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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

24.1.3.1.1 - Frisch Grid CZT Spectrometer

Brookhaven National Laboratory (BNL) worked with FLIR System Inc., the manufacturer of the nanoRAIDER, to develop a handheld field deployable detector based on the novel position-sensitive virtual Frisch-grid (VFG) Cadmium-Zinc-Telluride (CdZnTe or CZT) detectors (with 1% FWHM at 662 keV or better energy resolution). The detector called nanoRAIDER-VFG would be an improvement to the current nanoRAIDER, which is a compact gamma-ray detection instrument manufactured by FLIR Systems Inc. that employs relatively lower-performing CZT hemispheric detectors (i.e., 3%-FWHM CZT detectors). The nanoRAIDER-VFG would have significantly improved accuracy of measurements while maintaining similar efficiency, as compared to the nanoRAIDER, for in-field analysis of nuclear materials and detection of undeclared activities during inspections conducted by the International Atomic Energy Agency (IAEA). Since the nanoRAIDER is currently used by the IAEA as part of its Complementary Access toolkit, a relatively quick acceptance of the nanoRAIDER-VFG for safeguards was anticipated. The nanoRAIDER-VFG project was undertaken to address the following items in the IAEA's Long-Term R&D Plan, 2012-2023: 2.2 (elemental and isotopic signatures of fuel cycle processes); 2.3 (detect signatures of undeclared activity and improve analysis); and 2.6 (detect process emanations). The high energy-resolution of the nanoRAIDER-VFG would also have had applicability to 3.2 (fissile content of metal mixtures containing actinides Np, Am, etc.). The project was not completed due to a change in priorities within FLIR.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Holistic digital gamma-ray spectroscopy methods and instrumentation for high-throughput high-resolution applications

Method of real-time adaptive digital pulse signal processing for high count rate gamma-ray spectroscopy applications includes receiving a preamplifier signal at a pulse deconvolver, the preamplifier signal including resolution deterioration resulting from pulse pile-up. The method further includes generating a deconvoluted signal, by the pulse deconvolver, from the preamplifier signal, the deconvoluted signal having less resolution deterioration as compared to the received preamplifier signal. The method furthermore includes shaping of the deconvoluted signal by a trapezoid filter, the shaping comprising adjusting a shaping parameter of the trapezoid filter for an incoming signal based on a time separation from a subsequent incoming signal.

Hawari, Ayman I.↗
DOE OSTI2021

Coupled Air Quality and Boundary-Layer Meteorology in Western U.S. Basins during Winter: Design and Rationale for a Comprehensive Study

The wintertime episodes of high aerosol concentrations occur frequently in urban and agricultural basins and valleys worldwide. These episodes often arise following development of persistent cold-air pools (PCAPs) that limit mixing and modify chemistry. While field campaigns targeting either basin meteorology or wintertime pollution chemistry have been conducted, coupling between interconnected chemical and meteorological processes remains an insufficiently studied research area. Gaps in understanding the coupled chemical–meteorological interactions that drive high-pollution events make identification of the most effective air-basin specific emission control strategies challenging. To address this, a September 2019 workshop occurred with the goal of planning a future research campaign to investigate air quality in western U.S. basins. Approximately 120 people participated, representing 50 institutions and five countries. Workshop participants outlined the rationale and design for a comprehensive wintertime study that would couple atmospheric chemistry and boundary layer and complex-terrain meteorology within western U.S. basins. Participants concluded the study should focus on two regions with contrasting aerosol chemistry: three populated valleys within Utah (Salt Lake, Utah, and Cache Valleys) and the San Joaquin Valley in California. This paper describes the scientific rationale for a campaign that will acquire chemical and meteorological datasets using airborne platforms with extensive range, coupled to surface-based measurements focusing on sampling within the near-surface boundary layer, and transport and mixing processes within this layer, with high vertical resolution at a number of representative sites. No prior wintertime basin-focused campaign has provided the breadth of observations necessary to characterize the meteorological–chemical linkages outlined here, nor to validate complex processes within coupled atmosphere–chemistry models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Engineering Assembly Kinetics and Line Roughness in Solvent Vapor-Annealed Block Copolymer/Homopolymer Blends

