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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Exchange coupling transformations in Cu (II) heterospin complexes of “breathing crystals” under structural phase transitions

Family of “breathing crystals” is the polymer-chain complexes of Cu(hfac){sub 2} with nitroxides. The polymer chains consist of one-, two- or three-spin clusters. The “breathing crystals” experience simultaneous magnetic and Jahn-Teller type structural phase transitions with change of total cluster spin and drastic change of bond lengths (ca. 10-12%). For the first time the intra-cluster magnetic couplings in ”breathing crystals” have been calculated both by band structure methods GGA + U and hybrid DFT (B3LYP and PBE0) for the isolated exchange clusters. The temperature dependence of the magnetic coupling constant was calculated for two polymer-chain compounds of the “breathing crystal” family - C{sub 21}H{sub 19}CuF{sub 12}N{sub 4}O{sub 6} with the chains containing two-spin clusters and C{sub 22}H{sub 21}CuF{sub 12}N{sub 4}O{sub 6} with the chains of alternating three-spin clusters and one-spin sites. It was found that adding a Hubbard-like parameter not only to the copper 3d electrons but also to the oxygen 2p electrons (GGA + U{sub d} + U{sub p} approach) results in an improved description of exchange coupling in the “breathing crystal” compounds. At the same time treatment of the isolated clusters by a large basis hybrid DFT with high computational cost provides a similar quality fit of the experimental magneto-chemical data as that for the GGA + U{sub d} + U{sub p} band structure calculation scheme. Our calculations also showed that in spite of the abrupt transformation of the magnetic coupling constant under the phase transition, the band gap in the “breathing crystals” remains about the same value with temperature decrease.

36 MATERIALS SCIENCE↗
NASA NTRS2016

Improving and Expanding NASA Software Cost Estimation Methods

Estimators and analysts are increasingly being tasked to develop better models and reliable cost estimates in support of program planning and execution. While there has been extensive work on improving parametric methods for cost estimation, there is very little focus on the use of cost models based on analogy and clustering algorithms. In this paper we summarize the results of our research in developing an analogy method for estimating NASA spacecraft flight software using spectral clustering on system characteristics (symbolic nonnumerical data) and evaluate its performance by comparing it to a number of the most commonly used estimation methods. The strengths and weaknesses of each method based on their performance are also discussed. The paper concludes with an overview of the analogy estimation tool (ASCoT) developed for use within NASA that implements the recommended analogy algorithm.

Hihn, Jairus↗
NASA NTRS1996

IRAS Colors of the Pleiades

We present large scale images of the infrared emission of the region around the Pleiades using the ISSA data product from the IRAS mission. Residual Zodiacal background and a discontinuity in the image due to the scanning strategy of the satellite necessitated special background subtraction methods. The 60/100 color image clearly shows the heating of the ambient interstellar medium by the cluster. The 12/100 and 25/100 images peak on the cluster as expected for exposure of small dust grains to an enhanced UV radiation field; however, the 25/100 color declines to below the average interstellar value at the periphery of the cluster. Potential causes of the color deficit are discussed. A new method of identifying dense molecular material through infrared emission properties is presented. The difference between the 100 micron flux density and the 60 micron flux density scaled by the average interstellar 60/100 color ratio (Delta I(sub 100) is a sensitive diagnostic of material with embedded heating sources (Delta I(sub 100) less than 0) and cold, dense cores (Delta I(sub 100) greater than 0). The dense cores of the Taurus cloud complex as well as Lynds 1457 are clearly identified by this method, while the IR bright but diffuse Pleiades molecular cloud is virtually indistinguishable from the nearby infrared cirrus.

Carey, Sean J.↗
DOE OSTI2017

Testing approximate predictions of displacements of cosmological dark matter halos

