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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

High spatial resolution charge sensing of quantum Hall states

Charge distribution offers a unique fingerprint of important properties of electronic systems, including dielectric response, charge ordering, and charge fractionalization. Here, we develop an architecture for charge sensing in two-dimensional electronic systems in a strong magnetic field. We probe local change of the chemical potential in a proximitized detector layer using scanning tunneling microscopy, allowing us to infer the chemical potential and the charge profile in the sample. Our technique has both high energy (<0.3 meV) and spatial (<10 nm) resolution exceeding that of previous studies by an order of magnitude. We apply our technique to study the chemical potential of quantum Hall liquids in monolayer graphene under high magnetic fields and their responses to charge impurities. The chemical potential measurement provides a local probe of the thermodynamic gap of quantum Hall ferromagnets and fractional quantum Hall states. The screening charge profile reveals spatially oscillatory response of the quantum Hall liquids to charge impurities and is consistent with the composite Fermi liquid picture close to the half-filling. Our technique also paves the way to map moiré potentials, probe Wigner crystals, and investigate fractional charges in quantum Hall and Chern insulators.

charge sensing↗
DOE OSTI2025

A Gigaparsec-scale Hydrodynamic Volume Reconstructed with Deep Learning

The next generation of spectroscopic surveys will map the large-scale structure of the Universe at high redshifts (2 ≤ z ≤ 5) using millions of quasar spectra, enabling major advances in constraining both the standard cosmological model and its extensions. Robust cosmological analyses of these data sets require numerical simulations that both cover gigaparsec volumes and resolve features on ∼10 kpc scales and smaller. However, running such large-volume, high-resolution hydrodynamic simulations is computationally prohibitive. We present a generative deep learning model that enhances a low-resolution, gigaparsec-scale (960 h −1 Mpc) hydrodynamic simulation using a smaller (80 h −1 Mpc) high-resolution input hydrodynamic simulation as training data. The resulting enhanced simulation reproduces the line-of-sight power spectrum to within ∼10% and the three-dimensional power spectrum at the ∼20% level at intermediate to small scales (k ≲ 2 h Mpc −1 ). Our method shows strong promise for producing realistic simulations for cosmological analyses with current surveys such as the Dark Energy Spectroscopic Instrument and upcoming next-generation experiments, but further improvements are needed to accurately recover the large-scale modes. We publicly release the enhanced hydrodynamic simulation, along with a halo catalog from a companion N-body dark matter simulation to support the calibration of data analysis pipelines for these large-scale surveys.

Convolutional neural networks↗
DOE OSTI2024

Wind Loading on CSP Collectors

The project significantly enhanced the community's understanding of the fundamental physics drivers underlying the wind-loading experienced by concentrating solar power (CSP) collector structures (i.e., parabolic troughs and heliostats) as well as their support structures. This project had two overarching objectives: (1) detailed measurements to characterize the prevailing wind conditions and resulting operational loads on collector structures, and (2) development and validation of a computationally efficient, high-fidelity modeling tool capable of predicting wind-loading in deep-array installations. Over three years, we conducted comprehensive at-scale field measurements of the atmospheric turbulent wind conditions, and the resulting wind loads on parabolic troughs and heliostats. Two at-scale measurement campaigns yielded first-of-its-kind, high-resolution, long-term datasets that are used to characterize the complex flow field and wind loading on parabolic-troughs and heliostats in operational power plants. The high-resolution measurements collected during these campaigns were used to validate the high-fidelity computational models developed at NREL. These open-source computationally efficient models were shown to be accurate in predicting wind-driven loads on collectors without the need for a large supercomputer.

