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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Cloud processing and weeklong ageing affect biomass burning aerosol properties over the south-eastern Atlantic

Abstract Southern Africa produces a third of global biomass burning emissions, which have a long atmospheric lifetime and influence regional radiation balance and climate. Here, we use airmass trajectories to link different aircraft observations to investigate the evolution of biomass-burning aerosols during their westward transport from Southern Africa over the south-eastern Atlantic, where a semi-permanent stratocumulus cloud deck is located. Our results show secondary organic aerosol formation during the initial 3 days of transport, followed by decreases in organic aerosol via photolysis before reaching equilibrium. Aerosol absorption wavelength dependency decreases with ageing, due to an increase in particle size and photochemical bleaching of brown carbon. Cloud processing, including aqueous-phase reaction and scavenging, contributes to the oxidation of organic aerosols, while it strongly reduces large diameter particles and single-scattering albedo of biomass burning aerosols. Together, these processes resulted in a marine boundary layer with fewer yet more oxidized and absorbing aerosols.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

DISTEMA: distance map-based estimation of single protein model accuracy with attentive 2D convolutional neural network

Abstract Background Estimation of the accuracy (quality) of protein structural models is important for both prediction and use of protein structural models. Deep learning methods have been used to integrate protein structure features to predict the quality of protein models. Inter-residue distances are key information for predicting protein’s tertiary structures and therefore have good potentials to predict the quality of protein structural models. However, few methods have been developed to fully take advantage of predicted inter-residue distance maps to estimate the accuracy of a single protein structural model. Result We developed an attentive 2D convolutional neural network (CNN) with channel-wise attention to take only a raw difference map between the inter-residue distance map calculated from a single protein model and the distance map predicted from the protein sequence as input to predict the quality of the model. The network comprises multiple convolutional layers, batch normalization layers, dense layers, and Squeeze-and-Excitation blocks with attention to automatically extract features relevant to protein model quality from the raw input without using any expert-curated features. We evaluated DISTEMA’s capability of selecting the best models for CASP13 targets in terms of ranking loss of GDT-TS score. The ranking loss of DISTEMA is 0.079, lower than several state-of-the-art single-model quality assessment methods. Conclusion This work demonstrates that using raw inter-residue distance information with deep learning can predict the quality of protein structural models reasonably well. DISTEMA is freely at https://github.com/jianlin-cheng/DISTEMA

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Distinct regional meteorological influences on low-cloud albedo susceptibility over global marine stratocumulus regions

Abstract. Marine stratocumuli cool the Earth effectively due to their high reflectance of incoming solar radiation and persistent occurrence. The susceptibility of cloud albedo to droplet number concentration perturbations depends strongly on large-scale meteorological conditions. Studies focused on the meteorological dependence of cloud adjustments often overlook the covariability among meteorological factors and their geographical and temporal variability. We use 8 years of satellite observations sorted by day and geographical location to show the global distribution of marine low-cloud albedo susceptibility. We find an overall cloud brightening potential for most marine warm clouds, which is more pronounced over subtropical coastal regions. A weak cloud darkening potential in the annual mean is evident over the remote SE Pacific and SE Atlantic. We show that large-scale meteorological fields from the ERA5 reanalysis data, including lower-tropospheric stability, free-tropospheric relative humidity, sea surface temperature, and boundary layer depth, have distinct covariabilities over each of the eastern subtropical ocean basins where marine stratocumuli prevail. This leads to a markedly different annual cycle in albedo susceptibility over each basin. Moreover, we find that basin-specific regional relationships between key meteorological factors and albedo susceptibilities are absent in a global analysis. Our results stress the importance of considering the geographical distinctiveness of temporal meteorological covariability when scaling up the local-to-global response of cloud albedo to aerosol perturbations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

How to GIWAXS: Grazing Incidence Wide Angle X‐Ray Scattering Applied to Metal Halide Perovskite Thin Films

