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At least 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Machine-learning-assisted analysis of transition metal dichalcogenide thin-film growth

In situ reflective high-energy electron diffraction (RHEED) is widely used to monitor the surface crystalline state during thin-film growth by molecular beam epitaxy (MBE) and pulsed laser deposition. With the recent development of machine learning (ML), ML-assisted analysis of RHEED videos aids in interpreting the complete RHEED data of oxide thin films. The quantitative analysis of RHEED data allows us to characterize and categorize the growth modes step by step, and extract hidden knowledge of the epitaxial film growth process. In this study, we employed the ML-assisted RHEED analysis method to investigate the growth of 2D thin films of transition metal dichalcogenides (ReSe2) on graphene substrates by MBE. Principal component analysis (PCA) and K-means clustering were used to separate statistically important patterns and visualize the trend of pattern evolution without any notable loss of information. Using the modified PCA, we could monitor the diffraction intensity of solely the ReSe2 layers by filtering out the substrate contribution. These findings demonstrate that ML analysis can be successfully employed to examine and understand the film-growth dynamics of 2D materials. Further, the ML-based method can pave the way for the development of advanced real-time monitoring and autonomous material synthesis techniques.

36 MATERIALS SCIENCE↗
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 OSTI2013

Texture analysis improves level set segmentation of the anterior abdominal wall

Purpose: The treatment of ventral hernias (VH) has been a challenging problem for medical care. Repair of these hernias is fraught with failure; recurrence rates ranging from 24% to 43% have been reported, even with the use of biocompatible mesh. Currently, computed tomography (CT) is used to guide intervention through expert, but qualitative, clinical judgments, notably, quantitative metrics based on image-processing are not used. The authors propose that image segmentation methods to capture the three-dimensional structure of the abdominal wall and its abnormalities will provide a foundation on which to measure geometric properties of hernias and surrounding tissues and, therefore, to optimize intervention.Methods: In this study with 20 clinically acquired CT scans on postoperative patients, the authors demonstrated a novel approach to geometric classification of the abdominal. The authors’ approach uses a texture analysis based on Gabor filters to extract feature vectors and follows a fuzzy c-means clustering method to estimate voxelwise probability memberships for eight clusters. The memberships estimated from the texture analysis are helpful to identify anatomical structures with inhomogeneous intensities. The membership was used to guide the level set evolution, as well as to derive an initial start close to the abdominal wall.Results: Segmentation results on abdominal walls were both quantitatively and qualitatively validated with surface errors based on manually labeled ground truth. Using texture, mean surface errors for the outer surface of the abdominal wall were less than 2 mm, with 91% of the outer surface less than 5 mm away from the manual tracings; errors were significantly greater (2–5 mm) for methods that did not use the texture.Conclusions: The authors’ approach establishes a baseline for characterizing the abdominal wall for improving VH care. Inherent texture patterns in CT scans are helpful to the tissue classification, and texture analysis can improve the level set segmentation around the abdominal region.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS1974

An automated and repeatable data analysis procedure for remote sensing applications

A new multispectral data analysis procedure, based on LARSYS, has been developed which substantially reduces the influence of the analyst. The analysis is automated, including the interpretation of clustering results. The classification results obtained are repeatable and not biased by analyst subjectivity during the analysis.

Davis, B. J.↗
DOE OSTI2018

Stellar Variability at the Main-sequence Turnoff of the Intermediate-age LMC Cluster NGC 1846

Intermediate-age (IA) star clusters in the Large Magellanic Cloud (LMC) present extended main-sequence turn-offs (MSTO) that have been attributed to either multiple stellar populations or an effect of stellar rotation. Recently it has been proposed that these extended main sequences can also be produced by ill-characterized stellar variability. Here we present Gemini-S/Gemini Multi-Object Spectrometer (GMOS) time series observations of the IA cluster NGC 1846. Using differential image analysis, we identified 73 new variable stars, with 55 of those being of the Delta Scuti type, that is, pulsating variables close the MSTO for the cluster age. Considering completeness and background contamination effects, we estimate the number of δ Sct belonging to the cluster between 40 and 60 members, although this number is based on the detection of a single δ Sct within the cluster half-light radius. This amount of variable stars at the MSTO level will not produce significant broadening of the MSTO, albeit higher-resolution imaging will be needed to rule out variable stars as a major contributor to the extended MSTO phenomenon. Though modest, this amount of δ Sct makes NGC 1846 the star cluster with the highest number of these variables ever discovered. Lastly, our results present a cautionary tale about the adequacy of shallow variability surveys in the LMC (like OGLE) to derive properties of its δ Sct population.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

