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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
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

Snow plays a critical role in carbon cycling, vegetation dynamics, and permafrost hydrology at high latitudes by influencing surface energy exchange. Predicting snow distribution patterns is essential for understanding the evolution of Arctic ecosystems, yet scaling process-level knowledge to landscape predictions remains challenging. Here, we analyze snow depth (2019 and 2022), terrain elevation, and vegetation height from a watershed on the Seward Peninsula, Alaska, to examine how topography and shrubs shape snow redistribution across spatial scales. We find that snow depth is strongly coupled to terrain at scales below ∼60 m but becomes increasingly decoupled at larger scales. The topographic model of snow depth variation, which transforms terrain data to align with these scale-dependent snow patterns, is well correlated with local snow depth variations (linear fit R 2 > 0.5 for 85% of 100-m patches). A machine learning reconstruction of shrub canopy snow trapping reveals a simple exponential relationship between canopy structure and snow accumulation ( R 2 = 0.59), highlighting the combined influence of topography and vegetation on snow distribution. Together, these empirical relationships capture much of the observed snow variability in the watershed ( R 2 = 0.49, root mean square error (RMSE) = 30 cm), though systematic limitations persist in areas of strong scour and at coarser scales where wind-terrain interactions are more complex. These findings provide a framework for more efficient snow depth prediction and offer insights to improve snow-vegetation feedback representation in Earth System Models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Predicting weather impacts on corn production in a data-limited region using a transfer learning approach

The stability of food supply and prices may depend more on annual changes in yields from year-to-year variability in weather than on longer-term average changes from changing climatic conditions. However, the absence of high-quality data on crop yields at fine spatial resolutions in many regions of the world makes it challenging to statistically model their response to interannual variability in weather patterns. Therefore, there is a need for empirical methods that can project annual crop yield changes even in limited data regions. Here, we propose a transfer learning algorithm that uses high spatial resolution data from one region to project yields in another region with more limited data. The goal of our work is to understand what data types can be beneficial for transferring learning from a source region to a very different target region with more limited data. We utilize Long Short-Term Memory to develop a transfer learning model that is trained on historical county-level corn yield in the United States and predicts district-level corn yield variations in India. Even using smaller amounts of data in India, simulating a data-scarce region, we achieve an average root mean square error of 0.48 bu acre−1 in predicting interannual yield variations. Using Shapley values to interpret results, we explore the contribution of the different weather parameters to interannual yield variability and find a larger influence of precipitation-related variables. Our study demonstrates the usefulness of this method for transferring models of weather impacts on crop yields trained on a data-rich country to one with more limited data. It suggests the potential of applying the transfer learning model to mitigate the need for extensive raw data globally.

Vishwakarma, Srishti [ORNL] (ORCID:000000031674419↗
DOE OSTI2026

Automated Classification of Vehicle Movements at Signalized Intersections Using Vehicle Trajectories

Accurate vehicle movement classification through signalized intersections is of paramount importance to the analysis of intersection performance and the optimization of traffic control strategies. Conventional techniques for tracking vehicle turning movements depend on infrastructure-based strategies like human counts, loop detectors, and video analytics, all of which are costly, prone to errors, and spatially constrained. High-frequency trajectory data can be utilized to determine vehicle movement patterns in a scalable and infrastructure-independent method due to the adoption of connected vehicles (CVs). In recent years, several studies have utilized connected vehicle data to generate performance measures. Most of the trajectory-based performance measures approaches, however, require map matching-i.e., extracting geospatial references from maps to identify the movements that individual vehicles make at a signalized intersection. These approaches are often time-consuming and hinder scalability since geographic features need to be provided for an analysis to be conducted. Map matching methods are prone to errors as different map versions change these geographic features. This research presents a novel automatic classification pipeline that uses CV trajectory data to classify vehicle movements at signalized crossings, specifically pass-through left-turn and right-turn maneuvers. The process starts by filtering trips that cross a spatial bounding box that has been defined at the target intersection. Approach and departure headings for each trajectory crossing the boundary are computed and are clustered together to identify dominant movements. The proposed algorithm is used to classify the movement of vehicles at 10 intersections in the state of California, and the results indicate that the algorithm can classify movements at these intersections with varying traffic volumes and road network configurations, all in a map-less framework with no need for conflation of vehicle trajectories to a digital base map.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Light-driven nanoscale vectorial currents