Block copolymer (BCP) directed self-assembly (DSA) is a promising route to enhance lithography resolution by multiplying nanopattern density and reducing feature roughness. Eliminating kinetically trapped self-assembly defects requires fast self-assembly. However, acceleration strategies like solvent vapor annealing or homopolymer blending broaden domain interfaces, implying a trade-off in increased feature roughness. In this work, we experimentally investigate this apparent dilemma between self-assembly kinetics and line roughness for solvent vapor-annealed thin films of a lamellar poly(styrene-block-2-vinylpyridine) (PS-b-P2VP) BCP blended with PS and P2VP homopolymers. Binary blends with PS or P2VP homopolymers and ternary blends incorporating both in equal weight fractions were solvent vapor annealed using acetone, a near-neutral solvent for PS and P2VP, followed by P2VP-selective vapor-phase infiltration with alumina (AlOx) and polymer etching. Binary blends with P2VP exhibit a modest kinetic enhancement but also higher line-edge and -width roughness due to the increased frequency of P2VP protrusions and bridge defects in the alumina line patterns. In contrast, binary blends with PS self-assemble noticeably faster, while domain asymmetry from the added PS homopolymer reduces roughness by curbing the number of alumina protrusions and bridge defects. Ternary blends maintain DSA line patterns across a wider composition window and, at higher homopolymer loadings, reduce roughness at length scales near the lamellar period, consistent with a reduced impact of intradomain compositional fluctuations. These findings provide important insights for codesigning blend compositions and process flows to achieve high-resolution, defect free patterns with minimal roughness through BCP DSA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A HPC Theory-Guided Machine Learning Cyberinfrastructure for Communicating Hydrometeorological Data Across Scales

High-resolution predictions of hydrometeorological variables are critical for supporting hydropower generation decisions and flood control at hydroelectric power plants. Traditional climate and hydrologic models rely on the numerical simulation of detailed physical processes. Therefore, running these simulations is time-, labor-, and computation-intensive. Improving the spatial and temporal resolution in these modeling outputs could lead to cubic increases in both the simulation time and computational demands, rendering high-resolution hydrometeorological predictions expensive and impractical. Many past studies apply the super resolution (SR) technique to downscale climate models using deep learners. However, deep learners are deemed “black-boxes,” as their derivation processes from low-resolution outputs to high-resolution outputs are often hidden. Their results are difficult for domain scientists to interpret and validate. Thus, there is a need for an exploratory machine learning approach that can partially integrate domain-specific theory and knowledge into the data-driven mapping process between simulation outputs of different spatial scales. The domain-specific theory and knowledge can be incorporated into the data model through an inductive approach in which process-related environmental variables are used and analyzed as key drivers (i.e., environmental surrogates) to reflect the complex physical processes. Many of these variables, such as land use land cover, soil types, topography, digital elevation, air temperature, and various watershed characteristics, can be directly measured through sensors or remote sensing techniques. Additionally, SR applications that can downscale hydrological and hydrodynamics models to efficiently produce high-resolution (1 m) flood depth grids are still rare. Since the flood depth grid can be used to support critical decisions for flood control operation at hydroelectric power plants, it is crucial to enable an SR-based capability for interpolating high-resolution flood inundation maps.

