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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Note: Experimental observation of nano-channel pattern in light sheet laser interference nanolithography system

We experimentally observed nano-channel-like pattern in a light-sheet based interference nanolithography system. The optical system created nano-channel-like patterned illumination. Coherent counter-propagating light sheets are made to interfere at and near geometrical focus along the propagation z-axis. This results in the formation of nano-channel-like pattern (of size ≈ 300 nm and inter-channel periodicity of ≈337.5 nm) inside the sample due to constructive and destructive interference. In addition, the technique has the ability to generate large area patterning using larger light-sheets. Exciting applications are in the broad field of nanotechnology (nano-electronics and nano-fluidics).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Fabrication and independent control of patterned polymer gate for a few-layer WSe{sub 2} field-effect transistor

We report the fabrication of a patterned polymer electrolyte for a two-dimensional (2D) semiconductor, few-layer tungsten diselenide (WSe{sub 2}) field-effect transistor (FET). We expose an electron-beam in a desirable region to form the patterned structure. The WSe{sub 2} FET acts as a p-type semiconductor in both bare and polymer-covered devices. We observe a highly efficient gating effect in the polymer-patterned device with independent gate control. The patterned polymer gate operates successfully in a molybdenum disulfide (MoS{sub 2}) FET, indicating the potential for general applications to 2D semiconductors. The results of this study can contribute to large-scale integration and better flexibility in transition metal dichalcogenide (TMD)-based electronics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Rosette-scan video-rate atomic force microscopy: Trajectory patterning and control design

We introduce an analysis and a systematic design methodology for a novel nonraster scan method based on a rosette pattern and demonstrate its application in video-rate atomic force microscopy. This pattern is traced when the lateral axes of a parallel kinematic scanner are commanded to follow a combination of two sinusoids with identical amplitudes and different frequencies. We create an internal-model-based controller to enhance the tracking performance of this pattern and implement the scheme on a microelectromechanical system scanner. The conclusions reveal high-precision tracking of the rosette pattern in order to acquire time-lapsed atomic force microscope images at the rate of 10 frames/s.

42 ENGINEERING↗
DOE OSTI2023

Enumeration of Moiré patterns of a hexagonal twisted bilayer: Applications to intercalated transition metals

A real-space method using generating integers is used to determine possible commensurate lattice Moiré patterns for a bilayer of two equal hexagonal lattices, which can in principle be extended to lattice mismatched bilayers. These Moiré patterns can be classified by a pair of relatively prime integers (n,m), wherein a rotation θ(n,m) of the top hexagonal lattice maps its lattice vector (n,m) to (m,n) of the bottom lattice. Within this formulation, the area of the commensurate supercell is proportional to (n2+m2+nm) and the number of coincident lattice sites per supercell is given by (n−m)2. Taking bilayer boron nitride (BN) as an example, we present how to systematically generate Moiré patterns and explore the differences in local chemistry in the interstitial region by impurity intercalation. Systematic calculations of the properties of intercalated 3d transition metals were performed in an h-BN (4,3) bilayer, corresponding to a rotation of 9.43 degrees. These calculations reveal that local symmetry in the intercalated region significantly affect the energetics and magnetization of the intercalated species. These results highlight that Moiré pattern physics is not limited to optoelectronic/electronic phenomena, such as interfacial exciton formation or magic angle superconductivity, but it also produces chemical and magnetic atomic site selectivity, which may play important roles in adsorption, catalysis, or quantum information.

