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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Size- and temperature-dependent magnetization of iron nanoclusters

In this paper, the magnetic behavior of bcc iron nanoclusters, with diameters between 2 and 8 nm, is investigated by means of spin dynamics simulations coupled to molecular dynamics, using a distance-dependent exchange interaction. Finite-size effects in the total magnetization as well as the influence of the free surface and the surface/core proportion of the nanoclusters are analyzed in detail for a wide temperature range, going beyond the cluster and bulk Curie temperatures. Comparison is made with experimental data and with theoretical models based on the mean-field Ising model adapted to small clusters, and taking into account the influence of low coordinated spins at free surfaces. Our results for the temperature dependence of the average magnetization per atom M (T), including the thermalization of the transnational lattice degrees of freedom, are in very good agreement with available experimental measurements on small Fe nanoclusters. In contrast, significant discrepancies with experiment are observed if the translational degrees of freedom are artificially frozen. The finite-size effects on M (T) are found to be particularly important near the cluster Curie temperature. Simulated magnetization above the Curie temperature scales with cluster size as predicted by models assuming short-range magnetic ordering. Analytical approximations to the magnetization as a function of temperature and size are proposed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

MEASUREMENT OF GALAXY CLUSTER INTEGRATED COMPTONIZATION AND MASS SCALING RELATIONS WITH THE SOUTH POLE TELESCOPE

We describe a method for measuring the integrated Comptonization (Y {sub SZ}) of clusters of galaxies from measurements of the Sunyaev-Zel'dovich (SZ) effect in multiple frequency bands and use this method to characterize a sample of galaxy clusters detected in the South Pole Telescope (SPT) data. We use a Markov Chain Monte Carlo method to fit a β-model source profile and integrate Y {sub SZ} within an angular aperture on the sky. In simulated observations of an SPT-like survey that include cosmic microwave background anisotropy, point sources, and atmospheric and instrumental noise at typical SPT-SZ survey levels, we show that we can accurately recover β-model parameters for inputted clusters. We measure Y {sub SZ} for simulated semi-analytic clusters and find that Y {sub SZ} is most accurately determined in an angular aperture comparable to the SPT beam size. We demonstrate the utility of this method to measure Y {sub SZ} and to constrain mass scaling relations using X-ray mass estimates for a sample of 18 galaxy clusters from the SPT-SZ survey. Measuring Y {sub SZ} within a 0.'75 radius aperture, we find an intrinsic log-normal scatter of 21% ± 11% in Y {sub SZ} at a fixed mass. Measuring Y {sub SZ} within a 0.3 Mpc projected radius (equivalent to 0.'75 at the survey median redshift z = 0.6), we find a scatter of 26% ± 9%. Prior to this study, the SPT observable found to have the lowest scatter with mass was cluster detection significance. We demonstrate, from both simulations and SPT observed clusters that Y {sub SZ} measured within an aperture comparable to the SPT beam size is equivalent, in terms of scatter with cluster mass, to SPT cluster detection significance.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Modelling electron transfer in photosystem I: limits and perspectives

Uncovering the parameters underlying the electron transfer (ET) in photosynthetic reaction centres is of importance for understanding the molecular mechanisms underpinning their functionality. The reductive nature of most cofactors involved in photosynthetic ET makes the direct estimation of their properties difficult. Photosystem I (PSI) operates in a highly reducing regime, making the assessment of cofactor properties even more difficult. Kinetic modelling coupled to a non-adiabatic description of ET is a useful approach in overcoming this hindrance. Here we review the theory and modelling approaches that have been used in assessing parameters associated with ET reactions in PSI, with particular attention to ET reactions involving the phylloquinones and the iron–sulphur clusters. In most modelling studies, the goal is to estimate the driving force of ET, which is usually associated with the cofactor midpoint potentials. The driving force is sensitive to many factors, which define the ET rate, i.e. the reorganisation energy, the coupling with nuclear modes and the electronic matrix elements, which are explored and discussed here. The importance of an inclusive modelling of both forward and reverse ET processes is discussed and highlighted. It is shown that although estimates are indeed sensitive to the exact parameter sets employed in the modelling, a general consensus is still attained, pointing to a scenario where $ΔG^0_{A_{tA→Fx}}/ΔG^0_{A_{tB→Fx}}$ is weakly endergonic/exergonic, respectively. It is emphasised that to further refine those estimates, it will require a joint effort between computational modelling and more wide-ranging experimental studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Recent Advances on Computational Modeling of Supported Single-Atom and Cluster Catalysts: Characterization, Catalyst–Support Interaction, and Active Site Heterogeneity

