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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Anomalous refraction of light through slanted-nanoaperture arrays on metal surface

We report a nanoapertured metal surface that demonstrates anomalous refraction of light for a wide range of incident angles. A nanoslit aperture is designed to serve as a tilted vertical-dipole whose radiation pattern orients to a glancing angle direction to substrate. An array of such slanted nanoslits formed in a metal film redirects an incident beam into the direction of negative refraction angle: the aperture-transmitted wave makes a far-field propagation to the tilt-oriented direction of radiation pattern. The thus-designed nanoaperture array demonstrates the −1st order diffraction (i.e., to the negative refraction-angle direction) with well-suppressed background transmission (the zero-order direct transmission and other higher-order diffractions). Engineering the radiation pattern of nanoaperture offers an approach to overcoming the limits of conventional diffractive/refractive optics and complementing metasurface-based nano-optics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

A mechanically driven form of Kirigami as a route to 3D mesostructures in micro/nanomembranes

Assembly of 3D micro/nanostructures in advanced functional materials has important implications across broad areas of technology. Existing approaches are compatible, however, only with narrow classes of materials and/or 3D geometries. This article introduces ideas for a form of Kirigami that allows precise, mechanically driven assembly of 3D mesostructures of diverse materials from 2D micro/nanomembranes with strategically designed geometries and patterns of cuts. Theoretical and experimental studies demonstrate applicability of the methods across length scales from macro to nano, in materials ranging from monocrystalline silicon to plastic, with levels of topographical complexity that significantly exceed those that can be achieved using other approaches. A broad set of examples includes 3D silicon mesostructures and hybrid nanomembrane-nanoribbon systems, including heterogeneous combinations with polymers and metals, with critical dimensions that range from 100 nm to 30 mm. Lastly, a 3D mechanically tunable optical transmission window provides an application example of this Kirigami process, enabled by theoretically guided design.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Exploiting regulatory heterogeneity to systematically identify enhancers with high accuracy

Identifying functional enhancer elements in metazoan systems is a major challenge. Large-scale validation of enhancers predicted by ENCODE reveal false-positive rates of at least 70%. We used the pregrastrula-patterning network of Drosophila melanogaster to demonstrate that loss in accuracy in held-out data results from heterogeneity of functional signatures in enhancer elements. We show that at least two classes of enhancers are active during early Drosophila embryogenesis and that by focusing on a single, relatively homogeneous class of elements, greater than 98% prediction accuracy can be achieved in a balanced, completely held-out test set. The class of well-predicted elements is composed predominantly of enhancers driving multistage segmentation patterns, which we designate segmentation driving enhancers (SDE). Prediction is driven by the DNA occupancy of early developmental transcription factors, with almost no additional power derived from histone modifications. We further show that improved accuracy is not a property of a particular prediction method: after conditioning on the SDE set, naïve Bayes and logistic regression perform as well as more sophisticated tools. Applying this method to a genome-wide scan, we predict 1,640 SDEs that cover 1.6% of the genome. An analysis of 32 SDEs using whole-mount embryonic imaging of stably integrated reporter constructs chosen throughout our prediction rank-list showed >90% drove expression patterns. We achieved 86.7% precision on a genome-wide scan, with an estimated recall of at least 98%, indicating high accuracy and completeness in annotating this class of functional elements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Patterns in wetland microbial community composition and functional gene repertoire associated with methane emissions

