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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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374 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Binary pseudo-random array standard for extreme ultraviolet lithography tool characterization

Extreme ultraviolet (EUV) imaging tools play a crucial role in EUV lithography. Achieving high accuracy in EUV metrology is essential for advanced semiconductor manufacturing. A thorough characterization of the instrumentation in use is required. Binary pseudo-random arrays (BPRAs) are an established standard for calibrating and characterizing optical instruments in the frequency domain. Here, we expand the BPRA standard to applications in EUV imaging. To extend the technology to the EUV spectral range, a high-resolution BPRA target with the smallest feature size of 40 nm is developed. The EUV BPRA target establishes an in situ and portable calibration and alignment standard for EUV imaging. The target is patterned by means of electron-beam lithography, using a nickel absorber with a thickness of 39 nm. The substrate is a 4″ silicon wafer with a molybdenum/silicon multilayer coating. To demonstrate the efficacy of the target and develop the instrument calibration protocol, the target is imaged on the Sharp Hyper-NA Actinic Reticle Review Project EUV mask microscope. Power spectral density (PSD) data are presented. The characteristics of the imaging system are imprinted on the PSD. The modulation transfer function is extracted from the PSD data. A partially coherent imaging model is used as a reference to the experimental results.

BPRA↗
DOE OSTI2024

Trends and meteorological drivers of extreme daily reservoir evaporation events in the western United States

Extreme daily evaporation from reservoir surfaces can lead to significant short-term water losses, affecting water quality, water supply, and reservoir operation strategies. Historical trends in daily reservoir evaporation events have eluded the scientific and operational communities, largely due to a lack of long-term, consistent data record. This study quantifies trends in extreme daily reservoir evaporation events at 165 major reservoirs located in the western U.S. Here, we use the place-based energy balance and aerodynamic Daily Lake Evaporation Model (DLEM) driven by multiple meteorological data products (RTMA, gridMET, Daymet) to estimate daily evaporation rates at these reservoirs from 1981 to 2022. The results—while are based on different meteorological forcing datasets—consistently indicate that the California, Lower Colorado, and Rio Grande hydrologic regions are more prone to higher daily evaporation extremes. Compared to the rest of western U.S, these three regions also experience a more pronounced increasing trend in the annual maximum daily evaporation rate, at about 0.3 mm day -1 decade -1 during 1981-2022. The results show that heat and dryness are the main drivers to the increasing trend of extreme evaporation, while extreme wind speed is the primary contributor to exceptionally high daily evaporation events across all regions. This phenomenon is particularly prominent in the arid Lower Colorado region, but less significant in the cold and humid Pacific Northwest region. We also find that the correlation between extreme wind speed and extreme evaporation degrades as the time scale increases from daily, to monthly and seasonal. Our findings have strong implications for the pattern and distribution of extreme evaporation events at the western U.S. reservoirs, and illustrate how various drivers influence extreme evaporation across different time scales.

13 HYDRO ENERGY↗
DOE OSTI2025

Dynamical Signatures of Thermotoga maritima Maltose-Binding Proteins Affected by Ligand Binding

Functional segregation among protein isoforms depends on the interplay of their overall structures and the molecular dynamics of these structures. Thermotoga maritima maltose-binding protein (tmMBP) isoforms show size-dependent differential binding of maltose and malto-oligomers while maintaining remarkable fold conservation. This differential behavior needs detailed characterization in native-like aqueous conditions to understand the effects of protein dynamics on ligand binding and recognition. Small-angle neutron scattering (SANS), neutron spin echo (NSE) spectroscopy, and dynamic light scattering (DLS) were used in conjunction with previously published computational molecular dynamics (MD) simulations to understand the dynamic behavior of tmMBPs experimentally. SANS provided information on the overall structure of the molecules, while NSE was used to determine the dynamics in the nanosecond time scale. Both tmMBP2 and tmMBP3 have a bidomain architecture linked with a flexible hinge, with the binding pocket sitting in the cleft between the two domains. tmMBP2 and tmMBP3 showed different solution dynamics, with the translational and rotational components dominating the dynamics of both systems, resulting in a clear differentiation of their diffusion pattern. A faster dynamics component was also observed and was attributed to segmental dynamics. Differences observed between the ligand-free (apo) and ligand-bound (holo) states of the two proteins are attributed to conformational entropy. Our results highlight the intricacies of how structure and dynamics can together shape binding to a repertoire of substrates in structurally similar proteins.