Physics↗
DOE OSTI2019

Electricity consumption patterns within cities: application of a data-driven settlement characterization method

Urban areas presently consume around 75% of global primary energy supply, which is expected to significantly increase in the future due to urban growth. Having sustainable, universal energy access is a pressing challenge for most parts of the globe. Understanding urban energy consumption patterns may help to address the challenges to urban sustainability and energy security. However, urban energy analyses are severely limited by the lack of urban energy data. Such datasets are virtually non-existent for the developing countries. As per current projections, most of the new urban growth is bound to occur in these data-starved regions. Hence, there is an urgent need of research methods for monitoring and quantifying urban energy utilization patterns. Here, we apply a data-driven approach to characterize urban settlements based on their formality, which is then used to assess intra-urban urban energy consumption in Johannesburg, South Africa; Sana’a, Yemen; and Ndola, Zambia. Electricity is the fastest growing energy fuel. By analyzing the relationship between the settlement types and the corresponding nighttime light emission, a proxy of electricity consumption, we assess the differential electricity consumption patterns. Our study presents a simple and scalable solution to fill the present data void to understand intra-city electricity consumption patterns.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

The stability of Cl-, Br-, and I-passivated Si(100)-(2 × 1) in ambient environments for atomically-precise pattern preservation

Abstract Atomic precision advanced manufacturing (APAM) leverages the highly reactive nature of Si dangling bonds relative to H- or Cl-passivated Si to selectively adsorb precursor molecules into lithographically defined areas with sub-nanometer resolution. Due to the high reactivity of dangling bonds, this process is confined to ultra-high vacuum (UHV) environments, which currently limits its commercialization and broad-based appeal. In this work, we explore the use of halogen adatoms to preserve APAM-derived lithographic patterns outside of UHV to enable facile transfer into real-world commercial processes. Specifically, we examine the stability of H-, Cl-, Br-, and I-passivated Si(100) in inert N 2 and ambient environments. Characterization with scanning tunneling microscopy and x-ray photoelectron spectroscopy (XPS) confirmed that each of the fully passivated surfaces were resistant to oxidation in 1 atm of N 2 for up to 44 h. Varying levels of surface degradation and contamination were observed upon exposure to the laboratory ambient environment. Characterization by ex situ XPS after ambient exposures ranging from 15 min to 8 h indicated the Br– and I–passivated Si surfaces were highly resistant to degradation, while Cl–passivated Si showed signs of oxidation within minutes of ambient exposure. As a proof-of-principle demonstration of pattern preservation, a H–passivated Si sample patterned and passivated with independent Cl, Br, I, and bare Si regions was shown to maintain its integrity in all but the bare Si region post-exposure to an N 2 environment. The successful demonstration of the preservation of APAM patterns outside of UHV environments opens new possibilities for transporting atomically-precise devices outside of UHV for integrating with non-UHV processes, such as other chemistries and commercial semiconductor device processes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Deforestation impacts network co-occurrence patterns of microbial communities in Amazon soils

Co-occurrence networks allow for the identification of potential associations among species, which may be important for understanding community assembly and ecosystem functions. We employed this strategy to examine prokaryotic co-occurrence patterns in the Amazon soils and the response of these patterns to land use change to pasture, with the hypothesis that altered microbial composition due to deforestation will mirror the co-occurrence patterns across prokaryotic taxa. In this study, we calculated Spearman correlations between operational taxonomic units (OTUs) as determined by 16S rRNA gene sequencing, and only robust correlations were considered for network construction (-0.80 ≥ ρ ≥ 0.80, adjusted P <0.01). The constructed network represents distinct forest and pasture components, with altered compositional and topological features. A comparative analysis between two representative modules of these contrasting ecosystems revealed novel information regarding changes to metabolic pathways related to nitrogen cycling. Our results showed that soil physicochemical properties such as temperature, C/N and H + +Al 3+ had a significant impact on prokaryotic communities, with alterations to network topologies. Taken together, changes in co-occurrence patterns and physicochemical properties may contribute to ecosystem processes including nitrification and denitrification, two important biogeochemical processes occurring in tropical forest systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

