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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

A new ATLAS muon CSC readout system with system on chip technology on ATCA platform

The ATLAS muon Cathode Strip Chamber (CSC) backend readout system has been upgraded during the LHC 2013-2015 shutdown to be able to handle the higher Level-1 trigger rate of 100 kHz and the higher occupancy at Run-2 luminosity. The readout design is based on the Reconfigurable Cluster Element (RCE) concept for high bandwidth generic DAQ implemented on the Advanced Telecommunication Computing Architecture (ATCA) platform. The RCE design is based on the new System on Chip XILINX ZYNQ series with a processor-centric architecture with ARM processor embedded in FPGA fabric and high speed I/O resources. Together with auxiliary memories, all of these components form a versatile DAQ building block that can host applications tapping into both software and firmware resources. The Cluster on Board (COB) ATCA carrier hosts RCE mezzanines and an embedded Fulcrum network switch to form an online DAQ processing cluster. More compact firmware solutions on the ZYNQ for high speed input and output fiberoptic links and TTC allowed the full system of 320 input links from the 32 chambers to be processed by 6 COBs in one ATCA shelf. The full system was installed in September 2014. In conclusion, we will present the RCE/COB design concept, the firmware and software processing architecture, and the experience from the intense commissioning for LHC Run 2.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Th 2 O – , Th 2 Au – , and Th 2 AuO 1,2 – Anions: Photoelectron Spectroscopic and Computational Characterization of Energetics and Bonding

The observation and characterization of the anions: Th 2 O – , Th 2 Au – , and Th 2 AuO 1,2 – is reported. These species were studied through a synergetic combination of anion photoelectron spectroscopy and ab initio correlated molecular orbital theory calculations at the CCSD(T) level with large correlation-consistent basis sets. To better understand the energetics and bonding in these anions and their corresponding neutrals, a range of smaller diatomic to tetratomic species were studied computationally. Correlated molecular orbital theory calculations at the CCSD(T) level showed that in most of these cases, there are close-lying anions and neutral clusters with different geometries and spin states and are consistent with the experimentally observed spectra. Thus, comparison of experimentally determined and computationally predicted vertical detachment energies and electron affinities for different optimized geometries and spin states shows excellent agreement to within 0.1 eV. The structures for both the neutrals and anions have a significant ionic component to the bonding because of the large electron affinity of the Au atom and modest ionization potentials for Th 2 , Th 2 O, and Th 2 O 2 . The analysis of the bonding for the Th–Th bonds from the molecular orbitals is consistent with this ionic model. The results show that there is a wide variation in the bond distance from 2.7 to 3.5 Å for the Th–Th bonds all of which are less than twice the atomic radius of Th of 3.6 Å. The bond distances encompass bond orders from 4 to 0. Furthermore, there can be different bond orders for the same bond distance depending on the nature of the ionic bonding suggesting that one may not be able to correlate the bond order with the bond distance in these types of clusters. In addition, the presence of an Au atom may provide a unique probe of the bonding in such clusters because of its ability to accept an electron from clusters with modest ionization potentials.

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

Enabling Efficient and Accurate Computational Studies of MOF Reactivity via QM/MM and QM/QM Methods

Electronic structure calculations can provide unique insight into metal–organic framework (MOF) reactivity and defect formation. Such calculations can be broadly categorized as utilizing either periodic or cluster models, each with their respective advantages and disadvantages. In the present study, we demonstrate how multiscale methods can leverage the advantages of both approaches to enable high levels of accuracy and computational efficiency in studies of MOF reactivity. Using defect formation in a zeolitic imidazolate framework (ZIF) as a prototypical example, we benchmark a quantum mechanics/molecular mechanics (QM/MM) scheme that enables highly efficient cluster-based calculations on MOFs. We demonstrate the importance of correctly accounting for the influence of both dative bond cleavage in the QM cluster and long-range mechanical coupling to the bulk to achieving accurate QM/MM studies of MOFs. We subsequently leverage these cluster models in a QM/QM scheme that goes beyond standard DFT to yield “gold-standard” correlated wave function results on MOFs at modest computational cost. Crucially, we find several cases in which the incorporation of these correlated corrections yields qualitatively important corrections over conventional DFT values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Aces4: A Platform for Computational Chemistry Calculations with Extremely Large Block-Sparse Arrays

