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All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

A long-term space astrophysics research program: An x-ray perspective of the components and structure of galaxies

X-ray studies of galaxies by the Smithsonian Astrophysical Observatory (SAO) and MIT are described. Activities at SAO include ROSAT PSPC x-ray data reduction and analysis pipeline; x-ray sources in nearby Sc galaxies; optical, x-ray, and radio study of ongoing galactic merger; a radio, far infrared, optical, and x-ray study of the Sc galaxy NGC247; and a multiparametric analysis of the Einstein sample of early-type galaxies. Activities at MIT included continued analysis of observations with ROSAT and ASCA, and continued development of new approaches to spectral analysis with ASCA and AXAF. Also, a new method for characterizing structure in galactic clusters was developed and applied to ROSAT images of a large sample of clusters. An appendix contains preprints generated by the research.

Fabbiano, G.↗
NASA NTRS1995

Constraints on cold dark matter theories from observations of massive x-ray-luminous clusters of galaxies at high redshift

During the course of a gravitational lensing survey of distant, X-ray selected Einstein Observatory Extended Medium Sensitivity Survey (EMSS) clusters of galaxies, we have studied six X-ray-luminous (L(sub x) greater than 5 x 10(exp 44)(h(sub 50)(exp -2))ergs/sec) clusters at redshifts exceeding z = 0.5. All of these clusters are apparently massive. In addition to their high X-ray luminosity, two of the clusters at z approximately 0.6 exhibit gravitationally lensed arcs. Furthermore, the highest redshift cluster in our sample, MS 1054-0321 at z = 0.826, is both extremely X-ray luminous (L(sub 0.3-3.5keV)=9.3 x 10(exp 44)(h(sub 50)(exp -2))ergs/sec) and exceedingly rich with an optical richness comparable to an Abell Richness Class 4 cluster. In this Letter, we discuss the cosmological implications of the very existence of these clusters for hierarchical structure formation theories such as standard Omega = 1 CDM (cold dark matter), hybrid Omega = 1 C + HDM (hot dark matter), and flat, low-density Lambda + CDM models.

Luppino, G. A.↗
NASA NTRS1998

Soft X-Ray Spectra of AGN Discovered Via Their Hard X-Ray

This final report is a study of the Active Galactic Nuclei (AGN). Investigation of the soft x-ray spectra of AGN were performed by using their hard x-ray emission. ROSAT observations of AGN was also performed, which allowed for the study of these x-ray spectra and the structures of 7 clusters of galaxies.

Schwartz, Daniel↗
NASA NTRS2005

In-Situ Heating Decrease Kinetics of Aliphatic Hydrocarbons in Tagish Lake Meteorite by Micro-FTIR

Carbonaceous chondrites are known to contain up to 3wt.% C, the major part of which corresponds to a macromolecular organic fraction. Chondritic organic matter is based on small aromatic units, cross-linked by short aliphatic chains rather than large clusters of polyaromatic structures. Two main characteristic features of those organics measured by FTIR are: (1) an equivalent intensity of the asymmetric stretching mode absorptions for CH3 (2960/cm) and CH2 (2920/cm) and (2) a lack of aromatic CH-stretching mode (3040/cm). Tagish Lake is a new type of water- and carbon-rich type 2 carbonaceous chondrite. Its total carbon content is approx. 5 wt%, of which the organic carbon content reaches approx. 1.3 wt%. Tagish Lake may have never experienced temperatures higher than 120 C after formation of organics based on the disappearance of infrared (IR) organic peaks in step heating experiments. Here we report in-situ kinetic heating experiments of organics in Tagish Lake by micro-FTIR to characterize the nature of aliphatic hydrocarbons and their thermal stabilities.