We present a test to quantify how well some approximate methods, designed to reproduce the mildly non-linear evolution of perturbations, are able to reproduce the clustering of DM halos once the grouping of particles into halos is defined and kept fixed. The following methods have been considered: Lagrangian Perturbation Theory (LPT) up to third order, Truncated LPT, Augmented LPT, MUSCLE and COLA. The test runs as follows: halos are defined by applying a friends-of-friends (FoF) halo finder to the output of an N-body simulation. The approximate methods are then applied to the same initial conditions of the simulation, producing for all particles displacements from their starting position and velocities. The position and velocity of each halo are computed by averaging over the particles that belong to that halo, according to the FoF halo finder. This procedure allows us to perform a well-posed test of how clustering of the matter density and halo density fields are recovered, without asking to the approximate method an accurate reconstruction of halos. We have considered the results at z =0,0.5,1, and we have analysed power spectrum in real and redshift space, object-by-object difference in position and velocity, density Probability Distribution Function (PDF) and its moments, phase difference of Fourier modes. We find that higher LPT orders are generally able to better reproduce the clustering of halos, while little or no improvement is found for the matter density field when going to 2LPT and 3LPT. Augmentation provides some improvement when coupled with 2LPT, while its effect is limited when coupled with 3LPT. Little improvement is brought by MUSCLE with respect to Augmentation. The more expensive particle-mesh code COLA outperforms all LPT methods, and this is true even for mesh sizes as large as the inter-particle distance. This test sets an upper limit on the ability of these methods to reproduce the clustering of halos, for the cases when these objects are reconstructed at the object-by-object level.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Communication: A Jastrow factor coupled cluster theory for weak and strong electron correlation

We present a Jastrow-factor-inspired variant of coupled cluster theory that accurately describes both weak and strong electron correlation. Compatibility with quantum Monte Carlo allows for variational energy evaluations and an antisymmetric geminal power reference, two features not present in traditional coupled cluster that facilitate a nearly exact description of the strong electron correlations in minimal-basis N{sub 2} bond breaking. In double-ζ treatments of the HF and H{sub 2}O bond dissociations, where both weak and strong correlations are important, this polynomial cost method proves more accurate than either traditional coupled cluster or complete active space perturbation theory. These preliminary successes suggest a deep connection between the ways in which cluster operators and Jastrow factors encode correlation.

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

Electronic Structure and Properties of Berkelium Iodates

The reaction of 249 Bk(OH) 4 with iodate under hydrothermal conditions results in the formation of Bk(IO 3 ) 3 as the major product with trace amounts of Bk(IO 3 ) 4 also crystallizing from the reaction mixture. The structure of Bk(IO 3 ) 3 consists of nine-coordinate Bk III cations that are bridged by iodate anions to yield layers that are isomorphous with those found for Am III , Cf III , and with lanthanides that possess similar ionic radii. Bk(IO 3 ) 4 was expected to adopt the same structure as M(IO 3 ) 4 (M = Ce, Np, Pu), but instead parallels the structural chemistry of the smaller Zr IV cation. Bk III –O and Bk IV –O bond lengths are shorter than anticipated and provide further support for a postcurium break in the actinide series. Photoluminescence and absorption spectra collected from single crystals of Bk(IO 3 ) 4 show evidence for doping with Bk III in these crystals. In addition to luminescence from Bk III in the Bk(IO 3 ) 4 crystals, a broad-band absorption feature is initially present that is similar to features observed in systems with intervalence charge transfer. However, the high-specific activity of 249 Bk ( t 1/2 = 320 d) causes oxidation of Bk III and only Bk IV is present after a few days with concomitant loss of both the BkIII luminescence and the broadband feature. The electronic structure of Bk(IO 3 ) 3 and Bk(IO 3 ) 4 were examined using a range of computational methods that include density functional theory both on clusters and on periodic structures, relativistic ab initio wave function calculations that incorporate spin–orbit coupling (CASSCF), and by a full-model Hamiltonian with spin–orbit coupling and Slater–Condon parameters (CONDON). Some of these methods provide evidence for an asymmetric ground state present in Bk IV that does not strictly adhere to Russel–Saunders coupling and Hund’s Rule even though it possesses a half-filled 5 f 7 shell. Multiple factors contribute to the asymmetry that include 5 f electrons being present in microstates that are not solely spin up, spin–orbit coupling induced mixing of low-lying excited states with the ground state, and covalency in the Bk IV –O bonds that distributes the 5f electrons onto the ligands. These factors are absent or diminished in other f 7 ions such as Gd III or Cm III .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2019

Application of Machine Learning Techniques to Delay Tolerant Network Routing

This dissertation discusses several machine learning techniques to improve routing in delay tolerant networks (DTNs). These are networks in which there may be long one-way trip times, asymmetric links, high error rates, and deterministic as well as non-deterministic loss of contact between network nodes, such as interplanetary satellite networks, mobile ad hoc networks and wireless sensor networks. This work uses historical network statistics to train a multi-label classifier to predict reliable paths through the network. In addition, a clustering technique is used to predict future mobile node locations. Both of these techniques are used to reduce the consumption of resources such as network bandwidth, memory and data storage that is required by replication routing methods often used in opportunistic DTN environments. Thesis contributions include: an emulation tool chain developed to create a DTN test bed for machine learning, the network and software architecture for a machine learning based routing method, the development and implementation of classification and clustering techniques and performance evaluation in terms of machine learning and routing metrics.