To satisfy the need for catalyst materials with high activity, selectivity, and stability for energy conversion, material design and discovery guided by theoretical insights are a necessity. In the past decades, the rise in theoretical investigations into the properties of catalyst materials, reaction mechanisms, and catalyst design principles has shed light on the catalysis field. Quantitative structure–activity relationships have been developed through incorporating spectroscopic simulations, electronic structure calculations, and reaction mechanistic studies. Here, in this review, we report the state-of-the-art computational approaches to catalyst materials characterization for supported single-atom and cluster catalysts utilizing spectroscopic simulations, i.e., XANES simulation, and material properties investigation via electronic-structure calculations. Furthermore, approaches regarding reaction mechanisms, focusing on active site heterogeneity, are also discussed.

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

Microstructural characterization of Mg-based bulk metallic glass and nanocomposite

New magnesium-based bulk metallic glasses Mg{sub 60}Cu{sub 30}Y{sub 10} have been prepared by pressure casting. Glassy alloys were successfully annealed to become nanocomposite containing 200 nm crystallites in an amorphous matrix. The microstructure of bulk glassy alloy and nanocomposite obtained during heat treatment was examined by X-ray diffraction and scanning and high-resolution electron microscopy. Metallic glass has been also studied to explain the structural characteristics by the reverse Monte Carlo (RMC) modeling based on the diffraction data. The HRTEM images allow to indicate some medium-range order (MRO) regions about 2–3 nm in size and formation of local atomic clusters. The RMC modeling results confirmed some kinds of short range order (SRO) structures. It was found that the structure of bulk metallic glass formed by the pressure casting is homogeneous. The composite material contained very small particles in the amorphous matrix. Homogeneous glassy alloy had better corrosion resistance than a composite containing nanocrystalline particles in a glassy matrix. - Highlights: • RMC modeling demonstrates some kinds of SRO structures in Mg-based BMGs. • HRTEM indicated MRO regions about 2–3 nm and SRO regions about 0.5 nm in size. • Mg-based glassy alloys were successfully annealed to become nanocomposite material. • Crystalline particles have spherical morphology with an average diameter of 200 nm. • Glassy alloy had higher corrosion resistance than a nanocomposite sample.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Cosmological constraints from galaxy clusters in the 2500 square-degree SPT-SZ survey

We present cosmological parameter constraints obtained from galaxy clusters identified by their Sunyaev–Zel’dovich effect signature in the 2500 square-degree South Pole Telescope Sunyaev Zel’dovich (SPT-SZ) survey. We consider the 377 cluster candidates identified at z>0.25 with a detection significance greater than five, corresponding to the 95% purity threshold for the survey. We compute constraints on cosmological models using the measured cluster abundance as a function of mass and redshift. We include additional constraints from multi-wavelength observations, including Chandra X-ray data for 82 clusters and a weak lensing-based prior on the normalization of the mass-observable scaling relations. Assuming a spatially flat ΛCDM cosmology, we combine the cluster data with a prior on H {sub 0} and find σ{sub 8}=0.784±0.039 and Ω{sub m}=0.289±0.042, with the parameter combination σ{sub 8}(Ω{sub m}/0.27){sup 0.3}=0.797±0.031. These results are in good agreement with constraints from the cosmic microwave background (CMB) from SPT, WMAP, and Planck, as well as with constraints from other cluster data sets. We also consider several extensions to ΛCDM, including models in which the equation of state of dark energy w, the species-summed neutrino mass, and/or the effective number of relativistic species (N{sub eff}) are free parameters. When combined with constraints from the Planck CMB, H {sub 0}, baryon acoustic oscillation, and SNe, adding the SPT cluster data improves the w constraint by 14%, to w=−1.023±0.042.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Non-dilute helium-related defect interactions in the near-surface region of plasma-exposed tungsten

