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At least 829 records · Page 46

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NASA NTRS1989

Encapsulated diffusion of sulphur into InP

This talk outlines a simple process for the fabrication of n(+)-p solar cells in indium phosphide. Large area cells (greater than 0.25 sq cm) have been made by this process, with a photovoltaic conversion efficiency of 15.21 percent under AM0 conditions of illumination. An ideality factor of 1.1 and a saturation current density of 8 x 10 to the minus 15th power A/sq cm have been observed for these cells. The technique for cell fabrication involves the diffusion of sulfur into InP by an open tube process, and gives highly reproducible results from run to run. A vacuum-deposited layer of gallium sulphide (Ga2S3) was used as the source for sulfur diffusion, with a chemically vapor deposited SiO2 cap layer to prevent decomposition of the InP surface during heat treatment. Diffusions were carried out in a flowing nitrogen ambient at 585 to 708 C, and characterized by their surface carrier concentration and the diffusion constant. The diffusion profile for sulfur in InP is estimated to be of the complementary error function type. The activation energy of the diffusion was estimated to be 1.94 eV. The technique described here is ideally suited for the fabrication of shallow n(+)-p junctions in InP, and has been used for space-borne solar cells.

Parat, K. K.↗

DOE OSTI2021

Fractional chiral hinge insulator

We propose and study a wave function describing an interacting three-dimensional fractional chiral hinge insulator (FCHI) constructed by Gutzwiller projection of two noninteracting second-order topological insulators with chiral hinge modes at half filling. We use large-scale variational Monte Carlo computations to characterize the model states via the entanglement entropy and charge-spin fluctuations. We show that the FCHI possesses fractional chiral hinge modes characterized by a central charge c = 1 and Luttinger parameter K = 1/2, like the edge modes of a Laughlin 1/2 state. The bulk and surface topology is characterized by the topological entanglement entropy (TEE) correction to the area law. While our computations indicate a vanishing bulk TEE, we show that the gapped surfaces host an unconventional two-dimensional topological phase. In a clear departure from the physics of a Laughlin 1/2 state, we find a TEE per surface compatible with (ln √2 )/2, half that of a Laughlin 1/2 state. This value cannot be obtained from topological quantum field theory for purely two-dimensional systems. For the sake of completeness, we also investigate the topological degeneracy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Surface Oxidation Behavior of FeNi-based Metal Amorphous Nanocomposite (MANC) Alloys for High-Speed Motor Applications

New interest in high performance soft magnetic materials (SMMs) have been fueled by the need to lower losses at higher operating frequencies while maintaining high flux density and tunable permeability in electrical motors, transformer, and generator applications. Conventional SMMs like electrical steels and Fe-based metal amorphous nanocomposite (MANC) alloys are dominated by eddy current losses at high frequencies. Recent breakthrough in high-performance FeNi MANC have shown promise in reducing eddy current losses as compared to electrical steels. Their intrinsic adherent native surface oxide layer provides sufficient electrical insulation to reduce interlaminate eddy current losses. However, notwithstanding advances in MANCs, there exists a gap in literature on investigations of the surface oxide layer responsible for significant reduction of interlaminate eddy current losses in magnetic cores. This work presents a detailed characterization of the surface oxide, oxidation behavior, and relationship between oxide thickness and resistivity of a new FeNi MANC alloy (Fe70Ni30)80Nb4B14Si2.

Egbu, James↗

DOE OSTI2023

Multifunctional Effect of Fe Substitution in Na Layered Cathode Materials for Enhanced Storage Stability

In this study, developing stable cathode materials that are resistant to storage degradation is essential for practical development and industrial processing of Na-ion batteries, as many sodium layered oxide materials are susceptible to hygroscopicity and instability when exposed to ambient air. Among the various layered compounds, Fe-substituted O 3 -type Na(Ni 1/2 Mn 1/2 ) 1-x Fe x O 2 materials have emerged as a promising option for high-performance and low-cost cathodes. While previous reports have noted the decent air-storage stability of these materials, the role and origin of Fe substitution in improving storage stability remain unclear. In this study, we investigate the air resistant effect of Fe substitution in O 3 -Na(Ni 1/2 Mn 1/2 ) 1-x Fe x O 2 cathode materials by performing systematic surface and structural characterizations. We find that the improved storage stability can be attributed to the multifunctional effect of Fe substitution, which forms a surface protective layer containing an Fe-incorporated spinel phase and decreases the thermodynamical driving force for bulk chemical sodium extraction. With these mechanisms, the Fe-containing cathodes can suppress the cascades of cathode degradation processes and better retain the electrochemical performance after air storage.