Dudukovich, Rachel M.↗
DOE OSTI2016

Diffusion Monte Carlo studies of MB-pol (H{sub 2}O){sub 2−6} and (D{sub 2}O){sub 2−6} clusters: Structures and binding energies

We employ the diffusion Monte Carlo (DMC) method in conjunction with the recently developed, ab initio-based MB-pol potential energy surface to characterize the ground states of small (H{sub 2}O){sub 2−6} clusters and their deuterated isotopomers. Observables, other than the ground state energies, are computed using the descendant weighting approach. Among those are various spatial correlation functions and relative isomer fractions. Interestingly, the ground states of all clusters considered in this study, except for the dimer, are delocalized over at least two conformations that differ by the orientation of one or more water monomers with the relative isomer populations being sensitive to the isotope substitution. Most remarkably, the ground state of the (H{sub 2}O){sub 6} hexamer is represented by four distinct cage structures, while that of (D{sub 2}O){sub 6} is dominated by the prism, i.e., the global minimum geometry, with a very small contribution from a prism-book geometry. In addition, for (H{sub 2}O){sub 6} and (D{sub 2}O){sub 6}, we performed DMC calculations to compute the ground states constrained to the cage and prism geometries. These calculations compared results for three different potentials, MB-pol, TTM3/F, and q-TIP4P/F.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Machine learning based job status prediction in scientific clusters

Large high-performance computing systems are built with increasing number of components with more CPU cores, more memory, and more storage space. At the same time, scientific applications have been growing in complexity. Together, they are leading to more frequent unsuccessful job statuses on HPC systems. From measured job statuses, 23.4% of CPU time was spent to the unsuccessful jobs. Here, we set out to study whether these unsuccessful job statuses could be anticipated from known job characteristics. To explore this possibility, we have developed a job status prediction method for the execution of jobs on scientific clusters. The Random Forests algorithm was applied to extract and characterize the patterns of unsuccessful job statuses. Experimental results show that our method can predict the unsuccessful job statuses from the monitored ongoing job executions in 99.8% the cases with 83.6% recall and 94.8% precision. Lastly, this prediction accuracy can be sufficiently high that it can be used to mitigation procedures of predicted failures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

The environment of z > 1 3CR radio galaxies and QSOs: from proto-clusters to clusters of galaxies?

We study the cluster environment for a sample of 21 radio loud active galactic nuclei from the 3CR catalog at z>1, 12 radio galaxies (RGs) and nine quasars, with Hubble Space Telescope (HST) images in the optical and IR. We use two different approaches to determine cluster candidates. We identify the early-type galaxies (ETGs) in every field by modeling each of the sources within a 40″ radius of the targets with a Sèrsic profile. Using a simple passive evolution model, we derive the expected location of the ETGs on the red sequence (RS) in the color–magnitude diagram for each of the fields of our sources. For seven targets, the model coincides with the position of the ETGs. A second approach involves a search for over densities. We compare the object densities of the sample as a whole and individually against control fields taken from the GOODS-S region of 3D-HST survey. With this method we determine the fields of ten targets to be cluster candidates. Four cluster candidates are found by both methods. The two methods disagree in some cases, depending on the specific properties of each field. For the most distant RG in the 3CR catalog (3C 257 at z = 2.47), we identify a population of bluer ETGs that lie on the expected location of the RS model for that redshift. This appears to be the general behavior of ETGs in our fields and it is possibly a signature of the evolution of such galaxies. Our results are consistent with half of the z > 1 RGs being located in dense, rapidly evolving environments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Weak Lensing by Galaxy Clusters: from Pixels to Cosmology