Kebukawa, Y.↗
NASA NTRS2013

Fine-Scale Fluctuations in the Corona Observed with Hi-C

The High Resolution Coronal Imager(HiC) flew aboard a NASA sounding rocket on 2012 July11 and captured roughly 345 s of high spatial and temporal resolution images of the solar corona in a narrowband 193 Angstrom channel. We have analyzed the fluctuations in intensity of Active Region11520.We selected events based on a lifetime greater than 11s (twoHiC frames)and intensities greater than a threshold determined from the average background intensity in a pixel and the photon and electronic noise. We find fluctuations occurring down to the smallest timescale(~11s).Typical intensity fluctuations are 20% background intensity, while some events peaka t100%the background intensity.Generally the fluctuations are clustered in solar structures, particularly the moss.We interpret the fluctuations in the moss as indicative of heating events. We use the observed events to model the active region core.

Winebarger, Amy↗
NASA NTRS2013

Concurrent Supermassive Black Hole and Galazy Growth: Linking Environment and Nuclear Activity in Zeta Equals 2.23 H Alpha Emitters

We present results from an approximately equal 100 ks Chandra observation of the 2QZ Cluster 1004+00 structure at z = 2.23 (hereafter 2QZ Clus). 2QZ Clus was originally identified as an overdensity of four optically-selected QSOs at z = 2.23 within a 15 × 15 arcmin square region. Narrow-band imaging in the near-IR (within the K band) revealed that the structure contains an additional overdensity of 22 z = 2.23 H alpha-emitting galaxies (HAEs), resulting in 23 unique z = 2.23 HAEs/QSOs (22 within the Chandra field of view). Our Chandra observations reveal that three HAEs in addition to the four QSOs harbor powerfully accreting supermassive black holes (SMBHs), with 2-10 keV luminosities of approximately equal (8-60) × 10(exp 43) erg s(exp−1) and X-ray spectral slopes consistent with unobscured active galactic nucleus (AGN). Using a large comparison sample of 210 z = 2.23 HAEs in the Chandra-COSMOS field (C-COSMOS), we find suggestive evidence that the AGN fraction increases with local HAE galaxy density. The 2QZ Clus HAEs reside in a moderately overdense environment (a factor of approximately equal 2 times over the field), and after excluding optically-selected QSOs, we find that the AGN fraction is a factor of approximately equal 3.5(+3.8/ −2.2) times higher than C-COSMOS HAEs in similar environments. Using stacking analyses of the Chandra data and Herschel SPIRE observations at 250micrometers, we respectively estimate mean SMBH accretion rates ( M(BH)) and star formation rates (SFRs) for the 2QZ Clus and C-COSMOS samples. We find that the mean 2QZ Clus HAE stacked X-ray luminosity is QSO-like (L(2−10 keV) approximately equal [6-10] × 10(exp 43) erg s(exp −1)), and the implied M(BH)/SFR approximately equal (1.6-3.2) × 10(exp −3) is broadly consistent with the local M(BH)/Stellar Mass relation and z approximately equal 2 X-ray selected AGN. In contrast, the C-COSMOS HAEs are on average an order of magnitude less X-ray luminous and have M(BH)/SFR approximately equal (0.2-0.4) × 10(exp −3), somewhat lower than the local MBH/M relation, but comparable to that found for z approximately equal 1-2 star-forming galaxies with similar mean X-ray luminosities. We estimate that a periodic QSO phase with duty cycle approximately 2%-8% would be sufficient to bring star-forming galaxies onto the local M(BH)/Stellar Mass relation. This duty cycle is broadly consistent with the observed C-COSMOS HAE AGN fraction (Approximately equal 0.4%-2.3%) for powerful AGN with LX approximately greater than 10(exp 44) erg s(exp −1). Future observations of 2QZ Clus will be needed to identify key factors responsible for driving the mutual growth of the SMBHs and galaxies.