13 HYDRO ENERGY↗
DOE OSTI2022

Non‐Linear Dimensionality Reduction With a Variational Encoder Decoder to Understand Convective Processes in Climate Models

Abstract Deep learning can accurately represent sub‐grid‐scale convective processes in climate models, learning from high resolution simulations. However, deep learning methods usually lack interpretability due to large internal dimensionality, resulting in reduced trustworthiness in these methods. Here, we use Variational Encoder Decoder structures (VED), a non‐linear dimensionality reduction technique, to learn and understand convective processes in an aquaplanet superparameterized climate model simulation, where deep convective processes are simulated explicitly. We show that similar to previous deep learning studies based on feed‐forward neural nets, the VED is capable of learning and accurately reproducing convective processes. In contrast to past work, we show this can be achieved by compressing the original information into only five latent nodes. As a result, the VED can be used to understand convective processes and delineate modes of convection through the exploration of its latent dimensions. A close investigation of the latent space enables the identification of different convective regimes: (a) stable conditions are clearly distinguished from deep convection with low outgoing longwave radiation and strong precipitation; (b) high optically thin cirrus‐like clouds are separated from low optically thick cumulus clouds; and (c) shallow convective processes are associated with large‐scale moisture content and surface diabatic heating. Our results demonstrate that VEDs can accurately represent convective processes in climate models, while enabling interpretability and better understanding of sub‐grid‐scale physical processes, paving the way to increasingly interpretable machine learning parameterizations with promising generative properties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Debunking common myths in coastal circulation modeling

Despite tremendous progress in algorithm development, computational efficiency and transition into operations over the past two decades, coastal modeling still lacks scientific rigor due to proliferation of many ‘gray’ areas related to various modeling choices made by modelers. Here, in this paper, we propose some guiding principles for the modeling community to improve performance, and we also debunk commonly held myths that make the coastal modeling lack rigor. Using our own experience in developing seamless cross-scale unstructured-grid based models for the past two decades, we describe in unprecedented detail the end-to-end modeling process (i.e., from digital elevation models (DEMs) to mesh generation to post analysis), and demonstrate that defensible modeling is within reach for any end user by following three guiding principles: (1) Bathymetry is a first order forcing in coastal domains and thus should be respected in all aspects of modeling; (2) Oceanographic processes are driven across multiple spatial scales and so models should enable appropriate resolution as needed; and (3) Model assessment should focus on physical processes. Through qualitative and quantitative model assessments, we demonstrate the fundamental role played by bathymetry/topography as embedded in DEMs in making the results defensible, which is unfortunately glossed over in many modeling studies. Focusing on process-based assessment simplifies the calibration process. A major conclusion of this work is that model developers and operators should maximize the scientific rigor for in silico oceanography by avoiding some common pitfalls that rely on error compensation at the expense of representation of physical system processes. We present some best practice procedures for defensive and trustworthy numerical modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Scalable Nanoimprint Manufacturing of Functional Multilayer Metasurface Devices

Optical metasurfaces, consisting of subwavelength-scale meta-atom arrays, hold great promise of overcoming the fundamental limitations of conventional optics. Due to their structural complexity, metasurfaces usually require high-resolution yet slow and expensive fabrication processes. Here, using a metasurface polarimetric imaging device as an example, the photonic structures and the Nanoimprint lithography (NIL) processes are designed, creating two separate NIL molds over a patterning area of > 20 mm2 with designed Moiré alignment markers by electron-beam writing, and further subsequently integrate silicon and aluminum metasurface structures on a chip. Uniquely, the silicon and aluminum metasurfaces are fabricated by using the nanolithography and 3D pattern-transfer capabilities of NIL, respectively, achieving nanometer-scale linewidth uniformity, sub-200 nm translational overlay accuracy, and <0.017 rotational alignment error while significantly reducing fabrication complexity and surface roughness. Here, the micro-sized multilayer metasurfaces have high circular polarization extinction ratios as large as ≈20 and ≈80 in blue and red wavelengths. Further, the metasurface chip-integrated CMOS imager demonstrates high accuracy in broad-band, full Stokes parameter analysis in the visible wavelength ranges and single-shot polarimetric imaging. This novel, NIL-based, multilayered nanomanufacturing approach is applicable to the scalable production of large-area functional structures for ultra-compact optic, electronic, and quantum devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Photocaged functional nucleic acids for spatiotemporal imaging in biology