Controlled charge flows are fundamental to many areas of science and technology, serving as carriers of energy and information, as probes of material properties and dynamics and as a means of revealing or even inducing broken symmetries. Emerging methods for light-based current control offer particularly promising routes beyond the speed and adaptability limitations of conventional voltage-driven systems. However, optical generation and manipulation of currents at nanometre spatial scales remains a basic challenge and a crucial step towards scalable optoelectronic systems for microelectronics and information science. Here we introduce vectorial optoelectronic metasurfaces in which ultrafast light pulses induce local directional charge flows around symmetry-broken plasmonic nanostructures, with tunable responses and arbitrary patterning down to subdiffractive nanometre scales. Local symmetries and vectorial currents are revealed by polarization-dependent and wavelength-sensitive electrical readout and terahertz (THz) emission, whereas spatially tailored global currents are demonstrated in the direct generation of elusive broadband THz vector beams 17 . We show that, in graphene, a detailed interplay between electrodynamic, thermodynamic and hydrodynamic degrees of freedom gives rise to rapidly evolving nanoscale driving forces and charge flows under the extremely spatially and temporally localized excitation. These results set the stage for versatile patterning and optical control over nanoscale currents in materials diagnostics, THz spectroscopies, nanomagnetism and ultrafast information processing.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Two-dimensional patterning of mesoscale fibers using acoustophoresis

The performance of functional composites can rely critically on the arrangement of secondary phases; for example, patterned networks of conductive particles can impart anisotropic thermal, electric or ionic conductivity while preserving flexibility in the matrix. We demonstrate the use of standing acoustic waves to generate periodic patterns of short fibers. We extend the range of possible patterns with the first demonstration of both rectangular grids and arrays of octagons interspersed with rectangles. These newly demonstrated patterns are rationalized using theoretical models of acoustic forces and torques on fibers that account for two-dimensional spatial variations arising from applied acoustic fields. The models enable simulations of fiber motion, which are used to (i) map out final fiber positions as a function of initial position and orientation, and (ii) corroborate experiments visualizing fiber motion and final patterns. This approach provides a fast and accurate way to predict emergent fiber patterns as a function of excitation modality and fiber length. The theory and experiments clearly indicate strong coupling between the length of the fibers and the spacing of the acoustic nodes. Furthermore, this coupling is used to estimate reductions in percolation thresholds associated with the ratio of fiber length and acoustic wavelength.

25 ENERGY STORAGE↗
DOE OSTI2021

Diverse sediment microbiota shape methane emission temperature sensitivity in Arctic lakes

Abstract Northern post-glacial lakes are significant, increasing sources of atmospheric carbon through ebullition (bubbling) of microbially-produced methane (CH 4 ) from sediments. Ebullitive CH 4 flux correlates strongly with temperature, reflecting that solar radiation drives emissions. However, here we show that the slope of the temperature-CH 4 flux relationship differs spatially across two post-glacial lakes in Sweden. We compared these CH 4 emission patterns with sediment microbial (metagenomic and amplicon), isotopic, and geochemical data. The temperature-associated increase in CH 4 emissions was greater in lake middles—where methanogens were more abundant—than edges, and sediment communities were distinct between edges and middles. Microbial abundances, including those of CH 4 -cycling microorganisms and syntrophs, were predictive of porewater CH 4 concentrations. Results suggest that deeper lake regions, which currently emit less CH 4 than shallower edges, could add substantially to CH 4 emissions in a warmer Arctic and that CH 4 emission predictions may be improved by accounting for spatial variations in sediment microbiota.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A Pacific Tropical Decadal Variability Challenge for Climate Models

Understanding and forecasting Tropical Pacific Decadal-scale Variability (TPDV) strongly rely on climate model simulations. Using a Linear Inverse Modeling (LIM) diagnostic approach, we reveal Coupled Model Intercomparison Project Phase 6 models have significant challenges in reproducing the spatial structure and dominant mechanisms of TPDV. Specifically, while the models' ensemble mean pattern of TPDV resembles that of observations, the spread across models is very large and most models show significant differences from observations. In observations, removing the coupling between extratropics and tropics reduces TPDV by ~60%–70%, and removing the tropical thermocline variability makes the central tropical Pacific a key center of action for TPDV and El Niño Southern Oscillation variability. These characteristics are only confirmed in a subset of models. Differences between observations and simulations are outside the range of natural internal TPDV noise and pose important questions regarding our ability to model the impacts of natural internal low-frequency variability superimposed on long-term climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Precipitation regime changes in High Mountain Asia driven by cleaner air