Lehmer, B. D.↗
DOE OSTI2024

Generalized representative structures for atomistic systems

A new method is presented to generate atomic structures that reproduce the essential characteristics of arbitrary material systems, phases, or ensembles. Previous methods allow one to reproduce the essential characteristics (e.g. the chemical disorder) of a large random alloy within a small crystal structure. The ability to generate small representations of random alloys, along with the restriction to crystal systems, results from using the fixed-lattice cluster correlations to describe structural characteristics. A more general description of the structural characteristics of atomic systems is obtained using complete sets of atomic environment descriptors. These are used within for generating representative atomic structures without restriction to fixed lattices. A general data-driven approach is provided here utilizing the atomic cluster expansion (ACE) basis. The N-body ACE descriptors are a complete set of atomic environment descriptors that span both chemical and spatial degrees of freedom and are used within for describing atomic structures. The generalized representative structure (GRS) method presented within generates small atomic structures that reproduce ACE descriptor distributions corresponding to arbitrary structural and chemical complexity. It is shown that systematically improvable representations of crystalline systems on fixed parent lattices, amorphous materials, liquids, and ensembles of atomic structures may be produced efficiently through optimization algorithms. With the GRS method, we highlight reduced representations of atomistic machine-learning training datasets that contain similar amounts of information and small 40–72 atom representations of liquid phases. The ability to use GRS methodology as a driver for informed novel structure generation is also demonstrated. The advantages over other data-driven methods and state-of-the-art methods restricted to high-symmetry systems are highlighted.

atomic cluster expansion↗
NASA NTRS1994

Theoretical Study of Electron Scattering By Small Clusters and Adsorbates

Current interest in clusters stems from their role as novel materials as well as a possible extension of cluster results to bulk systems. Experimental investigations on clusters have been carried out using laser spectroscopy, microwave spectroscopy, heavy-particle collisions, as well as electron collisions with earlier experimental work on electron attachment and ionization having been reviewed previously. Recently, Mark and coworkers studied the decay channels of cluster ions following electron impact ionization. Rauth et al. reported the formation of the superhalogen ion SF7(-) and other nonstoichiometric cluster ions in their study of electron attachment to SF6 clusters. Kresin et al. measured the absolute electron-impact depletion cross section of metal clusters Na8, Na(20), and Na(40). They found that the inelastic scattering cross section increased with cluster size and was considerably greater than the hard sphere collision cross sections. They hypothesized that electron attachment and collision-induced fragmentation were the dominant physical processes responsible for this effect. For the two smaller clusters, they also found a sharp increase in the cross section near threshold. Most theoretical studies of clusters have been devoted to their electronic structures, vibrational relaxation, and predissociation while investigations of electron scattering from clusters has been lacking. In view of this, we recently undertook an ab initio study of electron scattering from small Be clusters and BeCO. Beryllium was chosen because it is readily amenable to ab t'nitio calculations. Moreover, the electronic structure of Be clusters has been studied extensively, showing that the Be-Be bond is relatively weak in comparison with a normal chemical bond. Our investigation focuses on how the cross sections change with cluster size and geometry. The range of energy studied, 0.05 - 5.0 eV, is chosen because of the ubiquitous resonance in the low-energy scattering of Be. Hence it can be determined if it is possible, as a consequence of the weaker bonds in the Be clusters, to identify the atomic origin of the cluster resonance.

Huo, Winifred M.↗
DOE OSTI2024

Discovering type I cis-AT polyketides through computational mass spectrometry and genome mining with Seq2PKS

Type 1 polyketides are a major class of natural products used as antiviral, antibiotic, antifungal, antiparasitic, immunosuppressive, and antitumor drugs. Analysis of public microbial genomes leads to the discovery of over sixty thousand type 1 polyketide gene clusters. However, the molecular products of only about a hundred of these clusters are characterized, leaving most metabolites unknown. Characterizing polyketides relies on bioactivity-guided purification, which is expensive and time-consuming. To address this, we present Seq2PKS, a machine learning algorithm that predicts chemical structures derived from Type 1 polyketide synthases. Seq2PKS predicts numerous putative structures for each gene cluster to enhance accuracy. The correct structure is identified using a variable mass spectral database search. Benchmarks show that Seq2PKS outperforms existing methods. Applying Seq2PKS to Actinobacteria datasets, we discover biosynthetic gene clusters for monazomycin, oasomycin A, and 2-aminobenzamide-actiphenol.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Impact and mitigation of spectroscopic systematics on DESI DR1 clustering measurements