Aces4 is a parallel programming platform comprising a DSL for Computational Chemistry and its runtime system. It offers a convenient way to express parallelism together with extensive support for extremely large, possibly sparse, distributed arrays. It aids scientists in the creation of performant, scalable, massively parallel programs that can effectively take advantage of leadership class computing systems to address important scientific questions. Aces4 has enabled the development and implementation of new methods in electronic structure theory which are breaking new ground in their ability to perform highly accurate calculations on ever larger molecular systems. In this paper the design of Aces4, which is based on the the Super Instruction Architecture approach, is described. Experimental scaling results for Molecular Cluster Perturbation Theory, a new method enabled by Aces4, and CCSD, a widely used computational chemistry method are given.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Reliable prediction of three-body intermolecular interactions using dispersion-corrected second-order Møller-Plesset perturbation theory

Three-body and higher intermolecular interactions can play an important role in molecular condensed phases. Recent benchmark calculations found problematic behavior for many widely used density functional approximations in treating 3-body intermolecular interactions. Here, we demonstrate that the combination of second-order Møller-Plesset (MP2) perturbation theory plus short-range damped Axilrod-Teller-Muto (ATM) dispersion accurately describes 3-body interactions with reasonable computational cost. The empirical damping function used in the ATM dispersion term compensates both for the absence of higher-order dispersion contributions beyond the triple-dipole ATM term and non-additive short-range exchange terms which arise in third-order perturbation theory and beyond. Empirical damping enables this simple model to out-perform a non-expanded coupled Kohn-Sham dispersion correction for 3-body intermolecular dispersion. The MP2 plus ATM dispersion model approaches the accuracy of O(N{sup 6}) methods like MP2.5 or even spin-component-scaled coupled cluster models for 3-body intermolecular interactions with only O(N{sup 5}) computational cost.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2015

The GRISM Lens-Amplified Survey from Space (GLASS). I. Survey overview and first data release

We give an overview of the Grism Lens Amplified Survey from Space (GLASS), a large Hubble Space Telescope program aimed at obtaining grism spectroscopy of the fields of 10 massive clusters of galaxies at redshift z = 0.308–0.686, including the Hubble Frontier Fields (HFF). The Wide Field Camera 3 (WFC3) yields near-infrared spectra of the cluster cores covering the wavelength range 0.81–1.69 μm through grisms G102 and G141, while the Advanced Camera for Surveys in parallel mode provides G800L spectra of the infall regions of the clusters. The WFC3 spectra are taken at two almost orthogonal position angles in order to minimize the effects of confusion. After summarizing the scientific drivers of GLASS, we describe the sample selection as well as the observing strategy and data processing pipeline. We then utilize MACS J0717.5+3745, a HFF cluster and the first one observed by GLASS, to illustrate the data quality and the high-level data products. Each spectrum brighter than H{sub AB}=23 is visually inspected by at least two co-authors and a redshift is measured when sufficient information is present in the spectra. Furthermore, we conducted a thorough search for emission lines through all of the GLASS WFC3 spectra with the aim of measuring redshifts for sources with continuum fainter than H{sub AB}=23. We provide a catalog of 139 emission-line-based spectroscopic redshifts for extragalactic sources, including three new redshifts of multiple image systems (one probable, two tentative). In addition to the data itself, we also release software tools that are helpful to navigate the data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

SpaRC: scalable sequence clustering using Apache Spark

MOTIVATION: Whole genome shotgun based next-generation transcriptomics and metagenomics studies often generate 100-1000 GB sequence data derived from tens of thousands of different genes or microbial species. Assembly of these data sets requires tradeoffs between scalability and accuracy. Current assembly methods optimized for scalability often sacrifice accuracy and vice versa. An ideal solution would both scale and produce optimal accuracy for individual genes or genomes. RESULTS: In this work we describe an Apache Spark-based scalable sequence clustering application, SparkReadClust (SpaRC), that partitions reads based on their molecule of origin to enable downstream assembly optimization. SpaRC produces high clustering performance on transcriptomes and metagenomes from both short and long read sequencing technologies. It reaches near-linear scalability with input data size and number of compute nodes. SpaRC can run on both cloud computing and HPC environments without modification while delivering similar performance. Our findings demonstrate that SpaRC provides a scalable solution for clustering billions of reads from next-generation sequencing experiments, and Apache Spark represents a cost-effective solution with rapid development/deployment cycles for similar large-scale sequence data analysis problems. AVAILABILITY AND IMPLEMENTATION: https://bitbucket.org/berkeleylab/jgi-sparc.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

PyCCE: A python package for custer correlation expansion simulations of spin qubit dynamics.