THE PROGRESSION OF STAR FORMATION IN THE ROSETTE MOLECULAR CLOUD

Using Spitzer Space Telescope and Chandra X-Ray Observatory data, we identify young stellar objects (YSOs) in the Rosette Molecular Cloud (RMC). By being able to select cluster members and classify them into YSO types, we are able to track the progression of star formation locally within the cluster environments and globally within the cloud. We employ the nearest neighbor method analysis to explore the density structure of the clusters and YSO ratio mapping to study age progressions in the cloud. We find a relationship between the YSO ratios and extinction that suggests star formation occurs preferentially in the densest parts of the cloud and that the column density of gas rapidly decreases as the region evolves. This suggests rapid removal of gas may account for the low star formation efficiencies observed in molecular clouds. We find that the overall age spread across the RMC is small. Our analysis suggests that star formation started throughout the complex around the same time. Age gradients in the cloud appear to be localized and any effect the H II region has on the star formation history is secondary to that of the primordial collapse of the cloud.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Analysis of Fourth-, Fifth-, and Infinite-Order Triple Excitations in Unitary Coupled Cluster Theory

Here, in this work, we introduce a perturbative correction to the unitary coupled cluster method with single and double excitations (UCCSD) that incorporates the effects of missing triple excitations through fifth-order in many-body perturbation theory (MBPT). Referred to as UCCSD[T-5], this method is benchmarked alongside the previously developed UCCSD[T] to lend insight into the behavior of perturbative triples corrections relative to UCCSDT, which inherently provides an infinite-order treatment of triple excitations, as well as full configuration interaction (FCI). Two key findings emerge from this analysis. First, UCCSD[T] consistently yields ground-state energies in closest agreement with FCI, outperforming both UCCSD[T-5] and UCCSDT. Second, UCCSD[T-5] largely emulates the behavior of UCCSDT, suggesting a close relationship between fifth- and infinite-order triple-excitation contributions. Given the growing interest in UCC ansätze for quantum computing and the limitations of current quantum hardware, these results highlight the potential of classically computed perturbative corrections within UCC theory to capture triple-excitation effects without the additional quantum resources required by the UCCSDT ansatz.

Windom, Zachary W. [Oak Ridge National Laboratory ↗
DOE OSTI2021

Combination of cluster number counts and two-point correlations: validation on mock Dark Energy Survey

ABSTRACT We present a method of combining cluster abundances and large-scale two-point correlations, namely galaxy clustering, galaxy–cluster cross-correlations, cluster autocorrelations, and cluster lensing. This data vector yields comparable cosmological constraints to traditional analyses that rely on small-scale cluster lensing for mass calibration. We use cosmological survey simulations designed to resemble the Dark Energy Survey Year 1 (DES-Y1) data to validate the analytical covariance matrix and the parameter inferences. The posterior distribution from the analysis of simulations is statistically consistent with the absence of systematic biases detectable at the precision of the DES-Y1 experiment. We compare the χ2 values in simulations to their expectation and find no significant difference. The robustness of our results against a variety of systematic effects is verified using a simulated likelihood analysis of DES-Y1-like data vectors. This work presents the first-ever end-to-end validation of a cluster abundance cosmological analysis on galaxy catalogue level simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