Wetland restoration on peat islands previously drained for agriculture has potential to reverse land subsidence and sequester atmospheric carbon dioxide as peat accretes. However, the emission of methane could potentially offset the greenhouse gas benefits of captured carbon. As microbial communities play a key role in governing wetland greenhouse gas fluxes, we are interested in how microbial community composition and functions are associated with wetland hydrology, biogeochemistry, and methane emission, which is critical to modeling the microbial component in wetland methane fluxes and to managing restoration projects for maximal carbon sequestration. Here, we couple sequence-based methods with biogeochemical and greenhouse gas measurements to interrogate microbial communities from a pilot-scale restored wetland in the Sacramento-San Joaquin Delta of California, revealing considerable spatial heterogeneity even within this relatively small site. A number of microbial populations and functions showed strong correlations with electron acceptor availability and methane production; some also showed a preference for association with plant roots. Marker gene phylogenies revealed a diversity of major methane-producing and -consuming populations and suggested novel diversity within methanotrophs. Methanogenic archaea were observed in all samples, as were nitrate-, sulfate-, and metal-reducing bacteria, indicating that no single terminal electron acceptor was preferred despite differences in energetic favorability and suggesting spatial microheterogeneity and microniches. Notably, methanogens were negatively correlated with nitrate-, sulfate-, and metal-reducing bacteria and were most abundant at sampling sites with high peat accretion and low electron acceptor availability, where methane production was highest. Wetlands are the largest nonanthropogenic source of atmospheric methane but also a key global carbon reservoir. Characterizing belowground microbial communities that mediate carbon cycling in wetlands is critical to accurately predicting their responses to changes in land management and climate. Here, we studied a restored wetland and revealed substantial spatial heterogeneity in biogeochemistry, methane production, and microbial communities, largely associated with the wetland hydraulic design. We observed patterns in microbial community composition and functions correlated with biogeochemistry and methane production, including diverse microorganisms involved in methane production and consumption. We found that methanogenesis gene abundance is inversely correlated with genes from pathways exploiting other electron acceptors, yet the ubiquitous presence of genes from all these pathways suggests that diverse electron acceptors contribute to the energetic balance of the ecosystem. These investigations represent an important step toward effective management of wetlands to reduce methane flux to the atmosphere and enhance belowground carbon storage.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

A switch from parallel to antiparallel strand orientation in a coiled-coil X-ray structure via two core hydrophobic mutations

The coiled-coil is one of the most ubiquitous and well studied protein structural motifs. Significant effort has been devoted to dissecting subtle variations of the typical heptad repeat sequence pattern that can designate larger topological features such as relative α-helical orientation and oligomer size. Here in this paper we report the X-ray structure of a model coiled-coil peptide, HA2-Del-L2seM, which forms an unanticipated core antiparallel dimer with potential sites for discrete higher-order multimerization (trimer or tetramer). In the X-ray structure, a third, partially-ordered α-helix is weakly associated with the antiparallel dimer and analytical ultracentrifugation experiments indicate the peptide forms a well-defined tetramer in solution. The HA2-Del-L2seM sequence is closely related to a parent model peptide, HA2-Del, which we previously reported adopts a parallel trimer; HA2-Del-L2seM differs by only hydrophobic leucine to selenomethione mutations and thus this subtle difference is sufficient to switch both relative α-helical topology and number of α-helices participating in the coiled-coil. Comparison of the X-ray structures of HA2-Del-L2seM (reported here) with the HA2-Del parent (reported previously) reveals novel interactions involving the selenomethionine residues that promote antiparallel coiled-coil configuration and preclude parallel trimer formation. Finally, these novel atomic insights are instructive for understanding subtle features that can affect coiled-coil topology and provide additional information for design of antiparallel coiled-coils.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Data mining of space heating system performance in affordable housing

The space heating in residential buildings accounts for a considerable amount of the primary energy use. Therefore, understanding the operation and performance of space heating systems becomes crucial in improving occupant comfort while reducing energy use. This study investigated the behavior of occupants adjusting their thermostat settings and heating system operations in a 62-unit affordable housing complex in Revere, Massachusetts, USA. The data mining methods, including clustering approach and decision trees, were used to ascertain occupant behavior patterns. Data tabulating ON/OFF space heating states was assessed, to provide a better understanding of the intermittent operation of space heating systems in terms of system cycling frequency and the duration of each operation. The decision tree was used to verify the link between room temperature settings, house and heating system characteristics and the heating energy use. The results suggest that the majority of apartments show fairly constant room temperature profiles with limited variations during a day or between weekday and weekend. Data clustering results revealed six typical patterns of room temperature profiles during the heating season. Space heating systems cycled more frequently than anticipated due to a tight range of room thermostat settings and potentially oversized heating capacities. In conclusion, from this study affirm data mining techniques are an effective method to analyze large datasets and extract hidden patterns to inform design and improve operations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2012