Diffusion↗
DOE OSTI2025

Disentangling the Impacts of Microtopography and Shrub Distribution on Snow Depth in a Subarctic Watershed: Toward a Predictive Understanding of Snow Spatial Variability: Supporting Data and Code

This repository contains R code and associated datasets for reproducing the analysis described in the manuscript titled “Disentangling the Impacts of Microtopography and Shrub Distribution on Snow Depth in a Subarctic Watershed: Toward a Predictive Understanding of Snow Spatial Variability” (DOI: 10.1029/2024JG008604). The provided scripts facilitate a comprehensive analysis of snow depth variability influenced by microtopography and vegetation distribution in a subarctic watershed. Included datasets are high-resolution spatial maps of snow depth, terrain elevation, vegetation height, and distance from shrubs taller than 1 meter, all formatted as text files (.txt). These data are fully describe in doi:10.15485/2316038. Users can adapt the provided R scripts to accommodate different data formats or larger spatial domains, noting that some output files may require modification due to their size.The code includes implementations for boosted regression tree analysis adapted from methods outlined in Elith et al. (2008). Users interested in understanding or modeling landscape-scale snow distribution patterns, particularly in Arctic or subarctic ecosystems, will find this package useful. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Moiré Patterns in Pt Overlayers on Gold: A Graph Neural Network Interatomic Potential Study

Overlayer structures in bimetallic catalysts are relevant to a variety of catalytic reactions, particularly in electrocatalysis for fuel cell applications. Previous computational studies largely consider these overlayer structures to be those of a pseudomorphic overlayer, where there is a 1:1 atomic ratio between the overlayer and the support metal. Our previous work based on density functional theory (DFT) has shown that there exist nonstoichiometric overlayer structures that are more stable than the stoichiometric ones. Here, in this work, we developed a graph neural network interatomic potential (GNN-IP) to analyze structures formed in Pt overlayers on Au(111). The GNN-IP was used to explore properties of nonstoichiometric overlayers at length scales that are prohibitively expensive to pursue with planewave DFT calculations. In particular, we examined large Pt islands on top of a 48 × 48 Au(111) unit cell to explore the influence of the rotational angle (α) between the Pt overlayer and support Au(111) on both the stability of and the preferred atomic density in the overlayer. Island structures with smaller rotational angles between the Pt overlayer and Au(111) tend to be more stable. Further, smaller rotational angles tend to result in lower atomic density in the Pt overlayer.

chemical structure↗
DOE OSTI2024

Quantifying the long-term changes of terrestrial water storage and their driving factors

Global warming is expected to cause changes in terrestrial water storage (TWS) across the land surface, with widespread impacts on ecosystems and society. Although extensive research has been performed to analyze TWS changes and possible drivers during the post-2000 period, longer-term evolution of TWS and associated environmental forcings remain relatively unexplored. In this study, we evaluated the performance of the Energy Exascale Earth System model (E3SM) land model ELM version 1 (ELM v1) in simulating global TWS, and used factorial simulations of ELMv1 to quantify global TWS changes and their drivers during 1948–2012. We found that ELM’s agreed best with existing satellites and reconstruction datasets in temperate regions unaffected by irrigation. Biome- and climate zone-averaged TWS mainly increased at rates between 0 and 10 mm/year over 1948–2012, but the second half of that period saw smaller positive trends than the first half or even negative trends. Climate change explained >80 % of the TWS trends across most biomes and climate zones, followed by land use and land cover change. The physiological and phenological effects of CO2 primarily induced noticeable TWS trends in the more humid biomes and climate zones across different latitudes. In contrast, nitrogen deposition and aerosol deposition generally had smaller and negative impacts across the biomes and climate regions. Among the meteorological drivers analyzed, the long-term average imbalance between precipitation (P), evapotranspiration (E), and runoff (Q) contributed >50 % of the TWS trends in most biomes and climate zones, with nonlinearity being induced by spatially heterogenous changes in E/P and Q/P ratios. The accumulated detrended anomalies in P, E, and Q also often contributed substantially, while the trends difference between P, E, and Q contributed little. Together, these findings unveiled an intensification of the global TWS and its diverse patterns of climate change and different non-withdrawal human-induced alterations, contributing to a more comprehensive understanding and projection of the global water cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Geophysical survey associated with NEON AOP survey, East River, CO 2018

The package contains data layers developed and used in Falco et al. 2024: “EcoImaging: Advanced Sensing to Investigate Plant and Abiotic Hierarchical Spatial Patterns in Mountainous Watersheds". The package is part of the DOE Watershed Function Science Focus Area (SFA) project and includes geophysical measurements collected at the East River, Colorado, in conjunction with the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) survey conducted in June 2018. This dataset provide soil geophysical information and were used to investigate soil-plant relationships. The dataset consists of: - NEON_2018_EMI_survey.zip: the electromagnetic induction (EMI) survey as shape-file; - NEON_plot_TDR.csv: plot‑level data from Time‑Domain Reflectometry (TDR) measurements, providing: * volumetric water content (VWC) in percent (%); * soil temperature in degrees Celsius (°C); - file level metadata (flmd.csv) - data dictionary (dd.csv) file This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2026

