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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
NASA NTRS2002

Redshifts for a Sample of Radio-Selected Poor Clusters

Multifiber optical spectroscopy has been performed on galaxies in the vicinity of strong, nearby radio galaxies. These radio galaxies were selected from the, 3CR and B2 catalogs based on their exclusion from the Abell catalog, which is puzzling given the hypothesis that an external medium is required to confine the radio plasma of such galaxies. Velocities derived from the spectra were used to confirm the existence of groups and poor clusters in the fields of most of the radio galaxies. We find that all radio galaxies with classical Fanaroff-Riley type I morphologies prove to reside in clusters, whereas the other radio galaxies often appear to be recent galaxy-galaxy mergers in regions of low galaxy density. These findings confirm the earlier result that the existence of extended X-ray emission combined with a statistical excess of neighboring galaxies can be used to identify poor clusters associated with radio galaxies.

Miller, Neal A.↗
DOE OSTI2022

Combined $\mathrm{APOGEE}$-$\mathrm{GALAH}$ stellar catalogues using the Cannon

APOGEE and GALAH are two high resolution multi-object spectroscopic surveys that provide fundamental stellar parameters and multiple elemental abundance estimates for about half a million stars in the Milky Way. Both surveys observe in different wavelength regimes and use different data reduction pipelines leading to significant offsets and trends in stellar parameters and abundances for the common stars observed in both surveys. Such systematic differences/offsets in stellar parameters and abundances make it difficult to effectively utilize them to investigate Galactic abundance trends in spite of the unique advantage provided by their complementary sky coverage and different Milky Way components they observe. Hence, we use the Cannon data-driven method selecting a training set of 4418 common stars observed by both surveys. This enables the construction of two catalogues, one with the APOGEE-scaled and the other with the GALAH-scaled stellar parameters. Using repeat observations in APOGEE and GALAH, we find high precision in metallicity (~0.02–0.4 dex) and alpha abundances (~0.02–0.03 dex) for spectra with good signal-to-noise ratio (SNR >; 80 for APOGEE and SNR > 40 for GALAH). We use open and globular clusters to validate our parameter estimates and find small scatter in metallicity (0.06 dex) and alpha abundances (0.03 dex) in APOGEE-scaled case. The final catalogues have been cross-matched with the Gaia EDR3 catalogue to enable their use to carry out detailed chemo-dynamic studies of the Milky Way from perspectives of APOGEE and GALAH.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1994

Theoretical expectations for bulk flows in large-scale surveys

We calculate the theoretical expectation for the bulk motion of a large-scale survey of the type recently carried out by Lauer and Postman. Included are the effects of survey geometry, errors in the distance measurements, clustering properties of the sample, and different assumed power spectra. We considered the power spectrum calculated from the Infrared Astronomy Satellite (IRAS)-QDOT survey, as well as spectra from hot + cold and standard cold dark matter models. We find that measurement uncertainty, sparse sampling, and clustering can lead to a much larger expectation for the bulk motion of a cluster sample than for the volume as a whole. However, our results suggest that the expected bulk motion is still inconsistent with that reported by Lauer and Postman at the 95%-97% confidence level.

Feldman, Hume A.↗
NASA NTRS2021

Topic Modeling Tool for PeTaL (Periodic Table of Life)

A topic modeling tool is constructed for the purpose of providing insights from biology to the engineer within the framework of PeTaL (Periodic Table of Life). The machine learning text mining tools–latent Dirichlet allocation (LDA) and nonnegative matrix factorization (NMF) with Kullback-Leibler (KL) divergence—are used to provide topic clusters to the user. Topic clusters are the underlying themes of a paper. For the text modeling problem, NMF-KL is the equivalent of probabilistic latent semantic analysis. Both LDA and NMF-KL are top-performing modeling tools. These tools are used to identify biological specimens relevant to the user. Various organisms solve a particular survival problem in nature differently. The topic clusters allow people without domain expertise to find these cross-topic themes in the body of documents and then branch out and examine papers whose target organisms solve the engineer’s problem. Abstracts from the Journal of Experimental Biology were used as input for the clustering tool in addition to a curated set of articles for validation. The tool is able to accept alternate input sources.

