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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

OBSERVATIONAL SCAN-INDUCED ARTIFICIAL COSMIC MICROWAVE BACKGROUND ANISOTROPY

Reliably detecting the cosmic microwave background (CMB) anisotropy is of great importance in understanding the birth and evolution of the universe. One of the difficulties in CMB experiments is the domination of measured CMB anisotropy maps by the Doppler dipole moment from the motion of the antenna relative to the CMB. For each measured temperature, the expected dipole component has to be calculated separately and then subtracted from the data. A small error in dipole direction, antenna pointing direction, sidelobe pickup contamination, and/or timing synchronism can introduce a significant deviation in the dipole-cleaned CMB temperature. After a full-sky observational scan, the accumulated deviations will be structured with a pattern closely correlated with the observation pattern with artificial anisotropies, including artificial quadrupole, octupole, etc., on large scales in the final CMB map. Such scan-induced anisotropies on large scales can be predicted by the true dipole moment and observational scan scheme. Indeed, the expected scan-induced quadrupole pattern of the Wilkinson Microwave Anisotropy Probe (WMAP) mission is perfectly in agreement with the published WMAP quadrupole. With the scan strategy of the Planck mission, we predict that scan-induced anisotropies will also produce an artificially aligned quadrupole. The scan-induced anisotropy is a common problem for all sweep missions and, like the foreground emissions, has to be removed from observed maps. Without doing so, CMB maps from COBE, WMAP, and Planck are not reliable for studying the CMB anisotropy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Self-organization of nanoparticles and molecules in periodic Liesegang-type structures

Chemical organization in reaction-diffusion systems offers a strategy for the generation of materials with ordered morphologies and structural hierarchy. Periodic structures are formed by either molecules or nanoparticles. On the premise of new directing factors and materials, an emerging frontier is the design of systems in which the precipitation partners are nanoparticles and molecules. We show that solvent evaporation from a suspension of cellulose nanocrystals (CNCs) and L -(+)-tartaric acid [ L -(+)-TA] causes phase separation and precipitation, which, being coupled with a reaction/diffusion, results in rhythmic alternation of CNC-rich and L -(+)-TA–rich rings. The CNC-rich regions have a cholesteric structure, while the L -(+)-TA–rich bands are formed by radially aligned elongated bundles. The moving edge of the pattern propagates with a finite constant velocity, which enables control of periodicity by varying film preparation conditions. This work expands knowledge about self-organizing reaction-diffusion systems and offers a strategy for the design of self-organizing materials.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Resistance of fly ash-Portland cement blends to thermal shock

Thermal-shock resistance of high-content fly ash-Portland cement blends was tested in the following ways. Activated and non-activated blends with 80-90 % fly ash F (FAF) were left to set at room temperature, then hydrated for 24 hours at 85°C and 24-more hours at 300°C and tested in five thermal-shock cycles (600°C heat - 25°C water quenching). XRD, and thermal gravimetric analyses, along with calorimetric measurements and SEM-EDX tests demonstrated that the activated blends form more hydrates after 24 hours at 300°C, and achieve a higher short-term compressive strength than do non-activated ones. Sodium meta-silicate and sodaash engendered the concomitant hydration of OPC and FAF, with the formation of mixed crystalline FAF-OPC hydrates and FAF hydrates, such as garranite, analcime, and wairakite, along with the amorphous FAF hydration products. In SS-activated and non-activated blends separate OPC (tobermorite) and FAF (amorphous gel) hydrates with no mixed crystalline products formed. The compressive strength of all tested blends decreased by nearly 50% after 5 thermal-shock test cycles. These changes in the compressive strength were accompanied by a marked decrease in the intensities of XRD patterns of the crystalline hydrates after the thermalshock. As a result, there was no significant difference in the performance of the blends with different activators

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

Effects of downscaled high-resolution meteorological data on the PSCF identification of emission sources