14 SOLAR ENERGY↗
DOE OSTI2020

Measurements of an AC-LGAD strip sensor with a 120 GeV proton beam

The development of detectors that provide high resolution in four dimensions has attracted wide-spread interest in the scientific community for several applications in high-energy physics, nuclear physics, medical imaging, mass spectroscopy as well as quantum information. In addition to high time resolution and thanks to the AC-coupling of the electrodes, LGAD silicon sensors can provide high resolution in the measurement of spatial coordinates of an incident minimum ionizing particle. Such AC-coupled LGADs, also known as AC-LGADs, are therefore considered as candidates for future detectors to provide 4-dimensional measurements in a single sensing device with 100% fill factor. This article presents the first characterization of an AC-LGAD sensor with a proton beam of 120 GeV momentum at Fermilab. The sensor consists of strips with 80 μm width, fabricated at Brookhaven National Laboratory. The signal properties, efficiency, spatial, and time resolution are presented. Overall, the experimental results show that the time resolution of such an AC-LGAD is compatible to standard LGADs with similar gain, and that AC-LGADs can be segmented with fine pitches as standard strip or pixel detectors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Measurements of an AC-LGAD strip sensor with a 120 GeV proton beam

The development of detectors that provide high resolution in four dimensions has attracted wide-spread interest in the scientific community for several applications in high-energy physics, nuclear physics, medical imaging, mass spectroscopy as well as quantum information. In addition to high time resolution and thanks to the AC-coupling of the electrodes, LGAD silicon sensors can provide high resolution in the measurement of spatial coordinates of an incident minimum ionizing particle. Such AC-coupled LGADs, also known as AC-LGADs, are therefore considered as candidates for future detectors to provide 4-dimensional measurements in a single sensing device with 100$\%$ fill factor. This article presents the first characterization of an AC-LGAD sensor with a proton beam of 120 GeV momentum at Fermilab. The sensor consists of strips with 80 $\mu$m width, fabricated at Brookhaven National Laboratory. The signal properties, efficiency, spatial, and time resolution are presented. The experimental results show that the time resolution of such an AC-LGAD is compatible to standard LGADs with similar gain, and that AC-LGADs can be segmented with fine pitches as standard strip or pixel detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Impact of selenium addition to the cadmium-zinc-telluride matrix for producing high energy resolution X-and gamma-ray detectors

Abstract Both material quality and detector performance have been steadily improving over the past few years for the leading room temperature radiation detector material cadmium-zinc-telluride (CdZnTe). However, although tremendous progress being made, CdZnTe still suffers from high concentrations of performance-limiting defects, such as Te inclusions, networks of sub-grain boundaries and compositional inhomogeneity due to the higher segregation coefficient of Zn. Adding as low as 2% (atomic) Se into CdZnTe matrix was found to successfully mitigate many performance-limiting defects and provide improved compositional homogeneity. Here we report record-high performance of Virtual Frisch Grid (VFG) detector fabricated from as-grown Cd 0.9 Zn 0.1 Te 0.98 Se 0.02 ingot grown by the Traveling Heater Method (THM). Benefiting from superior material quality, we achieved superb energy resolution of 0.77% at 662 keV (as-measured without charge-loss correction algorithms) registered at room temperature. The absence of residual thermal stress in the detector was revealed from white beam X-ray topographic images, which was also confirmed by Infra-Red (IR) transmission imaging under cross polarizers. Furthermore, neither sub-grain boundaries nor their networks were observed from the X-ray topographic image. However, large concentrations of extrinsic impurities were revealed in as-grown materials, suggesting a high likelihood for further reduction in the energy resolution after improved purification of the starting material.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Quantitative insights into the dislocation source behavior of twin boundaries suggest a new dislocation source mechanism