The large scale structure catalogs within DESI Data Release 1 (DR1) use nearly 6 million galaxies and quasars as tracers of the large-scale structure of the universe to measure the expansion history with baryon acoustic oscillations and the growth of structure with redshift-space distortions. In order to take advantage of DESI's unprecedented statistical power, we must ensure that the galaxy clustering measurements are unaffected by non-cosmological density fluctuations. One source of spurious fluctuations comes from variation in galaxy density with spectroscopic observing conditions, lowering the redshift efficiency (and thus galaxy density) in certain areas of the sky. We measure the uniformity of the redshift success rate for DESI luminous red galaxies (LRG), bright galaxies (BGS) and quasars (QSO), complementing the detailed discussion of emission line galaxy (ELG) systematics in a companion paper [1]. We find small but significant fluctuations of up to 3% in redshift success rate with the effective spectroscopic signal-to-noise, and create and describe weights that remove these fluctuations. We also describe the process to identify and remove data from certain poorly performing fibers from DESI DR1, and measure the stability of the redshift success rate with time. Finally, we find small but significant correlations of redshift success rate with position on the focal plane, survey speed, and number of exposures required, and show the impact of weights correcting these trends on the power spectrum multipoles and on cosmological parameters from BAO and RSD fits. These corrections change the best-fit parameters by <15% of their statistical errors, and thus contribute negligibly to the overall DESI error budget.

cosmological parameters from LSS↗
NASA NTRS1984

Research in extragalactic astrophysics

The spatial distribution of clusters of galaxies and the large scale structure of the universe is investigated. Correlations in the spatial cluster distribution are much stronger than those seen for galaxies, and over scales much larger than previously anticipated. The following main studies are completed and published; (1) The determination of the correlation functions of rich clusters of galaxies, and its dependence on richness and other parameters. Very large scale structure exists in the universe, and rich clusters participate in this structure more efficiently than galaxies. (2) A complete catalog of superclusters, is determined. The selection criteria is that of a volume density enhancement, and is done in 3 dimensions. (3) The giant galaxy void in Bootes is found to be surrouned by rich, large superclusters from the catalog described above. (4) A very large scale void of rich clusters of galaxies is found in the study of the spatial distribution of rich clusters.

Bahcall, N.↗
DOE OSTI2022

Computational studies of structural, energetic, and electronic properties of pure Pt and Mo and mixed Pt/Mo clusters: Comparative analysis of characteristics and trends

The added technological potential of bimetallic clusters and nanoparticles, as compared to their pure (i.e., one-component) counterparts, stems from the ability to further fine-tune their properties and, consequently, functionalities through a simultaneous use of the “knobs” of size and composition. The practical realization of this potential can be greatly advanced by the knowledge of the correlations and relationships between the various characteristics of bimetallic nanosystems on the one hand and those of their pure counterparts as well as pure constituent components on the other hand. Here, in this study, we present results of a density functional theory based study of pure Pt n and Mo n clusters aimed at revisiting and exploring further their structural, electronic, and energetic properties. These are then used as a basis for analysis and characterization of the results of calculations on two-component Pt n-m Mo m clusters. The analysis also includes establishing relationships between the properties of the Pt n-m Mo m clusters and those of their Pt n-m and Mo m components. One of the particularly intriguing findings suggested by the calculated data is a linear dependence of the average binding energy per atom in sets of Pt n-m Mo m clusters that have the same fixed number m of Mo atoms and different number n-m of Pt atoms on the fractional content (n-m)/n of Pt atoms. We derive an analytical model that establishes the fundamental basis for this linearity and expresses its parameters—the m-dependent slope and intercept—in terms of characteristic properties of the constituent components, such as the average binding energy per atom of Mo m and the average per-atom adsorption energy of the Pt atoms on Mo m . The conditions of validity and degree of robustness of this model and of the linear relationship predicted by it are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Robust Group Subspace Recovery: A New Approach for Multi-Modality Data Fusion

