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At least 631 records · Page 35

Cu site differentiation in tetracopper(I) sulfide clusters enables biomimetic N 2 O reduction

Copper clusters feature prominently in both metalloenzymes and synthetic nanoclusters that mediate catalytic redox transformations of gaseous small molecules. Such reactions are critical to biological energy conversion and are expected to be crucial parts of renewable energy economies. However, the precise roles of individual metal atoms within clusters are difficult to elucidate, particularly for cluster systems that are dynamic under operating conditions. Here, we present a metal site-specific analysis of synthetic Cu 4 (μ 4 -S) clusters that mimic the Cu Z active site of the nitrous oxide reductase enzyme. Leveraging the ability to obtain structural snapshots of both inactive and active forms of the synthetic model system, we analyzed both states using resonant X-ray diffraction anomalous fine structure (DAFS), a technique that enables X-ray absorption profiles of individual metal sites within a cluster to be extracted independently. Using DAFS, we found that a change in cluster geometry between the inactive and active states is correlated to Cu site differentiation that is presumably required for efficient activation of N 2 O gas. More precisely, we hypothesize that the Cu δ+ ∙∙∙Cu δ- pairs produced upon site differentiation are poised for N 2 O activation, as supported by computational modeling. These results provide an unprecedented level of detail on the roles of individual metal sites within the synthetic cluster system and how those roles interplay with cluster geometry to impact the reactivity function. We expect this fundamental knowledge to inform understanding of metal clusters in settings ranging from (bio)molecular to nanocluster to extended solid systems involved in energy conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Infrared emission from dust in the Coma cluster of galaxies

Detailed calculations of the infrared emission from collisionally heated dust in the Coma cluster are presented. The proposed model includes continuous dust injection from galaxies, grain destruction by sputtering, and transient grain heating by the hot plasma. The computed infrared fluxes are in agreement with the upper limits obtained from the IRAS. The calculations, and constraints implied by the IRAS observations, suggest that the intracluster dust in the central region of the cluster must be significantly depleted compared to interstellar abundances. The observed visual extinction can therefore not be attributed to the presence of dust in that region. Extinction due to cluster galaxies or their haloes is ruled out as well. The only alternative explanation is that the extinction is caused by dust at great distances from the cluster center.

Dwek, Eli↗

X-ray studies of coeval star samples. II - The Pleiades cluster as observed with the Einstein Observatory

Coronal X-ray emission of the Pleiades stars is investigated, and maximum likelihood, integral X-ray luminosity functions are computed for Pleiades members in selected color-index ranges. A detailed search is conducted for long-term variability in the X-ray emission of those stars observed more than once. An overall comparison of the survey results with those of previous surveys confirms the ubiquity of X-ray emission in the Pleiades cluster stars and its higher rate of emission with respect to older stars. It is found that the X-ray emission from dA and early dF stars cannot be proven to be dissimilar to that of Hyades and field stars of the same spectral type. The Pleiades cluster members show a real rise of the X-ray luminosity from dA stars to early dF stars. X-ray emission for the young, solarlike Pleiades stars is about two orders of magnitude more intense than for the nearby solarlike stars.

Micela, G.↗

Building Multi-Discipline, Multi-Format Digital Libraries Using Clusters and Buckets

Our objective was to study the feasibility of extending the Dienst protocol to enable a multi-discipline, multi-format digital library. We implemented two new technologies: cluster functionality and publishing buckets. We have designed a possible implementation of clusters and buckets, and have prototyped some aspects of the resultant digital library. Currently, digital libraries are segregated by the disciplines they serve (computer science, aeronautics, etc.), and by the format of their holdings (reports, software, datasets, etc.). NCSTRL+ is a multi-discipline, multi-format digital library (DL) prototype created to explore the feasibility of the design and implementation issues involved with created a unified, canonical scientific and technical information (STI) DL. NCSTRL+ is based on the Networked Computer Science Technical Report Library (NCSTRL), a World Wide Web (WWW) accessible DL that provides access to over 80 university departments and laboratories. We have extended the Dienst protocol (version 4.1.8), the protocol underlying NCSTRL, to provide the ability to cluster independent collections into a logically centralized DL based upon subject category classification, type of organization, and genre of material. The concept of buckets provides a mechanism for publishing and managing logically linked entities with multiple data formats.