Imaging of species in living organisms with high spatiotemporal resolution is essential for understanding biological processes. While functional nucleic acids (FNAs), such as catalytic nucleic acids and aptamers, have emerged as effective sensors for a wide range of molecules, photocaged control of these FNAs has played a key role in translating them into bioimaging agents with high spatiotemporal control. In this paper, we summarize methods and results of photocaged FNAs based on photolabile modifications, photoisomerization, and photothermal activation. Future directions, including strategies to improve the performance of these photocaged FNAs, are also described.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Field surveying data of low-cost networked flood sensors in southeast Texas

Floods are common natural disasters worldwide and pose substantial risks to life, property, food production, and natural resources. Effective measures for flood mitigation and warning are essential. Southeast Texas is still at significant risk of flooding, and Lamar University is assisting the region with asset management of a flood sensor network for flooding events. This network provides real-time water stage information. Lamar University developed a survey program to measure elevation and coordinates at each sensor site location to make this data more useful for flood monitoring and mapping. This paper overviews the measurement of the elevation and coordinates of 74 networked flood sensors and various flood stage thresholds at critical points that flood decision-makers can use for reference at each site. In the first phase of this program, these sensors were deployed throughout a 7-county region spanning nearly 6,000 square miles in Southeast Texas. The latitude and longitude of the sensors and their elevations were determined using survey-grade Global Navigation Satellite System (GNSS) technology. Various Continually Operating Reference Stations (CORS) were utilized for post-processing to achieve sub-inch resolution. The flood stage thresholds, water level sensors elevation, and the elevations and positions of other critical surrounding points are viewable to the public through two online repositories and a web-based sensor management dashboard. The data is used to aid with decisions related to road closures or modeling efforts by mitigation decision-makers, emergency managers, and the public, including the Texas Department of Transportation, Houston Transtar, the National Weather Service, and the Sabine River Authority of Texas (SRA).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Potential for constraining sequence stratigraphy and cycle stratigraphy with U-Pb dating of carbonates

Studies of sequence stratigraphy and cycle stratigraphy in carbonate formations increasingly improve our understanding of depositional systems and basinal to global correlations. However, there is still a scarcity of dated sequences to determine the time length of sequences and cycles. Furthermore, the durations of sequences and cycles provide tests of the processes that produce them. Poor age resolution mostly stems from the lack of recognizable volcanic ash deposits in many sections. Through continuing advances in analytical techniques and approaches to sampling, the current state of Usingle bondPb dating of carbonate sedimentary rocks provides opportunities to fill in age gaps. The approach should build on well-constrained 3-dimensional stratigraphic architectures and diagenetic stratigraphies.

58 GEOSCIENCES↗
DOE OSTI2025

Open-air spray deposition of PCBM/BCP electron transport layer for inverted perovskite solar cells

A [6,6]-phenyl C61 butyric acid methyl ester (PCBM) and bathocuproine (BCP) electron transport layer (ETL) is spray deposited in open air directly on top of a perovskite at linear speeds of 9 m/min. The PCBM precursor ink contains a binary mixture of 1:1 chlorobenzene:chloroform, which optimizes spray wettability on the perovskite surface and allows quick solvent evaporation. A near-infrared heating module additionally provides a flash cure (<5 s) for the formation of smooth, large-area PCBM films (∼20 cm 2 ). A BCP solution in isopropanol is subsequently sprayed to form an ultrathin (<5 nm) film and characterized with a suite of high-resolution metrologies. The spray-deposition processing and near-infrared treatment do not damage the underlying perovskite. Inverted architecture devices containing the sprayed ETL achieve a champion efficiency of 20.3% and demonstrate stable performance without additional interlayers or surface treatments. Here, the technoeconomic cost of the open-air spray process is compared against traditional vacuum-based evaporation, resulting in a decrease in manufacturing costs by 26%.

