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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Vertical meteorological patterns and their impact on the energy demand of tall buildings

In accordance with the developing economy and growing population, an increasing number of tall buildings have been constructed over the last 20 years. In 2017, there were 144 new buildings worldwide that were 200 m or greater in height; 50% of these buildings were in China. Due to the vertical gradient impact of meteorological parameters, the energy performance of tall buildings differs from that of general buildings. Few studies exist on vertical meteorological changes using measured data at different heights. Most studies on dynamic energy simulation simulate meteorological parameters using models. This study explores vertical meteorological patterns using hourly dry-bulb temperature, relative humidity, and wind speed data from 2007 to 2017 for a 325 m meteorological tower in Beijing. The temperature decreased significantly with increasing altitude (~0.9 °C per 100 m), while the daily temperature difference decreased with increasing altitude. The absolute humidity did not change significantly with height. The wind speed increased with altitude at approximately 2 m/s per 100 m. The building simulation showed that the annual heating load at a height of 320 m increased by 85% from that at 8 m; the annual cooling load decreased by 20%. Such significant differences in thermal loads for 300-m-tall buildings confirm the need to consider vertical meteorological differences in building performance simulations for tall buildings. A greater number of measurement points at different heights improve the simulation accuracy. Finally, guidance on selecting the heights for vertical metrological measurements is provided based on the influences of building thermal loads.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Multilevel peel-off patterning of a prototype semitransparent organic photovoltaic module

Semitransparent organic photovoltaics (ST-OPVs) with applications to power generating windows have shown substantial increases in power conversion efficiency (PCE) and average photopic transmission (APT) at the laboratory scale. Here, the demonstration of similarly efficient, large-scale ST-OPV modules with geometric fill factors (GFF) approaching 100%, however, remains a challenge. Here, we employ a multilevel peel-off patterning method that can achieve micron-scale resolution without exposing chemically sensitive organic materials to solvents. Eight, 4 cm × 0.4 cm cells are connected in series to realize a prototype ST-OPV module with GFF = 95.8%, with PCE = 7.3 ± 0.2% under simulated AM 1.5G illumination at 1 sun intensity, APT = 41.8 ± 1.4%, and a light utilization efficiency of LUE = 3.1 ± 0.1%. A neutral color STOPV module is also demonstrated with 1.7 ± 0.1% and International Commission on Illumination (CIE) LAB coordinates of (L*, a*, b*) = (53.7, -1.9, -3.9).

14 SOLAR ENERGY↗
DOE OSTI2022

GaAs Thermophotovoltaic Patterned Dielectric Back Contact Devices with Improved Sub-Bandgap Reflectance

We demonstrate GaAs thermophotovoltaic (TPV) devices with a patterned dielectric back contact (PDBC) architecture, featuring a dielectric spacer between the semiconductor and back metal contact over most of the back surface for high reflectance, and metal point contacts over a smaller area for electrical conduction. In the TPV application, high sub-bandgap reflectance is needed to reflect unused sub-bandgap photons to the thermal emitter to minimize energy losses in this portion of the thermal spectrum. We explore different PDBC fabrication processes with SU-8 and SiO2 dielectric spacer layers to maximize sub-bandgap reflectance while minimizing series resistance to increase TPV conversion efficiency. We successfully demonstrate GaAs SU-8 PDBC TPV devices with 2200 degrees C blackbody-weighted sub-bandgap reflectance of 94.9% and 96.5% with and without a front metal grid, respectively. This is 0.7% and 2.3% (absolute) higher than the mean sub-bandgap reflectance of 94.2% for GaAs baseline TPV devices with 100% Au back contact with front metal grid. Lower sub-bandgap reflectance in TPV devices with front grids indicates the front grid induces light scattering leading to additional parasitic absorption in the TPV device. We also show that for higher contact coverage fractions, the PDBC reflectance cannot in general be treated by a linear interpolation using simple 1D transfer matrix method modeling and should be treated instead as a diffraction grating by solving Maxwell's equations in 3D.

