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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Binary pseudo-random patterned structures for modulation transfer function calibration and resolution characterization of a full-field transmission soft x-ray microscope

We present a modulation transfer function (MTF) calibration method based on binary pseudo-random (BPR) one-dimensional sequences and two-dimensional arrays as an effective method for spectral characterization in the spatial frequency domain of a broad variety of metrology instrumentation, including interferometric microscopes, scatterometers, phase shifting Fizeau interferometers, scanning and transmission electron microscopes, and at this time, x-ray microscopes. The inherent power spectral density of BPR gratings and arrays, which has a deterministic white-noise-like character, allows a direct determination of the MTF with a uniform sensitivity over the entire spatial frequency range and field of view of an instrument. We demonstrate the MTF calibration and resolution characterization over the full field of a transmission soft x-ray microscope using a BPR multilayer (ML) test sample with 2.8 nm fundamental layer thickness. We show that beyond providing a direct measurement of the microscope’s MTF, tests with the BPRML sample can be used to fine tune the instrument’s focal distance. Our results confirm the universality of the method that makes it applicable to a large variety of metrology instrumentation with spatial wavelength bandwidths from a few nanometers to hundreds of millimeters.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Ionic Liquids as Additives to Polystyrene- Block -Poly(Methyl Methacrylate) Enabling Directed Self-Assembly of Patterns with Sub-10 nm Features

Polystyrene- block -poly(methyl methacrylate) (PS- b -PMMA) is one of the prototypical block copolymers in directed self-assembly (DSA) research and development, with standardized protocols in place for processing on industrially relevant 300 mm wafers. Scaling of DSA patterns to pitches below 20 nm using PS- b -PMMA, however, is hindered by the relatively low Flory–Huggins interaction parameter, $χ$. In this work, we investigate the approach of adding small amounts of ionic liquids (ILs) into PS- b -PMMA, which selectively segregates into the PMMA domain and effectively increases the $χ$ parameter and thus the pattern resolution. The amount of IL additive is small enough to result in limited changes in PS- b -PMMA’s surface and interfacial properties, thus maintaining industry-friendly processing by thermal annealing with a free surface. Three different ILs are studied comparatively regarding their compositional process window, capability of increasing $χ$, and thermal stability. By adding ~3.1 vol % of the champion IL into a low-molecular-weight PS- b -PMMA ( M n = 10.3k- b -9.5k), we demonstrated DSA on chemically patterned substrates of lamellar structures with feature sizes <8.5 nm. Compatibility of the PS- b -PMMMA/IL blends with the standardized processes that have been previously developed suggests that such blend materials could provide a drop-in solution for sub-10 nm lithography with the processing advantages of PS- b -PMMA.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Investigating flow patterns and related dynamics in multi-instability turbulent plasmas using a three-point cross-phase time delay estimation velocimetry scheme

Complexities of flow patterns in the azimuthal cross-section of a cylindrical magnetized helicon plasma and the corresponding plasma dynamics are investigated by means of a novel scheme for time delay estimation velocimetry. The advantage of this introduced method is the capability of calculating the time-averaged 2D velocity fields of propagating wave-like structures and patterns in complex spatiotemporal data. It is able to distinguish and visualize the details of simultaneously present superimposed entangled dynamics and it can be applied to fluid-like systems exhibiting frequently repeating patterns (e.g., waves in plasmas, waves in fluids, dynamics in planetary atmospheres, etc.). The velocity calculations are based on time delay estimation obtained from cross-phase analysis of time series. Each velocity vector is unambiguously calculated from three time series measured at three different non-collinear spatial points. This method, when applied to fast imaging, has been crucial to understand the rich plasma dynamics in the azimuthal cross-section of a cylindrical linear magnetized helicon plasma. The capabilities and the limitations of this velocimetry method are discussed and demonstrated for two completely different plasma regimes, i.e., for quasi-coherent wave dynamics and for complex broadband wave dynamics involving simultaneously present multiple instabilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Distinct assembly mechanisms underlie similar biogeographical patterns of rare and abundant bacteria in Tibetan Plateau grassland soils