Machine learning↗
DOE OSTI2024

Individual Data Sparsity in Smart Thermostat Big Data: Impacts on Modeling Thermostat Use Behavior Dynamics

This study explores the impacts of the sparsity of individual thermostat interaction data on modeling thermostat use behavior dynamics using a dataset of over 100,000 smart thermostats. In developing a data-driven model of Thermal Frustration Theory (TFT), we investigate the challenges and trade-offs in clustering occupant data to enhance predictive accuracy. Our findings reveal that a single, aggregated model fails to capture the diversity of occupant behaviors, resulting in extremely poor prediction performance. Conversely, excessive clustering exacerbates data sparsity, undermining model reliability. By identifying an optimal clustering strategy, we achieve a balance that significantly improves the prediction of manual setpoint changes during demand response (DR) events, enhancing energy management and occupant comfort

Fannon, David↗
NASA NTRS2015

Testing Secondary Models for the Origin of Radio Mini-Halos in Galaxy Clusters

We present an MHD simulation of the emergence of a radio minihalo in a galaxy cluster core in a "secondary" model, where the source of the synchrotron-emitting electrons is hadronic interactions between cosmic-ray protons with the thermal intracluster gas, an alternative to the "reacceleration model" where the cosmic ray electrons are reaccelerated by turbulence induced by core sloshing, which we discussed in an earlier work. We follow the evolution of cosmic-ray electron spectra and their radio emission using passive tracer particles, taking into account the time-dependent injection of electrons from hadronic interactions and their energy losses. We find that secondary electrons in a sloshing cluster core can generate diffuse synchrotron emission with luminosity and extent similar to observed radio minihalos. However, we also find important differences with our previous work. We find that the drop in radio emission at cold fronts is less prominent than that in our reacceleration-based simulations, indicating that in this flavor of the secondary model the emission is more spatially extended than in some observed minihalos. We also explore the effect of rapid changes in the magnetic field on the radio spectrum. While the resulting spectra in some regions are steeper than expected from stationary conditions, the change is marginal, with differences in the synchrotron spectral index of delta(spectral index) less than approximately 0.15-0.25, depending on the frequency band. This is a much narrower range than claimed in the best-observed minihalos and produced in the reacceleration model. Our results provide important suggestions to constrain these models with future observations.

clusters: general aEuro" magnetohydrodynamics (MHD↗
DOE OSTI2026

Using X-ray spectrum imaging to quantify fission gas in high-burnup UO2 fuel

Analysis of fission gas bubbles (FGBs) in light-water reactor (LWR) fuel is needed to improve the understanding and predictive capability of fuel evolution under normal- and transient conditions. One of the most important parameters of a FGB is the pressure of the gas, primarily Xe, inside it. Bubble volume and location (inter- vs. intragranular) are important considerations as well. However, experimental analysis of such bubbles is challenging due to their small size and embedded nature, and usefulness of the data requires large numbers be analyzed. This paper proposes a method to measure the pressure of Xe bubbles using X-ray spectrum imaging (XSI) in scanning transmission electron microscopy (STEM). From X-ray generation and instrumental parameters, the number of Xe atoms yielding a given number of Xe L-series X-ray counts is estimated, and then from the estimated volume of the bubble the Xe density is estimated, which can then be converted to pressure via an equation-of-state. We apply the method to XSI datasets from high burnup (HBu) fuel from North Anna 1 reactor in as-irradiated and post-LOCA-test conditions and find Xe pressures in the FGBs clustered around 1 GPa.

Parish, Chad [ORNL] (ORCID:0000000312097439)↗
DOE OSTI2021

Impact of Transition Metal Doping on the Structural and Optical Properties of Halide Perovskites

Metal ion doping into halide perovskite materials is a promising approach to enhance long-term film stability and improve solar cell performance. Moreover, the idea of doping metals into halide perovskites is also driven by applications in heterogeneous catalysis. Here, we investigate the incorporation of the transition metals Pt and Pd into mixed-halide perovskite materials. We find that Pt aggregates in large clusters in iodine- and bromine-rich perovskite film compositions, whereas Pd incorporation depends on the underlying bromine to iodine ratio. Furthermore, by using optical and structural characterization methods, we observe that phase segregation in the perovskite layer is suppressed upon doping of either of these metals into the material. This approach further shows the potential to obtain catalytically active halide perovskite films in which the perovskite can serve as a host matrix.