energy storage↗
DOE OSTI2024

Reversible Electron-Beam Patterning of Colloidal Nanoparticles at Fluid Interfaces

The directed self-assembly of colloidal nanoparticles (NPs) using external fields guides the formation of sophisticated hierarchical materials but becomes less effective with decreasing particle size. As an alternative, electron-beam-driven assembly offers a potential avenue for targeted nanoscale manipulation, yet remains poorly controlled due to the variety and complexity of beam interaction mechanisms. Here, we investigate the beam–particle interaction of silica NPs pinned to the fluid–vacuum interface of ionic liquid droplets. In these experiments, scanning electron microscopy of the droplet surface resolves NP trajectories over space and time while simultaneously driving their reorganization. With this platform, we demonstrate the ability to direct particle transport and create transient, reversible colloidal patterns on the droplet surface. By tuning the beam voltage, we achieve precise control over both the strength and sign of the beam–particle interaction, with low voltages repelling particles and high voltages attracting them. This response stems from the formation of well-defined solvent flow fields generated from trace radiolysis of the ionic liquid, as determined through statistical analysis of single-particle trajectories under varying solvent composition. Altogether, electron-beam-guided assembly introduces a versatile strategy for nanoscale colloidal manipulation, offering new possibilities for the design of dynamic, reconfigurable systems with applications in adaptive photonics and catalysis.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Liquid–Solid Mixtures of Ga Metal Infused with Cu Microparticles and Nanoparticles for Microscale and Nanoscale Patterning of Solid Metals at Room Temperature

This paper demonstrates and characterizes a simple ink for nanopatterning of solid metallic structures under ambient conditions by taking advantage of the low melting point of gallium and its affinity to form intermetallics with other metals. Bare copper micro- and nanoparticles readily mix with liquid gallium near room temperature to form a paste that ultimately amalgamates into a dense solid when mixed at the appropriate concentration ratios. The paste has sufficient shelf life that can be extruded from a nozzle at modest temperatures to form solid three-dimensional (3D) shapes. Additionally, the paste can be molded at room temperature to replicate feature sizes ranging from a few millimeters down to hundreds of nanometers. In situ X-ray diffraction (XRD) and thermo-mechanical analysis (TMA) data show gallium and copper readily interdiffuse to form the thermodynamically expected intermetallic phase. We describe the capabilities and limitations of a simple way to pattern solid metals in an additive fashion (syringe-based extrusion) and with high resolution (molding) at or near room temperature. Here, the use of a paste that solidifies provides a novel route for 3D printing of solid metals at ambient temperatures as well as the creation of micro- and nanostructured metallic surfaces that may be useful for optics, non-wetting surfaces, or electronic microcomponents.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Strain-Induced Lateral Heterostructures in Patterned Semiconductor Nanomembranes for Micro- and Optoelectronics

The ability to tailor the energy band lineup of semiconductor materials plays a key role in the development of many electronic and optoelectronic devices and normally relies on heteroepitaxy. In this work, we report a different method, based on strain engineering, for the controlled introduction of variations in bandgap energy with lateral position in thin films. External stress is applied on Ge nanomembranes stacked with an array of amorphous-Si pillars in order to create a non-uniform strain (and therefore bandgap energy) distribution commensurate with the sample thickness variations. The resulting strain profiles are mapped using Bragg diffraction with a hard X-ray probe featuring nanoscale spatial resolution. Compared with traditional heterostructures grown by epitaxial techniques, these strain-engineered samples involve a single chemical composition and are not limited in the choice of compatible materials by any restriction imposed by lattice-matching requirements. Furthermore, their energy band lineups can be patterned in nearly arbitrary shapes using nanolithography to control the thickness profile and can be tuned actively by varying the applied stress. As a result, these structures are attractive for a wide range of device applications (including lasers, LEDs, solar cells, and thermoelectrics) that require complex heterostructure lineups with multiple bandgap energies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Pattern formation and flocking for particles near the jamming transition on resource gradient substrates