Abstract The frequency of reports utilizing synchrotron‐based grazing incident wide angle X‐ray scattering (GIWAXS) to study metal halide perovskite thin films has exploded recently, as this technique has proven invaluable for understanding several structure‐property relationships that fundamentally limit optoelectronic performance. The GIWAXS geometry and temporal resolution are also inherently compatible with in situ and operando setups (including ISOS protocols), and a relatively large halide perovskite research community has deployed GIWAXS to unravel important kinetic and dynamic features in these materials. Considering its rising popularity, the aim here is to accelerate the required learning curve for new experimentalists by clearly detailing the underlying analytical concepts which can be leveraged to maximize GIWAXS studies of polycrystalline thin films and devices. Motivated by the vast range of measurement conditions offered, together with the wide variety of compositions and structural motifs available (i.e., from single‐crystal and polycrystalline systems, to quantum dots and layered superlatices), a comprehensive framework for conducting effective GIWAXS experiments is outlined for different purposes. It is anticipated that providing a clear perspective for this topic will help elevate the quality of future GIWAXS studies—which have become routine—and provide the impetus required to develop novel GIWAXS approaches to resolve unsettled scientific questions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A correlation between grain boundary character and deformation twin nucleation mechanism in coarse-grained high-Mn austenitic steel

Abstract In polycrystalline materials, grain boundaries are known to be a critical microstructural component controlling material’s mechanical properties, and their characters such as misorientation and crystallographic boundary planes would also influence the dislocation dynamics. Nevertheless, many of generally used mechanistic models for deformation twin nucleation in fcc metal do not take considerable care of the role of grain boundary characters. Here, we experimentally reveal that deformation twin nucleation occurs at an annealing twin (Σ3{111}) boundary in a high-Mn austenitic steel when dislocation pile-up at Σ3{111} boundary produced a local stress exceeding the twining stress, while no obvious local stress concentration was required at relatively high-energy grain boundaries such as Σ21 or Σ31. A periodic contrast reversal associated with a sequential stacking faults emission from Σ3{111} boundary was observed by in-situ transmission electron microscopy (TEM) deformation experiments, proving the successive layer-by-layer stacking fault emission was the deformation twin nucleation mechanism, different from the previously reported observations in the high-Mn steels. Since this is also true for the observed high Σ-value boundaries in this study, our observation demonstrates the practical importance of taking grain boundary characters into account to understand the deformation twin nucleation mechanism besides well-known factors such as stacking fault energy and grain size.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Filament Formation in TaO x Thin Films for Memristor Device Application: Modeling Electron Energy Loss Spectra and Electron Transport

Abstract Although understanding filament formation in oxide‐based memristive devices by theory has emerged, there are still fundamental unanswered questions. Importantly, for practical application of thin films the material in its amorphous state is to be considered, but mostly lacking so far, and details on sub‐stoichiometry are also scarce. To gain insight into the optical and electronic properties of sub‐stoichiometric amorphous tantalum oxide (TaO x ), the electron energy loss spectrum (EELS) of model systems is characterized theoretically and electron transport characteristics are analyzed in detail. Calculated blue‐shifts by increasing sub‐stoichiometry explained the measurements, potentially suggesting estimation of oxygen vacancy concentrations through EEL spectra. Electron transport results based on TaO x material models validated by EELS measurements show that oxygen vacancy filamentary paths are initiated at low bias upon increasing sub‐stoichiometry yet noting an interplay with the local amorphous structure. Contact resistances at interfaces of the TaO x switching layer and a tantalum scavenging layer or titanium nitride electrode are quantified, indicating the possibility for either oxygen vacancy‐ or metal cluster‐based conduction mechanisms at the interface. The computational work, combined with experimental characterization for validation, provides a basis for investigating effects of sub‐stoichiometry on filament formation in TaO x thin film memristive devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