The story of the origin and evolution of our Universe is told, equivalently, by space-time itself and by the structures that grow inside of it. Clusters of galaxies are the frontier of bottom-up structure formation. They are the most massive objects to have collapsed at the present epoch. By that virtue, their abundance and structural parameters are highly sensitive to the composition and evolution of the Universe. The most common probe of cluster cosmology, abundance, uses samples of clusters selected by some observable. Applying a mass-observable relation (MOR), cosmological parameters can be constrained by comparing the sample to predicted cluster abundances as a function of observable and redshift. Arguably, however, cluster probes have not yet entered the era of per cent level precision cosmology. The primary reason for this is our imperfect understanding of the MORs. The overall normalization, the slope of mass vs. observable, the redshift evolution, and the degree and correlation of intrinsic scatters of observables at fixed mass have to be constrained for interpreting abundances correctly. Mass measurement of clusters by means of the differential deflection of light from background sources in their gravitational field, i.e. weak lensing, is a powerful approach for achieving this. This thesis presents new methods for and scientific results of weak lensing measurements of clusters of galaxies. The former include, on the data reduction side, (i) the correction of CCD images for non-linear effects due to the electric fields of accumulated charges and (ii) a method for masking artifact features in sets of overlapping images of the sky by comparison to the median image. Also, (iii) I develop a method for the selection of background galaxy samples based on their color and apparent magnitude that includes a new correction for contamination with cluster member galaxies. The main scientific results are the following. (i) For the Hubble Frontier Field cluster RXC J2248.7--4431 our lensing analysis constrains mass and concentration of the cluster halo and we confirm the large mass predicted by X-ray and Sunyaev-Zel’dovich (SZ) observations. The study of cluster members shows the relation of galaxy morphology to luminosity and environment. (ii) Our lensing mass measurements for 12 clusters are consistent with X-ray masses derived under the assumption of hydrostatic equilibrium of the intra-cluster gas. We confirm the MORs derived by the South Pole Telescope collaboration for the detection significance of the cluster SZ signal in their survey. We find discrepancies, however, with the Planck SZ MOR. We hypothesize that these are related either to a shallower slope of the MOR or a size-, redshift- or noise-dependent bias in SZ signal extraction. (iii) Finally, using a combination of simulations and theoretical models for the variation of cluster profiles at fixed mass, we find that the latter is a significant contribution to the uncertainty of cluster lensing mass measurements. A cosmic variance model, such as the one we develop, is necessary for MOR constraints to be accurate at the level required for future surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Theoretical study of IR and photoelectron spectra of small gallium-arsenide clusters

Relative stabilities of small Ga{sub n}As{sub m} clusters, as well as their structural electronic and vibrational properties, were computed and analysed using a CCSD(T) reference method since experimental data in this area are sparse or unknown. With the aim of investigating larger clusters, we explored several DFT functionals and basis sets able to mimic the reliable CCSD(T) approach. Among them, the PBE0/SBKJC+sp,d appears as the most efficient to describe the structural and vibrational properties since average differences of about 0.042Å and 5.1cm{sup −1} were obtained for bond lengths and fundamental vibrational frequencies, respectively for the first small clusters [1] of the series found from our GSAM method [2]. As further test, this model is used in order to investigate and revisit an experimental IR spectrum of Ga{sub n}As{sub m} mixture previously published by Li et al. [3]. More complicated is the difficulty which arises in the electronic description due to the presence of numerous low lying electronic states nearly degenerated to correctly describe the electronic structure. The case of Ga{sub 2}As will be discussed and the photoelectron spectra of the Ga{sub 2}As anion reanalyzed on the ground of our calculations [4] comparatively to the experimental spectra obtained by Neumark and co-workers [5].

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2013

Permeation of low-Z atoms through carbon sheets: Density functional theory study on energy barriers and deformation effects

Energetic and geometric aspects of the permeation of the atoms hydrogen to neon neutral atoms through graphene sheets are investigated by investigating the associated energy barriers and sheet deformations. Density functional theory calculations on cluster models, where graphene is modeled by planar polycyclic aromatic hydrocarbons (PAHs), provide the energies and geometries. Particularities of our systems, such as convergence of both energy barriers and deformation curves with increasing size of the PAHs, are discussed. Three different interaction regimes, adiabatic, planar and vertical, are investigated by enforcing different geometrical constraints. The adiabatic energy barriers range from 5 eV for hydrogen to 20 eV for neon. We find that the permeation of oxygen and carbon into graphene is facilitated by temporary chemical bonding while for other, in principle reactive atoms, it is not. We discuss implications of our results for modeling chemical sputtering of graphite.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Fluorescence Color by Data-Driven Design of Genomic Silver Clusters