Here, we numerically examine a bidisperse system of active and passive particles coupled to a resource substrate. The active particles deplete the resource at a fixed rate and move toward regions with higher resources, while all of the particles interact sterically with each other. We show that at high densities, this system exhibits a rich variety of pattern-forming phases along with directed motion or flocking as a function of the relative rates of resource absorption and consumption as well as the active to passive particle ratio. These include partial phase separation into rivers of active particles flowing through passive clusters, strongly phase separated states where the active particles induce crystallization of the passive particles, mixed jammed states, and fluctuating mixed fluid phases. For higher resource recovery rates, we demonstrate that the active particles can undergo motility-induced phase separation, while at high densities, there can be a coherent flock containing only active particles or a solid mixture of active and passive particles. The directed flocking motion typically shows a transient in which the flow switches among different directions before settling into one direction, and there is a critical density below which flocking does not occur. We map out the different phases as function of system density, resource absorption and recovery rates, and the ratio of active to passive particles.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Peak effect and dynamics of stripe- and pattern-forming systems on a periodic one-dimensional substrate

Here we examine the ordering, pinning, and dynamics of two-dimensional pattern-forming systems interacting with a periodic one-dimensional substrate. In the absence of the substrate, particles with competing long-range repulsion and short-range attraction form anisotropic crystal, stripe, and bubble states. When the system is tuned across the stripe transition in the presence of a substrate, we find that there is a peak effect in the critical depinning force when the stripes align and become commensurate with the substrate. Under an applied drive, the anisotropic crystal and stripe states can exhibit soliton depinning and plastic flow. When the stripes depin plastically, they dynamically reorder into a moving stripe state that is perpendicular to the substrate trough direction. We also find that when the substrate spacing is smaller than the widths of the bubbles or stripes, the system forms pinned stripe states that are perpendicular to the substrate trough direction. The system exhibits multiple reentrant pinning effects as a function of increasing attraction, with the anisotropic crystal and large bubble states experiencing weak pinning but the stripe and smaller bubble states showing stronger pinning. We map out the different dynamic phases as a function of filling, the strength of the attractive interaction term, the substrate strength, and the drive, and demonstrate that the different phases produce identifiable features in the transport curves and particle orderings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Robust Avalanche (1.5 kV, 2 kA/cm²) in Vertical GaN Diodes on Patterned Sapphire Substrate

The lack of avalanche capability is a key limitation of current lateral GaN devices. Despite the report of avalanche in vertical GaN-on-GaN devices, the high wafer cost hinders device commercialization. Here, in this work, we demonstrate a circuit-level avalanche in vertical GaN diodes on low-cost patterned sapphire substrate (PSS), with the avalanche voltage (1.57 kV) and avalanche current density (>2 kA/cm 2 ) both being the highest reported in GaN devices on foreign substrates. The PSS enables a lower dislocation density than conventional sapphire substrate and is employed in high-voltage GaN devices for the first time. The avalanche voltage in the circuit test reaches 98% of the parallel-plane limit, further affirming that near-ideal avalanche breakdown can be realized on GaN devices on foreign substrates. These results show the promise of the GaN-on-PSS platform for low-cost, robust power devices.

42 ENGINEERING↗
DOE OSTI2022

Segmenting water and shadow regions within WorldView imagery using local binary patterns

Many shadow detection algorithms pertaining to remotely sensed imagery exist. Several of these algorithms exploit the spectral characteristics of shadows within imagery to identify shaded regions. However, these algorithms can have problems when water is also present within the imagery because water shares similar spectral characteristics with shadows. Many of these algorithms are applied to small image subsets instead of the image as a whole and frequently are applied to urban environments that require additional use of the normalized difference water index or other features to affect the removal of water from the shadow mask. This diversity of the image scene content coupled with the complexity and wide variety of environmental conditions that satellite imagery can acquire makes reliably separating shadow and water within larger images a complex problem. Thresholding various spectral indices to produce segmentation maps can be challenging when large, complex, and often imbalanced scenes are captured, which may require manual adjustment of algorithmic parameters for different image areas. Here, we present a methodology that makes use of the near-infrared channel using a watershed segmentation algorithm, local binary pattern measurements, and a support vector machine to classify shadow and water within a full WorldView scene. Results are promising with initial accuracies above 97% for both shadow and water.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Response patterns of simulated corn yield and soil nitrous oxide emission to precipitation change

