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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Title Coherent X-ray Studies of Surface Growth and Patterning Processes

X-ray Photon Correlation Spectroscopy (XPCS) is being developed as a tool to study nanoscale dynamics of fluctuations during thin film growth and surface patterning. XPCS examines the evolution of the X-ray scattering speckle pattern in reciprocal space to reveal dynamics information not accessible through any other means. Unlike low-coherence conventional X-ray scattering, which incoherently averages over different regions of a sample, coherent X-ray scattering is sensitive to the detailed structure of a given sample at that moment in time. In thin film growth processes, heterodyning, which occurs due to coherent mixing of two scattered signals, can be used to investigate the relationship between surface growth velocity and defect propagation. And, for polycrystalline thin film growth, the spatial coherence of the X-ray beam can substitute for the missing spatial coherence of the growth process to track layered growth in detail, even in a growth regime in which there are no conventional growth oscillations of the X-ray intensity. This has opened the door for detailed dynamics studies of individual atomic layers during real-world growth and patterning, not just in perfect single-crystal growth cases, which greatly expands the applicability of in-situ X-ray scattering methods. Step-flow dynamics in mounded polycrystalline growth has been studied separately for two thin film organic semiconductors deposited by thermal deposition in a vacuum environment, C60 and diindenoperylene (DIP). Highly oriented polycrystalline thin films are readily obtained in both systems, where mounds are composed of crystalline monolayer-height steps and terraces in a so-called wedding cake morphology. The formation of mounds is understood to be due to significant Ehrlich-Schwoebel step edge barriers that inhibit molecules from hopping down from one layer to the one below. The mounds exhibit local step flow, which can be monitored using coherent X-ray scattering. This is made possible due to heterodyning between scattering from the average mounds and the moving steps, which becomes visible in XPCS analysis. The effect of desorption, i.e. re-evaporation of deposited molecules is found to be important for understanding these processes. The impact of this work is to enable testing of models of step dynamics, the shape of mounds, and merging of mounds to form continuous thin films. Highly ordered polycrystalline thin films deposited on inexpensive substrates have applications in thin film solar cells and other organic electronic devices. In a separate set of experiments, speckle analysis during self-organized ion beam nanopatterning reveals memory stretching back to the beginning of patterning in the early stages and enables measurement of the velocity of self-organized patterns across surfaces providing the possibility of stringent new tests of the theory of pattern formation and motion.

36 MATERIALS SCIENCE↗
DOE OSTI2023

INTERSECT Architecture Specification: Use Case Design Patterns (V.0.9)

Connecting scientific instruments and robot-controlled laboratories with computing and data resources at the edge, the Cloud or the high-performance computing (HPC) center enables autonomous experiments, self-driving laboratories, smart manufacturing, and artificial intelligence (AI)-driven design, discovery and evaluation. The Self-driven Experiments for Science / Interconnected Science Ecosystem (INTERSECT) Open Architecture enables science breakthroughs using intelligent networked systems, instruments and facilities with a federated hardware/software architecture for the laboratory of the future. It relies on a novel approach, consisting of (1) science use case design patterns, (2) a system of systems architecture, and (3) a microservice architecture. This document introduces the science use case design patterns of the INTERSECT Architecture. It describes the overall background, the involved terminology and concepts, and the pattern format and classification. It further details the 12 defined patterns and provides insight into building solutions from these patterns. The document also describes the application of these patterns in the context of several INTERSECT autonomous laboratories. The target audience are computer, computational, instrument and domain science experts working in the field of autonomous experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Discovering multi-scale co-occurrence patterns of asthma and influenza with the Oak Ridge bio-surveillance toolkit

Here, we describe a data-driven unsupervised machine learning approach to extract geo-temporal co-occurrence patterns of asthma and the flu from large-scale electronic healthcare reimbursement claims (eHRC) datasets. Specifically, we examine the eHRC data from 2009 to 2010 pandemic H1N1 influenza season and analyze whether different geographic regions within the United States (US) showed an increase in co-occurrence patterns of the flu and asthma. Our analyses reveal that the temporal patterns extracted from the eHRC data show a distinct lag time between the peak incidence of the asthma and the flu. While the increased occurrence of asthma contributed to increased flu incidence during the pandemic, this co-occurrence is predominant for female patients. The geo-temporal patterns reveal that the co-occurrence of the flu and asthma are typically concentrated within the south-east US. Further, in agreement with previous studies, large urban areas (such as New York, Miami, and Los Angeles) exhibit co-occurrence patterns that suggest a peak incidence of asthma and flu significantly early in the spring and winter seasons. Together, our data-analytic approach, integrated within the Oak Ridge Bio-surveillance Toolkit platform, demonstrates how eHRC data can provide novel insights into co-occurring disease patterns.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Spatial–Temporal Patterns of Historical, Near-Term, and Projected Drought in the Conterminous United States