We report a systematic energetic analysis of helium-related defect interactions that mediate helium (He) segregation on surfaces of plasma-exposed tungsten at different levels of He ion implantation. We focus on high He fluences that increase the He content in the plasma-exposed material well beyond the dilute limit of He concentration and employ atomic configurations generated by large-scale molecular dynamics simulations of He-implanted tungsten. We perform systematic molecular statics computations of cluster– defect interaction energetics in the highly defect-rich near-surface region of plasma-exposed tungsten for small mobile helium clusters as a function of the cluster distance from the surface. In this region, mobile clusters are also subjected to the stress fields generated by defects such as helium bubbles and other clusters, which govern cluster–defect interactions in addition to the cluster–surface interaction. Based on systematic investigation of individual cluster–defect interactions, we develop a mathematical framework to describe the interaction energy landscapes consisting of elastic interaction potential perturbations to finite-width square-well potentials, where the potential well accounts for cluster trapping by the defect at close range and subsequent coalescence and the perturbation potential is parameterized according to elastic inclusion theory. Superposition of all the relevant interaction potentials provides a comprehensive description of the interaction energy landscape that would be experienced by a small mobile cluster along its migration path toward the plasma-exposed surface at high He fluence. Such descriptions are particularly important for developing atomistically-informed, hierarchical multi-scale models of helium cluster dynamics in plasma-facing materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Development of multi-scale computational frameworks to solve fusion materials science challenges

Over the past two decades, the US-DOE has funded multiple projects that rely on high-performance computing and exascale computing platforms to accelerate scientific discoveries and address grand scientific challenges, such as harnessing fusion energy. In this article, we review in detail one of these efforts aimed at enhancing our capability to model plasma-facing materials subject to plasma and high-energy ion/neutron irradiation. The plasma surface interactions project has built a multi-scale modeling framework where many of the plasma- and high-energy ion/neutron irradiation-induced effects occurring in tungsten are explored. Here, this knowledge is used to develop atomistically-informed, high-fidelity continuum and meso-scale models that can be validated against experiments. We review the developments within this project, with attention to experimental validation efforts, and specifically highlight activities associated with: helium bubble bursting and equation of state, and hydrogen-helium interactions in tungsten; atomistically-informed model development for beryllium-tungsten material mixing; coupling of scrape-of-layer plasma, sheath and material models; and coupling of stochastic cluster-dynamics and crystal plasticity models to address radiation effects in tungsten under stress. Finally, we present how the project is preparing for future computational architectures, for instance through efforts to adapt atomistic methods to exascale computing.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Phase Diagrams of Alloys and Their Hydrides via On-Lattice Graph Neural Networks and Limited Training Data

Efficient prediction of sampling-intensive thermodynamic properties is needed to evaluate material performance and permit high-throughput materials modeling for a diverse array of technology applications. To alleviate the prohibitive computational expense of high-throughput configurational sampling with density functional theory (DFT), surrogate modeling strategies like cluster expansion are many orders of magnitude more efficient but can be difficult to construct in systems with high compositional complexity. We therefore employ minimal-complexity graph neural network models that accurately predict and can even extrapolate to out-of-train distribution formation energies of DFT-relaxed structures from an ideal (unrelaxed) crystallographic representation. This enables the large-scale sampling necessary for various thermodynamic property predictions that may otherwise be intractable and can be achieved with small training data sets. Two exemplars, optimizing the thermodynamic stability of low-density high-entropy alloys and modulating the plateau pressure of hydrogen in metal alloys, demonstrate the power of this approach, which can be extended to a variety of materials discovery and modeling problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1993

Gamma rays from globular clusters

Globular clusters are known to contain a relatively large number of pulsars whose individual and collective emission in the X-ray and gamma-ray energy bands may be detectable by the instruments on board the Compton Gamma-Ray Observatory (CGRO), ROSAT, and possibly SIGMA. We discuss the several types of high-energy emission expected from isolated and interacting binary pulsars in globular clusters. Individual or collective high-energy emission from isolated pulsars is expected to be too low to be detected with current instruments. However, a class of high-luminosity hidden millisecond pulsars enshrouded in the evaporating material from irradiated companion stars can produce unpulsed shock emission detectable by the high-sensitivity instruments of ROSAT and CGRO. Establishing upper limits of high-energy emission from globular clusters will be valuable in constraining models for the formation of cluster millisecond pulsars.