High‐Loading Lithium‐Sulfur Batteries with Solvent‐Free Dry‐Electrode Processing

Abstract Lithium‐sulfur (Li‐S) batteries, with their high energy density, nontoxicity, and the natural abundance of sulfur, hold immense potential as the next‐generation energy storage technology. To maximize the actual energy density of the Li‐S batteries for practical applications, it is crucial to escalate the areal capacity of the sulfur cathode by fabricating an electrode with high sulfur loading. Herein, ultra‐high sulfur loading (up to 12 mg cm −2 ) cathodes are fabricated through an industrially viable and sustainable solvent‐free dry‐processing method that utilizes a polytetrafluoroethylene binder fibrillation. Due to its low porosity cathode architecture formed by the binder fibrillation process, the dry‐processed electrodes exhibit a relatively lower initial capacity compared to the slurry‐processed electrode. However, its mechanical stability is well maintained throughout the cycling without the formation of electrode cracking, demonstrating significantly superior cycling stability. Additionally, through the optimization of the dry‐processing, a single‐layer pouch cell with a loading of 9 mg cm −2 and a novel multi‐layer pouch cell that uses an aluminum mesh as its current collector with a total loading of 14 mg cm −2 are introduced. To address the reduced initial capacity of dry‐processed electrodes, strategies such as incorporating electrocatalysts or employing prelithiated active materials are suggested.

Chemistry↗
DOE OSTI2023

Wind Fields in Category 1–3 Tropical Cyclones Are Not Fully Represented in Wind Turbine Design Standards

Abstract Offshore wind energy deployment in the U.S. is expected to increase in the years to come, with proposed wind farm sites located in regions with high risk for tropical cyclones. Yet, the wind turbine design criteria outlined by the International Electrotechnical Commission for extreme events may not account for wind field characteristics unique to tropical cyclones. To evaluate if current design standards capture the extreme conditions of these storms, we perform idealized large‐eddy simulations of three tropical cyclones (one Category 1, one Category 2, and one Category 3 storms) using the Weather Research and Forecasting model. Wind conditions near the eyewall of Cat‐1, Cat‐2, and Cat‐3 storms can exceed current design standards for offshore wind turbines. Winds at 90 m can be faster than outlined in the design criteria for Class I and Class T turbines for 50‐year recurrence periods. Wind speed shear across the turbine rotor layer is also larger than assumed in design specifications. Moreover, vertical variations in wind direction across the turbine rotor layer are large for tropical cyclones of all intensity levels, suggesting design standards should include veer, which can amplify loads in wind turbines. The existence of hurricane wind field characteristics that are not represented in design standards does not imply that damage or failure will certainly occur. Engineering safety factors incorporated in the design of the turbine's blades and structural components may prevent damage from occurring.

17 WIND ENERGY↗
DOE OSTI2024

Impurity gas detection for SNF canisters using probabilistic deep learning and acoustic sensing *

Abstract Monitoring impurity gases in spent nuclear fuel (SNF) canisters is a novel structural health monitoring approach for SNF in dry storage. The SNF canisters are sealed containers that do not facilitate visual access to the inside. Acoustic sensing can be deployed by taking advantage of the pathways unobstructed by internal hardware. Although the ultrasonic time-of-flight measurement can provide valuable information, it is limited in its ability to discern the concentration of only one impurity gas. As such, deep learning algorithms, particularly convolutional neural networks (CNNs), offer a promising solution. In this study, CNN-based probabilistic deep learning models were implemented to detect and quantify multiple impurity gases in helium. An experimental platform was established to simulate canister conditions, and ultrasonic test data were collected. The presence of argon and air in helium at concentrations ranging from 0% to 1.2% at increments of 0.05% was considered. The multi-layer perceptron, decision tree, and logistic regression classifiers achieved high accuracies when distinguishing pure helium from helium with impurities. CNN with dropout layers and CNN using maximum likelihood estimation showed a similar performance, indicating their ability to capture uncertainties. The ensemble CNN model exhibited improved predictions and the ability to balance individual gas concentration by integrating 1D- and 2D-CNN models. These findings contribute probabilistic deep learning solutions for impurity gas detection and analysis within SNF canisters, thus ensuring safe storage and management of SNFs.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Effect of material properties on batch‐to‐glass conversion kinetics