Major droughts in the United States have heavily impacted the hydrologic system, negatively effecting energy and food production. Improved understanding of historical drought is critical for accurate forecasts. Data from global climate models (GCMs), commonly used to assess drought, cannot effectively evaluate local patterns because of their low spatial scale. This research leverages downscaled (~4 km grid spacing) temperature and precipitation estimates from nine GCMs’ data under the business-as-usual scenario (Representative Concentration Pathway 8.5) to examine drought patterns. Drought severity is estimated using the Palmer Drought Severity Index (PDSI) with the Thornthwaite evapotranspiration method. The specific objectives were (1) To reproduce historical (1966–2005) drought and calculate near-term to future (2011–2050) drought patterns over the conterminous USA. (2) To uncover the local variability of spatial drought patterns in California between 2012 and 2018 using a network-based approach. Our estimates of land proportions affected by drought agree with the known historical drought events of the mid-1960s, late 1970s to early 1980s, early 2000s, and between 2012 and 2015. Network analysis showed heterogeneity in spatial drought patterns in California, indicating local variability of drought occurrence. The high spatial scale at which the analysis was performed allowed us to uncover significant local differences in drought patterns. This is critical for highlighting possible weak systems that could inform adaptation strategies such as in the energy and agricultural sectors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Applying the Tremaine–Weinberg Method to Nearby Galaxies: Stellar-mass-based Pattern Speeds and Comparisons with ISM Kinematics

We apply the Tremaine–Weinberg method to 19 nearby galaxies using stellar mass surface densities and velocities derived from the PHANGS-MUSE survey, to calculate (primarily bar) pattern speeds (Ω{sub P}). After quality checks, we find that around half (10) of these stellar-mass-based measurements are reliable. For those galaxies, we find good agreement between our results and previously published pattern speeds, and we use rotation curves to calculate major resonance locations (corotation radii and Lindblad resonances). We also compare these stellar-mass-derived pattern speeds with Hα (from MUSE) and CO(J = 2 − 1) emission from the PHANGS-ALMA survey. We find that in the case of these clumpy interstellar medium (ISM) tracers, this method erroneously gives a signal that is simply the angular frequency at a representative radius set by the distribution of these clumps (Ω{sub clump}), and that this Ω{sub clump} is significantly different from Ω{sub P} (∼20% in the case of Hα, and ∼50% in the case of CO). Thus, we conclude that it is inadvisable to use “pattern speeds” derived from ISM kinematics. Finally, we compare our derived pattern speeds and corotation radii, along with bar properties, to the global parameters of these galaxies. Consistent with previous studies, we find that galaxies with a later Hubble type have a larger ratio of corotation radius to bar length, more molecular-gas-rich galaxies have higher Ω{sub P}, and more bulge-dominated galaxies have lower Ω{sub P}. Unlike earlier works, however, there are no clear trends between the bar strength and Ω{sub P}, nor between the total stellar mass surface density and the pattern speed.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2017

Diversity of Abundance Patterns of Light Neutron-capture Elements in Very-metal-poor Stars

We determine the abundances of neutron-capture elements from Sr to Eu for five very-metal-poor stars (−3 < [Fe/H] < −2) in the Milky Way halo to reveal the origin of light neutron-capture elements. Previous spectroscopic studies have shown evidence of at least two components in the r-process; one referred to as the “main r-process” and the other as the “weak r-process,” which is mainly responsible for producing heavy and light neutron-capture elements, respectively. Observational studies of metal-poor stars suggest that there is a universal pattern in the main r-process, similar to the abundance pattern of the r-process component of solar-system material. Still, it is uncertain whether the abundance pattern of the weak r-process shows universality or diversity, due to the sparseness of measured light neutron-capture elements. We have detected the key elements, Mo, Ru, and Pd, in five target stars to give an answer to this question. The abundance patterns of light neutron-capture elements from Sr to Pd suggest a diversity in the weak r-process. In particular, scatter in the abundance ratio between Ru and Pd is significant when the abundance patterns are normalized at Zr. Our results are compared with the elemental abundances predicted by nucleosynthesis models of supernovae with parameters such as electron fraction or proto-neutron-star mass, to investigate sources of such diversity in the abundance patterns of light neutron-capture elements. This paper presents that the variation in the abundances of observed stars can be explained with a small range of parameters, which can serve as constraints on future modeling of supernova models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Exploring precipitation pattern scaling methodologies and robustness among CMIP5 models