Rare biosphere represents the majority of Earth's biodiversity and performs vital ecological functions, yet little is known about its biogeographical patterns and community assembly processes in terrestrial ecosystems. Herein, we investigated the community composition and phylogeny of rare (relative abundance <0.1%) and abundant (>1%) bacteria in dryland grassland soils on the Tibetan Plateau. Results revealed similar biogeographical patterns of rare and abundant bacteria at both compositional and phylogenetic levels, but rare subcommunity was more heavily influenced by stochasticity (72%) than the abundant (57%). The compositional variation of rare bacteria was less explained by environmental factors (41%) than that of the abundant (80%), while the phylogeny of rare bacteria (36%) was more explained than that of the abundant (29%). The phylogeny of rare bacteria was equally explained by local factors (soil and vegetation) and geospatial distance (11.5% and 11.9% respectively), while that of the abundant was more explained by geospatial distance (22.1%) than local factors (11.3%). Furthermore, a substantially tighter connection between the community phylogeny and composition was observed in rare (R(2) = 0.65) than in abundant bacteria (R(2) = 0.08). Our study provides novel insights into the assembly processes and biographical patterns of rare and abundant bacteria in dryland soils.

Ji, Mukan↗
DOE OSTI2020

Analysis of Electric Vehicle Charging Behavior Patterns with Function Principal Component Analysis Approach

This manuscript focused on analyzing electric vehicles’ (EV) charging behavior patterns with a functional data analysis (FDA) approach, with the goal of providing theoretical support to the EV infrastructure planning and regulation, as well as the power grid load management. 5-year real-world charging log data from a total of 455 charging stations in Kansas City, Missouri, was used. The focuses were placed on analyzing the daily usage occupancy variability, daily energy consumption variability, and station-level usage variability. Compared with the traditional discrete-based analysis models, the proposed FDA modeling approach had unique advantages in preserving the smooth function behavior of the data, bringing more flexibility in the modeling process with little required assumptions or background knowledge on independent variables, as well as the capability of handling time series data with different lengths or sizes. In addition to the patterns revealed in the EV charging station’s occupancy and energy consumption, the differences between EV driver’s charging time and parking time were analyzed and called for the needs for parking regulation and enforcement. The different usage patterns observed at charging stations located on different land-use types were also analyzed.

Engineering↗
DOE OSTI2026

Data for Spatial Analysis of Cell Patterning to Aid Genetic and Phenotypic Understanding of Grass Stomatal Density: A Case Study in Maize

Biological processes involve complex hierarchies where composite traits result from multiple component traits. However, holistically understanding of how sets of component traits interact to underpin genotype-to-phenotype relationships is generally lacking. Stomatal density (SD) is a tractable model system for exploring how high-throughput phenotyping (HTP) data could be exploited by a new spatial analysis approach to better understand a developmentally and functionally important trait. SD is a composite trait, resulting from various components related to cell identity and size, which are themselves governed by a series of spatio-developmental processes. Data from 192 recombinant inbred lines of maize [Zea mays (L.)] were analyzed by a new stomatal patterning phenotype (SPP) to (1) describe the average spatial probability distribution of the nearest neighboring stomata; (2) derive a core set of component traits related to cell size, cell packing, and positional probabilities; (3) build a structural equation model of component traits underlying SD; and (4) identify stomatal patterning quantitative trait loci (QTL). The core set of SPP-derived traits explained 74% of the variation in SD. Analyzing SPP component traits allowed some loci previously identified as generic SD QTL to be recognized as specific to lateral versus longitudinal elements of stomatal patterning. Therefore, this study highlights how novel insights can be gained by decomposing a composite trait (e.g., SD) into a set of component traits that were present in HTP data but not previously exploited.