SEARCHING FOR BULK MOTIONS IN THE INTRACLUSTER MEDIUM OF MASSIVE, MERGING CLUSTERS WITH CHANDRA CCD DATA

We search for bulk motions in the intracluster medium (ICM) of massive clusters showing evidence of an ongoing or recent major merger with spatially resolved spectroscopy in Chandra CCD data. We identify a sample of six merging clusters with >150 ks Chandra exposure in the redshift range 0.1 < z < 0.3. By performing X-ray spectral analysis of projected ICM regions selected according to their surface brightness, we obtain the projected redshift maps for all of these clusters. After performing a robust analysis of the statistical and systematic uncertainties in the measured X-ray redshift z{sub X}, we check whether or not the global z{sub X} distribution differs from that expected when the ICM is at rest. We find evidence of significant bulk motions at more than 3σ in A2142 and A115, and less than 2σ in A2034 and A520. Focusing on single regions, we identify significant localized velocity differences in all of the merger clusters. We also perform the same analysis on two relaxed clusters with no signatures of recent mergers, finding no signs of bulk motions, as expected. Our results indicate that deep Chandra CCD data enable us to identify the presence of bulk motions at the level of v{sub BM} > 1000 km s{sup −1} in the ICM of massive merging clusters at 0.1 < z < 0.3. Although the CCD spectral resolution is not sufficient for a detailed analysis of the ICM dynamics, Chandra CCD data constitute a key diagnostic tool complementing X-ray bolometers on board future X-ray missions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Fractal Dimension Effect on the Magnetization Curves of Exchange-Coupled Clusters of Magnetic Nanoparticles

The effect of the fractal dimension of exchange-coupled clusters of magnetic nanoparticles on their magnetization curves is predicted by scaling estimates. These predictions form the basis for the experimental technique used for determining the fractal dimension of nanoparticle clusters from the magnetization curves. We estimate the reliability of determining the dimension by such methods with the help of micromagnetic simulation. It is shown that the effective dimension of magnetic correlation volumes, which is determined from analysis of the magnetization approaching saturation, is in conformity with the dimension of fractal clusters determined from analysis of their morphology. The dimension estimated from analysis of the coercive field on the particle size in a physically natural situation of the dipole–dipole interaction between nanoparticles provides estimates of the cluster dimension, which strongly differs from estimates obtained from analysis of their morphology.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2015

Pathway Aggregation in the Risk Assessment of Proliferation Resistance and Physical Protection (PR&PP) of Nuclear Energy Systems

The framework for Proliferation Resistance and Physical Protection (PR & PP) evaluation is to define a set of challenges, to obtain the system responses, and to assess the outcomes. The assessment of outcomes heavily relies on pathways, defined as sequences of events or actions that could potentially be followed by a State or a group of individuals in order to achieve a proliferation objective, with the defined threats as initiating events. There may be large number of segments connecting pathway stages (e.g. acquisition, processing, and fabrication for PR) which can lead to even larger number of pathways or scenarios through possible different combinations of segment connections, each with associated probabilities contributing to the overall risk. Clustering of these scenarios in specified stage attribute intervals is important for their tractable analysis and outcome assessment. A software tool for scenario generation and clustering (OSUPR) is developed that utilizes the PRCALC code developed at the Brookhaven National Laboratory for scenario generation and the K- means, mean shift and adaptive mean shift algorithms as possible clustering schemes. The results of the study using the Example Sodium Fast Breeder as an example system show that clustering facilitates the probabilistic or deterministic analysis of scenarios to identify system vulnerabilities and communication of the major risk contributors to stakeholders. The results of the study also show that the mean shift algorithm has the most potential for assisting the analysis of the scenarios generated by PRCALC.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2017

Understanding the Scarcity of Thorium Peroxide Clusters

The reaction of Th(NO 3 ) 4 ·5H 2 O with 3 equiv of 2,2',6',2"-terpyridine (terpy) in a mixture of acetonitrile and methanol results in formation of the trinuclear thorium peroxide cluster [Th(O 2 )(terpy)(NO 3 ) 2 ] 3 . This cluster is assembled via bridging by μ–η 2 :η 2 peroxide anions between thorium centers. It decomposes upon removal from the mother liquor to yield Th(terpy)(NO 3 ) 4 and Th(terpy)(NO 3 ) 4 (EtOH). The peroxide formation appears to be radiolytic in origin and is, most likely, generated from radiolysis of water by short-lived daughters generated from 232 Th decay. This cluster does not form when freshly recrystallized Th(NO 3 ) 4 ·5H 2 O is used as the starting material and requires an aged source of thorium. Analysis of the bonding in these clusters demonstrates that, unlike uranium(VI) peroxide interactions, thorium(IV) complexation by peroxide is quite weak and largely ionic. Furthermore, this explains its much lower stability, which is more comparable to that observed in similar zirconium(IV) peroxide clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Mass variance from archival X-ray properties of Dark Energy Survey Year-1 galaxy clusters