14 SOLAR ENERGY↗
DOE OSTI2022

The DOE E3SM v1.2 Cryosphere Configuration: Description and Simulated Antarctic Ice‐Shelf Basal Melting

Abstract The processes responsible for freshwater flux from the Antarctic Ice Sheet (AIS), ice‐shelf basal melting and iceberg calving, are generally poorly represented in current Earth System Models (ESMs). Here we document the cryosphere configuration of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) v1.2. This includes simulating Antarctic ice‐shelf basal melting, which has been implemented through simulating the ocean circulation within static Antarctic ice‐shelf cavities, allowing for the ability to calculate ice‐shelf basal melt rates from the associated heat and freshwater fluxes. In addition, we added the capability to prescribe forcing from iceberg melt, allowing for realistic representation of the other dominant mass loss process from the AIS. In standard resolution simulations (using a noneddying ocean) under preindustrial climate forcing, we find high sensitivity of modeled ocean/ice shelf interactions to the ocean state, which can result in a transition to a high basal melt regime under the Filchner‐Ronne Ice Shelf (FRIS), presenting a significant challenge to representing the ocean/ice shelf system in a coupled ESM. We show that inclusion of a spatially dependent parameterization of eddy‐induced transport reduces biases in water mass properties on the Antarctic continental shelf. With these improvements, E3SM produces realistic ice‐shelf basal melt rates across the continent that are generally within the range inferred from observations. The accurate representation of ice‐shelf basal melting within a coupled ESM is an important step toward reducing uncertainties in projections of the Antarctic response to climate change and Antarctica's contribution to global sea‐level rise.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

DASEventNet: AI‐Based Microseismic Detection on Distributed Acoustic Sensing Data From the Utah FORGE Well 16A (78)‐32 Hydraulic Stimulation

Abstract Distributed acoustic sensing (DAS) has emerged as a promising seismic technology for monitoring microearthquakes (MEQs) with high spatial resolution. Efficient algorithms are needed for processing large DAS data volumes. This study introduces a deep learning (DL) model based on a Residual Convolutional Neural Network (ResNet) for detecting MEQs using DAS data, named as DASEventNet. The test data were collected from the Utah FORGE 16A (78)‐32 hydraulic stimulation experiments conducted in April 2022. The DASEventNet model achieves a remarkable accuracy of 100% when discriminating MEQs from noise in the raw test set of 260 examples. Surprisingly, the model identified weak MEQ signatures that have been manually categorized as noise. The decision‐making process with the model is decoded by the classic activation map, which illuminates learning features of the DASEventNet model. These features provide clear illustrations of weak MEQs and varied noise types. Finally, we apply the trained model to the entire period (∼7 days) of continuous DAS recordings and find that it discovers >5,700 new MEQs, previously unregistered in the public Silixa DAS catalog. The DASEventNet model significantly outperforms the traditional seismic method Short‐Term Average/Long‐Term Average (STA/LTA), which detected only 1,307 MEQs. The DASEventNet detection threshold is M w −1.80 compared to the minimum magnitude of M w −1.14 detected by STA/LTA. The spatiotemporal distribution of the newly identified MEQs defines an extensive stimulation zone and more accurately characterizes fracture geometry. Our results highlight the potential of DL for long‐term, real‐time microseismic monitoring that can improve enhanced geothermal systems and other activities that include subsurface hydraulic fracturing.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Resolving Mesoscale Convective Systems: Grid Spacing Sensitivity in the Tropics and Midlatitudes