The pattern speed of the Milky Way bar from transverse velocities

ABSTRACT We use the continuity equation to derive a method for measuring the pattern speed of the Milky Way’s bar/bulge from proper motion data. The method has minimal assumptions but requires complete coverage of the non-axisymmetric component in two of the three Galactic coordinates. We apply our method to the proper motion data from a combination of Gaia DR2 and VISTA Variables in the Via Lactea (VVV) to measure the pattern speed of the bar as $\Omega _\mathrm{p}=(41\pm 3)\, \mathrm{km\, s^{-1}\, kpc^{-1}}$ (where the error is statistical). This puts the corotation radius at $(5.7\pm 0.4)\, \mathrm{kpc}$, under the assumptions of the standard peculiar motion of the Sun and the absence of non-axisymmetric streaming in the Solar neighbourhood. The obtained result uses only data on the near side of the bar which produces consistent measurements of the distance and velocity of the centre of the Galaxy. Addition of the data on the far side of the bar pulls the pattern speed down to $\Omega _\mathrm{p}=(31\pm 1)\, \mathrm{km\, s^{-1}\, kpc^{-1}}$ but requires a lower transverse velocity for the Galactic centre than observed. This suggests systematics of $5-10\, \mathrm{km\, s^{-1}kpc^{-1}}$ dominate the uncertainty. We demonstrate using a dynamically formed bar/bulge simulation that even with the limited field of view of the VVV survey our method robustly recovers the pattern speed.

Sanders, Jason L.↗
DOE OSTI2020

Measurement of Ehrlich-Schwoebel barrier contribution to the self-organized formation of ordered surface patterns on Ge(001)

Normal-incidence 1-keV Ar + ion bombardment leads to amorphization and ultrasmoothing of Ge at room temperature, but at elevated temperatures the Ge surface remains crystalline and is unstable to the formation of self-organized nanoscale patterns of ordered pyramid-shaped pits. The physical phenomenon distinguishing the high-temperature patterning from room-temperature ultrasmoothing is believed to be a surface instability due to the Ehrlich-Schwoebel barrier for diffusing vacancies and adatoms, which is not present on the amorphous material. This real-time grazing-incidence small-angle x-ray scattering study compares smoothing of a prepatterned Ge sample at room temperature with patterning of an initially flat Ge sample at an elevated temperature. In both experiments, when the nanoscale structures are relatively small in height, the average kinetics can be explained by a linear theory. Furthermore, the linear theory coefficients, indicating surface stability or instability, were extracted for both experiments. A comparison between the two measurements allows estimation of the contribution of the Ehrlich-Schwoebel barrier to the self-organized formation of ordered nanoscale patterns on crystalline Ge surfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Stable and unstable tiling patterns formed by ABC miktoarm star triblock terpolymers of symmetric interactions

Several discrepancies exist among previous self-consistent field calculations of symmetrically interacting ABC miktoarm star triblock terpolymer melts. Here we address this issue by including all known tiling patterns, as well as several lamellar-type phases known to bound the regions in the parameter space occupied by these patterns. After carefully studying the effect of numerical parameters on the free-energy accuracy, the central region of the phase diagram is constructed in detail; both the (3.4.6.4) pattern and the three-dimensional phase of hierarchical-hexagonal lamellae are found to be stable for the first time. The energetic and entropic contributions to the free-energy density of several phases are analyzed and compared in detail to reveal their stability mechanisms, including the important ( 3 2 .4.3.4) pattern. Comparisons to previous studies of the same model system are present throughout, with our results resolving the aforementioned discrepancies and providing a sound basis for future work to build upon. Published by the American Physical Society 2024

Materials Science↗
DOE OSTI2024

Random forest prediction of crystal structure from electron diffraction patterns incorporating multiple scattering