ABSTRACT Using archival X-ray observations and a lognormal population model, we estimate constraints on the intrinsic scatter in halo mass at fixed optical richness for a galaxy cluster sample identified in Dark Energy Survey Year-One (DES-Y1) data with the redMaPPer algorithm. We examine the scaling behaviour of X-ray temperatures, TX, with optical richness, λRM, for clusters in the redshift range 0.2 < z < 0.7. X-ray temperatures are obtained from Chandra and XMM observations for 58 and 110 redMaPPer systems, respectively. Despite non-uniform sky coverage, the TX measurements are $\gt 50{{\ \rm per\ cent}}$ complete for clusters with λRM > 130. Regression analysis on the two samples produces consistent posterior scaling parameters, from which we derive a combined constraint on the residual scatter, $\sigma _{\ln T \, |\, \lambda }= 0.275 \pm 0.019$. Joined with constraints for TX scaling with halo mass from the Weighing the Giants program and richness–temperature covariance estimates from the LoCuSS sample, we derive the richness-conditioned scatter in mass, $\sigma _{\ln M \, |\, \lambda }= 0.30 \pm 0.04\, _{({\rm stat})} \pm 0.09\, _{({\rm sys})}$, at an optical richness of approximately 100. Uncertainties in external parameters, particularly the slope and variance of the TX–mass relation and the covariance of TX and λRM at fixed mass, dominate the systematic error. The $95{{\ \rm per\ cent}}$ confidence region from joint sample analysis is relatively broad, $\sigma _{\ln M \, |\, \lambda }\in [0.14, \, 0.55]$, or a factor 10 in variance.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2004

Physics of Galaxy Clusters and How it Affects Cosmological Tests

We have worked on the analysis of the Chandra and XMM observations of the nearby and distant clusters of galaxies, and on the extended sample of the distant x- ray clusters selected in the archival ROSAT PSPC data. Some of the scientific results are discussed below.

Oliversen, Ronald J.↗
DOE OSTI2020

K-means-driven Gaussian Process data collection for angle-resolved photoemission spectroscopy

Abstract We propose the combination of k-means clustering with Gaussian Process (GP) regression in the analysis and exploration of 4D angle-resolved photoemission spectroscopy (ARPES) data. Using cluster labels as the driving metric on which the GP is trained, this method allows us to reconstruct the experimental phase diagram from as low as 12% of the original dataset size. In addition to the phase diagram, the GP is able to reconstruct spectra in energy-momentum space from this minimal set of data points. These findings suggest that this methodology can be used to improve the efficiency of ARPES data collection strategies for unknown samples. The practical feasibility of implementing this technology at a synchrotron beamline and the overall efficiency implications of this method are discussed with a view on enabling the collection of more samples or rapid identification of regions of interest.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Soar optical and near-infrared spectroscopic survey of newly discovered massive stars in the periphery of galactic massive star clusters I-NGC 3603

In this work, we present the results of a spectroscopic study of very massive stars (VMSs) found outside the center of the massive stellar cluster NGC 3603. From the analysis of the associated Southern Astrophysical Research (SOAR) Telescope spectroscopic data and related optical–near-IR (NIR) photometry, we confirm the existence of several VMSs in the periphery of NGC 3603. The first group of objects (MTT58, WR42e, and RF7) is composed of three new Galactic exemplars of the OIf*/WN type, all of them with probable initial masses well above 100 M{sub ⊙} and estimated ages of about 1 Myr. Based on our Goodman blue-optical spectrum of another source in our sample (MTT68), we can confirm the previous finding in the NIR of the only other Galactic exemplar (besides HD 93129A) of the O2If* type known to date. Based on its position relative to a set of theoretical isochrones in a Hertzprung–Russel (H–R) diagram, we concluded that the new O2If* star could be one of the most massive (150 M{sub ⊙}) and luminous (M {sub V} = −7.3) O-stars in the Galaxy. Also, another remarkable result is the discovery of a new O2v star (MTT31), which is the first exemplar of that class so far identified in the Milk Way. From its position in the H–R diagram it is found that this new star probably had an initial mass of 80 M{sub ⊙}, as well as an absolute magnitude of M {sub V} = −6.0, corresponding to a luminosity similar to other known O2v stars in the Large Magellanic Cloud. Finally, we also communicate the discovery of a new Galactic O3.5If* star (RFS8) that is quite an intriguing case. Indeed, it is located far to the south of the NGC 3603 center, in apparent isolation at a large radial projected linear distance of ∼62 pc. Its derived luminosity is similar to that of the other O3.5If* (Sh18) found in NGC 3603's innermost region, and the fact that a such high mass star is observed so isolated in the field led us to speculate that perhaps it could have been expelled from the innermost parts of the complex by a close fly-by dynamical encounter with a very massive hard binary system.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Optical/X-ray/radio view of Abell 1213: A galaxy cluster with anomalous diffuse radio emission