Stream Chemistry, Synoptic Surveys, East Fork Poplar Creek Watershed, TN, USA; April 2023 to February 2025

Impacts of developed land cover on stream chemistry can be difficult to discern from natural variability, particularly in carbonate watersheds where weathering of urban infrastructure and lithology generate similar signatures. We evaluated how spatial patterns of stream chemistry varied across perennial and non-perennial tributaries spanning an urban-to-forested gradient in a mid-order, carbonate-dominated watershed. This data package contains a processed and compiled summary of stream chemistry and properties obtained from 12 synoptic surveys of 54 stream sites across the East Fork Poplar Creek watershed located near Oak Ridge, TN, United States. The sites include non-perennial tributaries, perennial tributaries, and the main stem and span forested to urban (highly developed) land cover gradients. The data package includes the processed and flagged chemical data (WaDE_SynopticSummary_FinalChemistry), metadata describing data flagging and analysis (WaDE_SynopticSummary_Metadata), information about each site and its contributing subcatchment (WaDE_SynopticSummary_SiteInformation), and a comparison of instrument and field detection limits used to determine method detection limits for the study (WaDE_SynopticSummary_DetectionLimitComparison). Stream chemistry includes stream parameters measured in situ using multiparameter probes (dissolved oxygen, pH, specific conductance, temperature) and solutes including nutrients (nitrate, ammonium, soluble reactive phosphorus), dissolved organic carbon, dissolved inorganic carbon, major cations (calcium, magnesium, potassium, sodium), major anions (chloride, sulfate), and a broad suite of minor and trace elements.

EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SURFACE ↗
DOE OSTI2025

Observed and Imputed Volumetric Soil Water Content Timeseries for the New Mexico Elevation Gradient

Reliable soil water content (SWC) data are essential for understanding dryland ecosystem dynamics, but high-frequency SWC sensors often fail, creating gaps in critical datasets. To address this, we developed a Bayesian mixture model that imputes missing SWC using both linear interpolation and an ecosystem water balance model (SOILWAT2), tested across six AmeriFlux eddy covariance tower sites in the New Mexico Elevation Gradient, demonstrating its effectiveness in reconstructing SWC patterns while providing insights into the factors driving SWC variability. Daily volumetric soil water content (SWC) data are provided as csv-formatted spreadsheets for the six AmeriFlux sites (US-Seg, US-Ses, US-Wjs, US-Mpi, US-Vcp, and US-Vcs). For each site there is an observed SWC file (site_SWC_gapfill.csv) and a file that contains imputed SWC (imputed_SWC_site.csv). The observed SWC files contain temperature corrected sensor values, tower precipitation data, as well as outputs from SOILWAT2 simulations that were used to impute SWC. The imputed files contain the original observed SWC values and the imputed missing SWC values. When SWC was missing from the original data, the missing value was imputed based on the Bayesian imputation mixture model. The posterior mean of all imputed values is reported as "mean_X". When the observed SWC was NOT missing, mean_X = observed SWC value (original data). The standard deviation, 2.5th percentile and the 97.5th percentile for the imputed values are also reported in the imputed files. There are readme text files for each file type explaining the contents of each column.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Data and scripts associated with “Allometric scaling of hyporheic respiration across basins in the Pacific Northwest USA"

This data package is associated with the publication “Allometric scaling of hyporheic respiration across basins in the Pacific Northwest USA” submitted to JGR-Biogeosciences (Regier et al. 2025).This study used reach-scale modeled estimates of hyporheic aerobic respiration made by the River Corridor Model (Fang et al. 2020) and watershed characteristics across the Willamette and Yakima River basins to explore potential allometric scaling (i.e., power-law relationships between size and function) of cumulative hyporheic respiration across catchment-to-basin scales. Scaling was explored quantitatively via the R2, slope, and y-intercept of relationships between cumulative hyporheic respiration and watershed area, divided into hyporheic exchange flux (HEF) quantiles. We also explored relationships between allometric scaling and other watershed characteristics through linear regression, spatial patterns, and mutual information analyses. Our results also suggest variability of hyporheic respiration allometry for middle exchange flux quantiles, and in relation to land-cover. Our findings provide initial evidence that allometric scaling may be useful for predicting hyporheic biogeochemical dynamics across watersheds from reach to basin scales. This data package is associated with the GitHub repository found at https://github.com/peterregier/rc_wrb_yrb_scaling. The data package is organized into several key directories. The “data” folder contains multiple CSV files, including landscape heterogeneity, scaling analysis, and watershed boundary data. The “figures” folder has all figure files in both PDF and PNG formats. Core analysis scripts and figure generation scripts are in the “scripts” directory, systematically numbered for sequential execution. The root directory includes essential project files; please see the file ending in “flmd.csv” for a list and description of all files contained in this data package and the file ending in “dd.csv” for data dictionaries used to describe tabular column headers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Elevated-Mn ChemCam targets illuminating Mn redox cycling and diagenesis in the Bradbury Rise, Gale Crater, Mars

