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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 937 records · Page 52

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NASA NTRS1993

(abstract) The Atmospheric Infrared Sounder on EOS

The Atmospheric Infrared Sounder (AIRS) is a facility instrument on the Earth Observing System (EOS) P.M. platform. It will be launched into a 705 km high polar orbit in the year 2000. On the platform with AIRS are the Advanced Microwave Sounding Unit (AMSU) and the Microwave Humidity Sounder (MHS). The three instruments are designed to meet NASA's global change research objectives and NOAA's operational sounding requirements for global weather predictions. AIRS, AMSU, and MHS will provide global tempeature profiles with 1 k rms accuracy in 1 km thick layers in the troposphere and water burden with 10 % accuracy. This is more than a factor of two better than the current operational sounding system, TOVS, and is expected to result in a significant improvement in the medium range forecast accuracy.

remote sensing satellite temperature sounding mois↗

DOE OSTI2021

Li 2 S 6 ‐Integrated PEO‐Based Polymer Electrolytes for All‐Solid‐State Lithium‐Metal Batteries

Abstract The integration of Li 2 S 6 within a poly(ethylene oxide) (PEO)‐based polymer electrolyte is demonstrated to improve the polymer electrolyte's ionic conductivity because the strong interplay between O 2− (PEO) and Li + from Li 2 S 6 reduces the crystalline volume within the PEO. The Li/electrolyte interface is stabilized by the in situ formation of an ultra‐thin Li 2 S/Li 2 S 2 layer via the reaction between Li 2 S 6 and lithium metal, which increases the ionic transport at the interface and suppresses lithium dendrite growth. A symmetric Li/Li cell with the Li 2 S 6 ‐integrated composite electrolyte has excellent cyclability and a high critical current density of 0.9 mA cm −2 at 40 °C. Impressive electrochemical performance is demonstrated with all‐solid‐state Li/LiFePO 4 and high‐voltage Li/LiNi 0.8 Mn 0.1 Co 0.1 O 2 cells at 40 °C.

Fang, Ruyi↗

DOE OSTI2021

Li 2 S 6 ‐Integrated PEO‐Based Polymer Electrolytes for All‐Solid‐State Lithium‐Metal Batteries

Fang, Ruyi↗

DOE OSTI2022

The role of microstructural evolution during spark plasma sintering on the soft magnetic and electronic properties of a CoFe–Al2O3 soft magnetic composite

Abstract For transformers and inductors to meet the world’s growing demand for electrical power, more efficient soft magnetic materials with high saturation magnetic polarization and high electrical resistivity are needed. This work aimed at the development of a soft magnetic composite synthesized via spark plasma sintering with both high saturation magnetic polarization and high electrical resistivity for efficient soft magnetic cores. CoFe powder particles coated with an insulating layer of Al 2 O 3 were used as feedstock material to improve the electrical resistivity while retaining high saturation magnetic polarization. By maintaining a continuous non-magnetic Al 2 O 3 phase throughout the material, both a high saturation magnetic polarization, above 1.5 T, and high electrical resistivity, above 100 μΩ·m, were achieved. Through microstructural characterization of samples consolidated at various temperatures, the role of microstructural evolution on the magnetic and electronic properties of the composite was elucidated. Upon consolidation at relatively high temperature, the CoFe was to found plastically deform and flow into the Al 2 O 3 phase at the particle boundaries and this phenomenon was attributed to low resistivity in the composite. In contrast, at lower consolidation temperatures, perforation of the Al 2 O 3 phase was not observed and a high electrical resistivity was achieved, while maintaining a high magnetic polarization, ideal for more efficient soft magnetic materials for transformers and inductors.

36 MATERIALS SCIENCE↗

DOE OSTI2022

U.S. national water and energy land dataset for integrated multisector dynamics research

Abstract Understanding resource demands and tradeoffs among energy, water, and land socioeconomic sectors requires an explicit consideration of spatial scale. However, incorporation of land dynamics within the energy-water nexus has been limited due inconsistent spatial units of observation from disparate data sources. Herein we describe the development of a National Water and Energy Land Dataset (NWELD) for the conterminous United States. NWELD is a 30-m, 86-layer rasterized dataset depicting the land use of mappable components of the United States energy sector life cycles (and related water used for energy), specifically the extraction, development, production, storage, distribution, and operation of eight renewable and non-renewable technologies. Through geospatial processing and programming, the final products were assembled using four different methodologies, each depending upon the nature and availability of raw data sources. For validation, NWELD provided a relatively accurate portrayal of the spatial extent of energy life cycles yet displayed low measures of association with mainstream land cover and land use datasets, indicating the provision of new land use information for the energy-water nexus.