Pop-in statistics from nanoindentation with spherical indenters are used to determine the stress required to activate dislocation sources in twin boundaries (TBs) in copper and its alloys. The TB source activation stress is smaller than that needed for bulk single crystals, irrespective of the indenter size, dislocation density and stacking fault energy. Because an array of pre-existing Frank partial dislocations is present at a TB, we propose that dislocation emission from the TB occurs by the Frank partials splitting into Shockley partials moving along the TB plane and perfect lattice dislocations, both of which are mobile. The proposed mechanism is supported by recent high resolution transmission electron microscopy images in deformed nanotwinned (NT) metals and may help to explain some of the superior properties of nanotwinned metals (e.g. high strength and good ductility), as well as the process of detwinning by the collective formation and motion of Shockley partial dislocations along TBs.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Peering into cloud physics using ultra-fine resolution radar and lidar systems

Cloud microphysical processes, such as droplet activation, condensational growth, and collisional growth, play a central role in the evolution of clouds and precipitation. Accurate representations of these processes in numerical models are challenging partially due to incomplete understanding of them at the process-level arising from limited systematic observations. Most surface-based active remote sensors, including today’s operational cloud radars and lidars, have a resolution on the order of tens of meters. This resolution is insufficient to resolve cloud microphysical processes that manifest at finer (meter and sub-meter) scales. A new set of ultra-high-resolution ground-based radar and lidar systems have been developed to address this observational gap. The newly developed 94-GHz cloud radar has a range resolution down to 2.8 m, or a factor of 10 finer than typical radars, using a large bandwidth and quadratic phase coding techniques. The lidar has a range resolution down to 10 cm, or a factor of 100 finer than typical lidars, using a time-gated time-correlated single photon counting technique. Such high-resolution observations were previously only achievable through in situ aircraft measurements. Even then, aircraft measurements do not permit continuous long-term cloud observation as is possible with ground-based remote sensing instruments. In this study, the first-light cloud observations from the new radar and lidar systems are shown to reveal detailed cloud structures that conventional sensors could only perceive in a bulk sense, thus providing new avenues to investigate cloud microphysical processes and their impact on weather and climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Super Resolution for Renewable Energy Resource Data With Wind From Reanalysis Data (Sup3rWind) and Application to Ukraine [Slides]

In this work we present a novel deep learning-based downscaling method, using generative adversarial networks (GANs), for generating high-resolution wind resource data from ECMWF Reanalysis v5 data (ERA5). We show that by training a GAN model on ERA5, as opposed to coarsened high-resolution data, we achieve results that are competitive with conventional dynamical downscaling. This GAN-based downscaling method additionally reduces computational costs over dynamical downscaling by two orders of magnitude. All GANs are trained on data sampled from CONUS, selected to provide a diverse sampling of terrain conditions, and validated on observational data along with data held out from training. This cross-validation shows low error and high correlations with observations and excellent agreement with hold out data across physical distributions. Our approach is finally used to downscale 30km hourly ERA5 to 2-km 5-minute wind data, for January 2000 through December 2023, at multiple hub heights, over Ukraine, Moldova, and part of Romania. Comparisons against observational data from Meteorological Assimilation Data Ingest System (MADIS) and multiple wind farms show the same level of performance as for CONUS validation. This 24 year data record is the first member of the "super resolution for renewable energy resource data with wind from reanalysis data" dataset (Sup3rWind).

17 WIND ENERGY↗
DOE OSTI2022

Surface Water Mass Transformation in the Southern Ocean: The Role of Eddies Revisited

The water mass transformation (WMT) framework describes how water of one class, such as a discrete interval of density, is converted into another class via air–sea fluxes or interior mixing processes. Here, this paper investigates how this process is modified at the surface when mesoscale ocean eddies are present, using a state-of-the-art high-resolution climate model with reasonable fidelity in the Southern Ocean. The method employed is to coarse-grain the high-resolution model fields to remove eddy signatures, and compare the results with those from the full model fields. This method shows that eddies reduced the WMT by 2–4 Sv (10%–20%; 1 Sv ≡ 10 6 m 3 s −1 ) over a wide range of densities, from typical values of 20 Sv in the smoothed case. The corresponding water mass formation was reduced by 40% at one particular density increment, namely, between 1026.4 and 1026.5 kg m −3 , which corresponds to the lighter end of the range of Indian Ocean Mode Water in the model. The effect of eddies on surface WMT is decomposed into three terms: direct modulation of the density outcrops, then indirectly, by modifying the air–sea density flux, and the combined effect of the two, akin to a covariance. It is found that the first and third terms dominate, i.e., smoothing the outcrops alone has a significant effect, as does the combination of smoothing both outcrops and density flux distributions, but smoothing density flux fields alone has little effect. Results from the coarse-graining method are compared to an alternative approach of temporally averaging the data. Implications for climate model resolution are also discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Expanded Capabilities and Opportunities for Virtual Beamline Code