Tavani, Marco↗
DOE OSTI2014

A Cluster-based Method to Map Urban Area from DMSP/OLS Nightlights

Accurate information of urban areas at regional and global scales is important for both the science and policy-making communities. The Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime stable light data (NTL) provide a potential way to map urban area and its dynamics economically and timely. In this study, we developed a cluster-based method to estimate the optimal thresholds and map urban extents from the DMSP/OLS NTL data in five major steps, including data preprocessing, urban cluster segmentation, logistic model development, threshold estimation, and urban extent delineation. Different from previous fixed threshold method with over- and under-estimation issues, in our method the optimal thresholds are estimated based on cluster size and overall nightlight magnitude in the cluster, and they vary with clusters. Two large countries of United States and China with different urbanization patterns were selected to map urban extents using the proposed method. The result indicates that the urbanized area occupies about 2% of total land area in the US ranging from lower than 0.5% to higher than 10% at the state level, and less than 1% in China, ranging from lower than 0.1% to about 5% at the province level with some municipalities as high as 10%. The derived thresholds and urban extents were evaluated using high-resolution land cover data at the cluster and regional levels. It was found that our method can map urban area in both countries efficiently and accurately. Compared to previous threshold techniques, our method reduces the over- and under-estimation issues, when mapping urban extent over a large area. More important, our method shows its potential to map global urban extents and temporal dynamics using the DMSP/OLS NTL data in a timely, cost-effective way.

Cities↗
DOE OSTI2016

The chemical homogeneity of open clusters

Determining the level of chemical homogeneity in open clusters is of fundamental importance in the study of the evolution of star-forming clouds and that of the Galactic disk. Yet limiting the initial abundance spread in clusters has been hampered by difficulties in obtaining consistent spectroscopic abundances for different stellar types. Without reference to any specific model of stellar photospheres, a model for a homogeneous cluster is that it forms a one-dimensional sequence, with any differences between members due to variations in stellar mass and observational uncertainties. I present a novel method for investigating the abundance spread in open clusters that tests this one-dimensional hypothesis at the level of observed stellar spectra, rather than constraining homogeneity using derived abundances as is traditionally done. Using high-resolution APOGEE spectra for 49 giants in M67, NGC 6819, and NGC 2420 I demonstrate that these spectra form one-dimensional sequences for each cluster. With detailed forward modeling of the spectra and Approximate Bayesian Computation, I derive strong limits on the initial abundance spread of 15 elements: <0.01 (0.02) dex for C and Fe, ≲0.015 (0.03) dex for N, O, Mg, Si, and Ni, ≲0.02 (0.03) dex for Al, Ca, and Mn, and ≲0.03 (0.05) dex for Na, S, K, Ti, and V (at 68% and 95% confidence, respectively). The strong limits on C and O imply that no pollution by massive core-collapse supernovae occurred during star formation in open clusters, which, thus, need to form within ≲6 Myr. Further development of this and related techniques will bring the power of differential abundances to stars other than solar twins in large spectroscopic surveys and will help unravel the history of star formation and chemical enrichment in the Milky Way through chemical tagging.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Computational Study of Ethanol Conversion on Al 8 O 12 as a Model for γ-Al 2 O 3

Correlated molecular orbital theory at the coupled cluster CCSD(T) level with density functional theory geometries is used to study ethanol dehydration, dehydrogenation, and condensation reactions on an the Al8O12 cluster which is a model for γ-Al2O3. The Al in the active site on the cluster is a strong Lewis acid. The reactions begin with formation of a very stable Lewis acid–base ethanol–cluster adduct. Dehydration proceeds by β-H transfer to a bicoordinate oxygen leading to the direct formation of ethylene and two OH groups following an E2 mechanism. Dehydrogenation proceeds directly by α-H transfer to the active metal center and a proton transfer to a bicoordinate bridge O to form acetaldehyde plus a metal hydride and a hydroxyl, again an E2 mechanism. After addition of a second ethanol, diethyl ether is generated by an α-C transfer from the first to the second ethanol, an acid-driven SN2 mechanism. Condensation and dehydration with two alcohols have comparable energy barriers. The addition of a second ethanol or a water molecule raises the energy barriers. Condensation and dehydration are predicted to be more likely than dehydrogenation. The computational results for the mechanism and the energetics agree well with the available experimental data.

Fang, Zongtang↗
DOE OSTI2023

Reduced-Order Models of Static Power Grids based on Spectral Clustering

For large-scale interconnected power systems that cover large geographical areas, certain electrical studies are required so that appropriate decisions ensure system reliability and low cost. For such studies, it is often neither practical nor necessary to model in detail the entire power system, which is increasingly complex due to a more diverse range of grid assets to choose from in both short and long-term planning. The goal of this paper is to present a methodology to reduce the order of large-scale power networks based on spectral graph theory given that current methods for static network reduction are not scalable. A brief analysis of some spectral clustering properties to determine which graph Laplacian matrix should be used and why is included. The analysis shows that the utilization of the normalized graph Laplacian is more advantageous for clustering purposes. Techniques are proposed to approximate cost functions for the aggregated generators. This is done via linear regression. The reduced-order model obtained with the proposed methodology has an accuracy above 94% and solves the scalability issue commonly present in other reduction methods. If the utilization of the reduced-order model is either constrained to load levels above mid-peak demand, or cost functions of aggregated units are approximated via a piecewise quadratic approach, then the error distribution is in the order of 10^-3. .

