge from hundreds down to three candidate architectures recommended for development. The analysis identified valuable opportunities for international collaboration to increase the revisit frequency, adding value for all partners, leading to a clear measurement strategy for an observing system architecture.

54 ENVIRONMENTAL SCIENCES↗