The Potential Source Contribution Function (PSCF) model has been successfully used for identifying regions of emission source at a long distance in this study, the PSCF model relies on backward trajectories calculated by the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. In this study, we investigated the impacts of grid resolution and Planetary Boundary Layer (PBL) parameterization (e.g., turbulent transport of pollutants) on the PSCF analysis. The Mellor-Yamada-Janjic (MYJ) and Yonsei University (YUS) parameterization schemes were selected to model the turbulent transport in the PBL within the Weather Research and Forecasting (WRF version 3.6) model. Two separate domain grid sizes (83 and 27 km) were chosen in the WRF downscaling in generating the wind data for driving the HYSPLIT calculation. The effects of grid size and PBL parameterization are important in incorporating the influ- ence of regional and local meteorological processes such as jet streaks, blocking patterns, Rossby waves, and terrain-induced convection on the transport of pollutants by a wind trajectory. We found high resolution PSCF did discover and locate source areas more precisely than that with lower resolution meteorological inputs. The lack of anticipated improvement could also be because a PBL scheme chosen to produce the WRF data was only a local parameterization and unable to faithfully duplicate the real atmosphere on a global scale. The MYJ scheme was able to replicate PSCF source identification by those using the Reanalysis and discover additional source areas that was not identified by the Reanalysis data. In conclusion, a potential benefit for using high-resolution wind data in the PSCF modeling is that it could discover new source location in addition to those identified by using the Reanalysis data input.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Facile fabrication of p-BiOI/n-Zn{sub 2}SnO{sub 4} heterostructures with highly enhanced visible light photocatalytic performances

Highlights: • The BiOI/Zn{sub 2}SnO{sub 4} photocatalysts were prepared by a mild wet chemical method. • The ZB-1/2 (Zn to Bi molar ratio = 1/2) exhibits the best photocatalytic activity. • The enhanced performance results from high separation of photogenerated carriers. - Abstract: New BiOI/Zn{sub 2}SnO{sub 4} p–n heterojunction photocatalysts were prepared by anchoring n-type Zn{sub 2}SnO{sub 4} nanoparticles on p-type BiOI plates. The physicochemical characteristics of the catalysts were studied by X-ray powder diffraction pattern (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray photoelectron spectra (XPS), Ultraviolet visible (UV–vis) diffuse reflectance spectroscopy (DRS), nitrogen adsorption–desorption, and photoelectrochemistry measurement. The as-prepared catalysts exhibited excellent photocatalytic activity for the decomposition of methyl orange (MO) under visible light irradiation. The enhanced photocatalytic performance of BiOI/Zn{sub 2}SnO{sub 4} was not only attributed to the matched band potentials but also the interconnected heterojunction of BiOI and Zn{sub 2}SnO{sub 4} nanoparticles.

36 MATERIALS SCIENCE↗
DOE OSTI2012

A Measurement of the Two Track Charged Current Quasi-Elastic Cross Section with the MINER$\nu$A Detector

The MINER$\nu$A detector collected 1.2 × 10 20 POT of $\nu$ μ data with the NuMI beam at Fermi National Laboratory from 03/2010 to 07/2010. I will describe an analysis to identify two track charged current muon neutrino quasi-elastic interactions using this data set. The final state muon was identified by curvature using the MINOS detector. The final state contained proton was identified by the energy deposited per unit length at the end of the track. Two additional cuts were applied to separate signal from background: a cut on the extra energy in the event and a cut on a proton energy dependent variable. The dσ/dQ2 using this selection is presented. An initial list of systematic errors is introduced and calculated. In addition to this analysis work, I also developed both pattern recognition schemes used by the experiment, wrote MINOS muon track matching algorithms, implemented a Kalman Filter track fitting algorithm and contributed to various other tasks to the MINER$\nu$A experiment; I will provide an explanation of these. I will also give a brief overview of neutrino physics, the NuMI beam, and the MINER$\nu$A detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Wind Supply Chain Security: Hardware Enumeration and Analysis

This project, undertaken by Idaho National Laboratory (INL) for the Department of Energy (DOE) Wind Energy Technologies Office (WETO), focused on the enumeration and analysis of six key devices important to wind technologies. The devices analyzed included Beckhoff Bus Terminal Controllers (BK1120 and BC9000), a Beckhoff Economy Built-in Panel PC (CP6231), an N-Tron Managed Industrial Ethernet Switch (711FX3), a Bachmann M1 Gateway, and a Bachmann Smart Power Plant Controller. Device selection was driven by availability and budget constraints, with several components sourced from existing wind farms and others procured through a co-agreement with another WETO-funded project. The project's primary objective was to create a hardware bill of materials (HBOM) for each device, identifying and documenting all components to assess potential security and supply chain risks. A detailed analysis revealed over 750 unique components across the six devices, with 80% successfully identified and accompanied by datasheets. Notably, Texas Instruments emerged as the leading supplier, providing over 16% of the components, followed by ON Semiconductor at 11.3%, Analog Devices at 5.3%, and Renesas Electronics Corp at 4.1%. Other notable vendors included Toshiba Corporation, iC-Haus Corporation, Atmel, Vishay, and STMicroelectronics. The enumeration process involved thorough documentation of each component, including its designation, quantity, identifiers, pin package, description, vendor, model, and country of origin. This process provided valuable insights into the complexity and diversity of the electronic systems within these wind devices. It also highlighted the distinct separation of components between vendors, suggesting a trend of vendor-specific component usage. Key findings from the project emphasized the importance of broadening the scope of vendor analysis in future research to gain a comprehensive understanding of component distribution and commonality. The identification of vendor-specific component usage patterns offers new avenues for research and underscores the significance of continued investigation in this field. Overall, this project provides critical insights into the component composition of wind devices, aiding in the development of improved supply chain management and component sourcing strategies. The results contribute valuable knowledge to the wind technology sector, laying the groundwork for enhanced security and resilience in wind energy systems.