Abstract A recently developed model of the cold cap—the reacting glass batch (melter feeds) floating on molten glass in an electric glass melter—couples heat transfer with the feed‐to‐glass conversion kinetics. The model allows for determining the distributions of temperature and various properties within the cold cap. In the present study, this model is applied to four melter feeds designed for high‐level and low‐activity nuclear wastes. Profiles of temperature, conversion degree, cold cap porosity and density, condensed matter velocity, and heating rate were determined using the material properties of the cold cap. Effects of vigorous foaming at the cold cap bottom were considered. Density, thermal conductivity, and glass production rate strongly affect the cold cap thickness and the fraction of undissolved silica entering the melt under the cold cap. The heating rate profile in the cold cap is highly nonlinear, with high heating rates observed in the foam layer.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Strontium‐Enriched Barite for Enhanced PbSO 4 Nucleation in Lead‐Acid Batteries

Abstract Barite (BaSO 4 ) crystals are an important additive in lead acid batteries due to their ability to promote the controlled nucleation and growth of anglesite (PbSO 4 ) during battery cycling. This is due to BaSO 4 ’s isostructural match with PbSO 4 , which facilitates epitaxial nucleation. However, BaSO 4 ’s efficacy as a nucleation promoter is limited by lattice mismatches between the two phases of 1–5%. Here, strontium‐enriched barite, (Ba,Sr)SO 4 , is synthesized to produce a nucleating promoter that displays an improved lattice match with PbSO 4 . Nucleation of PbSO 4 from Pb‐rich sulfuric acid solutions on strontium‐free and strontium‐enriched barite (up to 17 mol% Sr) is investigated using in‐situ atomic force microscopy and optical microscopy. At low strontium concentrations, PbSO 4 forms by the Stranski–Krastanov growth pathway (monolayer + island formation), with most nucleation occurring on edges and surface defects. At higher concentrations, the layer‐by‐layer growth mechanism known as Frank van‐der‐Merwe growth is observed, which allows for facile growth of continuous PbSO 4 films across the BaSO 4 surface. These films are successfully re‐dissolved on exposure to Pb‐free sulfuric acid. The results show that strontium incorporation fundamentally alters the mechanism of PbSO 4 nucleation on BaSO 4 , and thus provides a potential avenue for creating improved nucleation promoters in lead‐acid batteries.

Campbell, Colin T. [Pacific Northwest National Lab↗
DOE OSTI2022

Fast and Accurate Predictions of Total Energy for Solid Solution Alloys with Graph Convolutional Neural Networks

We use graph convolutional neural networks (GCNNs) to produce fast and accurate predictions of the total energy of solid solution binary alloys. GCNNs allow us to abstract the lattice structure of a solid material as a graph, whereby atoms are modeled as nodes and metallic bonds as edges. This representation naturally incorporates information about the structure of the material, thereby eliminating the need for computationally expensive data pre-processing which would be required with standard neural network (NN) approaches. We train GCNNs on ab-initio density functional theory (DFT) for copper-gold (CuAu) and iron-platinum (FePt) data that has been generated by running the LSMS-3 code, which implements a locally self-consistent multiple scattering method, on OLCF supercomputers Titan and Summit. GCNN outperforms the ab-initio DFT simulation by orders of magnitude in terms of computational time to produce the estimate of the total energy for a given atomic configuration of the lattice structure. We compare the predictive performance of GCNN models against a standard NN such as dense feedforward multi-layer perceptron (MLP) by using the root-mean-squared errors to quantify the predictive quality of the deep learning (DL) models. We find that the attainable accuracy of GCNNs is at least an order of magnitude better than that of the MLP.