Manganese plays a crucial role as a paleo-environmental and geological indicator due to its sensitivity to redox potential and pH variations in the environment. On Earth, the association between the rise of atmospheric oxygen during the Great Oxidation Event and the presence of Mn in the sedimentary rock record underscores its significance. Here, in this study, we reexamined ChemCam targets from the first 600 sols of the Mars Science Laboratory mission, focusing on identifying instances of above-average Mn within these targets. These elevated-Mn targets were categorized into distinct geologic classes, revealing a pattern linking heightened Mn levels with diagenetically altered materials, such as calcium-sulfate veins and concretions, as well as clay minerals within the same targets, indicating a compelling relationship between Mn enrichment and diagenetic processes. High concentrations of Mn were observed in chemically altered targets, suggesting the occurrence of multiple fluid events: the first to alter the material and the second to deposit Mn. The observed patterns suggest multiple diagenetic events and redox cycling that facilitated the deposition and transport of Mn subsequent to the initial dissolution of basaltic materials. This research sheds light on the complexity of martian diagenetic processes and their implications for the planet’s environmental evolution.

58 GEOSCIENCES↗
DOE OSTI2025

Orbital inversion and emergent lattice dynamics in infinite layer CaCoO 2

The layered cobaltate CaCoO 2 exhibits a unique herringbone-like structure. Serving as a potential prototype for a new class of complex lattice patterns, we study the properties of CaCoO 2 using X-ray absorption spectroscopy (XAS) and resonant inelastic X-ray scattering (RIXS). Our results reveal a significant inter-plane hybridization between the Ca 4s- and Co 3d- orbitals, leading to an inversion of the textbook orbital occupation of a square planar geometry. Further, our RIXS data reveal a strong low energy mode, with anomalous intensity modulations as a function of momentum transfer close to a quasi-static response. These findings indicate that the newly discovered herringbone structure exhibited in CaCoO 2 may serve as a promising laboratory for the design of materials having strong electronic, orbital and lattice correlations.

Electronic properties and materials↗
DOE OSTI2025

Experimental signature of layer skyrmions and implications for band topology in twisted WSe 2 bilayers

Twisted homobilayers of transition-metal dichalcogenides have been established as an ideal platform for studying strong correlation phenomena, as exemplified by the recent discovery of fractional Chern insulator states in twisted MoTe 2 , as well as Chern insulators and unconventional superconductivity in twisted WSe 2 . In these systems, a non-trivial topology in the strongly layer-hybridized regime can arise from a spatial patterning of interlayer tunnelling amplitudes and layer-dependent potentials that yields a lattice of layer skyrmions. Here, in this work, we report experimental signatures of skyrmion textures in the layer degree of freedom of rhombohedral-stacked twisted WSe 2 homobilayers. Using scanning tunnelling spectroscopy that separately resolves the Γ-valley and K-valley moiré electronic states, we reveal opposite layer polarizations of the K valley at two different lattice sites with opposite stacking order within the moiré unit cell. These findings are consistent with the theoretically predicted layer-skyrmion texture. We also use our experimental results to parameterize a common continuum model of moiré bands in twisted bilayers, further establishing a direct correlation between the shape of the local density of states in real space and the topology of the topmost moiré band.

electronic properties and materials↗
DOE OSTI2026

Pattern-enhanced Resonant Soft X-ray Scattering for Operando monitoring of electrochemical solid-liquid interfaces

Unveiling interfaces at sub-nanometer scales is essential for advancing the understanding of complex chemical transformations. However, characterizing solid-liquid interfaces with high dimensional sensitivity and temporal resolution remains challenging, due to their dynamic nature and inaccessibility by conventional probes. Here we present an approach, Pattern-enhanced Resonant Soft X-ray Scattering, to overcome the challenges. Rooted in a “sample-as-optics” philosophy, this technique utilizes precisely engineered line-grating nanopatterns to modulate near-field X-ray illumination, coherently enhancing scattering signals from the line-gratings. We implement the method using Ni line-grating nanopatterns in electrochemical water oxidation. The periodic nanostructures serve as diffractive optical elements to reveal the Ni oxidation gradients and structural dynamics at the electrode-electrolyte interfaces. Finite-element simulations corroborate the observed trends by modeling variations in compositions and structures during electrocatalysis. Through integrating advanced sample design with coherent wave nature of soft X-rays, our approach opens accessible pathways to operando exploring chemical evolution and sub-nanometer dimensional variations simultaneously in electrochemical systems. This non-destructive method is efficient and element-specific, making it valuable for probing chemical and dimensional dynamics with appropriate modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