Nelson, Michael L.↗

A balanced submatrix merging algorithm for multiprocessor architectures

In this article, a parallel algorithm which applies Givens rotations to selectively annihilate k(k + 1)/2 nonzero elements from two k x n(k not more than n) upper trapezoidal submatrices is described. The new algorithm is suitable for implementation on either a pair of directly connected local-memory processors or two clusters of multiple tightly-coupled processors. Analyses show that in both cases the proposed algorithms achieve optimal speed-up by balancing the work load distribution and masking interprocessor or intercluster communication by computation if k is much small than n. In the context of solving large scale least squares problems, this submatrix merging step is repetitively needed during the entire computation and, furthermore, there are usually many pairs of such submatrices to be merged with each submatrix stored in the memory of a processor or a cluster of processors. The proposed algorithm can be applied to each pair of submatrices concurrently, and thus parallelizes an important step in solving the least squares problems.

Chu, Eleanor↗

Single-Walled Carbon Nanotubes with Confined Chalcogens as the Catalysts and Electrodes for Oxygen Reduction Reaction in Fuel Cells

The goal of this project is to synthesize and characterize a new non-metal electro-catalyst for oxygen reduction reaction (ORR) for fuel cell applications. The intended catalyst is a composite material composed of sulfur chains encapsulated in narrow diameter single-walled carbon nanotubes (S@SWNTs). S@SWNTs were successfully synthesized through sulfur vapor infusion method, and validated with Raman spectroscopy. However, the electrochemical analysis on the ORR catalytic activity of S@SWNTs indicated that it had low ORR catalytic activity. Our theoretical study based on density functional theory (DFT) revealed that the poor oxygen adsorption (low binding energy) on the surface of S@SWNTs was the bottleneck of the entire catalytic reaction. The focus of the project was subsequently pivoted to the development of a new non-noble metal ORR catalyst that could provide durability in acidic electrolyte. The hypothesis was to encapsulate small iron (Fe) clusters in SWNTs (Fe@SWNTs) can provide ORR electro-catalytic activity and long durability in acidic environment. DFT-based computational studies were carried out to explore the feasibility of the Fe@SWNTs catalyst. The theoretical study indicated that Fe@SWNTs indeed could catalyze the ORR with lower theoretical overpotential than platinum (Pt). However, its weaker bonding energy with oxygen was the bottleneck of the overall reaction. On the other hand, Fe clusters (composed of 7 Fe atoms) encapsulated in nitrogen-doped SWNTs (Fe 7 @N 4 WSNTs) showed proper oxygen adsorption by the Fe cluster and low theoretical overpotential of ORR. Comparing to the Fe single atom catalyst on N-doped SWNTs (Fe-N 4 SWNTs), which is one the best non-noble metal ORR catalysts reported in the literature, the Fe 7 @N 4 WSNTs showed lower overpotential and better resistance to acidic environment. Fe encapsulated N-doped SWNTs were synthesized with ferrocene as the Fe precursors through vapor infusion method, and experimental validate is underway. This study theoretically demonstrated the feasibility of a new type of non-noble metal electro-catalyst for ORR that could have high catalytic activity and long durability.