Abstract Mesoscale convective systems (MCSs) are a critical global water cycle component and drive extreme precipitation events in tropical and midlatitude regions. However, simulating deep convection remains challenging for modern numerical weather and climate models due to the complex interactions of processes from microscales to synoptic scales. Recent models with kilometer‐scale horizontal grid spacings offer notable improvements in simulating deep convection compared to coarser‐resolution models. Still, deficiencies in representing key physical processes, such as entrainment, lead to systematic biases. Additionally, evaluating model outputs using process‐oriented observational data remain difficult. This study presents an ensemble of MCS simulations with spanning the deep convective gray zone ( from 12 km to 125 m) in the Southern Great Plains of the U.S. and the Amazon Basin. Comparing these simulations with Atmospheric Radiation Measurement (ARM) wind profiler observations, we find greater sensitivity in the Amazon Basin compared to the Great Plains. Convective drafts converge structurally at sub‐kilometer scales, but some deficiencies remain. In both regions, simulated up and downdrafts are too deep and extreme downdrafts are not strong enough. Furthermore, Amazonian updrafts are too strong. Overall, we observe higher sensitivity in the tropics, including an artificial buildup in vertical kinetic energy at scales of , suggesting a need for 250 m in this region. Nevertheless, bulk convergence—agreement of storm‐average statistics—is achievable with kilometer‐scale simulations within a 10% error margin with 1 km providing a good balance between accuracy and computational cost.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Ultrafast nano-imaging and nano-spectroscopy

Ultrafast pump–probe nano-imaging combines scanning probe-based optical near-field microscopy with ultrafast spectroscopy to enable imaging with deep sub-wavelength spatial resolution, femtosecond temporal resolution and simultaneous spectral resolution. Ultrafast nano-imaging has gained increased attention for its ability to provide far-from-equilibrium excitation and excited-state contrast. With coherent and nonlinear probing, coupled electron, spin and lattice dynamics on elementary timescale and length scale can be resolved. Through nano-movies, ultrafast nano-imaging visualizes correlated quantum dynamics underlying the properties of solid-state materials, semiconductors, molecular electronic, photonic, photovoltaic and other functional materials. With nanometre spatial resolution, this method probes elementary dynamic processes across multiple length scales that are otherwise obscured in conventional ultrafast spectroscopy in which heterogeneities are spatially averaged. Furthermore, this Primer describes the theoretical background and experimental implementation of ultrafast nano-imaging; signal interpretation and modelling; representative examples and a perspective for the future development of the field.

Microscopy↗
DOE OSTI2026

A Bayesian desmearing algorithm for Bonse–Hart USANS with anisotropic scattering

Ultra-small-angle neutron scattering (USANS) using Bonse–Hart optics provides micrometer-scale structural insights but suffers from severe slit-geometry smearing. While well-established for isotropic systems, quantitative desmearing of anisotropic data remains a challenge because conventional corrections break down for non-radial scattering. In this work, we address this by developing a resolution-aware Bayesian framework that explicitly incorporates anisotropy via an affine deformation to the scattering pattern, guided by the principle of parsimony. This results in orientation-resolved point-spread functions that enable a self-consistent determination of both the resolution and deformation parameters. Using Gaussian process regression with uncertainty quantification and a probabilistic correction for multiple scattering, we demonstrate the framework’s effectiveness through numerical benchmarks and experimental studies of a stretched polymer melt. Our approach enables the seamless integration of SANS and USANS data, facilitating quantitative structural analysis of deformed materials at nanometer to micrometer scales.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Vibration-Damping Properties of 3D-Printed Auxetic Structures

Two-photon polymerization is a recently developed technique that is used to print millimeter-size cellular structures with micrometer resolution. The two-photon polymerization process discussed in this paper is used to build structures to stabilize direct-drive targets that are imploded at cryogenic temperatures. These targets are supported by a very thin stalk (10 to 18 µm diameter) that can be broken (or dislodged) by vibrations that occur when the target is transported or when the cryogenic shroud is removed. And any vibration at the moment of implosion affects how precisely the target is aligned to the focus of the laser beams. Finally, this study investigates the mechanical properties of different millimeter-sized cellular auxetic structures (~0.2 g/cm 3 ) at room and cryogenic temperatures (20°C and −140°C) and how well the most promising structure dampens vibrations at room temperature.

auxetic structures↗