High Mountain Asia (HMA) has experienced a spatial imbalance in water resources in recent decades, partly due to a dipolar pattern of precipitation changes known as South Drying-North Wetting. These changes can be influenced by both human activities and internal climate variability. While climate projections indicate a future widespread wetting trend over HMA, the timing and mechanism of the transition from a dipolar to a monopolar pattern remain unknown. Here, we demonstrate that the observed dipolar precipitation change in HMA during summer is primarily driven by westerly- and monsoon-associated precipitation patterns. The weakening of the Asian westerly jet, caused by uneven emission of anthropogenic aerosols, favors the dipolar precipitation trend during 1951-2020. Additionally, the phase transition of the interdecadal Pacific oscillation induces an out-of-phase precipitation change between the core region of the South Asian monsoon and southeastern HMA. Under medium or high emission scenarios, corresponding to a global warming of 0.6-1.1 °C compared to the present, the dipolar pattern is projected to shift into a monopolar wetting trend in the 2040s. This shift of precipitation patterns is mainly attributed to the intensified jet stream resulting from reduced emissions of anthropogenic aerosols. In conclusion, these findings underscore the importance of considering the impact of aerosol emission reduction in future social planning by policymakers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Explorative Visualization for Traffic Safety using Adaptive Study Areas

The pressing need to improve traffic safety has become a societal concern in many cities around the world. Many traffic accidents are not occurring as stand-alone events but as consequences of other road incidents and hazards. To capture the traffic safety indications from a holistic aspect, this paper presents a suite of visualization techniques to explore large traffic safety datasets collected from different sources using adaptive study areas which include the whole region (Hamilton County, Ohio, U.S.) as well as smaller sub-areas. In the present study, these data source include (1) Hamilton County’s 911 emergency response data, which includes traffic incidents as well as other types of incidents throughout the county, and (2) Tennessee crash data, which contains only vehicle crashes with more detail on the circumstances of each crash. We find that both abstract and spatial visualization techniques are used to derive a better understanding of traffic safety patterns for different traffic participants in various urban environments. In addition to the entire region of Hamilton County, safety is examined on the highways, in the downtown area, and in a shopping district east of the city center. It is possible to characterize incidents in the different areas, gain a better understanding of common incident patterns, and identify outliers in the data. Finally, a textured tile calendar is presented to compare spatiotemporal patterns.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Pseudo-gray-scale halftone gratings for shearing and Hartmann wavefront sensors

Now in use on x-ray beamlines worldwide, shearing interferometry and Hartmann wavefront sensing provide effective feedback for measuring and optimizing high-quality beams. Conventionally, both approaches spatially modulate the beam properties (amplitude or phase) using two-tone, binary patterns, leading to deleterious diffraction effects that must be mitigated. In shearing, the presence of multiple diffraction orders affects measurement near boundaries. In Hartmann, diffraction limits the measurement point density. We demonstrate that the use of pseudo-gray-scale halftone patterns in the diffracting elements can improve the performance of both techniques.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Myriad World Baseline: Global Geodemographic Estimates

The LandScan Myriad World Baseline (MWB) method produces global, residential (nighttime/home-location) gridded geodemographic estimates based on 5-year age/gender cohorts—at 30-arcsecond (≈1 km) resolution. MWB is designed to fill gaps where detailed, georeferenced survey data (e.g., Demographic and Health Surveys (DHS)) are missing or outdated, and to provide a baseline that can support human security analysis, including consequence assessment, “patterns of life” modeling, and scenario-based population futures. MWB’s workflow spatializes household-level age/gender characteristics from the GLOPOP-S dataset by conflating household and gridded expected relative wealth adapted from Global Gridded Relative Deprivation Index (GRDI), then adjusts them to a target year of interest. Age/gender estimates are then applied to harmonize lowest-administrative-level statistics with LandScan residential counts, yielding final geodemographic estimates. Two validation case studies are presented: Ghana (2021) and Tokyo/Kanagawa, Japan (2020), illustrating spatial variability in demographic cohorts and comparing MWB outputs to official gridded statistics. Results show close overall alignment relative to validation criteria including population pyramids and age-dependency ratios.