08 HYDROGEN↗

Understanding the Existence of a Na 2 Dimer in a High-Spin State

The recent observation of a high-spin Na 2 dimer formed on the surface of liquid helium nanodroplets raises some fundamental questions, as the ground state of Na 2 is known to have zero spin. Is it protected against spontaneous dissociation? What is its binding energy and interatomic distance? Is it stable at a higher temperature? Using calculations based on density functional theory (with and without long-range interaction) and coupled cluster methods, CCSD(T), we show that the bonding in the high-spin Na 2 dimer is governed by van der Waals interaction with binding energy (bond length) varying between −0.030 eV (5.108 Å) and −0.192 eV (4.231 Å), depending on the computational method used. Thus, the experimental method used by Kresin and coworkers can be very useful to study larger metastable high-spin clusters such as Li 4 which was predicted in 1985 to have a tetrahedral structure carrying a magnetic moment of 2 μ B , while its ground state is planar and nonmagnetic.

Basis sets↗

Compute Server Performance Results

Parallel-vector supercomputers have been the workhorses of high performance computing. As expectations of future computing needs have risen faster than projected vector supercomputer performance, much work has been done investigating the feasibility of using Massively Parallel Processor systems as supercomputers. An even more recent development is the availability of high performance workstations which have the potential, when clustered together, to replace parallel-vector systems. We present a systematic comparison of floating point performance and price-performance for various compute server systems. A suite of highly vectorized programs was run on systems including traditional vector systems such as the Cray C90, and RISC workstations such as the IBM RS/6000 590 and the SGI R8000. The C90 system delivers 460 million floating point operations per second (FLOPS), the highest single processor rate of any vendor. However, if the price-performance ration (PPR) is considered to be most important, then the IBM and SGI processors are superior to the C90 processors. Even without code tuning, the IBM and SGI PPR's of 260 and 220 FLOPS per dollar exceed the C90 PPR of 160 FLOPS per dollar when running our highly vectorized suite,

Stockdale, I. E.↗

Boosting H I -Galaxy Cross-Clustering Signal through Higher-Order Cross-Correlations

After reionization, neutral hydrogen (${\rm H\, \small {I}}$) traces the large-scale structure (LSS) of the Universe, enabling ${\rm H\, \small {I}}$ intensity mapping (IM) to capture the LSS in 3D and constrain key cosmological parameters. We present a new framework utilizing higher-order cross-correlations to study ${\rm H\, \small {I}}$ clustering around galaxies, tested using real-space data from the IllustrisTNG300 simulation. This approach computes the joint distributions of k-nearest neighbor (kNN) optical galaxies and the ${\rm H\, \small {I}}$ brightness temperature field smoothed at relevant scales (the kNN-field framework), providing sensitivity to all higher-order cross-correlations, unlike two-point statistics. To simulate ${\rm H\, \small {I}}$ data from actual surveys, we add random thermal noise and apply a simple foreground cleaning model, filtering out Fourier modes of the brightness temperature field with k ∥ < k min,∥ . Under current levels of thermal noise and foreground cleaning, typical of a Canadian Hydrogen Intensity Mapping Experiment (CHIME)-like survey, the ${\rm H\, \small {I}}$-galaxy cross-correlation signal in our simulations, using the kNN-field framework, is detectable at >30σ across r = [3, 12] h –1 Mpc. In contrast, the detectability of the standard two-point correlation function (2PCF) over the same scales depends strongly on the foreground filter: a sharp k ∥ filter can spuriously boost detection to 8σ due to position-space ringing, whereas a less sharp filter yields no detection. Nonetheless, we conclude that kNN-field cross-correlations are robustly detectable across a broad range of foreground filtering and thermal noise conditions, suggesting their potential for enhanced constraining power over 2PCFs.

79 ASTRONOMY AND ASTROPHYSICS↗

Ionization potential of radium monofluoride

The ionization potential (IP) of radium monofluoride (RaF) was measured to be 4.969(2)[10] eV, revealing a relativistic enhancement in the series of alkaline earth monofluorides. The results are in agreement with a relativistic coupled-cluster prediction of 4.981(7) eV, incorporating up to quantum electrodynamics corrections. Using the same computational methodology, an improved calculation for the dissociation energy (𝐷 0 ) of 5.54(5) eV is presented. This confirms that RaF joins the group of diatomic molecules for which 𝐷 0 > IP, paving the way for precision control and interrogation of its Rydberg states.