Reducing methylmercury accumulation in the food webs of San Francisco Bay and its local watersheds

San Francisco Bay (California, USA) and its local watersheds present an interesting case study in estuarine mercury (Hg) contamination. This review focuses on the most promising avenues for attempting to reduce methylmercury (MeHg) contamination in Bay Area aquatic food webs and identifying the scientific information that is most urgently needed to support these efforts. Concern for human exposure to MeHg in the region has led to advisories for consumption of sport fish. Striped bass from the Bay have the highest average Hg concentration measured for this species in USA estuaries, and this degree of contamination has been constant for the past 40 years. Similarly, largemouth bass in some Bay Area reservoirs have some of the highest Hg concentrations observed in the entire US. Bay Area wildlife, particularly birds, face potential impacts to reproduction based on Hg concentrations in the tissues of several Bay species. Source control of Hg is one of the primary possible approaches for reducing MeHg accumulation in Bay Area aquatic food webs. Recent findings (particularly Hg isotope measurements) indicate that the decades-long residence time of particle-associated Hg in the Bay is sufficient to allow significant conversion of even the insoluble forms of Hg into MeHg. Past inputs have been thoroughly mixed throughout this shallow and dynamic estuary. The large pool of Hg already present in the ecosystem dominates the fraction converted to MeHg and accumulating in the food web. Consequently, decreasing external Hg inputs can be expected to reduce MeHg in the food web, but it will likely take many decades to centuries before those reductions are achieved. Extensive efforts to reduce loads from the largest Hg mining source (the historic New Almaden mining district) are underway. Hg is spread widely across the urban landscape, but there are a number of key sources, source areas, and pathways that provide opportunities to capture larger quantities of Hg and reduce loads from urban runoff. Atmospheric deposition is a lower priority for source control in the Bay Area due to a combination of a lack of major local sources. Internal net production of MeHg is the dominant source of MeHg that enters the food web. Controlling internal net production is the second primary management approach, and has the potential to reduce food web MeHg in some habitats more effectively and within a much shorter time-frame. Controlling net MeHg production and accumulation in the food web of upstream reservoirs and ponds is very promising due to the many features of these ecosystems that can be manipulated. The most feasible control options in tidal marshes relate to the design of flow patterns and subhabitats in restoration projects. Options for controlling MeHg production in open Bay habitat are limited due primarily to the highly dispersed distribution of Hg throughout the ecosystem. Other changes in these habitats may also have a large influence on food web MeHg, including temperature changes due to global warming, sea level rise, food web alterations due to introduced species and other causes, and changes in sediment supply. Other options for reducing or mitigating exposure and risk include controlling bioaccumulation, cleanup of contaminated sites, and reducing other factors (e.g., habitat availability) that limit at-risk wildlife populations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Coupling polariton quantum boxes in sub-wavelength grating microcavities

We report the construction of decoupled, coupled, and quasi-one dimensional polariton systems from zero dimensional polariton quantum boxes using microcavities with sub-wavelength gratings as the top mirror. By designing the tethering patterns around the suspended sub-wavelength gratings, we control the coupling between individual quantum boxes through different optical potentials. Energy levels and real-space or momentum space distributions of the confined modes were measured, which agreed well with simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Searching for primordial non-Gaussianity in Planck CMB maps using a combined estimator