Lupo Pasini, Massimiliano↗
DOE OSTI2020

Morphological and nanomechanical changes in tungsten in high heat flux conditions

Abstract Morphological and nanomechanical alteration of tungsten in extreme environments, like those in edge localized modes in nuclear fusion environments, up to 46.3 GWm −2 heat fluxes were experimentally simulated using electrothermal plasma. Surface and subsurface damage to the tungsten is seen mainly in the form of pore formation, cracks, and resolidified melt instabilities. Mirco voids, rosette-type microfeatures, core-shell structure, particle enrichment, and submicron channels all manifest in the damaged subsurface. The formation of voids in the subsurface was determined to originate from the ductile fracture of hot tungsten by plastic flow but not developed to cracking. The voids were preferentially settled in grain boundaries, interfaces. The directionality of elongated voids and grains is biased to the heat flow vector or plasma pathway, which is the likely consequence of the thermally driven grain growth and sliding in the high-temperature conditions. The presence of a border between the transient layer and heat-affected zone is observed and attributed to plasma shock and thermal spallation of fractural tungsten at high temperature. Plasma peening-like hardening effects in tungsten were observed in the range of 22.7–46.3 GWm −2 but least in the case of the lowest heat flux, 12.5 GWm −2 .

36 MATERIALS SCIENCE↗
DOE OSTI2023

Hydrogen-induced degradation dynamics in silicon heterojunction solar cells via machine learning

Abstract Among silicon-based solar cells, heterojunction cells hold the world efficiency record. However, their market acceptance is hindered by an initial 0.5% per year degradation of their open circuit voltage which doubles the overall cell degradation rate. Here, we study the performance degradation of crystalline-Si/amorphous-Si:H heterojunction stacks. First, we experimentally measure the interface defect density over a year, the primary driver of the degradation. Second, we develop SolDeg, a multiscale, hierarchical simulator to analyze this degradation by combining Machine Learning, Molecular Dynamics, Density Functional Theory, and Nudged Elastic Band methods with analytical modeling. We discover that the chemical potential for mobile hydrogen develops a gradient, forcing the hydrogen to drift from the interface, leaving behind recombination-active defects. We find quantitative correspondence between the calculated and experimentally determined defect generation dynamics. Finally, we propose a reversed Si-density gradient architecture for the amorphous-Si:H layer that promises to reduce the initial open circuit voltage degradation from 0.5% per year to 0.1% per year.

14 SOLAR ENERGY↗
DOE OSTI2023

Intensification of Hurricane Sally (2020) over the Mississippi River Plume

Abstract Tropical Cyclone (TC) Sally formed on 11 September 2020, traveled through the Gulf of Mexico (GMX), and intensified rapidly before making landfall on the Alabama coast as a devastating category-2 TC with extensive coastal and inland flooding. In this study, using a combination of observations and idealized numerical model experiments, we demonstrate that the Mississippi River plume played a key role in the intensification of Sally near the northern Gulf Coast. As the storm intensified and its translation slowed before landfall, sea surface cooling was reduced along its track, coincident with a pronounced increase in SSS. Further analysis reveals that TC Sally encountered a warm Loop Current eddy in the northern GMX close to the Mississippi River plume. Besides deepening the thermocline, the eddy advected low-salinity Mississippi River plume water into the storm’s path. This resulted in the development of strong upper-ocean salinity stratification, with a shallow layer of freshwater lying above a deep, warm “barrier layer.” Consequently, TC-induced mixing and the associated sea surface cooling were reduced, aiding Sally’s intensification. These results suggest that the Mississippi River plume and freshwater advection by the Loop Current eddies can play an important role in TC intensification near the U.S. Gulf Coast.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Development of inter-grid-cell lateral unsaturated and saturated flow model in the E3SM Land Model (v2.0)