58 GEOSCIENCES↗

DOE OSTI2024

Fiber optic computing using distributed feedback

Abstract The widespread adoption of machine learning and other matrix intensive computing algorithms has renewed interest in analog optical computing, which has the potential to perform large-scale matrix multiplications with superior energy scaling and lower latency than digital electronics. However, most optical techniques rely on spatial multiplexing, requiring a large number of modulators and detectors, and are typically restricted to performing a single kernel convolution operation per layer. Here, we introduce a fiber-optic computing architecture based on temporal multiplexing and distributed feedback that performs multiple convolutions on the input data in a single layer. Using Rayleigh backscattering in standard single mode fiber, we show that this technique can efficiently apply a series of random nonlinear projections to the input data, facilitating a variety of computing tasks. The approach enables efficient energy scaling with orders of magnitude lower power consumption than GPUs, while maintaining low latency and high data-throughput.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Switching charge states in quasi-2D molecular conductors

Abstract 2D molecular entities build next-generation electronic devices, where abundant elements of organic molecules are attractive due to the modern synthetic and stimuli control through chemical, conformational, and electronic modifications in electronics. Despite its promising potential, the insufficient control over charge states and electronic stabilities must be overcome in molecular electronic devices. Here, we show the reversible switching of modulated charge states in an exfoliatable 2D-layered molecular conductor based on bis(ethylenedithio)tetrathiafulvalene molecular dimers. The multiple stimuli application of cooling rate, current, voltage, and laser irradiation in a concurrent manner facilitates the controllable manipulation of charge crystal, glass, liquid, and metal phases. The four orders of magnitude switching of electric resistance are triggered by stimuli-responsive charge distribution among molecular dimers. The tunable charge transport in 2D molecular conductors reveals the kinetic process of charge configurations under stimuli, promising to add electric functions in molecular circuitry.

Huang, Yulong (ORCID:0000000296160134)↗

DOE OSTI2021

Permafrost thaw with warming reduces microbial metabolic capacities in subsurface soils

Abstract Microorganisms are major constituents of the total biomass in permafrost regions, whose underlain soils are frozen for at least two consecutive years. To understand potential microbial responses to climate change, here we examined microbial community compositions and functional capacities across four soil depths in an Alaska tundra site. We showed that a 5‐year warming treatment increased soil thaw depth by 25.7% ( p = .011) within the deep organic layer (15–25 cm). Concurrently, warming reduced 37% of bacterial abundance and 64% of fungal abundances in the deep organic layer, while it did not affect microbial abundance in other soil layers (i.e., 0–5, 5–15, and 45–55 cm). Warming treatment altered fungal community composition and microbial functional structure ( p < .050), but not bacterial community composition. Using a functional gene array, we found that the relative abundances of a variety of carbon (C)‐decomposing, iron‐reducing, and sulphate‐reducing genes in the deep organic layer were decreased, which was not observed by the shotgun sequencing‐based metagenomics analysis of those samples. To explain the reduced metabolic capacities, we found that warming treatment elicited higher deterministic environmental filtering, which could be linked to water‐saturated time, soil moisture, and soil thaw duration. In contrast, plant factors showed little influence on microbial communities in subsurface soils below 15 cm, despite a 25.2% higher ( p < .05) aboveground plant biomass by warming treatment. Collectively, we demonstrate that microbial metabolic capacities in subsurface soils are reduced, probably arising from enhanced thaw by warming.