PyCCE, an open-source Python library for simulating the dynamics of spin qubits in a spin bath, is presented using the cluster-correlation expansion (CCE) method. PyCCE includes modules to generate realistic spin baths, employing coupling parameters computed from first principles with electronic structure codes, and enables the user to run simulations with either the conventional or generalized CCE method. Three use cases of the Python library are illustrated: the calculation of the Hahn-echo coherence time of the nitrogen-vacancy in diamond; the calculation of the coherence time of the basal divacancy in silicon carbide at avoided crossings; and the calculation for magnetic field orientation-dependent dynamics of a shallow donor in silicon. The complete documentation, downloadable tutorials, and installation instructions are available at https://pycce.readthedocs.io/en/latest/.

coherence↗
DOE OSTI2026

Direct CO 2 Reduction to CO with an Fe 4 S 4 -Based Coordination Polymer

Fe 4 S 4 clusters play essential roles in nature, classically in electron transport but increasingly in newly discovered reactivity or catalysis. These roles have spurred interest in developing synthetic Fe 4 S 4 systems and while several molecular and material systems built from Fe 4 S 4 clusters have been developed, comparatively few examples of synthetic Fe 4 S 4 cluster-based catalysts exist. Herein, we present the use of an Fe 4 S 4 -based coordination polymer as a catalyst for the direct and selective electroreduction of CO 2 to CO. Computational studies suggest that the reaction proceeds through CO 2 binding to a reduced Fe 4 S 4 cluster, followed by a series of protonation, reduction, and H 2 O loss steps to yield a CO-bound cluster that can finally exchange with CO 2 to restart the catalytic cycle. CO bound clusters are predicted to be thermodynamically stable, suggesting that carbonyl species might be off-cycle intermediates. Mechanistic CV studies as well as in situ studies by IR spectroscopy provide evidence for carbonyl-ligated clusters, supporting these compounds as unusual examples of small molecule binding to Fe 4 S 4 clusters. Finally, this work establishes Fe 4 S 4 cluster-based coordination polymers as direct electrocatalysts for CO 2 reduction and provides mechanistic insights into how these species mediate catalytic conversions of small molecules.

cluster chemistry↗
DOE OSTI2013

Optical absorption in B{sub 13} cluster: A time-dependent density functional approach

The linear optical absorption spectra of three isomers of planar boron cluster B{sub 13} are calculated using time-dependent spin-polarized density functional approach. The geometries of these cluster are optimized at the B3LYP/6-311+G* level of theory. Even though the isomers are almost degenerate, the calculated spectra are quite different, indicating a strong structure-property relationship. Therefore, these computed spectra can be used in the photo-absorption experiments to distinguish between different isomers of a cluster.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Modeling investigation of the stability and irradiation-induced evolution of nanoscale precipitates in advanced structural materials

Materials used in extremely hostile environment such as nuclear reactors are subject to a high flux of neutron irradiation, and thus vast concentrations of vacancy and interstitial point defects are produced because of collisions of energetic neutrons with host lattice atoms. The fate of these defects depends on various reaction mechanisms which occur immediately following the displacement cascade evolution and during the longer-time kinetically dominated evolution such as annihilation, recombination, clustering or trapping at sinks of vacancies, interstitials and their clusters. The long-range diffusional transport and evolution of point defects and self-defect clusters drive a microstructural and microchemical evolution that are known to produce degradation of mechanical properties including the creep rate, yield strength, ductility, or fracture toughness, and correspondingly affect material serviceability and lifetimes in nuclear applications. Therefore, a detailed understanding of microstructural evolution in materials at different time and length scales is of significant importance. The primary objective of this work is to utilize a hierarchical computational modeling approach i) to evaluate the potential for nanoscale precipitates to enhance point defect recombination rates and thereby the self-healing ability of advanced structural materials, and ii) to evaluate the stability and irradiation-induced evolution of such nanoscale precipitates resulting from enhanced point defect transport to and annihilation at precipitate interfaces. This project will utilize, and as necessary develop, computational materials modeling techniques within a hierarchical computational modeling approach, principally including molecular dynamics, kinetic Monte Carlo and spatially-dependent cluster dynamics modeling, to identify and understand the most important physical processes relevant to promoting the “selfhealing” or radiation resistance in advanced materials containing nanoscale precipitates. In particular, the interfacial structure of embedded nanoscale precipitates will be evaluated by electronic- and atomic-scale modeling methods, and the efficiency of the validated interfaces for trapping point defects will next be evaluated by atomic-scale modeling (e.g., determining the sink strength of the precipitates), addressing key questions related to the optimal interface characteristics to attract point defects and enhance their recombination. Kinetic models will also be developed to simulate microstructural evolution of the nanoscale features and irradiation produced defect clusters, and compared with observed microstructural changes.