Wilkins, S. G. [Massachusetts Inst. of Technology ↗

Using Apptainer in a Pilot-based Distributed Workload

GlideinWMS is a pilot and pressure-based workload manager for distributed scientific computing. Many experiments like CMS and Fermilab’s Neutrino experiments use it to provision elastic clusters for their analysis and simulations, split into close to a million concurrent jobs. Most user jobs require containers, and the pilots use Apptainer to set up the desired platform. For the pilots that run as regular batch jobs, Apptainer is safer, lighter, and easier to use than other containerization solutions. Many images used by the pilots are expanded SIF images distributed via the CernVM-FS: this combination is very efficient. At Fermilab, for example, we store on GitHub Dockerfiles that mimic the platform in the worker nodes of local clusters. GitHub workflows build and push the images to Docker Hub, and a service periodically pulls and converts them to the expanded SIF images in the CernVM-FS, so the scientists can find a familiar environment everywhere. Apptainer has also been used to run services inside the pilot jobs, like benchmarks that characterize the worker node being used, or a Triton Inference Server that allows sharing a GPU with all the jobs that run in parallel on a node.

Mambelli, Marco [Fermilab] (ORCID:0000000294892681↗

Be-10 and Al-26 contents of eucrites - Implications for production rates and exposure ages

This paper presents the Be-10 contents of 20 and the Al-26 contents of nine eucrites. Most have Be-10 production rates between 16 and 26 dpm/kg. The average value of 21.8 dpm/kg agrees to within 10 percent with the value expected and does not support the suggestion that the eucrites received an unusually low flux of cosmic rays during the last few million years. Measured Be-10 and Al-26 contents are consistent with semiempirical calculations of nuclear production rates. The Al-26 contents provide a basis for computing shielding-corrected Ar-38 exposure ages of eucrites which show little evidence for clustering. Relatively more eucrites than diogenites are younger than 20 Ma.

Aylmer, D.↗

Recursive Hierarchical Image Segmentation by Region Growing and Constrained Spectral Clustering

This paper describes an algorithm for hierarchical image segmentation (referred to as HSEG) and its recursive formulation (referred to as RHSEG). The HSEG algorithm is a hybrid of region growing and constrained spectral clustering that produces a hierarchical set of image segmentations based on detected convergence points. In the main, HSEG employs the hierarchical stepwise optimization (HS WO) approach to region growing, which seeks to produce segmentations that are more optimized than those produced by more classic approaches to region growing. In addition, HSEG optionally interjects between HSWO region growing iterations merges between spatially non-adjacent regions (i.e., spectrally based merging or clustering) constrained by a threshold derived from the previous HSWO region growing iteration. While the addition of constrained spectral clustering improves the segmentation results, especially for larger images, it also significantly increases HSEG's computational requirements. To counteract this, a computationally efficient recursive, divide-and-conquer, implementation of HSEG (RHSEG) has been devised and is described herein. Included in this description is special code that is required to avoid processing artifacts caused by RHSEG s recursive subdivision of the image data. Implementations for single processor and for multiple processor computer systems are described. Results with Landsat TM data are included comparing HSEG with classic region growing. Finally, an application to image information mining and knowledge discovery is discussed.

Tilton, James C.↗

High Speed Networking and Large-scale Simulation in Geodynamics

Large-scale numerical simulation has been one of the most important approaches for understanding global geodynamical processes. In this approach, peta-scale floating point operations (pflops) are often required to carry out a single physically-meaningful numerical experiment. For example, to model convective flow in the Earth's core and generation of the geomagnetic field (geodynamo), simulation for one magnetic free-decay time (approximately 15000 years) with a modest resolution of 150 in three spatial dimensions would require approximately 0.2 pflops. If such a numerical model is used to predict geomagnetic secular variation over decades and longer, with e.g. an ensemble Kalman filter assimilation approach, approximately 30 (and perhaps more) independent simulations of similar scales would be needed for one data assimilation analysis. Obviously, such a simulation would require an enormous computing resource that exceeds the capacity of a single facility currently available at our disposal. One solution is to utilize a very fast network (e.g. 10Gb optical networks) and available middleware (e.g. Globus Toolkit) to allocate available but often heterogeneous resources for such large-scale computing efforts. At NASA GSFC, we are experimenting with such an approach by networking several clusters for geomagnetic data assimilation research. We shall present our initial testing results in the meeting.