The extensive search for deviations from Gaussianity in cosmic microwave background radiation (CMB) data is very important due to the information about the very early moments of the universe encoded there. Recent analyses from Planck CMB data do not exclude the presence of non-Gaussianity of small amplitude, although they are consistent with the Gaussian hypothesis. The use of different techniques is essential to provide information about types and amplitudes of non-Gaussianities in the CMB data. In particular, we find interesting to construct an estimator based upon the combination of two powerful statistical tools that appears to be sensitive enough to detect tiny deviations from Gaussianity in CMB maps. This estimator combines the Minkowski functionals with a Neural Network, maximizing a tool widely used to study non-Gaussian signals with a reinforcement of another tool designed to identify patterns in a data set. We test our estimator by analyzing simulated CMB maps contaminated with different amounts of local primordial non-Gaussianity quantified by the dimensionless parameter f{sub NL}. We apply it to these sets of CMB maps and find ∼> 98% of chance of positive detection, even for small intensity local non-Gaussianity like f{sub NL} = 38±18, the current limit from Planck data for large angular scales. Additionally, we test the suitability to distinguish between primary and secondary non-Gaussianities: first we train the Neural Network with two sets, one of nearly Gaussian CMB maps (|f{sub NL}| ≤ 10) but contaminated with realistic inhomogeneous Planck noise (i.e., secondary non-Gaussianity) and the other of non-Gaussian CMB maps, that is, maps endowed with weak primordial non-Gaussianity (28 ≤ f{sub NL} ≤ 48); after that we test an ensemble composed of CMB maps either with one of these non-Gaussian contaminations, and find out that our method successfully classifies ∼ 95% of the tested maps as being CMB maps containing primordial or secondary non-Gaussianity. Furthermore, we analyze the foreground-cleaned Planck maps obtaining constraints for non-Gaussianity at large-angles that are in good agreement with recent constraints. Finally, we also test the robustness of our estimator including cut-sky masks and realistic noise maps measured by Planck, obtaining successful results as well.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Tricoupled hybrid lattice Boltzmann model for nonisothermal drying of colloidal suspensions in micropore structures

A tricoupled hybrid lattice Boltzmann model (LBM) is developed to simulate colloidal liquid evaporation and colloidal particle deposition during the nonisothermal drying of colloidal suspensions in micropore structures. An entropic multiple-relaxation-time multirange pseudopotential two-phase LBM for isothermal interfacial flow is first coupled to an extended temperature equation for simulating nonisothermal liquid drying. Then the coupled model is further coupled with a modified convection diffusion equation to consider the nonisothermal drying of colloidal suspensions. Two drying examples are considered. First, drying of colloidal suspensions in a two-pillar micropore structure is simulated in two dimensions (2D), and the final configuration of colloidal particles is compared with the experimental one. Good agreement is observed. Second, at the temperature of 343.15 K ( 70°C ), drying of colloidal suspensions in a complex spiral-shaped micropore structure containing 220 pillars is simulated (also in 2D). The drying pattern follows the designed spiral shape due to capillary pumping, i.e., transport of the liquid from larger pores to smaller ones by capillary pressure difference. Because the colloidal particles are passively carried with liquid, they accumulate at the small menisci as drying proceeds. As liquid evaporates at the small menisci, colloidal particles are deposited, eventually forming solid structures between the pillars (primarily), and at the base of the pillars (secondarily). As a result, the particle deposition conforms to the spiral route. Qualitatively, the simulated liquid and particle configurations agree well with the experimental ones during the entire drying process. Quantitatively, the model demonstrates that the evaporation rate and the particle accumulation rate slowly decrease during drying, similar to what is seen in the experimental results, which is due to the reduction of the liquid-vapor interfacial area. In conclusion, the hybrid model shows the capability and accuracy for simulating nonisothermal drying of colloidal suspensions in a complex micropore structure both qualitatively and quantitatively, as it includes all the required physics and captures all the complex features observed experimentally. Such a tricoupled LBM has a high potential to become an efficient numerical tool for further investigation of real and complex engineering problems incorporating drying of colloidal suspensions in porous media.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Forecast of Wildfire Potential Across California USA Using a Transformer