25 ENERGY STORAGE↗

NASA NTRS1986

Martian surface properties

The objectives were: to characterize surficial geologic units through integration of Infrared Thermal Mapper (IRTM)-derived regolith properties with other existing remote sensing data; to determine the physical and spectral properties of volcanic units in the mid-latitudes of Mars through the synthesis of the highest resolution IRTM, radar, and imaging data available; and to identify and characterize aeolian terrains on Mars using physical surface characteristics determined from remote sensing data.

Greeley, R.↗

NASA NTRS1998

Real Time Land-Surface Hydrologic Modeling Over Continental US

The land surface component of the hydrological cycle is fundamental to the overall functioning of the atmospheric and climate processes. Spatially and temporally variable rainfall and available energy, combined with land surface heterogeneity cause complex variations in all processes related to surface hydrology. The characterization of the spatial and temporal variability of water and energy cycles are critical to improve our understanding of land surface-atmosphere interaction and the impact of land surface processes on climate extremes. Because the accurate knowledge of these processes and their variability is important for climate predictions, most Numerical Weather Prediction (NWP) centers have incorporated land surface schemes in their models. However, errors in the NWP forcing accumulate in the surface and energy stores, leading to incorrect surface water and energy partitioning and related processes. This has motivated the NWP to impose ad hoc corrections to the land surface states to prevent this drift. A proposed methodology is to develop Land Data Assimilation schemes (LDAS), which are uncoupled models forced with observations, and not affected by NWP forcing biases. The proposed research is being implemented as a real time operation using an existing Surface Vegetation Atmosphere Transfer Scheme (SVATS) model at a 40 km degree resolution across the United States to evaluate these critical science questions. The model will be forced with real time output from numerical prediction models, satellite data, and radar precipitation measurements. Model parameters will be derived from the existing GIS vegetation and soil coverages. The model results will be aggregated to various scales to assess water and energy balances and these will be validated with various in-situ observations.

Houser, Paul R.↗

DOE OSTI2022

Fabrication and Characterization of Iron-Based Catalysts for the Dehydrogenation of Fossil Fuels

For a prosperous and sustainable future, hydrogen is an encouraging solution due to its simple transition for industrial decarbonization and synergy for economic development. Paradoxically, current hydrogen production pathways release substantial amount of greenhouse gases into the atmosphere contributing to climate change. To keep up with increasing demand, hydrogen could be produced through microwave-assisted thermocatalytic dehydrogenation of fossil fuels without emitting carbon dioxide. This requires specified catalysts to meet the requirements of hydrogen yield and selectivity. The objective of the present research is to fabricate, characterize, and compare iron-based alumina (FeAlxOy) catalysts produced via solution combustion synthesis and iron-based catalysts on silicon carbide support (Fe/SiC) produced via incipient wetness impregnation. Heat mode, fuel type, and oxidizer mole ratio were varied for FeAlxOy catalysts, and metal loading was varied for Fe/SiC catalysts. Each resultant product was characterized by X-ray diffraction analysis, scanning electron microscopy, laser diffraction particle size analysis, and Brunauer-Emmett-Teller (BET) surface area analysis. Characterization suggests that fabrication of iron-based alumina nanocomposites through solution combustion synthesis in a muffle furnace using citric acid as the fuel yields the most promising catalyst.

Reyes, Victoria Isabel↗

NASA NTRS1996

Least Squares Best Fit Method for the Three Parameter Weibull Distribution: Analysis of Tensile and Bend Specimens with Volume or Surface Flaw Failure

Material characterization parameters obtained from naturally flawed specimens are necessary for reliability evaluation of non-deterministic advanced ceramic structural components. The least squares best fit method is applied to the three parameter uniaxial Weibull model to obtain the material parameters from experimental tests on volume or surface flawed specimens subjected to pure tension, pure bending, four point or three point loading. Several illustrative example problems are provided.