Pattern scaling is a well-established method for approximating modeled spatial distributions of changes in temperature by assuming a time-invariant pattern that scales with changes in global mean temperature. We compare two methods of pattern scaling for annual mean precipitation (regression and epoch difference) and evaluate which method is better in particular circumstances by quantifying their robustness to interpolation/extrapolation in time, inter-model variations, and inter-scenario variations. Both the regression and epoch-difference methods (the two most commonly used methods of pattern scaling) have good absolute performance in reconstructing the climate model output, measured as an area-weighted root mean square error. We decompose the precipitation response in the RCP8.5 scenario into a CO 2 portion and a non-CO 2 portion. Extrapolating RCP8.5 patterns to reconstruct precipitation change in the RCP2.6 scenario results in large errors due to violations of pattern scaling assumptions when this CO 2 -/non-CO 2 -forcing decomposition is applied. As a result, the methodologies discussed in this paper can help provide precipitation fields to be utilized in other models (including integrated assessment models or impacts assessment models) for a wide variety of scenarios of future climate change.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1974

Pattern recognition principles

The present work gives an account of basic principles and available techniques for the analysis and design of pattern processing and recognition systems. Areas covered include decision functions, pattern classification by distance functions, pattern classification by likelihood functions, the perceptron and the potential function approaches to trainable pattern classifiers, statistical approach to trainable classifiers, pattern preprocessing and feature selection, and syntactic pattern recognition.

Tou, J. T.↗
NASA NTRS1979

Data pattern sensitivity in tracking performance of an AC coupled Costas loop with hard-limited in-phase channel

This paper is concerned with data pattern sensitivity in carrier tracking performance of an AC coupled Costas loop with a suppressed BPSK signal. The signal amplitude suppression factor is derived as a function of data 'asymmetry ratio' - the ratio of '1's to the total number of bits in a period of a periodic signal. For an asymmetric pattern, the effect of AC coupling is noticeable whereas there is almost no effect for symmetric square wave. The tracking performance with an asymmetric pattern is worse than that with a symmetric pattern. However, it is also shown that as expected, the tracking performance of a DC coupled loop with an asymmetric pattern is better than that with a symmetric pattern.

Park, Y. H.↗
NASA NTRS1982

The structure of the antenna pattern of an adaptive array

The antenna pattern of a receiving adaptive array is investigated for the case of its operation in an environment of one desirable narrow-band signal and (K-1) narrow-band jammers. Results show that the adapted (voltage) antenna pattern of the array is a linear combination of k (or less) basis-patterns, each of which is a function of one source only. It is determined that these basis-patterns have a simple physical meaning in that the k-th basis-pattern is the pattern formed by the array when the transmission of source k is considered a desired signal and all other sources are turned off.

Zohar, S.↗
NASA NTRS1984

Binary Correlator for Electromagnetic Signal Patterns

Modulation patterns recognized with extensive calculations. Set of shift registers contains patterns of 1's and 0's representing presence or absence of received signal in designated time/frequency bins. Pattern in shift registers correlated with pattern of expected signal by shifting each cell to right according to expected pattern and summing shift-register outputs in analog summing network. Useful in applications requiring identification of smaller pattern of 1-bit data within larger matrix of such data.

Garrison, J. B.↗
NASA NTRS1982

Radiation patterns of interfacial dipole antennas

The radiation pattern of an infinitesimal electric dipole is calculated for the case where the dipole is vertically located on the plane interface of two dielectric half spaces and for the case where the dipole is lying horizontally along the interface. For the vertical case, it is found that the radiation pattern has nulls at the interface and along the dipole axis. For the horizontal case, it is found that the pattern has a null at the interface; that the pattern in the upper half space, whose index of refraction is taken to be less than that of the lower half space, has a single lobe whose maximum is normal to the interface; and that in the lower half space, in the plane normal to the interface and containing the dipole, the pattern has three lobes, whereas in the plane normal to the interface and normally bisecting the dipole, the pattern has two maxima located symmetrically about a minimum. Interpretation of these results in terms of the Cerenkov effect is given.