Kuang, Weijia↗

Research on Spectroscopy, Opacity, and Atmospheres

I propose to continue providing observers with basic data for interpreting spectra from stars, novas, supernovas, clusters, and galaxies. These data will include allowed and forbidden line lists, both laboratory and computed, for the first five to ten ions of all atoms and for all relevant diatomic molecules. I will eventually expand to all ions of the first thirty elements to treat far UV and X-ray spectra, and for envelope opacities. I also include triatomic molecules provided by other researchers. I have also made CDs with Partridge and Schwenke's water data for work on UV stars. The line data also serve as input to my model atmosphere and synthesis programs that generate energy distributions, photometry, limb darkening, and spectra that can be used for planning observations and for fitting observed spectra. The spectrum synthesis programs produce detailed plots with the lines identified. Grids of stellar spectra can be used for radial velocity-, rotation-, or abundance templates and for population synthesis. I am fitting spectra of bright stars to test the data and to produce atlases to guide observers. For each star the whole spectrum is computed from the UV to the far IR. The line data, opacities, models, spectra, and programs are freely distributed on CDs and on my Web site and represent a unique resource for many NASA programs. I am now in full production of new line lists for atoms. I am computing all ions of all elements from H to Zn and the first 5 ions of all the heavier elements, about 800 ions. For each ion I treat as many as 61 even and 61 odd configurations, computing all energy levels and eigenvectors. The Hamiltonian is determined from a scaled-Hartree-Fock starting guess by least squares fitting the observed energy levels. The average energy of each configuration is used in computing scaled-Thomas-Fermi-Dirac wavefunctions for each configuration which in turn are used to compute allowed and forbidden transition integrals. These are multiplied into the LS allowed and forbidden transition arrays. The transition arrays are transformed to the observed coupling to yield the allowed and forbidden line lists. Results are put on the web as they are finished. Provided I get funding,there will be more than 500 million lines. I will then compare ion by ion, to all the laboratory and computed data in the literature and make up a working line list for spectrum synthesis and opacity calculations with the best available data. As the laboratory spectrum analyses are improved, I will redo the calculations with the new energy levels. My original plan when I started the new calculations was to run through all the atoms using my old Cray programs from the 1980's that were limited to 1100 x 1100 arrays in the Hamiltonian for each J. Then I would go back and rerun the more complicated cases with 3000 x 3000 arrays so that I could include many more configurations and more configuration interactions. At present I am limited to 61 even and 61 odd configurations and I try to include everything up through n = 9. The current program runs on Alpha workstations. I decided to test the big program on Fe I and Fe II to see whether there was any great difference in the low configurations compared to those from the Cray program. Besides increasing the number of E1 lines by a factor of 6 to 7.7 million, there was an unexpected result: the electric quadrupole transitions were 10 times stronger than before because the transition integrals are weighted by r(exp 2) ---they become very large for high n, and because there are numerous configuration interactions that mix the low and high configurations. As a check I was able to reproduce Carstang's (1962) lower results by running his three configurations with my program. Since my model atom is still only a subset of a real Fe II ion, the true quadrupole A values are probably larger than mine. The magnetic dipole lines are affected by the mixing but the overall scale does not change. Because of this scovery I decided that there was no point in computing the small array cases. I have been running with as many configurations as I can and with thousands of parameters in the Hamiltonian. The computer runs take much longer to set up and produce than I had expected. I have concentrated on redoing the low iron group spectra, especially to get data for supernova modelers. I have done only Ca I -- Zn I, Ca II -- Zn II, CU I -- Cu XXIX, Zn I - Zn XXX, for practice at high stages of ionization, C I, C II, S I, and CL I and Ag I for people who were working on the laboratory spectra. Check my web site kurucz.harvard.edu for current additions. My latest calculations have been for carbon I and sulphur I, and silicon I is under way using the same elaborate approach as for C I, which took many months to do. These line lists greatly increase the number of lines in the ultraviolet, in the visible, and especially in the infrared. They will increase the opacity in A, F, and G stars. They will account for many unidentified lines in the sun.