36 MATERIALS SCIENCE↗
DOE OSTI2023

G 0 W 0 Ionization Potentials of First-Row Transition Metal Aqua Ions

Here, we report computations of the vertical ionization potentials within the GW approximation of the near-complete series of first-row transition metal (V–Cu) aqua ions in their most common oxidation states, i.e., V 3+ , Cr 3+ , Cr 2+ , Mn 2+ , Fe 3+ , Fe 2+ , Co 2+ , Ni 2+ , and Cu 2+ . The d-orbital occupancy of these systems spans a broad range from d 2 to d 9 . All of the structures were first optimized at the density functional theory level using a large cluster of explicit water molecules that are embedded in a continuum solvation model. Vertical ionization potentials were computed with the one-shot G 0 W 0 approach on a range of transition metal ion clusters (6, 18, 40, and 60 explicit water molecules), wherein the convergence with respect to the basis set size was evaluated using the systems with 40 water molecules. We assess the results using three different density functional approximations as starting points for the vertical ionization potential calculations, namely, G 0 W 0 @PBE, G 0 W 0 @PBE0, and G 0 W 0 @r 2 SCAN. While the predicted ground-state structures are similar to all three exchange-correlation functionals, the vertical ionization potentials were in closer agreement with experiment when using the G 0 W 0 @PBE0 and G 0 W 0 @r 2 SCAN approaches, with the r 2 SCAN-based calculations being significantly less expensive. Computed bond distances and vertical ionization potentials for all structures are in good agreement with available experimental data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Elucidating the geometric and electronic structure of a fully sulfided analog of an Anderson polyoxomolybdate cluster

The catalytic activity of transition metal sulfide (TMS) clusters in small molecule activation, redox transformations, and charge transfer has inspired the design of novel TMS-based materials for energy-related catalysis and chemical applications. Polyoxometalates (POMs), known for their structural diversity, can in principle be transformed into TMS clusters; however, fully sulfided analogs are rarely isolated, likely due to the strong tendency of uncapped TMS clusters to agglomerate. Here, we report the geometric and electronic structure of a capping ligand-free fully sulfided analog of heptamolybdate Anderson POM [Mo VI 7 O 24 ] 6− , synthesized through the sulfidation of a nanoconfined POM secured within a porous Zr-metal organic framework (NU-1000). A combined computational and experimental analysis indicates that the sulfided counterpart of the Anderson POM is geometrically and electronically more sophisticated than the parent POM. Comparison of experimental pair distribution function (PDF) data with computational simulations confirms that, unlike the oxygen-only [Mo VI 7 O 24 ] 6− cluster, the [Mo IV 7 (μ 3 -S) 6 (μ 2 -SH) 6 (S 2 ) 6 ] 2− polythiometalate (PTM) exhibits diverse sulfur anions (S 2− , HS − , S 2 2− ). DFT calculations indicate that H 2 S acts as a reducing agent, and together with terminal disulfide (S 2 2− ) ligands in the PTM structure, facilitates the complete reduction of all seven Mo VI centers in the parent POM to Mo IV . These findings are supported by X-ray photoelectron spectroscopy (XPS), which confirms exclusive Mo IV , and elemental analysis, which shows quantitative sulfur incorporation. Difference envelope density (DED) mapping further reveals that the PTM clusters are spatially confined within the MOF pores, preventing agglomeration and preserving molecular integrity.