Tuccillo, Joe [ORNL] (ORCID:0000000259300943)↗
DOE OSTI2025

Identifying spatiotemporal patterns in opioid vulnerability: investigating the links between disability, prescription opioids and opioid-related mortality

Background: The opioid crisis remains one of the most daunting and complex public health problems in the United States. This study investigates the national epidemic by analyzing vulnerability profiles of three key factors: opioid-related mortality rates, opioid prescription dispensing rates, and disability rank ordered rates. Methods: This study utilizes county level data, spanning the years 2014 through 2020, on the rates of opioid-related mortality, opioid prescription dispensing, and disability. To successfully estimate and predict trends in these opioid-related factors, we augment the Kalman Filter with a novel spatial component. To define opioid vulnerability profiles, we create heat maps of our filter’s predicted rates across the nation’s counties and identify the hotspots. In this context, hotspots are defined on a year-by-year basis as counties with rates in the top 5% nationally. Results: Our spatial Kalman filter demonstrates strong predictive performance. From 2014 to 2018, these predictions highlight consistent spatiotemporal patterns across all three factors, with Appalachia distinguished as the nation’s most vulnerable region. Starting in 2019 however, the dispensing rate profiles undergo a dramatic and chaotic shift. Conclusions: The initial primary drivers of opioid abuse in the Appalachian region were likely prescription opioids; however, it now appears that abuse is sustained by illegal drugs. Additionally, we find that the disabled subpopulation may be more at risk of opioid-related mortality than the general population. Public health initiatives must extend beyond controlling prescription practices to address the transition to and impact of illicit drug use.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Direct-write laser-assisted patterning of form birefringence in wave plates fabricated by glancing-angle deposition

The development of optics that provide spatial control of birefringence could enable better control of laser beam polarization, but available solutions are limited. Here we demonstrate a method to locally modify the birefringence of wave plates fabricated by glancing-angle deposition. The method employs localized melting of the anisotropic microstructure in a vacuum environment to alter the local birefringence. We demonstrate that this process is only possible under high vacuum to avoid trapping air within the melt zone. The direct-write method presented here can be readily utilized for coatings exhibiting form birefringence of virtually any chemical composition, size, and format.

42 ENGINEERING↗
DOE OSTI2022

Modulation of North Atlantic Polar Low Activity and Associated Flow Patterns by Sudden Stratospheric Warmings

Abstract Polar lows (PLs) are intense maritime mesoscale cyclones that can pose hazards to coastal communities and marine operation in the Arctic. This study examines the impacts of sudden stratospheric warmings (SSWs) on PL activity in the subarctic North Atlantic. The 20 days following SSWs are characterized by tropospheric circulation anomalies resembling the negative phase of the North Atlantic Oscillation. PL activity decreases significantly over the Labrador Sea, which can be attributed to the infrequent occurrence of low static stability and strong environmental baroclinicity, as well as reduced surface turbulent heat fluxes. These results suggest that a skillful prediction of SSWs can improve the extended-range forecast of PL activity over the Labrador Sea. For the Nordic seas, the results imply that the spatial structure of an SSW event is important for the PL modulation through different tropospheric circulation patterns. Situations with increased PL frequency in the Nordic seas are characterized by SSWs centered close to northern Greenland occurring over a smaller area, and a tropospheric response featuring enhanced cold-air outbreaks over the Norwegian Sea. Conversely, PL activity is suppressed over the Nordic seas when the SSW favors the formation of a tropospheric anticyclone above Greenland and Scandinavia. Significance Statement This study investigates the relationships between polar lows (PLs) and sudden stratospheric warmings (SSWs) over the subarctic North Atlantic. A better understanding of the effect of SSWs on PL development has the potential to improve extended-range forecasts of PLs. It is shown that SSWs are responsible for the significantly suppressed regional PL activity over the Labrador Sea, suggesting that SSWs can serve as a predictor for the extended-range forecast of PLs over this region. Following SSW events, the thermodynamic state of atmosphere becomes more stable over the Labrador Sea and hinders the convective development of PLs. For the northern Nordic seas, the impacts of SSWs on PL activity are sensitive to the spatial structure of stratospheric warming.