AI/ML↗
DOE OSTI2025

Effect of pattern transfer process on roughness of block copolymer patterns from directed self-assembly

Block copolymer-directed self-assembly (DSA) remains promising for improving pattern quality and reducing the stochastic variations that challenge high numerical aperture extreme ultraviolet lithography. Equally critical is refining pattern transfer methods for accurately transferring the rectified DSA features to the underlying substrate. We compare two atomic layer deposition (ALD)-based techniques: sequential infiltration synthesis (SIS) and dry liftoff, applied to polystyrene-block-poly(methyl methacrylate) (PS-b-PMMA) DSA patterns. Both methods utilize aluminum oxide hard masks, with one synthesized through infiltration into the PMMA domains and the other through conformal ALD coating. High-resolution scanning electron micrographs were analyzed to measure line edge, width, and placement roughness for both the line (PMMA) and space (PS) features. Although both methods yielded similar overall 3σ rms roughness, they differed significantly in the frequency-dependent power spectral density (PSD) profiles. SIS reduced line placement roughness at length scales associated with the polymer pitch, but increased space width roughness at low frequencies, whereas dry liftoff mimicked the frequency content of the original guiding pattern. This study underscores the importance of PSD evaluation in selecting optimal pattern transfer strategies for specific applications.

Block copolymers↗
DOE OSTI2018

Attribution of Anthropogenic Influence on Atmospheric Patterns Conducive to Recent Most Severe Haze Over Eastern China

Severe haze pollution in eastern China has caused substantial health impacts and economic loss. Conducive atmospheric conditions are important to affect occurrence of severe haze events, and circulation changes induced by future global climate warming are projected to increase the frequency of such events. However, a potential contribution of an anthropogenic influence to recent most severe haze (December 2015 and January 2013) over eastern China remains unclear. Here we show that the anthropogenic influence, which is estimated by using large ensemble runs with a climate model forced with and without anthropogenic forcings, has already increased the probability of the atmospheric patterns conducive to severe haze by at least 45% in January 2013 and 27% in December 2015, respectively. We further confirm that simulated atmospheric circulation pattern changes induced by anthropogenic influence are driven mainly by increased greenhouse gas emissions. Our results suggest that more strict reductions in pollutant emissions are needed under future anthropogenic warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Rapid Identification of X-ray Diffraction Patterns Based on Very Limited Data by Interpretable Convolutional Neural Networks

Large volumes of data from material characterizations call for rapid and automatic data analysis to accelerate materials discovery. Herein, we report a convolutional neural network (CNN) that was trained based on theoretical data and very limited experimental data for fast identification of experimental X-ray diffraction (XRD) patterns of metal–organic frameworks (MOFs). To augment the data for training the model, noise was extracted from experimental data and shuffled; then it was merged with the main peaks that were extracted from theoretical spectra to synthesize new spectra. For the first time, one-to-one material identification was achieved. Theoretical MOFs patterns (1012) were augmented to a whole data set of 72 864 samples. It was then randomly shuffled and split into training (58 292 samples) and validation (14 572 samples) data sets at a ratio of 4:1. For the task of discriminating, the optimized model showed the highest identification accuracy of 96.7% for the top 5 ranking on a test data set of 30 hold-out samples. Neighborhood component analysis (NCA) on the experimental XRD samples shows that the samples from the same material are clustered in groups in the NCA map. Analysis on the class activation maps of the last CNN layer further discloses the mechanism by which the CNN model successfully identifies individual MOFs from the XRD patterns. Furthermore, this CNN model trained by the data augmentation technique would not only open numerous potential applications for identifying XRD patterns for different materials, but also pave avenues to autonomously analyze data by other characterization tools such as FTIR, Raman, and NMR spectroscopies.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Future precipitation increase constrained by climatological pattern of cloud effect