Rabbani, S. M. Gulam [The Ohio State University, C↗
DOE OSTI2019

Direct diabatization and analytic representation of coupled potential energy surfaces and couplings for the reactive quenching of the excited 2 Σ + state of OH by molecular hydrogen

In this work, we have employed extended multiconfiguration quasidegenerate perturbation theory, fourfold-way diabatic molecular orbitals, and configurational uniformity to develop a global three-state diabatic representation of the potential energy surfaces and their couplings for the electronically nonadiabatic reaction OH* + H 2 → H 2 O + H, where * denotes electronic excitation to the A 2 Σ + state. To achieve sign consistency of the computed diabatic couplings, we developed a graphics processing unit-accelerated algorithm called the cluster-growing algorithm. Having obtained consistent signs of the diabatic couplings, we fit the diabatic matrix elements (which consist of the diabatic potentials and the diabatic couplings) to analytic representations. Adiabatic potential energy surfaces are generated by diagonalizing the 3 × 3 diabatic potential energy matrix. The comparisons between the fitted and computed diabatic matrix elements and between the originally computed adiabatic potential energy surfaces and those generated from the fits indicate that the current fit is accurate enough for dynamical studies, and it may be used for quantal or semiclassical dynamics calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Avoiding excess computation in asynchronous evolutionary algorithms

Abstract Asynchronous evolutionary algorithms are becoming increasingly popular as a means of making full use of many processors while solving computationally expensive search and optimization problems. These algorithms excel at keeping large clusters fully utilized, but may sometimes inefficiently sample an excess of fast‐evaluating solutions at the expense of higher‐quality, slow‐evaluating ones. We have previously introduced a steady‐state parent selection strategy, SWEET (“Selection whilE EvaluaTing”), that sometimes selects individuals that are still being evaluated and allows them to reproduce early. We perform a takeover‐time analysis that confirms that this strategy gives slow‐evaluating individuals that have higher fitnesses an increased ability to multiply in the population. We also find that SWEET appears effective at improving optimization performance on problems in which solution quality is positively correlated with evaluation time. We evaluate our approach on six simulated real‐valued optimization problems and three real‐world applications: an autonomous vehicle controller problem that involves tuning a spiking neural network and two adversarial EA problems. We further evaluate SWEET versus a basic asynchronous process in a simulated setting. We present evidence that SWEET outperforms basic asynchronous processes in a use‐case in which performance is positively correlated with evaluation time, and performs comparably (and often better) than basic asynchronous processes in several use‐cases where performance is negatively correlated with evaluation time. That said, in the cases where performance and evaluation time are negatively correlated the variance of outcomes for SWEET is notably high.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Improving computational efficiency of Monte Carlo simulations with variance reduction

CCFE perform Monte-Carlo transport simulations on large and complex tokamak models such as ITER. Such simulations are challenging since streaming and deep penetration effects are equally important. In order to make such simulations tractable, both variance reduction (VR) techniques and parallel computing are used. It has been found that the application of VR techniques in such models significantly reduces the efficiency of parallel computation due to 'long histories'. VR in MCNP can be accomplished using energy-dependent weight windows. The weight window represents an 'average behaviour' of particles, and large deviations in the arriving weight of a particle give rise to extreme amounts of splitting being performed and a long history. When running on parallel clusters, a long history can have a detrimental effect on the parallel efficiency - if one process is computing the long history, the other CPUs complete their batch of histories and wait idle. Furthermore some long histories have been found to be effectively intractable. To combat this effect, CCFE has developed an adaptation of MCNP which dynamically adjusts the WW where a large weight deviation is encountered. The method effectively 'de-optimises' the WW, reducing the VR performance but this is offset by a significant increase in parallel efficiency. Testing with a simple geometry has shown the method does not bias the result. This 'long history method' has enabled CCFE to significantly improve the performance of MCNP calculations for ITER on parallel clusters, and will be beneficial for any geometry combining streaming and deep penetration effects. (authors)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Comparative Study of Clustering Techniques for Real-Time Dynamic Model Reduction

Dynamic model reduction in power systems is necessary for improving computational efficiency. Traditional model reduction using linearized models or offline analysis would not be adequate to capture power system dynamic behaviors, especially the new mix of intermittent generation and intelligent consumption makes the power system more dynamic and non-linear. Real time dynamic model reduction emerges as an important need. This paper explores the use of clustering techniques to analyze real-time phasor measurements to determine generator groups and representative generators for dynamic model reduction. Two clustering techniques – graph clustering and evolutionary clustering – are studied in this paper. Various implementations of these techniques are compared and also compared with a previously developed Singular Value Decomposition (SVD)-based dynamic model reduction approach. Various methods exhibit different levels of accuracy when comparing the reduced model simulation against the original model. But some of them are consistently accurate. From this comparative perspective, this paper provides a good reference point for practical implementations.

model reduction, graph clustering, svd, evolutiona↗