Gross, Bernard↗

DOE OSTI2025

Error field measurements and correction on MUSE permanent magnet stellarator

The magnetic field topology and error fields are measured in the MUSE permanent magnet stellarator with an electron beam and fluorescent rod. The effective magnetization of the magnets is determined by measuring rational flux surface locations. Electron magnetic drift effects must be considered self-consistently due to the small magnetic shear on MUSE. Error fields are characterized by flux surface shape deviation and magnetic island chain width and phase. Error fields are then corrected by adjusting the permanent magnet (PM) holders as rigid bodies. Resonant error fields are on the order of or smaller than 3 x 10 -6 of the toroidal field after correction and surface shape matches well with the design. Resonant components of the quasi-symmetry deviation are estimated, using a novel magnetic drift measurement, to be in the 10 −4 range. The PM approach is validated as a low-cost and precise way to build optimized stellarators.

electron beam mapping↗

DOE OSTI2022

Modeling Spatial Distribution of Snow Water Equivalent by Combining Meteorological and Satellite Data with Lidar Maps

Abstract An accurate characterization of the water content of snowpack, or snow water equivalent (SWE), is necessary to quantify water availability and constrain hydrologic and land surface models. Recently, airborne observations (e.g., lidar) have emerged as a promising method to accurately quantify SWE at high resolutions (scales of ∼100 m and finer). However, the frequency of these observations is very low, typically once or twice per season in the Rocky Mountains of Colorado. Here, we present a machine learning framework that is based on random forests to model temporally sparse lidar-derived SWE, enabling estimation of SWE at unmapped time points. We approximated the physical processes governing snow accumulation and melt as well as snow characteristics by obtaining 15 different variables from gridded estimates of precipitation, temperature, surface reflectance, elevation, and canopy. Results showed that, in the Rocky Mountains of Colorado, our framework is capable of modeling SWE with a higher accuracy when compared with estimates generated by the Snow Data Assimilation System (SNODAS). The mean value of the coefficient of determination R 2 using our approach was 0.57, and the root-mean-square error (RMSE) was 13 cm, which was a significant improvement over SNODAS (mean R 2 = 0.13; RMSE = 20 cm). We explored the relative importance of the input variables and observed that, at the spatial resolution of 800 m, meteorological variables are more important drivers of predictive accuracy than surface variables that characterize the properties of snow on the ground. This research provides a framework to expand the applicability of lidar-derived SWE to unmapped time points. Significance Statement Snowpack is the main source of freshwater for close to 2 billion people globally and needs to be estimated accurately. Mountainous snowpack is highly variable and is challenging to quantify. Recently, lidar technology has been employed to observe snow in great detail, but it is costly and can only be used sparingly. To counter that, we use machine learning to estimate snowpack when lidar data are not available. We approximate the processes that govern snowpack by incorporating meteorological and satellite data. We found that variables associated with precipitation and temperature have more predictive power than variables that characterize snowpack properties. Our work helps to improve snowpack estimation, which is critical for sustainable management of water resources.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2003

Physical association and functional interaction between beta1 integrin and CD98 on human T lymphocytes

CD98 is a cell surface protein previously characterized as a cell activation marker, an amino acid transporter, and has recently been implicated in integrin-related functions. Integrins are cell surface proteins, important for homotypic cell aggregation, cell adhesion, and coactivation of T lymphocytes. We have previously shown that the anti-CD98 mAb 80A10, when coimmobilized with anti-CD3 mAb OKT3, is able to mediate human T cell coactivation that is inhibited by anti-beta1 integrin specific mAb 18D3. These results indicated a functional association of CD98 and beta1 integrin signaling but left open the question of a physical association. We now show the induction of homotypic aggregation through CD98 among human T cells and this aggregation was inhibited by anti-beta1 integrin mAb. Therefore, CD98-dependent lymphocyte proliferation and adhesion may involve integrins. Competitive binding assays and fluorescence colocalization analysis suggested that CD98 and beta1 integrin were physically associated. Differential extraction techniques and immunoprecipitations provided the first evidence that the alpha4beta1 integrin and CD98 are specifically associated on human T lymphocytes.