Kurucz, Robert L.↗

Onboard Algorithms for Data Prioritization and Summarization of Aerial Imagery

Many current and future NASA missions are capable of collecting enormous amounts of data, of which only a small portion can be transmitted to Earth. Communications are limited due to distance, visibility constraints, and competing mission downlinks. Long missions and high-resolution, multispectral imaging devices easily produce data exceeding the available bandwidth. To address this situation computationally efficient algorithms were developed for analyzing science imagery onboard the spacecraft. These algorithms autonomously cluster the data into classes of similar imagery, enabling selective downlink of representatives of each class, and a map classifying the terrain imaged rather than the full dataset, reducing the volume of the downlinked data. A range of approaches was examined, including k-means clustering using image features based on color, texture, temporal, and spatial arrangement

Chien, Steve A.↗

Qualitative mechanism models and the rationalization of procedures

A qualitative, cluster-based approach to the representation of hydraulic systems is described and its potential for generating and explaining procedures is demonstrated. Many ideas are formalized and implemented as part of an interactive, computer-based system. The system allows for designing, displaying, and reasoning about hydraulic systems. The interactive system has an interface consisting of three windows: a design/control window, a cluster window, and a diagnosis/plan window. A qualitative mechanism model for the ORS (Orbital Refueling System) is presented to coordinate with ongoing research on this system being conducted at NASA Ames Research Center.

Farley, Arthur M.↗

Force-Free Identification of Minimum-Energy Pathways and Transition States for Stochastic Electronic Structure Theories

Here, the accurate mapping of potential energy surfaces (PESs) is crucial to our understanding of the numerous physical and chemical processes mediated by atomic rearrangements, such as conformational changes and chemical reactions, and the thermodynamic and kinetic feasibility of these processes. Stochastic electronic structure theories, e.g., Quantum Monte Carlo (QMC) methods, enable highly accurate total energy calculations that in principle can be used to construct the PES. However, their stochastic nature poses a challenge to the computation and use of forces and Hessians, which are typically required in algorithms for minimum-energy pathway (MEP) and transition state (TS) identification, such as the nudged elastic band (NEB) algorithm and its climbing image formulation. Here, we present strategies that utilize the surrogate Hessian line-search method, previously developed for QMC structural optimization, to efficiently identify MEP and TS structures without requiring force calculations at the level of the stochastic electronic structure theory. By modifying the surrogate Hessian algorithm to operate in path-orthogonal subspaces and at saddle points, we show that it is possible to identify MEPs and TSs by using a force-free QMC approach. We demonstrate these strategies via two examples, the inversion of the ammonia (NH 3 ) molecule and the nucleophilic substitution (S N 2) reaction F – + CH 3 F → FCH 3 + F – . We validate our results using Density Functional Theory (DFT)- and Coupled Cluster (CCSD, CCSD(T))-based NEB calculations. We then introduce a hybrid DFT-QMC approach to compute thermodynamic and kinetic quantities, free energy differences, rate constants, and equilibrium constants that incorporates stochastically optimized structures and their energies, and show that this scheme improves upon DFT accuracy. Our methods generalize straightforwardly to other systems and other high-accuracy theories that similarly face challenges computing energy gradients, paving the way for highly accurate PES mapping, transition state determination, and thermodynamic and kinetic calculations at significantly reduced computational expense.

Iyer, Gopal R.↗