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

Neural Network for Principle of Least Action

The principle of least action is the cornerstone of classical mechanics, theory of relativity, quantum mechanics, and thermodynamics. Here, we describe how a neural network (NN) learns to find the trajectory for a Lennard-Jones (LJ) system that maintains balance in minimizing the Onsager–Machlup (OM) action and maintaining the energy conservation. The phase-space trajectory thus calculated is in excellent agreement with the corresponding results from the “ground-truth” molecular dynamics (MD) simulation. Furthermore, we show that the NN can easily find structural transformation pathways for LJ clusters, for example, the basin-hopping transformation of an LJ 38 from an incomplete Mackay icosahedron to a truncated face-centered cubic octahedron. Unlike MD, the NN computes atomic trajectories over the entire temporal domain in one fell swoop, and the NN time step is a factor of 20 larger than the MD time step. The NN approach to OM action is quite general and can be adapted to model morphometrics in a variety of applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

When do short-range atomistic machine-learning models fall short?

In this work, we explore the role of long-range interactions in atomistic machine-learning models by analyzing the effects on fitting accuracy, isolated cluster properties, and bulk thermodynamic properties. Such models have become increasingly popular in molecular simulations given their ability to learn highly complex and multi-dimensional interactions within a local environment; however, many of them fundamentally lack a description of explicit long-range interactions. In order to provide a well-defined benchmark system with precisely known pairwise interactions, we chose as the reference model a flexible version of the Extended Simple Point Charge (SPC/E) water model. Our analysis shows that while local representations are sufficient for predictions of the condensed liquid phase, the short-range nature of machine-learning models falls short in representing cluster and vapor phase properties. These findings provide an improved understanding of the role of long-range interactions in machine learning models and the regimes where they are necessary.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Sculpting crystals one Burgers vector at a time: Toward colloidal lattice robot swarms

Plastic deformation of crystalline materials with isotropic particle attractions proceeds by the creation and migration of dislocations under the influence of external forces. If dislocations are produced and migrated under the action of local forces, then material shape change can occur without the application of surface forces. We investigate how particles with variable diameters can be embedded in colloidal monolayers to produce dislocations on demand. Additionally, we find in simulation that when embedded clusters of variable diameter particles are taken through multiple cycles of swelling and shrinking, large cumulative plastic slip is produced by the creation and biased motion of dislocation pairs in the solid for embedded clusters of particular geometries. In this way, dislocations emitted by these clusters (biased “dislocation emitters”) can be used to reshape colloidal matter. Our results are also applicable to larger-scale swarms of robotic particles that organize into dense ordered two-dimensional (2D) arrangements. We conclude with a discussion of how dislocations fulfill for colloids the role sought by “metamodules” in lattice robotics research and show how successive applications of shear as a unit operation can produce shape change through slicing and swirling.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Advances in ArborX to support exascale applications

ArborX is a performance portable geometric search library developed as part of the Exascale Computing Project (ECP). In this paper, we explore a collaboration between ArborX and a cosmological simulation code HACC. Large cosmological simulations on exascale platforms encounter a bottleneck due to the in-situ analysis requirements of halo finding, a problem of identifying dense clusters of dark matter (halos). This problem is solved by using a density-based DBSCAN clustering algorithm. With each MPI rank handling hundreds of millions of particles, it is imperative for the DBSCAN implementation to be efficient. In addition, the requirement to support exascale supercomputers from different vendors necessitates performance portability of the algorithm. We describe how this challenge problem guided ArborX development, and enhanced the performance and the scope of the library. We explore the improvements in the basic algorithms for the underlying search index to improve the performance, and describe several implementations of DBSCAN in ArborX. Further, we report the history of the changes in ArborX and their effect on the time to solve a representative benchmark problem, as well as demonstrate the real world impact on production end-to-end cosmology simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

On the Nature of Extra-Framework Aluminum Species and Improved Catalytic Properties in Steamed Zeolites