Abstract. The lateral transport of water in the subsurface is important in modulating terrestrial water energy distribution. Although a few land surface models have recently included lateral saturated flow within and across grid cells, it is not a default configuration in the Climate Model Intercomparison Project version 6 experiments. In this work, we developed the lateral subsurface flow model within both unsaturated and saturated zones in the Energy Exascale Earth System Model (E3SM) Land Model version 2 (ELMv2.0). The new model, called ELMlat, was benchmarked against PFLOTRAN, a 3D subsurface flow and transport model, for three idealized hillslopes that included a convergent hillslope, divergent hillslope, and tilted V-shaped hillslope with variably saturated initial conditions. ELMlat showed comparable performance against PFLOTRAN in terms of capturing the dynamics of soil moisture and groundwater table for the three benchmark hillslope problems. Specifically, the mean absolute errors (MAEs) of the soil moisture in the top 10 layers between ELMlat and PFLOTRAN were within 1 %±3 %, and the MAEs of water table depth were within ±0.2 m. Next, ELMlat was applied to the Little Washita experimental watershed to assess its prediction of groundwater table, soil moisture, and soil temperature. The spatial pattern of simulated groundwater table depth agreed well with the global groundwater table benchmark dataset generated from a global model calibrated with long-term observations. The effects of lateral groundwater flow on the energy flux partitioning were more prominent in lowland areas with shallower groundwater tables, where the difference in simulated annual surface soil temperature could reach 0.3–0.4 ∘C between ELMv2.0 and ELMlat. Incorporating lateral subsurface flow in ELM improves the representation of the subsurface hydrology, which will provide a good basis for future large-scale applications.

58 GEOSCIENCES↗
DOE OSTI2022

Age and chemistry of dissolved organic carbon reveal enhanced leaching of ancient labile carbon at the permafrost thaw zone

Abstract. Climate change will alter the balance between frozen and thawed conditions in Arctic systems. Increased temperatures will make the extensive northern permafrost carbon stock vulnerable to decomposition and translocation. Production, cycling, and transport of dissolved organic carbon (DOC) are crucial processes for high-latitude ecosystem carbon loss that result in considerable export off the Arctic landscape. To identify where and under what conditions permafrost DOC is mobilized in an Arctic headwater catchment, we measured radiocarbon (14C) of DOC and assessed DOC composition with ultraviolet–visible spectroscopy (UV–Vis) of surface waters and shallow and deep subsurface porewaters from 17 drainages in the Barrow Environmental Observatory in Alaska. Samples were collected in July and September 2013 to assess changes in age and chemistry of DOC over time. DOC age was highly variable ranging from modern (19 ‰ Δ14C) to approximately 7000 BP (−583 ‰ Δ14C). DOC age increased with depth, over the summer as the active layer deepened, and with increasing drainage size. DOC quality indicators reflected a DOC source rich in high molecular-weight and aromatic compounds, characteristics consistent with vegetation-derived organic matter that had undergone little microbial processing, throughout the summer and a weak relationship with DOC age. In deep porewaters, DOC age was also correlated with several biogeochemical indicators (including dissolved methane concentration, δ13C, and the apparent fractionation factor), suggesting a coupling between carbon and redox biogeochemistry influencing methane production. In the drained thawed lake basins included in this study, DOC concentrations and contributions of vegetation-derived organic matter declined with increasing basin age. The weak relationship between DOC age and chemistry and consistency in DOC chemical indicators over the summer suggest a high lability of old DOC released by thawing permafrost.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

WMS Server 2.0

This software is a simple, yet flexible server of raster map products, compliant with the Open Geospatial Consortium (OGC) Web Map Service (WMS) 1.1.1 protocol. The server is a full implementation of the OGC WMS 1.1.1 as a fastCGI client and using Geospatial Data Abstraction Library (GDAL) for data access. The server can operate in a proxy mode, where all or part of the WMS requests are done on a back server. The server has explicit support for a colocated tiled WMS, including rapid response of black (no-data) requests. It generates JPEG and PNG images, including 16-bit PNG. The GDAL back-end support allows great flexibility on the data access. The server is a port to a Linux/GDAL platform from the original IRIX/IL platform. It is simpler to configure and use, and depending on the storage format used, it has better performance than other available implementations. The WMS server 2.0 is a high-performance WMS implementation due to the fastCGI architecture. The use of GDAL data back end allows for great flexibility. The configuration is relatively simple, based on a single XML file. It provides scaling and cropping, as well as blending of multiple layers based on layer transparency.

Plesea, Lucian↗