Wu, Linwei↗

DOE OSTI2025

Dopant Sensitive Electrolytic Etching of Germanium with High Selectivity

Abstract The enhanced charge carrier mobility and photon absorption compared to silicon make germanium attractive for next-generation photo diodes. However, the complex oxidation behavior of germanium challenges dopant-dependent selective etching that is desired for the fabrication of backside imaging architectures. This report demonstrates electrolytic wet etching of p-doped germanium which proceeds up to 17,500x faster than etching of intrinsic germanium. Homoepitaxially grown layers of germanium were electrolytically etched in potassium hydroxide over a range of biases. Intermittent acquisition of cyclic voltammetry spectra during etching has suppressed the formation of electric double layers, maintained appreciable etch rates, and allowed for in operando process control. The observed etch rates scaled with dopant concentration. An effective etch rate of germanium removal of 2.100±0.044 µm/min was accomplished for a boron dopant concentration of 6E18cm-3. For nominally intrinsic germanium, however, an effective etch rate of only 0.00012±0.00011 µm/min was observed. A series of systematic electrolytic etch experiments have revealed the transfer of 4 electrons per germanium atom removed.

Wood, Joseph G.↗

NASA NTRS1994

(abstract) Transmission Electron Microscopy of Al(sub x)Ga(sub 1-x)N/SiC Multilayer Structures Grown on Sapphire Substrates

The potential of wide-band-gap III-V nitrides as ultraviolet sensors and light emitters has prompted an increasing amount of work recently, including the fabrication of the first UV sensors from as-deposited single crystal GaN. We have used high resolution transmission electron microscopy (TEM) to study the microstructure of two novel developments of wide-band-gap III-V nitrides: the growth of ultra-short period GaN/AlN superlattices; and the incorporation of SiC layers into Al(sub x)Ga(sub 1-x)N structures. By varying the relative periods in a GaN/AlN superlattice, the band gap of the composite can be tailored to lie between the elemental values of 365 nm for GaN and 200 nm for AlN. The group IV semiconductor, SiC, has a wide band-gap and has a close lattice match (less than 3 %) to Al(sub x)Ga(sub 1-x)N for growth on the basal plane. Demonstration of epitaxial growth for Al(sub x)Ga(sub 1-x)N/SiC multilayers would introduce a wide band-gap analog to the already existing family of III-V and Si(sub 1-x)Ge(sub x) heteroepitaxial growth systems. Although good quality growth of GaN on SiC substrates has been demonstrated, Al(sub x)Ga(sub 1-x)N/SiC multilayer structures have never been grown and the interfacial structure is unknown.

GaN AlN GaN/AlN↗

DOE OSTI2024

Platinum/Tantalum Carbide Core–Shell Nanoparticles with Sub‐Monolayer Shells for Methanol and Oxygen Electrocatalysis

Abstract Core–shell architectures provide great opportunities to improve catalytic activity, but achieving nanoparticle stability under electrochemical cycling remains challenging. Herein, core–shell nanoparticles comprising atomically thin Pt shells over earth‐abundant TaC cores are synthesized and used as highly durable electrocatalysts for the methanol oxidation reaction (MOR) and the oxygen reduction reaction (ORR) needed to drive direct methanol fuel cells (DMFCs). Characterization data show that a thin oxidic passivation layer protects the TaC core from undergoing dissolution in the fuel cell‐relevant potential range, enabling the use of partially covered Pt/TaC core–shell nanoparticles for MOR and ORR with high stability and enhanced catalytic performance. Specifically, at the anode the surface‐oxidized TaC further enhances MOR activity compared to conventional Pt nanoparticles. At the cathode, the Pt/TaC catalyst feature increases tolerance to methanol crossover. These results show unique synergistic advantages of the core–shell particles and open opportunities to tailor catalytic properties for electrocatalytic reactions.