DNA nucleobase sequence controls the size of DNA-stabilized silver clusters, leading to their well-known yet little understood sequence-tuned colors. The enormous space of possible DNA sequences for templating clusters has challenged the understanding of how sequence selects cluster properties and has limited the design of applications that employ these clusters. Here, we investigate the genomic role of DNA sequence for fluorescent silver clusters using a data-driven approach. Employing rapid parallel silver cluster synthesis and fluorimetry, we determine the fluorescence spectra of silver cluster products stabilized by 1432 distinct DNA oligomers. By applying pattern recognition algorithms to this large experimental data set, we discover certain DNA base patterns, or “motifs,” that correlate to silver clusters with similar fluorescence spectra. These motifs are employed in machine learning classifiers to predictively design DNA template sequences for specific fluorescence color bands. Our method improves selectivity of templates by 330% for silver clusters with peak emission wavelengths beyond 660 nm. The discovered base motifs also provide physical insights into how DNA sequence controls silver cluster size and color. Finally, this predictive design approach for color of DNA-stabilized silver clusters exhibits the potential of machine learning and data mining to increase the precision and efficiency of nanomaterials design, even for a soft-matter-inorganic hybrid system characterized by an extremely large parameter space.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Land cover classification in multispectral imagery using clustering of sparse approximations over learned feature dictionaries

We present results from an ongoing effort to extend neuromimetic machine vision algorithms to multispectral data using adaptive signal processing combined with compressive sensing and machine learning techniques. Our goal is to develop a robust classification methodology that will allow for automated discretization of the landscape into distinct units based on attributes such as vegetation, surface hydrological properties, and topographic/geomorphic characteristics. We use a Hebbian learning rule to build spectral-textural dictionaries that are tailored for classification. We learn our dictionaries from millions of overlapping multispectral image patches and then use a pursuit search to generate classification features. Land cover labels are automatically generated using unsupervised clustering of sparse approximations (CoSA). We demonstrate our method on multispectral WorldView-2 data from a coastal plain ecosystem in Barrow, Alaska. We explore learning from both raw multispectral imagery and normalized band difference indices. We explore a quantitative metric to evaluate the spectral properties of the clusters in order to potentially aid in assigning land cover categories to the cluster labels. In this study, our results suggest CoSA is a promising approach to unsupervised land cover classification in high-resolution satellite imagery.

42 ENGINEERING↗
DOE OSTI2014

Cosmological constraints from galaxy clustering and the mass-to-number ratio of galaxy clusters: marginalizing over the physics of galaxy formation

Many approaches to obtaining cosmological constraints rely on the connection between galaxies and dark matter. However, the distribution of galaxies is dependent on their formation and evolution as well as on the cosmological model, and galaxy formation is still not a well-constrained process. Thus, methods that probe cosmology using galaxies as tracers for dark matter must be able to accurately estimate the cosmological parameters. This can be done without knowing details of galaxy formation a priori as long as the galaxies are well represented by a halo occupation distribution (HOD). We apply this reasoning to the method of obtaining Ω {sub m} and σ{sub 8} from galaxy clustering combined with the mass-to-number ratio of galaxy clusters. To test the sensitivity of this method to variations due to galaxy formation, we consider several different models applied to the same cosmological dark matter simulation. The cosmological parameters are then estimated using the observables in each model, marginalizing over the parameters of the HOD. We find that for models where the galaxies can be well represented by a parameterized HOD, this method can successfully extract the desired cosmological parameters for a wide range of galaxy formation prescriptions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

In situ evolution of highly dispersed amorphous CoO x clusters for oxygen evolution reaction

Electrocatalytic water splitting is a key technique to produce hydrogen fuels, which can be considered as an efficient strategy to store renewable energy. Oxygen evolution reaction (OER) that occurs at the anode side requires a four-electron transfer under highly oxidizing conditions. OER has a large overpotential and therefore determines the overall efficiency. Certain electrocatalysts can efficiently help to improve the reaction kinetics. Owing to the high cost of precious metals such as Pt, Ru, and Ir, non-precious metal oxide catalysts have been vigorously investigated under alkaline conditions. Herein, we synthesized novel highly dispersed amorphous CoO x for the first time in the form of a cluster favorable to enhance the OER activity using a facile method via the air dielectric barrier discharge (DBD) plasma. Compared with the pristine biopolymer–cobalt complex, the amorphous CoO x cluster exhibits a much higher current density and a lower overpotential for OER, e.g., the overpotential of 290 mV at 10 mA cm -2 and the overpotential of only 350 mV at 300 mA cm -1 . The excellent electrocatalytic OER activity was attributed to the unsaturated catalytic sites on the amorphous CoO x cluster. In addition, we studied the reaction mechanism, and it was observed that pure O 2 DBD plasma could lead to the evolution of crystalline CoO x ; however, the presence of N 2 and O 2 in DBD plasma could ensure the facile evolution of amorphous CoO x clusters. This study provides a new strategy, therefore, to design amorphous materials for electrocatalysis and beyond.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