Diffraction is the most common method to solve for unknown or partially known crystal structures. However, it remains a challenge to determine the crystal structure of a new material that may have nanoscale size or heterogeneities. Here, in this study, we train an architecture of hierarchical random forest models capable of predicting the crystal system, space group, and lattice parameters from one or more unknown two-dimensional electron diffraction patterns. Our initial model correctly identifies the crystal system of a simulated electron diffraction pattern from a 20-nm-thick specimen of arbitrary orientation 67% of the time. We achieve a topline accuracy of 79% when aggregating predictions from ten patterns of the same material but different zone axes. The space group and lattice predictions range from 70% to 90% accuracy and median errors of 0.01-0.5Å, respectively, for cubic, hexagonal, trigonal, and tetragonal crystal systems while being less reliable on orthorhombic and monoclinic systems. We apply this architecture to a four-dimensional scanning transmission electron microscopy scan of gold nanoparticles, where it accurately predicts the crystal structure and lattice constants. These random forest models can be used to significantly accelerate the analysis of electron diffraction patterns, particularly in the case of unknown crystal structures. Additionally, due to the speed of inference, these models could be integrated into live transmission electron microscopy experiments, allowing real-Time labeling of a specimen.

36 MATERIALS SCIENCE↗
DOE OSTI2026

High-speed quantitative X-ray multi-contrast imaging with deep learning based modulated pattern analysis

The advent of X-ray multi-contrast imaging methods, providing absorption, phase, and dark-field images, holds tremendous promise for complementary and non-destructive visualization of inner structures within materials and bio-samples. However, the low efficiency in measuring and analyzing X-ray modulated patterns has hindered their application in high-resolution in situ imaging. In this work, the Enhanced Scanning Pattern-based Imaging Neural Network (ESPINNet) is introduced as a powerful tool for achieving high-speed, high-resolution quantitative imaging. ESPINNet is faster than correlation-based speckle tracking methods such as XSVT and UMPA, and provides a balanced performance in terms of resolution and speed for data collection by using fewer scanning images. In comparison with our previously developed neural network, ESPINNet introduces the capability to generate dark-field images, further enhancing its versatility. By leveraging scanning patterns, ESPINNet significantly improves resolution and measurement precision. Furthermore, its adaptability to various modulation patterns, including those produced by sandpaper, coded masks, or gratings, ensures broad applicability. These features enable real-time 2D and 3D multi-contrast imaging, positioning ESPINNet as a transformative solution for applications in materials science and biomedical research, particularly for high-speed and in situ measurements.

X-ray at-wavelength metrology↗
DOE OSTI2024

A Suppression-based STDP Rule Resilient to Jitter Noise in Spike Patterns for Neuromorphic Computing

Multi-spike models of synaptic plasticity, such as the triplet and suppression spike-timing-dependent plasticity (STDP) rules, exhibit better alignment with neurophysiological data in the brain compared to the pair-based STDP rule. Previous studies have empirically shown that the pair-based STDP rule can detect spatiotemporal spike patterns hidden in equally dense distractor spike trains in an unsupervised manner. However, it fails to detect spike patterns influenced by jitter noise. Given that spiking neural networks (SNNs) exhibit variability in generated spike trains in response to the same inputs, it becomes imperative to have learning rules capable of detecting spike patterns even in the presence of jitter noise. In this study, we introduce a simplified suppression-based STDP rule that demonstrates significantly enhanced tolerance to jitter in spike patterns compared to the pair-based STDP rule. Unlike the ideal suppression STDP rule, characterized by an exponential learning window and requiring high-resolution synapses, the simplified rule limits the synaptic efficacy update to a single bit at any given instant. Moreover, it employs 4-bit fixed-point synapses, facilitating straightforward implementation in neuromorphic hardware.