Wildfires are a major issue facing the United States, a matter further exacerbated by an ever-changing climate. In California alone, wildfires are responsible for billions of dollars in damages and take lives each year. Accurately predicting fire danger conditions allows preparation awareness before wildfires start. Transformers are a class of deep learning models designed to identify patterns in sequential datasets. In recent years, transformers have gained popularity through their impressive performance in natural language processing and other applications of signal recognition. This analysis demonstrates the ability of a transformer with a residual connection to forecast fire danger potential over the state of California. Wildland fire potential index (WFPI) maps collected from the US Geological Survey database from January 1st 2020 to December 31st 2023 were used to tune, train and evaluate the transformer. Meteorological inputs (provided by Daymet daily weather and climatological summaries), the normalized difference vegetation index (NDVI) (calculated from the Moderate Resolution Imaging Spectroradiometer (MODIS)), and outputs from the Scott and Burgman fire behavior fuel models (to characterize maps of fuel types), were used as inputs. Our results show that a transformer can effectively emulate the US Forest Service modeled WFPI maps of California USA for four week long forecasts over the month of July, 2023, with correlations ranging from 0.85 – 0.98.

Limber, Russell [ORNL]↗
DOE OSTI2021

Improving I/O Performance for Exascale Applications through Online Data Layout Reorganization

The applications being developed within the U.S. Exascale Computing Project (ECP) to run on imminent Exascale computers will generate scientific results with unprecedented fidelity and record turn-around time. Many of these codes are based on particle-mesh methods and use advanced algorithms, especially dynamic load-balancing and mesh-refinement, to achieve high performance on Exascale machines. Yet, as such algorithms improve parallel application efficiency, they raise new challenges for I/O logic due to their irregular and dynamic data distributions. Thus, while the enormous data rates of Exascale simulations already challenge existing file system write strategies, the need for efficient read and processing of generated data introduces additional constraints on the data layout strategies that can be used when writing data to secondary storage. We review these I/O challenges and introduce two online data layout reorganization approaches for achieving good tradeoffs between read and write performance. We demonstrate the benefits of using these two approaches for the ECP particle-in-cell simulation WarpX, which serves as a motif for a large class of important Exascale applications. Here, we show that by understanding application I/O patterns and carefully designing data layouts we can increase read performance by more than 80 percent.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Sequential self-folding of polymer sheets

Shape plays an important role in defining the function of materials, particularly those found in nature. Several strategies exist to program materials to change from one shape to another; however, few can temporally and spatially control the shape. Programming the sequence of shape transformation with temporal control has been driven by the desire to generate complex shapes with high yield and to create multiple shapes from the same starting material. This paper demonstrates a markedly simple strategy for programmed self-folding of two-dimensional (2D) polymer sheets into 3D objects in a sequential manner using external light. Printed ink on the surface of the polymer sheets discriminately absorbs light on the basis of the wavelength of the light and the color of the ink that defines the hinge about which the sheet folds. The absorbed light gradually heats the underlying polymer across the thickness of the sheet, which causes relief of strain to induce folding. These color patterns can be designed to absorb only specific wavelengths of light (or to absorb differently at the same wavelength using color hues), thereby providing control of sheet folding with respect to time and space. This type of shape programming may have numerous applications, including reconfigurable electronics, actuators, sensors, implantable devices, smart packaging, and deployable structures.