In the 25 years since LLNL broke ground on the National Ignition Facility (NIF) - a cornerstone of the National Nuclear Security Administration’s Stockpile Stewardship Program - the NIF and Photon Science (NIF&PS) Directorate has steadily pushed the boundaries of laser physics, nonlinear optics, and photonics in service of inertial confinement fusion experiments, and advanced photon sources development. Beyond the 192 beamlines of the primary laser facility with its world-record energy and fusion yields, NIF&PS capabilities have expanded to include chirped-pulse amplification, kilojoule petawatt-class short-pulse systems to generate hard x-ray radiographic probes, high-average power lasers as secondary sources for generation or wake field particle acceleration along directed energy applications, and other scientific pursuits. The Computing Directorate partners with NIF&PS on numerous projects and technologies from diagnostic measurements and high performance control systems to data analysis, information technology infrastructure, and scientific simulation code development. “This strong collaboration enables cutting-edge science, particularly with regard to physics-based modeling and simulation,” says physicist Jean-Michel Di Nicola. One crucial capability for NIF&PS is the Virtual Beamline (VBL) laser simulation code. It can model all the major laser physics and technology involved in the design optimization, commissioning, and operations of advanced laser architectures from tabletop to NIF-scale. VBL provides researchers with high-fidelity models and high-resolution calculations of laser performance predictions—including for the entire NIF laser system, the Advanced Radiographic Capability, parts of the High Repetition-Rate Advanced Petawatt Laser System laser delivered to the Czech Republic, and the Optical Science Laser. After more than two decades of experimentally verified physics and computing enhancements, this unique workhorse code is wrapping up another major milestone: migration from Java to C++ with a flurry of user interface and optimization features, as well as laser physics and high-resolution enhancements thanks to parallel execution on Livermore Computing platforms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Automation of Laser Plasma Focused Ion Beam Microscopy for Next-Gen Energy Materials

Automation can revolutionize the use of ultrafast laser ablation and plasma-focused ion beam (PFIB) techniques for high-throughput, reproducible cross-sectioning and various sample preparation in materials characterization. As these methods become essential for analyzing complex energy materials and next-generation devices, efficient, standardized workflows are needed to minimize variability and enhance precision. This work highlights our advancements in developing automated processes for sample preparation that integrates machine learning, workflow optimization, and large-scale data acquisition to improve efficiency and scalability in applications such as electrolyzers, photovoltaic cells, and microelectronics. To streamline cross-sectioning and lamella fabrication, we have implemented fully automated workflows that standardize laser ablation and PFIB milling sequences. These workflows incorporate pre-programmed protocols for material removal, alignment, and thinning, reducing user intervention and ensuring consistency across different sample types. Machine learning algorithms further enhance automation by predicting optimal milling strategies and adapting parameters based on material properties and sectioning requirements. This approach significantly improves throughput while maintaining the structural integrity of prepared samples for high-resolution imaging and analysis, including transmission electron microscopy. Beyond sample preparation, our automation platform enables the acquisition of large, high-resolution datasets through serial sectioning, image alignment, and 3D reconstruction. These automated routines facilitate multi-scale characterization, capturing structural and compositional details from the nanoscale to the device level. By reducing variability and increasing efficiency, our automated approach enhances defect analysis, failure diagnostics, and process optimization, accelerating advancements in materials research and device engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Hydropower Infrastructure - LAkes, Reservoirs, and RIvers (HILARRI), v4