17 - WIND ENERGY↗
DOE OSTI2022

An Updated Review of Hypotheses Regarding Bat Attraction to Wind Turbines

Patterns of bat activity and mortalities at wind energy facilities suggest that bats are attracted to wind turbines based on bat behavioral responses to wind turbines. For example, current monitoring efforts suggest that bat activity increases post-wind turbine construction, with bats making multiple passes near wind turbines. We separated the attraction hypothesis into five previously proposed explanations of bat interactions at or near wind turbines, including attraction based on noise, roost sites, foraging and water, mating behavior, and lights, and one new hypothesis regarding olfaction, and provide a state of the knowledge in 2022. Our review indicates that future research should prioritize attraction based on social behaviors, such as mating and scent-marking, as this aspect of the attraction hypothesis has many postulates and remains the most unclear. Relatively more data regarding attraction to wind turbines based on lighting and noise emission exist, and these data indicate that these are unlikely attractants. Analyzing attraction at the species-level should be prioritized because of differences in foraging, flight, and social behavior among bat species. Lastly, research assessing bat attraction at various scales, such as the turbine or facility scale, is lacking, which could provide important insights for both wind turbine siting decisions and bat mortality minimization strategies. Identifying the causes of bat interactions with wind turbines is critical for developing effective impact minimization strategies.

17 WIND ENERGY↗
DOE OSTI2015

Challenge Online Time Series Clustering For Demand Response A Theory to Break the ‘Curse of Dimensionality'

The advent of smart meters and advanced communication infrastructures catalyzes numerous smart grid applications such as dynamic demand response, and paves the way to solve challenging research problems in sustainable energy consumption. The space of solution possibilities are restricted primarily by the huge amount of generated data requiring considerable computational resources and efficient algorithms. To overcome this Big Data challenge, data clustering techniques have been proposed. Current approaches however do not scale in the face of the “increasing dimensionality” problem where a cluster point is represented by the entire customer consumption time series. To overcome this aspect we first rethink the way cluster points are created and designed, and then design an efficient online clustering technique for demand response (DR) in order to analyze high volume, high dimensional energy consumption time series data at scale, and on the fly. Our online algorithm is randomized in nature, and provides optimal performance guarantees in a computationally efficient manner. Unlike prior work we (i) study the consumption properties of the whole population simultaneously rather than developing individual models for each customer separately, claiming it to be a ‘killer’ approach that breaks the “curse of dimensionality” in online time series clustering, and (ii) provide tight performance guarantees in theory to validate our approach. Our insights are driven by the field of sociology, where collective behavior often emerges as the result of individual patterns and lifestyles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Spatiotemporal Patterns of Precipitation-Modulated Landslide Deformation From Independent Component Analysis of InSAR Time Series

We present that long-term landslide deformation is disruptive and costly in urbanized environments. We rely on TerraSAR-X satellite images (2009–2014) and an improved data processing algorithm (SqueeSAR™) to produce an exceptionally dense Interferometric Synthetic Aperture Radar ground deformation time series for the San Francisco East Bay Hills. Independent and principal component analyses of the time series reveal four distinct spatial and temporal surface deformation patterns in the area around Blakemont landslide, which we relate to different geomechanical processes. Two components of time-dependent landslide deformation isolate continuous motion and motion driven by precipitation-modulated pore pressure changes controlled by annual seasonal cycles and multiyear drought conditions. Two components capturing more widespread seasonal deformation separate precipitation-modulated soil swelling from annual cycles that may be related to groundwater level changes and thermal expansion of buildings. Lastly, high-resolution characterization of landslide response to precipitation is a first step toward improved hazard forecasting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Thermodynamic Stability of Molybdenum Oxycarbides Formed from Orthorhombic Mo 2 C in Oxygen-Rich Environments