Baquedano-Aguilar, Mario D.↗
DOE OSTI2014

The orbital motion of the quintuplet cluster—a common origin for the arches and quintuplet clusters?

We investigate the orbital motion of the Quintuplet cluster near the Galactic center with the aim of constraining formation scenarios of young, massive star clusters in nuclear environments. Three epochs of adaptive optics high-angular resolution imaging with the Keck/NIRC2 and Very Large Telescope/NAOS-CONICA systems were obtained over a time baseline of 5.8 yr, delivering an astrometric accuracy of 0.5-1 mas yr{sup –1}. Proper motions were derived in the cluster reference frame and were used to distinguish cluster members from the majority of the dense field star population toward the inner bulge. Fitting the cluster and field proper motion distributions with two-dimensional (2D) Gaussian models, we derive the orbital motion of the cluster for the first time. The Quintuplet is moving with a 2D velocity of 132 ± 15 km s{sup –1} with respect to the field along the Galactic plane, which yields a three-dimensional orbital velocity of 167 ± 15 km s{sup –1} when combined with the previously known radial velocity. From a sample of 119 stars measured in three epochs, we derive an upper limit to the velocity dispersion of σ{sub 1D} < 10 km s{sup –1} in the core of the Quintuplet cluster. Knowledge of the three velocity components of the Quintuplet allows us to model the cluster orbit in the potential of the inner Galaxy. Under the assumption that the Quintuplet is located in the central 200 pc at the present time, these simulations exclude the possibility that the cluster is moving on a circular orbit. Comparing the Quintuplet's orbit with our earlier measurements of the Arches' orbit, we discuss the possibility that both clusters originated in the same area of the central molecular zone (CMZ). According to the model of Binney et al., two families of stable cloud orbits are located along the major and minor axes of the Galactic bar, named x1 and x2 orbits, respectively. The formation locus of these clusters is consistent with the outermost x2 orbit and might hint at cloud collisions at the transition region between the x1 and x2 orbital families located at the tip of the minor axis of the Galactic bar. The formation of young, massive star clusters in circumnuclear rings is discussed in the framework of the channeling in of dense gas by the bar potential. We conclude that the existence of a large-scale bar plays a major role in supporting ongoing star and cluster formation, not only in nearby spiral galaxies with circumnuclear rings, but also in the Milky Way's CMZ.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Accelerating Subsurface Transport Simulation on Heterogeneous Clusters

Reactive transport numerical models simulate chemical and microbiological reactions that occur along a flowpath. These models have to compute reactions for a large number of locations. They solve the set of ordinary differential equations (ODEs) that describes the reaction for each location through the Newton-Raphson technique. This technique involves computing a Jacobian matrix and a residual vector for each set of equation, and then solving iteratively the linearized system by performing Gaussian Elimination and LU decomposition until convergence. STOMP, a well known subsurface flow simulation tool, employs matrices with sizes in the order of 100x100 elements and, for numerical accuracy, LU factorization with full pivoting instead of the faster partial pivoting. Modern high performance computing systems are heterogeneous machines whose nodes integrate both CPUs and GPUs, exposing unprecedented amounts of parallelism. To exploit all their computational power, applications must use both the types of processing elements. For the case of subsurface flow simulation, this mainly requires implementing efficient batched LU-based solvers and identifying efficient solutions for enabling load balancing among the different processors of the system. In this paper we discuss two approaches that allows scaling STOMP's performance on heterogeneous clusters. We initially identify the challenges in implementing batched LU-based solvers for small matrices on GPUs, and propose an implementation that fulfills STOMP's requirements. We compare this implementation to other existing solutions. Then, we combine the batched GPU solver with an OpenMP-based CPU solver, and present an adaptive load balancer that dynamically distributes the linear systems to solve between the two components inside a node. We show how these approaches, integrated into the full application, provide speed ups from 6 to 7 times on large problems, executed on up to 16 nodes of a cluster with two AMD Opteron 6272 and a Tesla M2090 per node.

GPU↗