HILARRI is a database of links between major datasets of operational hydropower dams and powerplants, and inland water bodies. These connections are critical for conducting large-scale analysis of hydropower infrastructure and their associated natural and engineered water systems. Features include: – Dams from the National Inventory of Dams (2025) and the Global Reservoir and Dam Database (GRanD v1.3) – Hydropower plants from the Existing Hydropower Assets dataset (EHA 2025) – Power plants that are listed in the 2025 U.S. Hydropower Development Pipeline Data or were listed in previous versions of the dataset These hydropower infrastructure features are linked to several major datasets that provide hydrologic and hydraulic information relevant for analysis of hydropower systems that includes the integral water resources. That information comes from: – Products from the National Hydrography Dataset (NHD) – NHDPlusV2 Medium Resolution river network flowlines, – NHD waterbodies (limited to lakes and reservoirs), – NHD Watershed Boundary Dataset (HUC12-level for the Conterminous United States (CONUS)) – NHD High Resolution waterbodies – HydroLAKES water bodies (lakes and reservoirs) – LAGOS-US lakes and reservoirs – EPA National Lakes Assessment (2007, 2012, 2017, and 2022) – The Reservoir Sedimentation Database (RESSED) – EPA SuRGE sampling locations Unique identifiers are used to facilitate joining to the original full datasets. For example, characteristics of NHD flowlines such as estimated average flow rate can be joined from the NHDPlusV2 dataset to a dam or power plant listed in HILARRI based on the ID field, “COMID”, that is common to both datasets. HILARRI only includes basic information about identifiers, location, and data quality or usage notes. It does not contain the attributes or time series data associated with these sites. The HILARRI dataset incorporates information from several datasets to facilitate more effective and accurate analysis of hydropower infrastructure and their associated waterbodies. For example, dams were checked against the most recent American Rivers Dam Removal Database to identify and flag facilities that may no longer exist. Additionally, dams that are listed multiple times in the NID are identified and flagged to avoid double-counting when analyzing and summarizing information. Other quality flags include certainty of operational hydropower (i.e., if one or more datasets indicates hydropower at a particular location), whether an associated water body is accurate or composed of multiple polygons, or whether there is a known issue with reported characteristics in one of the underlying datasets. These additional data flags are designed to increase confidence in data usage for individual to large-scale analyses.

Hansen, Carly [ORNL] (ORCID:0000000193280838)↗
DOE OSTI2021

Whole-organism 3D quantitative characterization of zebrafish melanin by silver deposition micro-CT

We previously described X-ray histotomography, a high-resolution, non-destructive form of X-ray microtomography (micro-CT) imaging customized for three-dimensional (3D), digital histology, allowing quantitative, volumetric tissue and organismal phenotyping (Ding et al., 2019). Here, we have combined micro-CT with a novel application of ionic silver staining to characterize melanin distribution in whole zebrafish larvae. The resulting images enabled whole-body, computational analyses of regional melanin content and morphology. Normalized micro-CT reconstructions of silver-stained fish consistently reproduced pigment patterns seen by light microscopy, and further allowed direct quantitative comparisons of melanin content across wild-type and mutant samples, including subtle phenotypes not previously noticed. Silver staining of melanin for micro-CT provides proof-of-principle for whole-body, 3D computational phenomic analysis of a specific cell type at cellular resolution, with potential applications in other model organisms and melanocytic neoplasms. Advances such as this in whole-organism, high-resolution phenotyping provide superior context for studying the phenotypic effects of genetic, disease, and environmental variables.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A new μ -high energy resolution fluorescence detection microprobe imaging spectrometer at the Stanford Synchrotron Radiation Lightsource beamline 6-2