Chemistry↗

DOE OSTI2022

Anode‐Free Lithium–Sulfur Cells Enabled by Rationally Tuning Lithium Polysulfide Molecules

Abstract The two major barriers of practical lithium–sulfur batteries are the poor reversibility of lithium‐metal anode and sluggish kinetics of sulfur cathode. Here, we report a simple yet cogent, molecular tailoring approach for lithium polysulfides, enabling a synergistic enhancement of anode reversibility and cathode kinetics. We show that SnI 4 coordinates with lithium polysulfides to form soluble complexes, resulting in a Li 2 SnS 3 ‐rich anode interphase layer. As Li 2 SnS 3 is stable against parasitic reactions and has a lower ionic resistance over cycling, the Li plating/stripping efficiency is greatly improved. In addition, the formation of soluble complexes between SnI 4 and lithium polysulfides play a non‐negligible role in suppressing the clustering behavior of lithium polysulfide molecules, resulting in a significant enhancement in sulfur conversion kinetics under lean electrolyte conditions. The synergistic improvement is validated in anode‐free, lean‐electrolyte pouch cells with a Li 2 S cathode that displays capacity retention of 78 % after 100 cycles.

Ren, Yuxun↗

DOE OSTI2024

TiN‐Au/HfO 2 ‐Au Multilayer Thin Films with Tunable Hyperbolic Optical Response

Abstract Hyperbolic metamaterials (HMM) possess significant anisotropic physical properties and tunability and thus find many applications in integrated photonic devices. HMMs consisting of metal and dielectric phases in either multilayer or vertically aligned nanocomposites (VAN) form are demonstrated with different hyperbolic properties. Herein, self‐assembled HfO 2 ‐Au/TiN‐Au multilayer thin films, combining both the multilayer and VAN designs, are demonstrated. Specifically, Au nanopillars embedded in HfO 2 and TiN layers forming the alternative layers of HfO 2 ‐Au VAN and TiN‐Au VAN. The HfO 2 and TiN layer thickness is carefully controlled by varying laser pulses during pulsed laser deposition (PLD). Interestingly, tunable anisotropic physical properties can be achieved by adjusting the bi‐layer thickness and the number of the bi‐layers. Type II optical hyperbolic dispersion can be obtained from high layer thickness structure (e.g., 20 nm), while it can be transformed into Type I optical hyperbolic dispersion by reducing the thickness to a proper value (e.g., 4 nm). This new nanoscale hybrid metamaterial structure with the three‐phase VAN design shows great potential for tailorable optical components in future integrated devices.

Chemistry↗

DOE OSTI2022

Anisotropic MagnetoMemristance

Abstract In the last decade, nanoscale resistive devices with memory have been the subject of intense study because of their possible use in brain-inspired computing. However, operational endurance is one of the limiting factors in the adoption of such technology. For this reason, we discuss the emergence of current-induced memristance in magnetic materials, known for their durability. We show analytically and numerically that a single ferromagnetic layer can possess GHz memristance, due to a combination of two factors: a current-induced transfer of angular momentum (Zhang-Li torque) and the anisotropic magnetoresistance (AMR). We term the resulting effect the anisotropic magneto-memristance (AMM). We connect the AMM to the topology of the magnetization state, within a simple model of a one-dimensional annulus-shaped magnetic layer, confirming the analytical results with micromagnetic simulations for permalloy. Our results open a new path towards the realization of single-layer magnetic memristive devices operating at GHz frequencies.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2005

Lunar and Planetary Science XXXVI, Part 5

Topics discussed include: Automation Recognition oF Crater-Like Structures in Terrestrial and Plantary Images; Condensation from Cluster-IDP Enriched Vapor Inside the Snow Line: Implications for Mercury, Asteroids, and Enstatite Chondrites; Tomographic Location of Potential Melt-Bearing Phenocrysts in Lunar Glass Spherules; Source and Evolution of Vapor Due to Impacts into Layered Carbonates and Silicates; Noble Gases and I-Xe Ages of the Zag Meteorite; The MArs Hand Lens Imager (MAHLI) for the 209 Mars Science Laboratory; The Sedimentary Rocks of Meridiani Planum, in Context; Three-System Isotopic of Lunar Norite 78238: Rb-Sr Results; Constraints on the Role of Curium-247 as a Source of Fission Xenon in the Early Solar System; New Features in the ADS Abstract Service; Cassini RADAR's First Look at Titan; Volcanism and Volatile Recycling on Venus from Lithospheric Delamination; The Fate of Water in the Martian Magma Ocean and the Formation of an Early Atmosphere; Mars Odyssey Neutron Spectrometer Water-Equivalent Hydrogen: Comparison with Glacial; Landforms on Tharsis; Using Models of Permanent Shadow to Constrain Lunar Polar Water Ice Abundances; Martian Radiative Transfer Modeling Using the Optimal Spectral Sampling Method; Petrological and Geochemical Consideration on the Tuserkanite Meteorite; and Mineralogy of Asteroids from Observations with the Spitzer Space Telescope.