NASA Discipline Cell Biology↗

NASA NTRS2002

Development of Metal-impregnated Single Walled Carbon Nanotubes for Toxic Gas Contaminant Control in Advanced Life Support Systems

The success of physico-chemical waste processing and resource recovery technologies for life support application depends partly on the ability of gas clean-up systems to efficiently remove trace contaminants generated during the process with minimal use of expendables. Carbon nanotubes promise superior performance over conventional approaches to gas clean-up due to their ability to direct the selective uptake of gaseous species based on their controlled pore size, high surface area, ordered chemical structure that allows functionalization and their effectiveness also as catalyst support materials for toxic gas conversion. We present results and findings from a preliminary study on the effectiveness of metal impregnated single walled nanotubes as catalyst/catalyst support materials for toxic gas contaminate control. The study included the purification of single walled nanotubes, the catalyst impregnation of the purified nanotubes, the experimental characterization of the surface properties of purified single walled nanotubes and the characterization of physisorption and chemisorption of uptake molecules.

Pisharody, Suresh A.↗

NASA NTRS2012

Validation and Verification of Operational Land Analysis Activities at the Air Force Weather Agency

The NASA developed Land Information System (LIS) is the Air Force Weather Agency's (AFWA) operational Land Data Assimilation System (LDAS) combining real time precipitation observations and analyses, global forecast model data, vegetation, terrain, and soil parameters with the community Noah land surface model, along with other hydrology module options, to generate profile analyses of global soil moisture, soil temperature, and other important land surface characteristics. (1) A range of satellite data products and surface observations used to generate the land analysis products (2) Global, 1/4 deg spatial resolution (3) Model analysis generated at 3 hours. AFWA recognizes the importance of operational benchmarking and uncertainty characterization for land surface modeling and is developing standard methods, software, and metrics to verify and/or validate LIS output products. To facilitate this and other needs for land analysis activities at AFWA, the Model Evaluation Toolkit (MET) -- a joint product of the National Center for Atmospheric Research Developmental Testbed Center (NCAR DTC), AFWA, and the user community -- and the Land surface Verification Toolkit (LVT), developed at the Goddard Space Flight Center (GSFC), have been adapted to operational benchmarking needs of AFWA's land characterization activities.

Shaw, Michael↗

NASA NTRS2006

Construction and Resource Utilization Explorer (CRUX): Implementing Instrument Suite Data Fusion to Characterize Regolith Hydrogen Resources

CRUX is a modular suite of geophysical and borehole instruments combined with display and decision support system (MapperDSS) tools to characterize regolith resources, surface conditions, and geotechnical properties. CRUX is a NASA-funded Technology Maturation Program effort to provide enabling technology for Lunar and Planetary Surface Operations (LPSO). The MapperDSS uses data fusion methods with CRUX instruments, and other available data and models, to provide regolith properties information needed for LPSO that cannot be determined otherwise. We demonstrate the data fusion method by showing how it might be applied to characterize the distribution and form of hydrogen using a selection of CRUX instruments: Borehole Neutron Probe and Thermal Evolved Gas Analyzer data as a function of depth help interpret Surface Neutron Probe data to generate 3D information. Secondary information from other instruments along with physical models improves the hydrogen distribution characterization, enabling information products for operational decision-making.

in situ resource utilization (ISRU)↗

DOE OSTI2025

Let’s Stick Together: Interplay of Moisture, Particle Size, and Anatomical Fraction in the Flowability of Corn Stover Crumbles

Handling of agricultural waste biomass feedstocks (such as corn stover) is a persistent challenge in the production of biofuels and chemicals at integrated biorefineries. Inconsistent flowability and high feedstock variability creates equipment downtime and processing challenges. This work investigates the influence of anatomical fractionation and moisture content on the bulk solids handling behavior of corn stover crumbles. A combination of rotational shear testing, tribological measurements, and surface and sorption characterization techniques (inverse gas chromatography (IGC), dynamic vapor sorption (DVS), and electron microscopy) were used to evaluate the contributions of particle composition, size, and surface properties to flow behavior. Shear and frictional testing revealed that moisture content has the greatest effect on flowability, significantly increasing unconfined yield strength (ƒ c ) and reducing the flow function coefficient (F F C), regardless of anatomical fraction. While differences in surface energy were observed between fractions, particularly in polar contributions (γ AB ), these did not correspond to meaningful differences in flow behavior. Coarser 6 mm particles exhibited poorer flow performance than 4 mm crumbles, likely due to broader particle size distributions and increased particle interlocking. Taken together, these results suggest that anatomical fractionation provides minimal benefit from a bulk handling perspective. Moisture content and particle size heterogeneity dominate handling behavior, reinforcing the utility of unfractionated corn stover in processing environments. These insights can inform the design of more efficient and reliable feedstock processing systems for agricultural biomass in integrated biorefineries.