42 ENGINEERING↗
DOE OSTI2012

Solution-Procesed Small-Molecule OLED Luminaire for Interior Illumination

Prototype lighting panels and luminaires were fabricated using DuPont Displays solution-processed small-molecule OLED technology. These lighting panels were based on a spatially-patterned, 3-color design, similar in concept to an OLED display panel, with materials chosen to maximize device efficacy. The majority of the processing steps take place in air (rather than high vacuum). Optimization of device architecture, processing and construction was undertaken, with a final prototype design of 50 cm{sup 2} being fabricated and tested. Performance of these panels reached 35 lm/W at illuminant-A. A unique feature of this technology is the ability to color tune the emission, and color temperatures ranging from 2700 to > 6,500K were attained in the final build. Significant attention was paid to low-cost fabrication techniques.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Hydropower Flexibility Framework (Final Technical Report)

The Hydropower Flexibility Framework (HFF) tool focuses on providing the hydropower community with an effective means of assessing optimized hydropower plant outcomes. This tool combines both site specific characteristics, which act to constrain plant operation, and the hydrologic and grid characteristics which drive hydropower plant operation. The hydropower community faces a confluence of factors which drive the importance of developing such a capability, including an aging hydropower fleet subject to a range of modernization opportunities, a large number of hydropower plant relicensing activities which may affect operational requirements, an electrical grid with increasing levels of variable resources which must be balanced to maintain grid stability, and climate change influencing riverine hydrologic patterns outside of design characteristics. With support from the hydropower community, the project team developed the HFF tool and demonstrated the tool through a series of Use Cases. This guidance was developed as a part of the larger HFF tool User’s Manual (see Appendix B), a resource designed to inform other users and to empower community uptake of the tool. The HFF tool, hosted at https://hfftool.com/, was developed with the support of the U.S. Department of Energy (DOE) Water Power Technologies Office (WPTO). EPRI is currently exploring alternatives to support the continued maintenance and functionally of the online tool.

13 HYDRO ENERGY↗
DOE OSTI2026

Direct Ink Write and Processing of Complex 3D Marine Compatible Structures with Calcium Carbonate Slurries

Ocean acidification heavily impacts marine ecosystems by reducing calcification. Many coral-algae symbiotic relationships are in jeopardy due to the destruction of coral reefs. Here, a ceramic ink compatible with the direct ink write additive manufacturing technique was formulated and used to print marine compatible structures that could grow algae and restore that relationship. A diacrylate polymer was mixed with calcium carbonate, a material that comprises a coral skeleton, to create a slurry with shear thinning properties. Rheology studies were conducted to confirm printing properties and characterize the slurry. Printed parts demonstrated strong control over print features, including size and infill design. Various infill patterns and percentages were attempted to optimize printability and potential algae growth. Thermogravimetric analysis helped determine a logical burnout and sintering procedure to avoid large cracking. This project developed a printable and sinter-able calcium carbonate ceramic slurry for complex marine-compatible structures and algae growth. This research was conducted in the support of the Eco Reef project.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Funding for the 2ND IAEA technical meeting on fusion data processing, validation and analysis

The International Atomic Energy Agency (IAEA) will organize the second Technical Meeting on Fusion Da Processing, Validation and Analysis from 30 May to 02 June, 2017, in Cambridge, MA USA. The meeting w be hosted by the MIT Plasma Science and Fusion Center (PSFC). The objective of the meeting is to provide a platform where a set of topics relevant to fusion data processing, validation and analysis are discussed with the view of extrapolation needs to next step fusion devices such as ITER. The validation and analysis of experimental data obtained from diagnostics used to characterize fusion plasmas are crucial for a knowledge based understanding of the physical processes governing the dynamics of these plasmas. The meeting will aim at fostering, in particular, discussions of research and development results that set out or underline trends observed in the current major fusion confinement devices. General information on the IAEA, including its mission and organization, can be found at the IAEA websit Uncertainty quantification (UQ) Model selection, validation, and verification (V&V) Probability theory and statistical analysis Inverse problems & equilibrium reconstru ction Integrated data analysis Real time data analysis Machine learning Signal/image proc essing & pattern recognition Experimental design and synthetic diagnostics Data management

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