Source record↗

NASA NTRS1994

(abstract) Transmission Electron Microscopy of Al(sub x)Ga(sub 1-x)N/SiC Multilayer Structures

The potential of wide-band-gap III-V nitrides as solar-blind ultraviolet sensors and light emitters has prompted an increasing amount of work recently, including the fabrication of the first UV sensors from as-deposited single crystal GaN. We have used high resolution transmission electron microscopy (TEM) to study the microstructure of two novel developments of wide-band-gap III-V nitrides: the growth of ultra-short period GaN/AlN super lattices (digital alloys); and the incorporation of SiC layers into Al(sub x)Ga(sub 1-x)N structures. By varying the relative periods in a GaN/AlN superlattice, it should be possible to tailor the band gap of the composite to lie between the elemental values of 365 nm for GaN and 200 nm for AlN. The group IV semiconductor, SiC, has a close lattice match (< 3%) to Al(sub x)Ga(sub 1-x)N for growth on the basal plane. Demonstration of epitaxial growth for Al(sub x)Ga(sub 1-x)N/SiC multilayers could enable an extension of direct band-gap material towards the visible.

microscopy GaN AlN semiconductor SiC↗

DOE OSTI2023

Direct imaging of electron density with a scanning transmission electron microscope

Abstract Recent studies of secondary electron (SE) emission in scanning transmission electron microscopes suggest that material’s properties such as electrical conductivity, connectivity, and work function can be probed with atomic scale resolution using a technique known as secondary electron e-beam-induced current (SEEBIC). Here, we apply the SEEBIC imaging technique to a stacked 2D heterostructure device to reveal the spatially resolved electron density of an encapsulated WSe 2 layer. We find that the double Se lattice site shows higher emission than the W site, which is at odds with first-principles modelling of valence ionization of an isolated WSe 2 cluster. These results illustrate that atomic level SEEBIC contrast within a single material is possible and that an enhanced understanding of atomic scale SE emission is required to account for the observed contrast. In turn, this suggests that, in the future, subtle information about interlayer bonding and the effect on electron orbitals could be directly revealed with this technique.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Reduced order modeling for flow and transport problems with Barlow Twins self-supervised learning

Abstract We propose a unified data-driven reduced order model (ROM) that bridges the performance gap between linear and nonlinear manifold approaches. Deep learning ROM (DL-ROM) using deep-convolutional autoencoders (DC–AE) has been shown to capture nonlinear solution manifolds but fails to perform adequately when linear subspace approaches such as proper orthogonal decomposition (POD) would be optimal. Besides, most DL-ROM models rely on convolutional layers, which might limit its application to only a structured mesh. The proposed framework in this study relies on the combination of an autoencoder (AE) and Barlow Twins (BT) self-supervised learning, where BT maximizes the information content of the embedding with the latent space through a joint embedding architecture. Through a series of benchmark problems of natural convection in porous media, BT–AE performs better than the previous DL-ROM framework by providing comparable results to POD-based approaches for problems where the solution lies within a linear subspace as well as DL-ROM autoencoder-based techniques where the solution lies on a nonlinear manifold; consequently, bridges the gap between linear and nonlinear reduced manifolds. We illustrate that a proficient construction of the latent space is key to achieving these results, enabling us to map these latent spaces using regression models. The proposed framework achieves a relative error of 2% on average and 12% in the worst-case scenario (i.e., the training data is small, but the parameter space is large.). We also show that our framework provides a speed-up of $$7 \times 10^{6}$$ 7 × 10 6 times, in the best case, and $$7 \times 10^{3}$$ 7 × 10 3 times on average compared to a finite element solver. Furthermore, this BT–AE framework can operate on unstructured meshes, which provides flexibility in its application to standard numerical solvers, on-site measurements, experimental data, or a combination of these sources.

97 MATHEMATICS AND COMPUTING↗