09 BIOMASS FUELS↗

DOE OSTI2026

Superconducting Material Growth for Radio-Frequency (RF) Cavities

Superconducting radio-frequency (SRF) cavities, usually manufactured from Niobium (Nb), are vital components of modern particle accelerators because of their ability to achieve high acceleration gradients with little power dissipation. Naturally forming Nb surface oxides significantly alter cavity performance by changing surface resistance. A nondestructive characterization of oxide thickness is helpful for relating surface processing treatments to cavity performance. This work develops a protocol to measure Nb oxide thickness using Angle-Resolved X-ray Photoelectron Spectroscopy (ARXPS) while correcting instrumental errors. Using uniform bulk standard samples (Silver, Aluminum oxide, and Germanium), we determined a baseline correction factor to account for analyzer-related intensity evolution as the measurement angle increases. The correction factor was then applied to Nb 3d ARXPS data. Applying the Strohmeier equation to the corrected data yielded a Nb2O5 thickness of 6.04 nm, closely matching the 5.5 (±.05) nm value obtained from cross-sectional transmission electron microscopy. Our approach will bring a method to incorporate inherent errors in the thickness measurements using ARXPS and can be broadly applied to improve the accuracy of thickness measurements in a wide range of heterostructures.

Lambert, Nathan [Fermilab]↗

NASA NTRS1983

Effects of vegetation canopy on the radar backscattering coefficient

Airborne L- and C-band scatterometer data, taken over both vegetation-covered and bare fields, were systematically analyzed and theoretically reproduced, using a recently developed model for calculating radar backscattering coefficients of rough soil surfaces. The results show that the model can reproduce the observed angular variations of radar backscattering coefficient quite well via a least-squares fit method. Best fits to the data provide estimates of the statistical properties of the surface roughness, which is characterized by two parameters: the standard deviation of surface height, and the surface correlation length. In addition, the processes of vegetation attenuation and volume scattering require two canopy parameters, the canopy optical thickness and a volume scattering factor. Canopy parameter values for individual vegetation types, including alfalfa, milo and corn, were also determined from the best-fit results. The uncertainties in the scatterometer data were also explored.

Mo, T.↗

NASA NTRS1992

Multi-resolution processing for fractal analysis of airborne remotely sensed data

Fractal geometry is increasingly becoming a useful tool for modeling natural phenomenon. As an alternative to Euclidean concepts, fractals allow for a more accurate representation of the nature of complexity in natural boundaries and surfaces. Since they are characterized by self-similarity, an ideal fractal surface is scale-independent; i.e. at different scales a fractal surface looks the same. This is not exactly true for natural surfaces. When viewed at different spatial resolutions parts of natural surfaces look alike in a statistical manner and only for a limited range of scales. Images acquired by NASA's Thermal Infrared Multispectral Scanner are used to compute the fractal dimension as a function of spatial resolution. Three methods are used to determine the fractal dimension - Schelberg's line-divider method, the variogram method, and the triangular prism method. A description of these methods and the results of applying these methods to a remotely-sensed image is also presented. Five flights were flown in succession at altitudes of 2 km (low), 6 km (mid), 12 km (high), and then back again at 6 km and 2 km. The area selected was the Ross Barnett reservoir near Jackson, Mississippi. The mission was flown during the predawn hours of 1 Feb. 1992. Radiosonde data was collected for that duration to profile the characteristics of the atmosphere. This corresponds to 3 different pixel sizes - 5m, 15m, and 30m. After, simulating different spatial sampling intervals within the same image for each of the 3 image sets, the results are cross-correlated to compare the extent of detail and complexity that is obtained when data is taken at lower spatial intervals.

Jaggi, S.↗