Chang, Chuan-Chieh↗
DOE OSTI2020

Plasmon-Mediated Intramolecular Methyl Migration with Nanoscale Spatial Control

Plasmonic materials interact strongly with light to focus and enhance electromagnetic radiation down to nanoscale volumes. Due to this localized confinement, materials that support localized surface plasmon resonances are capable of driving energetically unfavorable chemical reactions. In certain cases, the plasmonic nanostructures are able to preferentially catalyze the formation of specific photoproducts, which offers an opportunity for the development of solar-driven chemical synthesis. Here, using plasmonic environments, we report inducing an intramolecular methyl migration reaction, forming 4-methylpyridine from N-methylpyridinium. Using both experimental and computational methods, we were able to confirm the identity of the N-methylpyridinium by making spectral comparisons against possible photoproducts. This reaction involves breaking a C–N bond and forming a new C–C bond, highlighting the ability of plasmonic materials to drive complex and selective reactions. Additionally, we observe that the product yield depends strongly on optical illumination conditions. This is likely due to steric hindrance in specific regions on the nanostructured plasmonic substrate, providing an optical handle for driving plasmonic catalysis with spatial specificity. Furthermore, this work adds yet another class of reactions accessible by surface plasmon excitation to the ever-growing library of plasmon-mediated chemical reactions.

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

Laser Speckle Pattern Stability in Hypersonic Regimes for Experimental Mechanics and Metrological Studies

Here, an empirical study assessing the suitability of laser speckle patterns for use in experimental mechanics research conducted at hypersonic conditions is presented. Speckle patterns generated via coherent optical scattering from a gold-coated graphite surface inserted into a Mach 10 air stream were collected and analyzed using Computer-Aided Speckle Interferometry using two methodologies: a typical spanwise approach involving increasing temporal span between image pairs, and a sequential approach that utilizes a combination of temporal re-referencing and spatial resampling. Results were characterized for spatial-temporal stability and variance. Our observations demonstrate that optical methods relying on stable and properly formed speckle patterns can be used in a hypersonic regime at various Reynolds numbers and common camera frame rates, but the technique is sensitive to the conditions of the airflow and the processing methodology chosen.

42 ENGINEERING↗
DOE OSTI2021

Correlative analysis of structure and chemistry of Li x FePO 4 platelets using 4D-STEM and X-ray ptychography

Lithium iron phosphate (Li x FePO 4 ), a cathode material used in rechargeable Li-ion batteries, phase separates upon de/lithiation under equilibrium. The interfacial structure and chemistry within these cathode materials affects Li-ion transport, and therefore battery performance. Here, correlative imaging of Li x FePO 4 was performed using four-dimensional scanning transmission electron microscopy (4D-STEM), scanning transmission X-ray microscopy (STXM), and X-ray ptychography in order to analyze the local structure and chemistry of the same particle set. Over 50,000 diffraction patterns from 10 particles provided measurements of both structure and chemistry at a nanoscale spatial resolution (16.6–49.5 nm) over wide (several micron) fields-of-view with statistical robustness. Li x FePO 4 particles at varying stages of delithiation were measured to examine the evolution of structure and chemistry as a function of delithiation. In lithiated and delithiated particles, local variations were observed in the degree of lithiation even while local lattice structures remained comparatively constant, and calculation of linear coefficients of chemical expansion suggest pinning of the lattice structures in these populations. Partially delithiated particles displayed broadly core–shell-like structures, however, with highly variable behavior both locally and per individual particle that exhibited distinctive intermediate regions at the interface between phases, and pockets within the lithiated core that correspond to FePO 4 in structure and chemistry. The results provide insight into the Li x FePO 4 system, subtleties in the scope and applicability of Vegard’s law (linear lattice parameter-composition behavior) under local versus global measurements, and demonstrate a powerful new combination of experimental and analytical modalities for bridging the crucial gap between local and statistical characterization.

25 ENERGY STORAGE↗
DOE OSTI2020

Boundary-directed epitaxy of block copolymers

Directed self-assembly of block copolymers (BCPs) enables nanofabrication at sub-10 nm dimensions, beyond the resolution of conventional lithography. However, directing the position, orientation, and long-range lateral order of BCP domains to produce technologicallyuseful patterns is a challenge. Here, we present a promising approach to direct assembly using spatial boundaries between planar, low-resolution regions on a surface with different composition. Pairs of boundaries are formed at the edges of isolated stripes on a background substrate. Vertical lamellae nucleate at and are pinned by chemical contrast at each stripe/ substrate boundary, align parallel to boundaries, selectively propagate from boundaries into stripe interiors (whereas horizontal lamellae form on the background), and register to wide stripes to multiply the feature density. Ordered BCP line arrays with half-pitch of 6.4 nm are demonstrated on stripes >80 nm wide. Boundary-directed epitaxy provides an attractive path towards assembling, creating, and lithographically defining materials on sub-10 nm scales.

36 MATERIALS SCIENCE↗