In this report we describe a new synchrotron X-ray Fluorescence (XRF) imaging instrument with an integrated High Energy Fluorescence Detection X-ray Absorption Spectroscopy (HERFD-XAS) spectrometer at the Stanford Synchrotron Radiation Lightsource at beamline 6-2. The X-ray beam size on the sample can be defined via a range of pinhole apertures or focusing optics. XRF imaging is performed using a continuous rapid scan system with sample stages covering a travel range of 250 × 200 mm 2 , allowing for multiple samples and/or large samples to be mounted. The HERFD spectrometer is a Johann-type with seven spherically bent 100 mm diameter crystals arranged on intersecting Rowland circles of 1 m diameter with a total solid angle of about 0.44% of 4π sr. A wide range of emission lines can be studied with the available Bragg angle range of ~64.5°–82.6°. With this instrument, elements in a sample can be rapidly mapped via XRF and then selected features targeted for HERFD-XAS analysis. Furthermore, utilizing the higher spectral resolution of HERFD for XRF imaging provides better separation of interfering emission lines, and it can be used to select a much narrower emission bandwidth, resulting in increased image contrast for imaging specific element species, i.e., sparse excitation energy XAS imaging. This combination of features and characteristics provides a highly adaptable and valuable tool in the study of a wide range of materials.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Pressure cells for in situ neutron total scattering: time and real-space resolution during deuterium absorption

In situ gas-loading sample holders for two-dimensionally arranged detectors in time-of-flight neutron total scattering experiments have been developed to investigate atomic arrangements during deuterium absorption using time and real-space resolution. A single-crystal sapphire container was developed that allows conditions of 473 K and 10 MPa hydrogen gas pressure. High-resolution transient measurements detected deuterium absorption by palladium that proceeded within a few seconds. A double-layered container with thick- and thin-walled vanadium allowed conditions of 423 K and 10 MPa hydrogen gas pressure. The deuterium occupation sites of a lanthanum–nickel–aluminium alloy are discussed in detail on the basis of real-space high-resolution data obtained from in situ neutron scattering measurements and reverse Monte Carlo structural modeling.

08 HYDROGEN↗
DOE OSTI2023

Clear-Sky Probability for the 2023 Annular Solar Eclipse and the 2024 Total Solar Eclipse Using the NREL National Solar Radiation Database

The National Renewable Energy Laboratory (NREL) and collaborators have created a clear-sky probability analysis to help guide viewers to the 2023 annular solar eclipse and the 2024 total solar eclipse. Using cloud and solar data from the NREL National Solar Radiation Database (NSRDB), the analysis provides cloudless-sky probabilities specific to the date, time, and location of each eclipse with a 4-km resolution. Though not intended to be an eclipse weather forecast, the detailed maps can help guide eclipse enthusiasts to likely optimal viewing locations. Additionally, high-resolution data are presented for the centerline of the path of each eclipse, representing the likelihood for cloudless skies and atmospheric clarity. The NSRDB provides industry, academia, and other stakeholders with high-resolution solar irradiance data to support feasibility analyses for photovoltaic and concentrating solar power generation projects.

14 SOLAR ENERGY↗
DOE OSTI2020

ADC Nonlinearity Correction for the Majorana Demonstrator

Imperfections in analog-to-digital conversion cannot be ignored when signal digitization requirements demand both wide dynamic range and high resolution, as is the case for the MAJORANA DEMONSTRATOR 76 Ge neutrinoless double beta decay search. Enabling the experiment's high-resolution spectral analysis and efficient pulse shape discrimination required careful measurement and correction of ADC nonlinearites. Here, a simple measurement protocol was developed that did not require sophisticated equipment or lengthy data taking campaigns. A slope-dependent hysteresis was observed and characterized. A correction applied to digitized waveforms prior to signal processing reduced the differential and integral nonlinearites by an order of magnitude, eliminating these as dominant contributions to the systematic energy uncertainty at the double-beta decay Q value.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