The fractional increase in global mean precipitation (?P ¯/P ¯) is a first-order measure of the hydrological cycle intensification under anthropogenic warming. However, ?P ¯/P ¯ varies by a factor of more than three among model projections, hindering credible assessments of the associated climate impacts. The uncertainty in ?P ¯/P ¯ stems from uncertainty in both hydrological sensitivity (global mean precipitation increase per unit warming) and climate sensitivity (global mean temperature increase per forcing). Here, by investigating hydrological and climate sensitivities in a unified surface-energy-balance perspective, we find that both sensitivities are significantly correlated with surface shortwave cloud feedback, which is further linked to the climatological pattern of cloud shortwave effect. The observed pattern of cloud effect thus constrains both sensitivities and consequently constrains ?P ¯/P ¯. The 5%-95% uncertainty range of ?P ¯/P ¯ from 1979-2005 to 2080-2100 under the high-emission (moderate-emission) scenario is constrained from 6.34±3.53% (4.19±2.28%) in the raw ensemble-model projection to 7.03±2.59% (4.63±1.71%). The constraint thus suggests a higher most-likely ?P ¯/P ¯ and reduces the uncertainty by ~25%, providing valuable information for impact assessments.

Zhou, Wenyu↗
DOE OSTI2023

Pattern of global spin alignment of ϕ and K*0 mesons in heavy-ion collisions

The strong force, as one of the four fundamental forces at work in the universe, governs interactions of quarks and gluons, and binds together the atomic nucleus. Notwithstanding decades of progress since Yukawa first developed a description of the force between nucleons in terms of meson exchange 1 , a full understanding of the strong interaction remains a major challenge in modern science. One remaining difficulty arises from the non-perturbative nature of the strong force, which leads to the phenomenon of quark confinement at distance scales on the order of the size of the proton. Here we show that in relativistic heavy-ion collisions, where quarks and gluons are set free over an extended volume, two species of produced vector (spin-1) mesons, namely φ and K∗0 , emerge with a surprising pattern of global spin alignment. In particular, the global spin alignment for φ is unexpectedly large, while that for K∗0 is consistent with zero. The observed spin-alignment pattern and magnitude for the φ cannot be explained by conventional mechanisms, while a model with strong force fields2, 3 accommodates the current data. This is the first time that the strong force field is experimentally supported as a key mechanism that leads to global spin alignment. We extract a quantity proportional to the intensity of the field of the strong force. Within the framework of the Standard Model, where the strong force is typically described in the quark and gluon language of Quantum Chromodynamics, the field being considered here is an effective proxy description. This is a qualitatively new class of measurement, which opens a new avenue for studying the behaviour of strong force fields via their imprint on spin alignment.

Abdallah, M. S.↗
DOE OSTI2014

Measurement of dynamic patterns of an elastic membrane at bi-modal vibration using high speed electronic speckle pattern interferometry

Implementing a hybrid arrangement of Laser Doppler Vibrometry (LDV) and high speed Electronic Speckle Pattern Interferometry (ESPI) we were able to measure the dynamic patterns of a flat rectangular elastic membrane clamped at its edges stimulated with the sum of two resonance frequencies. ESPI is a versatile technique to analyze in real-time the deformation of a membrane since its low computational cost and easy implementation of the optical setup. Elastic membranes present nonlinear behaviors when stimulated with low amplitude signals. The elastic membrane under test, with several non rational related vibrating modals below the 200 Hz, was stimulated with two consecutives resonant frequencies. The ESPI patterns, acquired at high speed rates, shown a similar behavior for the dual frequency stimulation as in the case of patterns formed with the entrainment frequency. We think this may be related to the effects observed in the application of dual frequency stimulation in ultrasound.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Patterning of graphene oxide with optoelectronic tweezers

Optoelectronic tweezers (OET) offer a means for parallel trapping and dynamic manipulation of micro-scale particles using low-intensity light. Such capabilities can facilitate the formation of bulk materials with a precisely tailored microstructure. Here, we report the use of OET to vertically align, trap, and reposition sheets of graphene oxide (GO) in liquids, paving the way for textured and patterned graphene macroassemblies that could offer superior performance for applications in energy storage, catalysis, and electronic devices. Trapping can be achieved with low-power light from inexpensive digital projectors and diode lasers, making it simple for users to create and apply patterns while avoiding undesirable photothermal heating effects. To give users a quantitative idea of trap stiffness, we also present a theoretical framework for predicting the maximum achievable speed of a GO platelet in an OET trap.