Abstract Background Precipitation plays an important role in crop production and soil greenhouse gas emissions. However, how crop yield and soil nitrous oxide (N 2 O) emission respond to precipitation change, particularly with different background precipitations (dry, normal, and wet years), has not been well investigated. In this study, we examined the impacts of precipitation changes on corn yield and soil N 2 O emission using a long-term (1981–2020, 40 years) climate dataset as well as seven manipulated precipitation treatments with different background precipitations using the DeNitrification-DeComposition (DNDC) model. Results Results showed large variations of corn yield and precipitation but small variation of soil N 2 O emission among 40 years. Both corn yield and soil N 2 O emission showed near linear relationships with precipitation based on the long-term precipitation data, but with different response patters of corn yield and soil N 2 O emission to precipitation manipulations. Corn yield showed a positive linear response to precipitation manipulations in the dry year, but no response to increases in precipitation in the normal year, and a trend of decrease in the wet year. The extreme drought treatments reduced corn yield sharply in both normal and wet years. In contrast, soil N 2 O emission mostly responded linearly to precipitation manipulations. Decreases in precipitation in the dry year reduced more soil N 2 O emission than those in the normal and wet years, while increases in precipitation increased more soil N 2 O emission in the normal and wet years than in the dry year. Conclusions This study revealed different response patterns of corn yield and soil N 2 O emission to precipitation and highlights that mitigation strategy for soil N 2 O emission reduction should consider different background climate conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Hypothesis Tests on Rayleigh Wave Radiation Pattern Shapes: A Theoretical Assessment for Source Screening (Independent Review: LANL Source Physics LCP) [Slides]

Background for TRL 0-1 Research: we require a simple regional source discriminant that has a predictive capability and a quantifiable screening performance (probability of correct attribution); Challenge: many local and near-regional source discriminants do not test source mechanism; rather, they test depth. Such empirically validated discriminants are not all theoretically justified; and, Proposal: we test Rayleigh wave radiation patterns for any significant deviation from circular shape as a discriminant.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Enabling New Approaches to Low-Cost Dopant Patterning for Interdigitated Back Contact Crystalline Silicon Solar Cells: Cooperative Research and Development, CRADA Number CRD-17-00665 (Final Report)

NREL is sub to the Department of Energy (DOE) Photovoltaic Research & Development (PVRD) project, titled "New Approaches to Low-Cost Scalable Doping for Interdigitated Back Contact Crystalline Silicon Solar Cells", awarded to Colorado School of Mines. The goal of this project was to develop an industrially relevant dopant patterning technique that enable high performing, cost efficient Interdigitated Back Contact (IBC) solar cells based on n-Cz silicon wafer. Several possibilities were explored at the beginning of the project and the masked plasma deposition was deselected as the most promising and industrially relevant. This method was thoroughly explored ion the course of the project, its limitations revealed and mitigated. NREL successfully the masked deposition integrated into the cell's process flow and produced the cells, alongside with numerous process development steps and application of in-house advanced characterization techniques. The report describes these developments by the task and in detail.

14 SOLAR ENERGY↗
DOE OSTI2022

An “Eddy β-Spiral” mechanism for vertical velocity dipole patterns of isolated oceanic mesoscale eddies

Oceanic eddies accompanied by a significant vertical velocity ( w ) are known to be of great importance for the vertical transport of various climatically, biologically or biogeochemically relevant properties. Using quasi-geostrophic w -thinking to extend the classic “ β -spiral” w -theory for gyre circulations to isolated and nearly symmetric oceanic mesoscale eddies, we propose that their w motion will be dominated by a strong east-west dipole pattern with deep ocean penetrations. Contrasting numerical simulations of idealized isolated eddies together with w -equation diagnostics confirm that the w -dipole is indeed dominated by the “eddy β -spiral” mechanism in the β -plane simulation, whereas this w -dipole expectedly disappears in the f -plane simulation. Analyses of relatively isolated warm and cold eddy examples show good agreement with the proposed mechanism. Our studies further clarify eddy vertical motions, have implications for ocean mixing and vertical transport, and inspire further studies.