Engheta, N.↗
NASA NTRS1983

The steady-state antenna patterns of adaptive arrays

A decomposition of the adapted pattern generated by an adaptive array operating in an environment with one narrowband signal, K-1 narrowband jammers, and programmed to produce the maximum SNR is presented. The antenna voltage pattern is demonstrated to be a linear combination of K (or less) basis patterns, each from a sole source, and the kth basis pattern becomes the desired signal realized by the array. Isotropic array patterns result in retrodirective basis patterns, and the decomposition can be configured to obtain the retrodirective beams for all K.

Zohar, S.↗
NASA NTRS1988

Orthogonal patterns in binary neural networks

A binary neural network that stores only mutually orthogonal patterns is shown to converge, when probed by any pattern, to a pattern in the memory space, i.e., the space spanned by the stored patterns. The latter are shown to be the only members of the memory space under a certain coding condition, which allows maximum storage of M=(2N) sup 0.5 patterns, where N is the number of neurons. The stored patterns are shown to have basins of attraction of radius N/(2M), within which errors are corrected with probability 1 in a single update cycle. When the probe falls outside these regions, the error correction capability can still be increased to 1 by repeatedly running the network with the same probe.

Baram, Yoram↗
NASA NTRS1992

A pattern synthesis technique for array feeds to improve radiation performance of large distorted reflector antennas

Technologies exist for construction of antennas with adaptive surfaces that can compensate for many of the larger distortions caused by thermal and gravitational forces. However, as the frequency and size of the reflectors increase, the subtle surface errors become significant and degrade the overall electromagnetic performance. Electronic compensation through an adaptive feed array offers a means for mitigation of surface distortion effects. A pattern synthesis approach for electromagnetic compensation of surface error is presented. The pattern synthesis approach uses a localized algorithm in which pattern corrections are directed toward specific portions of the pattern requiring improvement. The pattern synthesis technique uses radiation pattern data to perform the compensation.

Smith, William T.↗
NASA NTRS1995

Hierarchical analysis of spatial pattern and processes of Douglas-fir forests

There has been an increased interest in the quantification of pattern in ecological systems over the past years. This interest is motivated by the desire to construct valid models which extend across many scales. Spatial methods must quantify pattern, discriminate types of pattern, and relate hierarchical phenomena across scales. Wavelet analysis is introduced as a method to identify spatial structure in ecological transect data. The main advantage of the wavelet transform over other methods is its ability to preserve and display hierarchical information while allowing for pattern decomposition. Two applications of wavelet analysis are illustrated, as a means to: (1) quantify known spatial patterns in Douglas-fir forests at several scales, and (2) construct spatially-explicit hypotheses regarding pattern generating mechanisms. Application of the wavelet variance, derived from the wavelet transform, is developed for forest ecosystem analysis to obtain additional insight into spatially-explicit data. Specifically, the resolution capabilities of the wavelet variance are compared to the semi-variogram and Fourier power spectra for the description of spatial data using a set of one-dimensional stationary and non-stationary processes. The wavelet cross-covariance function is derived from the wavelet transform and introduced as a alternative method for the analysis of multivariate spatial data of understory vegetation and canopy in Douglas-fir forests of the western Cascades of Oregon.

Bradshaw, G. A.↗
NASA NTRS1995

Searching for patterns in remote sensing image databases using neural networks

We have investigated a method, based on a successful neural network multispectral image classification system, of searching for single patterns in remote sensing databases. While defining the pattern to search for and the feature to be used for that search (spectral, spatial, temporal, etc.) is challenging, a more difficult task is selecting competing patterns to train against the desired pattern. Schemes for competing pattern selection, including random selection and human interpreted selection, are discussed in the context of an example detection of dense urban areas in Landsat Thematic Mapper imagery. When applying the search to multiple images, a simple normalization method can alleviate the problem of inconsistent image calibration. Another potential problem, that of highly compressed data, was found to have a minimal effect on the ability to detect the desired pattern. The neural network algorithm has been implemented using the PVM (Parallel Virtual Machine) library and nearly-optimal speedups have been obtained that help alleviate the long process of searching through imagery.

Paola, Justin D.↗
NASA NTRS1996

Pattern Search Algorithms for Bound Constrained Minimization

We present a convergence theory for pattern search methods for solving bound constrained nonlinear programs. The analysis relies on the abstract structure of pattern search methods and an understanding of how the pattern interacts with the bound constraints. This analysis makes it possible to develop pattern search methods for bound constrained problems while only slightly restricting the flexibility present in pattern search methods for unconstrained problems. We prove global convergence despite the fact that pattern search methods do not have explicit information concerning the gradient and its projection onto the feasible region and consequently are unable to enforce explicitly a notion of sufficient feasible decrease.

Lewis, Robert Michael↗