Context. Abell 1213, a low-richness galaxy system, is known to host an anomalous radio halo detected in data of the Very Large Array (VLA). It is an outlier with regard to the relation between the radio halo power and the X-ray luminosity of the parent clusters. Aims. Our aim is to analyze the cluster in the optical, X-ray, and radio bands to characterize the environment of its diffuse radio emission and to shed new light on its nature. Methods. We used optical data from the Sloan Digital Sky Survey to study the internal dynamics of the cluster. We also analyzed archival XMM-Newton X-ray data to unveil the properties of its hot intracluster medium. Finally, we used recent data from the LOw Frequency ARray (LOFAR) at 144 MHz, together with VLA data at 1.4 GHz, to study the spectral behavior of the diffuse radio source. Results. Both our optical and X-ray analysis reveal that this low-mass cluster exhibits disturbed dynamics. In fact, it is composed of several galaxy groups in the peripheral regions and, in particular, in the core, where we find evidence of substructures oriented in the NE–SW direction, with hints of a merger nearly along the line of sight. The analysis of the X-ray emission adds further evidence that the cluster is in an unrelaxed dynamical state. At radio wavelengths, the LOFAR data show that the diffuse emission is ~510 kpc in size. Moreover, there are hints of low-surface-brightness emission permeating the cluster center. Conclusions. The environment of the diffuse radio emission is not what we would expect for a classical halo. The spectral index map of the radio source is compatible with a relic interpretation, possibly due to a merger in the N–S or NE–SW directions, in agreement with the substructures detected through the optical analysis. The fragmented, diffuse radio emissions at the cluster center could be attributed to the surface brightness peaks of a faint central radio halo.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Fatty acid capped, metal oxo clusters as the smallest conceivable nanocrystal prototypes

Metal oxo clusters of the type M 6 O 4 (OH) 4 (OOCR) 12 (M = Zr or Hf) are valuable building blocks for materials science. Here, we synthesize a series of zirconium and hafnium oxo clusters with ligands that are typically used to stabilize oxide nanocrystals (fatty acids with long and/or branched chains). The fatty acid capped oxo clusters have a high solubility but do not crystallize, precluding traditional purification and single-crystal XRD analysis. We thus develop alternative purification strategies and we use X-ray total scattering and Pair Distribution Function (PDF) analysis as our main method to elucidate the structure of the cluster core. We identify the correct structure from a series of possible clusters (Zr3, Zr4, Zr6, Zr12, Zr10, and Zr26). Excellent refinements are only obtained when the ligands are part of the structure model. Further evidence for the cluster composition is provided by nuclear magnetic resonance (NMR), infrared spectroscopy (FTIR), thermogravimetry analysis (TGA), and mass spectrometry (MS). We find that hydrogen bonded carboxylic acid is an intrinsic part of the oxo cluster. Using our analytical tools, we elucidate the conversion from a Zr6 monomer to a Zr12 dimer (and vice versa), induced by carboxylate ligand exchange. Finally, we compare the catalytic performance of Zr12-oleate clusters with oleate capped, 5.5 nm zirconium oxide nanocrystals in the esterification of oleic acid with ethanol. The oxo clusters present a five times higher reaction rate, due to their higher surface area. Since the oxo clusters are the lower limit of downscaling oxide nanocrystals, we present them as appealing catalytic materials, and as atomically precise model systems. In addition, the lessons learned regarding PDF analysis are applicable to other areas of cluster science as well, from semiconductor and metal clusters, to polyoxometalates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