Molybdenum carbide (Mo 2 C) nanoparticles and thin films are particularly suitable catalysts for catalytic fast pyrolysis (CFP) as they are effective for deoxygenation and can catalyze certain reactions that typically occur on noble metals. Oxygen deposited during deoxygenation reactions may alter the carbide structure, leading to the formation of oxycarbides, which can determine changes in catalytic activity or selectivity. Despite emerging spectroscopic evidence of bulk oxycarbides, so far there have been no reports of their precise atomic structure or their relative stability with respect to orthorhombic Mo 2 C. This knowledge is essential for assessing the catalytic properties of molybdenum (oxy)carbides for CFP. In this article, we use density functional theory (DFT) calculations to (a) describe the thermodynamic stability of surface and subsurface configurations of oxygen and carbon atoms for a commonly studied Mo-terminated surface of orthorhombic Mo 2 C and (b) determine atomic structures for oxycarbides with a Mo:C ratio of 2:1. The surface calculations suggest that oxygen atoms are not stable under the top Mo layer of the Mo 2 C(100) surface. Coupling DFT calculations with a polymorph sampling method, we determine (Mo 2 C) x O y oxycarbide structures for a wide range of oxygen compositions. Oxycarbides with lower oxygen content (y/x = 2) adopt layered structures reminiscent of the parent carbide phase, with flat Mo layers separated by layers of oxygen and carbon; for higher oxygen content, our results suggest the formation of amorphous phases, as the atomic layers lose their planarity with increasing oxygen content. We characterize the oxidation states of Mo in the oxycarbide structures determined computationally, and simulate their X-ray diffraction (XRD) patterns in order to facilitate comparisons with experiments. Our study may provide a platform for large-scale investigations of the catalytic properties of oxycarbides and their surfaces and for tailoring the catalytic properties for different desired reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Surfactant-like peptide gels are based on cross-β amyloid fibrils

Surfactant-like peptides, in which hydrophilic and hydrophobic residues are encoded within different domains in the peptide sequence, undergo facile self-assembly in aqueous solution to form supramolecular hydrogels. These peptides have been explored extensively as substrates for the creation of functional materials since a wide variety of amphipathic sequences can be prepared from commonly available amino acid precursors. The self-assembly behavior of surfactant-like peptides has been compared to that observed for small molecule amphiphiles in which nanoscale phase separation of the hydrophobic domains drives the self-assembly of supramolecular structures. Here, we investigate the relationship between sequence and supramolecular structure for a pair of bola-amphiphilic peptides, Ac-KLIIIK-NH 2 (L2) and Ac-KIIILK-NH 2 (L5). Despite similar length, composition, and polar sequence pattern, L2 and L5 form morphologically distinct assemblies, nanosheets and nanotubes, respectively. Cryo-EM helical reconstruction was employed to determine the structure of the L5 nanotube at near-atomic resolution. Rather than displaying self-assembly behavior analogous to conventional amphiphiles, the packing arrangement of peptides in the L5 nanotube displayed steric zipper interfaces that resembled those observed in the structures of β-amyloid fibrils. Like amyloids, the supramolecular structures of the L2 and L5 assemblies were sensitive to conservative amino acid substitutions within an otherwise identical amphipathic sequence pattern. This study highlights the need to better understand the relationship between sequence and supramolecular structure to facilitate the development of functional peptide-based materials for biomaterials applications.

Das, Abhinaba [Emory University, Atlanta, GA (Unit↗
DOE OSTI2025

Reuniting crystallography with real space: Ab initio structure elucidation with 4D-STEM

Structure elucidation via single-crystal methods has historically lacked experimental access to real-space information, instead relying exclusively on diffraction-space measurements of Bragg reflections. Here we exploit the dual-space imaging power of 4D scanning transmission electron microscopy to meaningfully integrate real-space information into the crystallographic workflow. We show that virtual apertures assembled by segmentation of high-angle annular dark-field images enable i) pixel-by-pixel separation of coherent Bragg signal from clusters of closely spaced nanocrystals and ii) selective extraction of integrated intensities from thinner subregions of individual specimens, facilitating retroactive tuning of multiple scattering artifacts. This strategy empowers us to simply pick and choose whichever nanoscale regions of interest generate the highest-quality diffraction patterns, allowing us to solve several independent structures of the metal-organic framework UiO-66 from specimens whose agglomerated morphology proved intractable for conventional microcrystal electron diffraction. Our method is compatible with both rotational and serial approaches to data processing, ultimately divulging the first scanning nanobeam electron diffraction structures determined by direct methods at subangstrom resolution.