58 GEOSCIENCES↗
DOE OSTI2020

A Pattern-Recognition-Based Ensemble Data Imputation Framework for Sensors from Building Energy Systems

Building operation data are important for monitoring, analysis, modeling, and control of building energy systems. However, missing data is one of the major data quality issues, making data imputation techniques become increasingly important. There are two key research gaps for missing sensor data imputation in buildings: the lack of customized and automated imputation methodology, and the difficulty of the validation of data imputation methods. In this paper, a framework is developed to address these two gaps. First, a validation data generation module is developed based on pattern recognition to create a validation dataset to quantify the performance of data imputation methods. Second, a pool of data imputation methods is tested under the validation dataset to find an optimal single imputation method for each sensor, which is termed as an ensemble method. The method can reflect the specific mechanism and randomness of missing data from each sensor. The effectiveness of the framework is demonstrated by 18 sensors from a real campus building. The overall accuracy of data imputation for those sensors improves by 18.2% on average compared with the best single data imputation method.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Long Short-Term Memory Networks for Pattern Recognition of Synthetical Complete Earthquake Catalog

Exploring the spatiotemporal distribution of earthquake activity, especially earthquake migration of fault systems, can greatly to understand the basic mechanics of earthquakes and the assessment of earthquake risk. By establishing a three-dimensional strike-slip fault model, to derive the stress response and fault slip along the fault under regional stress conditions. Our study helps to create a long-term, complete earthquake catalog. We modelled Long-Short Term Memory (LSTM) networks for pattern recognition of the synthetical earthquake catalog. The performance of the models was compared using the mean-square error (MSE). Our results showed clearly the application of LSTM showed a meaningful result of 0.08% in the MSE values. Our best model can predict the time and magnitude of the earthquakes with a magnitude greater than Mw = 6.5 with a similar clustering period. These results showed conclusively that applying LSTM in a spatiotemporal series prediction provides a potential application in the study of earthquake mechanics and forecasting of major earthquake events.

58 GEOSCIENCES↗
DOE OSTI2022

Spatial patterns of snow distribution in the sub-Arctic

Abstract. The spatial distribution of snow plays a vital role in sub-Arctic and Arctic climate, hydrology, and ecology due to its fundamental influence on the water balance, thermal regimes, vegetation, and carbon flux. However, the spatial distribution of snow is not well understood, and therefore, it is not well modeled, which can lead to substantial uncertainties in snow cover representations. To capture key hydro-ecological controls on snow spatial distribution, we carried out intensive field studies over multiple years for two small (2017–2019; ∼ 2.5 km2) sub-Arctic study sites located on the Seward Peninsula of Alaska. Using an intensive suite of field observations (> 22 000 data points), we developed simple models of the spatial distribution of snow water equivalent (SWE) using factors such as topographic characteristics, vegetation characteristics based on greenness (normalized different vegetation index, NDVI), and a simple metric for approximating winds. The most successful model was random forest, using both study sites and all years, which was able to accurately capture the complexity and variability of snow characteristics across the sites. Approximately 86 % of the SWE distribution could be accounted for, on average, by the random forest model at the study sites. Factors that impacted year-to-year snow distribution included NDVI, elevation, and a metric to represent coarse microtopography (topographic position index, TPI), while slope, wind, and fine microtopography factors were less important. The characterization of the SWE spatial distribution patterns will be used to validate and improve snow distribution modeling in the Department of Energy's Earth system model and for improved understanding of hydrology, topography, and vegetation dynamics in the sub-Arctic and Arctic regions of the globe.

54 ENVIRONMENTAL SCIENCES↗