Gautam, Ashish [ORNL]↗
DOE OSTI2025

RE-INTEGRATE EMT Simulation Software: Graph Convolutional Network for Sparse Matrix Pattern Detection

The increasing complexity of power networks, driven by proliferation of inverters, presents analytical challenges that simplified models often fail to capture, necessitating Electromagnetic Transient (EMT) simulations. EMT models are represented as discretized differential-algebraic equations (DAEs), forming a linear system Ax = b that is computationally intensive to solve. Due to inherent sparsity of adjacency matrix A, distinct patterns emerge that, when accurately identified, enable efficient solver selection to minimize computation time. However, identifying ideal pattern is complicated by numerous reordering algorithms and limited structural insights. To address this, we introduce a Graph Convolutional Network (GCN) model for classifying sparse matrix patterns common in power system analysis. The model, achieving 96% test accuracy, is validated using PV plant models of 125 MW capacities connected to New England 39-bus transmission system (TS), and further scaled to a 4,992-bus network with 384 PV plants, yielding 191, 616 × 191, 616 sized A matrix. For all cases, the GCN model accurately identifies the matrix’s intrinsic sparse pattern, demonstrating its potential to enhance solver performance in EMT analysis.

Hossain, Md Rifat [Florida International Universit↗
DOE OSTI2024

Temporal mismatches in flight activity patterns between Pipistrellus kuhlii and Prays oleae in olive farms: Implications for biocontrol services potential

Abstract Biocontrol services are widely recognized to provide key incentives for bat conservation. However, we have virtually no information on whether and how disruptions in bat‐mediated biocontrol services are driven by mismatches between the temporal activity patterns of insectivorous bats and insect pests. We investigated the temporal relationship between the nightly activity patterns of the common pipistrelle bat ( Pipistrellus kuhlii ) and the olive fruit moth ( Prays oleae ). Temporal mismatches between species pairs were estimated as the time difference (expressed as a percentage of the night) at which P. kuhlii and P. oleae reached 50% of their abundance. The study was carried out during spring, summer, and fall between 2017 and 2019 in 60 olive farms representing increasing levels of structural simplification (as a surrogate of agricultural intensification). Olive farms were classified as exhibiting high (i.e. HIGH olive farms; n = 27), intermediate (MID; n = 18), and low (LOW; n = 15) structural complexity. Temporal mismatches between the activity levels of P. kuhlii and P. oleae varied between seasons and types of olive farms, being comparatively lower in summer than in spring and fall. Furthermore, summer was the only season in which temporal mismatches between species pairs differed between types of olive farms, with higher temporal mismatches found in LOW than in HIGH and MID olive farms. Overall, our work demonstrates the existence of temporal mismatches between the nightly activity patterns of P. kuhlii and P. oleae . Furthermore, it demonstrates that the structural simplification of olive farms increases temporal mismatches between species pairs, particularly in summer when bat‐mediated biocontrol services are most needed. Synthesis and applications . Future research should consider mismatches between the temporal activity patterns of insectivorous bats and insect pests. Otherwise, the actual impact of agricultural intensification on bat‐mediated biocontrol services as well as the economic impact of their loss on the agriculture industry might be underestimated. To enhance biocontrol services, we propose increasing the availability of suitable roosting and foraging sites as well as conserving areas of remnant native woodland and scattered hollow‐bearing trees.

Herrera, José M.↗
DOE OSTI2019

Regional patterns of genetic diversity in swine influenza A viruses in the United States from 2010 to 2016

Background Regular spatial and temporal analyses of the genetic diversity and evolutionary patterns of influenza A virus (IAV) in swine inform control efforts and improve animal health. Initiated in 2009, the USDA passively surveils IAV in U.S. swine, with a focus on subtyping clinical respiratory submissions, sequencing the hemagglutinin (HA) and neuraminidase (NA) genes at a minimum, and sharing these data publicly. Objectives In this study, our goal was to quantify and describe regional and national patterns in the genetic diversity and evolution of IAV in U.S. swine from 2010 to 2016. Methods A comprehensive phylogenetic and epidemiological analysis of publicly available HA and NA genes generated by the USDA surveillance system collected from January 2010 to December 2016 was conducted. Results The dominant subtypes and genetic clades detected during the study period were H1N1 (H1-γ/1A.3.3.3, N1-classical, 29%), H1N2 (H1-δ1/1B.2.2, N2-2002, 27%), and H3N2 (H3-IV-A, N2-2002, 15%), but many other minor clades were also maintained. Year-round circulation was observed, with a primary epidemic peak in October-November and a secondary epidemic peak in March-April. Partitioning these data into 5 spatial zones revealed that genetic diversity varied regionally and was not correlated with aggregated national patterns of HA/NA diversity. Conclusions These data suggest that vaccine composition and control efforts should consider IAV diversity within swine production regions in addition to aggregated national patterns.