Robust Subspace Recovery (RoSuRe) algorithm was recently introduced as a principled and numerically efficient algorithm that unfolds underlying Unions of Subspaces (UoS) structure, present in the data. The union of Subspaces (UoS) is capable of identifying more complex trends in data sets than simple linear models. In this work, we build on and extend RoSuRe to prospect the structure of different data modalities individually. We propose a novel multi-modal data fusion approach based on group sparsity which we refer to as Robust Group Subspace Recovery (RoGSuRe). Relying on a bi-sparsity pursuit paradigm and non-smooth optimization techniques, the introduced framework learns a new joint representation of the time series from different data modalities, respecting an underlying UoS model. We subsequently integrate the obtained structures to form a unified subspace structure. The proposed approach exploits the structural dependencies between the different modalities data to cluster the associated target objects. The resulting fusion of the unlabeled sensors’ data from experiments on audio and magnetic data has shown that our method is competitive with other state of the art subspace clustering methods. The resulting UoS structure is employed to classify newly observed data points, highlighting the abstraction capacity of the proposed method.

47 OTHER INSTRUMENTATION↗
NASA NTRS2006

Diurnal Variability of Vertical Structure from a TRMM Passive Microwave "Virtual Radar" Retrieval

Robust description of the diurnal cycle from TRMM observations is complicated by the limitations of Low Earth Orbit (LEO) sampling; from a 'climatological' perspective, sufficient sampling must exist to control for both spatial and seasonal variability, before tackling an additional diurnal component (e.g., with 8 additional 3-hourly or 24 1-hourly bins). For documentation of vertical structure, the narrow sample swath of the TRMM Precipitation Radar limits the resolution of any of these components. A neural-network based 'virtual radar" retrieval has been trained and internally validated, using multifrequency / multipolarization passive microwave(TM1) brightness temperatures and textures parameters and lightning (LIS) observations, as inputs, and PR volumetric reflectivity as targets (outputs). By training the algorithms (essentially highly multivariate, nonlinear regressions) on a very large sample of high-quality co-located data from the center of the TRMM swath, 3D radar reflectivity and derived parameters (VIL, IWC, Echo Tops, etc.) can be retrieved across the entire TMI swath, good to 8-9% over the dynamic range of parameters. As a step in the retrieval (and as an output of the process), each TMI multifrequency pixel (at 85 GHz resolution) is classified into one of the 25 archetypal radar profile vertical structure "types", previously identified using cluster analysis. The dynamic range of retrieved vertical structure appears to have higher fidelity than the current (Version 6) experimental GPROF hydrometeor vertical structure retrievals. This is attributable to correct representation of the prior probabilities of vertical structure variability in the neural network training data, unlike the GPROF cloud-resolving model training dataset used in the V6 algorithms. The LIS lightning inputs are supplementary inputs, and a separate offline neural network has been trained to impute (predict) LIS lightning from passive-microwave-only data. The virtual radar retrieval is thus, in principle, extensible to Aqua/AMSR-E and NPOESS/CMIS passive microwave instruments. The virtual radar approach yields a threefold increase in effective sampling from the mission, albeit of lower-quality "retrieved" data, reducing the variance of local estimates by one third (or the standard deviation by-0.57). In this talk, the variance reduction is leveraged to more finely resolve global diurnal variability in both space and time (local hour).