Saha, Ambarneil↗
DOE OSTI2022

Plant Nutrition Influences Resistant Maize Defense Responses to the Fall Armyworm ( Spodoptera frugiperda )

Plants are often confronted by different groups of herbivores, which threaten their growth and reproduction. However, they are capable of mounting defenses against would-be attackers which may be heightened upon attack. Resistance to insects often varies among plant species, with different genotypes exhibiting unique patterns of chemical and physical defenses. Within this framework, plant access to nutrients may be critical for maximal functioning of resistance mechanisms and are likely to differ among plant genotypes. In this study, we aimed to test the hypothesis that access to nutrition would alter the expression of plant resistance to insects and alter insect performance in a manner consistent with fertilization regime. We used two maize (Zea mays) genotypes possessing different levels of resistance and the fall armyworm (Spodoptera frugiperda) as model systems. Plants were subjected to three fertilization regimes prior to assessing insect-mediated responses. Upon reaching V4 stage, maize plants were separated into two groups, one of which was infested with fall armyworm larvae to induce plant defenses. Plant tissue was collected and used in insect bioassays and to measure the expression of defense-related genes and proteins. Insect performance differed between the two plant genotypes substantially. For each genotype, fertilization altered larval performance, where lower fertilization rates hindered larval growth. Induction of plant defenses by prior herbivory substantially reduced naïve fall armyworm growth in both genotypes. The effects between fertilization and induced defenses were complex, with low fertilization reducing induced defenses in the resistant maize. Gene and protein expression patterns differed between the genotypes, with herbivory often increasing expression, but differing between fertilization levels. The soluble protein concentrations did not change across fertilization levels but was higher in the susceptible maize genotype. These results demonstrate the malleability of plant defenses and the cascading effects of plant nutrition on insect herbivory.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Deposition of Pd–Ag thin film membranes on ceramic supports for hydrogen purification/separation

Highlights: • Thin film Pd–Ag membranes have been produced for hydrogen selectivity. • Magnetron sputtering yields Pd–Ag compact films for atomic H diffusion. • The thin film Pd–Ag membranes yielded a selectivity of α (H{sub 2}/N{sub 2}) = 10. - Abstract: Pd–Ag based membranes supported on porous α-Al{sub 2}O{sub 3} (doped with yttria-stabilized zirconia) were studied for hydrogen selective separation. Magnetron sputtering technique was employed for the synthesis of thin film membranes. The hydrogen permeation flux is affected by the membrane columnar structure, which is formed during deposition. From scanning electron microscopy analysis, it was observed that different sputtering deposition pressures lead to distinct columnar structure growth. X-ray diffraction patterns provided evidence of a Pd–Ag solid solution with an average crystallite domain size of 21 nm, whose preferential growth can be altered by the deposition pressure. The gas-permeation results have shown that the Pd–Ag membrane supported on porous α-Al{sub 2}O{sub 3} is selective toward H{sub 2}. For optimized membrane synthesis conditions, the permeance toward N{sub 2} is 0.076 × 10{sup −6} mol m{sup −2} s{sup −1} Pa{sup −1} at room temperature, whereas for a pressure difference of 300 kPa the H{sub 2}-flux is of the order of ca. 0.21 mol m{sup −2} s{sup −1}, which corresponds to a permeance of 0.71 × 10{sup −6} mol m{sup −2} s{sup −1} Pa{sup −1}, yielding a selectivity of α (H{sub 2}/N{sub 2}) = 10. These findings suggest that the membrane has a reasonable capacity to selectively permeate this gas.

36 MATERIALS SCIENCE↗
DOE OSTI2011

Phospholipid fatty acid biomarkers in a freshwater periphyton community exposed to uranium: discovery by non-linear statistical learning

Phospholipid fatty acids (PLFA) have been widely used to characterize environmental microbial communities, generating community profiles that can distinguish phylogenetic or functional groups within the community. The poor specificity of organism groups with fatty acid biomarkers in the classic PLFA-microorganism associations is a confounding factor in many of the statistical classification/clustering approaches traditionally used to interpret PLFA profiles. In this paper we demonstrate that non-linear statistical learning methods, such as a support vector machine (SVM), can more accurately find patterns related to uranyl nitrate exposure in a freshwater periphyton community than linear methods, such as partial least squares discriminant analysis. In addition, probabilistic models of exposure can be derived from the identified lipid biomarkers to demonstrate the potential model-based approach that could be used in remediation. The SVM probability model separates dose groups at accuracies of ~87.0%, ~71.4%, ~87.5%, and 100% for the four groups; Control (non-amended system), low-dose (amended at 10 µg U L-1), medium dose (amended at 100 µg U L-1), and high dose (500 µg U L-1). The SVM model achieved an overall cross-validated classification accuracy of ~87% in contrast to ~59% for the best linear classifier.

54 ENVIRONMENTAL SCIENCES↗