Infectious Diseases↗
DOE OSTI2024

Effects of human presence on African mammal waterhole attendance and temporal activity patterns

Abstract Human impacts on the environment and wildlife populations are increasing globally, threatening thousands of species with extinction. While wildlife‐based tourism is beneficial for educating tourists, generating income for conservation efforts, and providing local employment, more information is needed to understand how this industry may impact wildlife. In this study, we used motion‐activated cameras at 12 waterholes on a private game reserve in northern Namibia to determine if the presence of humans and permanent infrastructure affected mammal visits by examining their (1) number of visits, (2) time spent, and (3) diel activity patterns. Our results revealed no differences in the number of visits based on human presence for any of the 17 mammal species studied. However, giraffes ( Giraffe camelopardalis ) spent more time at waterholes before observer presence compared to during. Additionally, several species changed diel activity patterns when human observers were present. Notably, several carnivore and ungulate species increased overlap in their activity patterns during periods while humans were present relative to when humans were absent. These modifications of mammal temporal activity patterns due to human presence could eventually lead to changes in community structure and trophic dynamics because of altered predator–prey interactions. As humans continue to expand into wildlife habitats, and wildlife‐based tourism increases globally, it is imperative that we fully understand the effects of anthropogenic pressures on mammal behavior. Monitoring of wildlife behavioral changes in response to human activity is crucial to further develop wildlife tourism opportunities in a way that optimizes the impact of conservation goals.

Patterson, J. R. [Savannah River Ecology Lab, Warn↗
DOE OSTI2022

Genome-wide DNA methylation patterns harbour signatures of hatchling sex and past incubation temperature in a species with environmental sex determination

Conservation of thermally sensitive species depends on monitoring organismal and population-level responses to environmental change in real time. Epigenetic processes are increasingly recognized as key integrators of environmental conditions into developmentally plastic responses, and attendant epigenomic data sets hold potential for revealing cryptic phenotypes relevant to conservation efforts. Here, we demonstrate the utility of genome-wide DNA methylation (DNAm) patterns in the face of climate change for a group of especially vulnerable species, those with temperature-dependent sex determination (TSD). Due to their reliance on thermal cues during development to determine sexual fate, contemporary shifts in temperature are predicted to skew offspring sex ratios and ultimately destabilize sensitive populations. Using reduced-representation bisulphite sequencing, we profiled the DNA methylome in blood cells of hatchling American alligators (Alligator mississippiensis), a TSD species lacking reliable markers of sexual dimorphism in early life stages. We identified 120 sex-associated differentially methylated cytosines (DMCs; FDR < 0.1) in hatchlings incubated under a range of temperatures, as well as 707 unique temperature-associated DMCs. We further developed DNAm-based models capable of predicting hatchling sex with 100% accuracy (in 20 training samples and four test samples) and past incubation temperature with a mean absolute error of 1.2°C (in four test samples) based on the methylation status of 20 and 24 loci, respectively. Though largely independent of epigenomic patterning occurring in the embryonic gonad during TSD, DNAm patterns in blood cells may serve as nonlethal markers of hatchling sex and past incubation conditions in conservation applications. These findings also raise intriguing questions regarding tissue-specific epigenomic patterning in the context of developmental plasticity.

59 BASIC BIOLOGICAL SCIENCES↗