Boccippio, Dennis J.↗
NASA NTRS2012

Cold Fronts in Clusters of Galaxies: Observations and Modeling

Mergers of galaxy clusters -- some of the most energetic events in the Universe -- produce disturbances in hot intracluster medium, such as shocks and cold fronts, that can be used as tools to study the physics of galaxy clusters. Cold fronts may constrain viscosity and the structure and strength of the cluster magnetic fields. Combined with radio data, these observations also shed light on the production of ultrarelativistic particles that are known to coexist with the cluster thermal plasma. This talk will summarize the current X-ray observations of cluster mergers, as well as some recent radio data and high resolution hydrodynamic simulations.

Markevitch, Maxim↗
DOE OSTI2022

Broken-Symmetry Density Functional Theory Analysis of the Ω Intermediate in Radical S -Adenosyl- l -methionine Enzymes: Evidence for a Near-Attack Conformer over an Organometallic Species

Radical S-adenosyl-L-methionine (SAM) enzymes are found in all domains of life and catalyze a wide range of biochemical reactions. Recently, an organometallic intermediate, Ω, has been experimentally implicated in the 5'-deoxyadenosyl radical generation mechanism of the radical SAM superfamily. In this work, we employ broken-symmetry density functional theory to evaluate several structural models of Ω. The results show that the calculated hyperfine coupling constants (HFCCs) for the proposed organometallic structure of Ω are inconsistent with the experiment. In contrast, a near-attack conformer of SAM bound to the catalytic [4Fe–4S] cluster, in which the distance between the unique iron and SAM sulfur is ~3 Å, yields HFCCs that are all within 1 MHz of the experimental values. Furthermore, these results clarify the structure of the ubiquitous Ω intermediate and suggest a paradigm shift reversal regarding the mechanism of SAM cleavage by members of the radical SAM superfamily.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Isolated and H 2 -reduced Anderson clusters catalyse low-temperature hydrogenation of CO 2 to methanol

CO 2 hydrogenation, especially to methanol, is crucial to establishing sustainable closed-loop systems for carbon utilization. However, the difficulties of CO 2 activation at low temperatures and the ambiguity of structure–activity correlations are obstacles to reducing the energy consumption of the hydrogenation process. Here we report that molecularly defined Anderson PtMo 6 O 24 clusters, sited within a robust metal–organic framework, are catalytic for low-temperature CO 2 hydrogenation. The performance of the cluster showed no signs of decay in either its activity or methanol selectivity over 3,600 h at 180 °C. It also achieves a per-pass yield exceeding that of state-of-the-art heterogeneous catalysts under similar conditions. Combined in situ spectroscopy and density functional theory calculations demonstrated that CH 3 OH formation is dominated by the reverse water–gas shift and subsequent CO* hydrogenation pathway, while the HCOO* pathway may serve as a supplementary route. The well-defined cluster structure offers an ideal model for elucidating structure–activity correlations and opens exciting avenues for the rational design of high-activity, low-temperature catalysts for CO 2 hydrogenation.

heterogeneous catalysis↗
DOE OSTI2021

Advances in the electron diffraction characterization of atomic clusters and nanoparticles

Nanoparticles and metallic clusters continue to make a remarkable impact on novel and emerging technologies. In recent years, there have been impressive advances in the controlled synthesis of clusters and their advanced characterization. One of the most common ways to determine the structures of nanoparticles and clusters is by means of X-ray diffraction methods. However, this requires the clusters to crystallize in a similar way to those used in protein studies, which is not possible in many cases. Novel methods based on electron diffraction have been used to efficiently study individual nanoparticles and clusters and these can overcome the obstacles commonly encountered during X-ray diffraction methods without the need for large crystals. These novel methodologies have improved with advances in electron microscopy instrumentation and electron detection. Here, we review advanced methodologies for characterizing metallic nanoparticles and clusters using a variety of electron diffraction procedures. These include selected area electron diffraction, nanobeam diffraction, coherent electron diffraction, precession electron diffraction, scanning transmission electron microcopy diffraction, and high throughput data analytics, which leverage deep learning to reduce the propensity for data errors and translate nanometer and atomic scale measurements into material data.

77 NANOSCIENCE AND NANOTECHNOLOGY↗