Lim, Matthew B. (ORCID:0000000161299876)↗
DOE OSTI2017

Photoinduced Domain Pattern Transformation in Ferroelectric-Dielectric Superlattices

The nanodomain pattern in ferroelectric/dielectric superlattices transforms to a uniform polarization state under above-bandgap optical excitation. X-ray scattering reveals a disappearance of domain diffuse scattering and an expansion of the lattice. Furthermore, the reappearance of the domain pattern occurs over a period of seconds at room temperature, suggesting a transformation mechanism in which charge carriers in long-lived trap states screen the depolarization field. A Landau-Ginzburg-Devonshire model predicts changes in lattice parameter and a critical carrier concentration for the transformation.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Patterns of longer-term climate change effects on CO 2 efflux from biocrusted soils differ from those observed in the short term

Biological soil crusts (biocrusts) are predicted to be sensitive to the increased temperature and altered precipitation associated with climate change. We assessed the effects of these factors on soil carbon dioxide (CO 2 ) balance in biocrusted soils using a sequence of manipulations over a 9-year period. We warmed biocrusted soils by 2 and, later, by 4 °C to better capture updated forecasts of future temperature at a site on the Colorado Plateau, USA. We also watered soils to alter monsoon-season precipitation amount and frequency and had plots that received both warming and altered precipitation treatments. Within treatment plots, we used 20 automated flux chambers to monitor net soil exchange (NSE) of CO 2 hourly, first in 2006–2007 and then again in 2013–2014, for a total of 39 months. Net CO 2 efflux from biocrusted soils in the warming treatment increased a year after the experiment began (2006–2007). However, after 9 years and even greater warming (4 °C), results were more mixed, with a reversal of the increase in 2013 (i.e., controls showed higher net CO 2 efflux than treatment plots) and with similarly high rates in all treatments during 2014, a wet year. Over the longer term, we saw evidence of reduced photosynthetic capacity of the biocrusts in response to both the temperature and altered precipitation treatments. Patterns in biocrusted soil CO 2 exchange under experimentally altered climate suggest that (1) warming stimulation of CO 2 efflux was diminished later in the experiment, even in the face of greater warming; and (2) treatment effects on CO 2 flux patterns were likely driven by changes in biocrust species composition and by changes in root respiration due to vascular plant responses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Face recognition system and method using face pattern words and face pattern bytes

The present invention provides a novel system and method for identifying individuals and for face recognition utilizing facial features for face identification. The system and method of the invention comprise creating facial features or face patterns called face pattern words and face pattern bytes for face identification. The invention also provides for pattern recognitions for identification other than face recognition. The invention further provides a means for identifying individuals based on visible and/or thermal images of those individuals by utilizing computer software implemented by instructions on a computer or computer system and a computer readable medium containing instructions on a computer system for face recognition and identification.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Pollen Cell Wall Patterns Form from Modulated Phases

The ornately geometric walls of pollen grains have inspired scientists for decades. Here, we show that the evolved diversity of these patterns is entirely recapitulated by a biophysical model in which an initially uniform polysaccharide layer in the extracellular space, mechanically coupled to the cell membrane, phase separates to a spatially modulated state. Experiments reveal this process occurring in living cells. We observe that in ~10% of extant species, this phase separation reaches equilibrium during development such that individual pollen grains are identical and perfectly reproducible. About 90% of species undergo an arrest of this process prior to equilibrium such that individual grains are similar but inexact copies. Equilibrium patterns have appeared multiple times during the evolution of seed plants, but selection does not favor these states. This framework for pattern development provides a route to rationalizing the surface textures of other secreted structures, such as cell walls and insect cuticle.

59 BASIC BIOLOGICAL SCIENCES↗