Steamed zeolites exhibit improved catalytic properties for hydrocarbon activation (alkane cracking and dehydrogenation). The nature of this practically important phenomenon has remained a mystery for the last six decades and was suggested to be related to the increased strength of zeolitic Bronsted acid sites after dealumination. We now utilize state-of-the-art infrared spectroscopy measurements and prove that during steaming, aluminum oxide clusters evolve (due to hydrolysis of Al out of framework positions with the following clustering) in the zeolitic micropores with properties very similar to (nano) facets of hydroxylated transition alumina surfaces. The Bronsted acidity of the zeolite does not increase and the total number of Bronsted acid sites decreases during steaming. O 5 Al(VI)-OH surface sites of alumina clusters dehydroxylate at elevated temperatures to form penta-coordinate Al 1 O 5 sites that are capable of initiating alkane cracking by breaking the first C-H bond very effectively with much lower barriers (at lower temperatures) than for protolytic C-H bond activation, with the following reaction steps catalyzed by nearby zeolitic Bronsted acid sites. This explains the underlying mechanism behind the improved alkane cracking and alkane dehydrogenation activity of steamed zeolites: heterolytic C-H bond breaking occurs on Al-O sites of aluminum oxide clusters confined in zeolitic pores. Our findings explain the origin of enhanced activity of steamed zeolites at the molecular level and provide the missing understanding of the nature of extra-framework Al species formed in steamed/dealuminated zeolites.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Evolution of the Thermodynamic Properties of Clusters of Galaxies out to Redshift of 1.8

The thermodynamic properties of the hot plasma in galaxy clusters retains information on the processes leading to the formation and evolution of the gas in their deep, dark matter potential wells. These processes are dictated not only by gravity but also by gas physics, e.g. AGN feedback and turbulence. Here, we study the thermodynamic properties, e.g. density, temperature, pressure, and entropy, of the most massive and the most distant (z > 1.2) SPT-selected clusters, and compare them with those of the nearby clusters (z < 0.1) to constrain their evolution as a function of time and radius. We find that thermodynamic properties in the outskirts of high redshift clusters are remarkably similar to the low redshift clusters, and their evolution follows the prediction of the self-similar model. Their intrinsic scatter is larger, indicating that the physical properties that lead to the formation and virialization of cluster outskirts show evolving variance. On the other hand, thermodynamic properties in the cluster cores deviates significantly from self-similarity indicating that the processes that regulate the core are already in place in these very high redshift clusters. This result is supported by the unevolving physical scatter of all thermodynamic quantities in cluster cores.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

The Atacama Cosmology Telescope: Mitigating the Impact of Extragalactic Foregrounds for the DR6 Cosmic Microwave Background Lensing Analysis

We investigate the impact and mitigation of extragalactic foregrounds for the cosmic microwave background (CMB) lensing power spectrum analysis of Atacama Cosmology Telescope (ACT) data release 6 (DR6) data. Two independent microwave sky simulations are used to test a range of mitigation strategies. We demonstrate that finding and then subtracting point sources, finding and then subtracting models of clusters, and using a profile bias-hardened lensing estimator together reduce the fractional biases to well below statistical uncertainties, with the inferred lensing amplitude, A lens , biased by less than 0.2σ. We also show that another method where a model for the cosmic infrared background (CIB) contribution is deprojected and high-frequency data from Planck is included has similar performance. Other frequency-cleaned options do not perform as well, either incurring a large noise cost or resulting in biased recovery of the lensing spectrum. In addition to these simulation-based tests, we also present null tests on the ACT DR6 data for sensitivity of our lensing spectrum estimation to differences in foreground levels between the two ACT frequencies used, while nulling the CMB lensing signal. These tests pass whether the nulling is performed at the map or bandpower level. The CIB-deprojected measurement performed on the DR6 data is consistent with our baseline measurement, implying that contamination from the CIB is unlikely to significantly bias the DR6 lensing spectrum. This collection of tests gives confidence that the ACT DR6 lensing measurements and cosmological constraints presented in companion papers to this work are robust to extragalactic foregrounds.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1990

Astrometry with the ATF

A detailed study of the effects of gravitational radiation on the relative positions of objects was carried out with the hope that astrometric detection of gravitational radiation might be possible. The results are discouraging. It would appear that narrow-field instruments in the Astrometric Telescope Facility (ATF) class are still several orders of magnitude less accurate than would be required for this very delicate kind of measurement. However, the situation changes considerably when wide-field instruments are considered. An instrument such as POINTS ought to be able to detect gravitational radiation at this level with ease. The list of bright quasars has been augmented. Of particular interest is the finding of quasars near two open clusters and one planetary nebula. These would be useful in determining absolute parallaxes of these objects.

Jefferys, William H.↗
NASA NTRS1991

Using Gaussian windows to explore a multivariate data set

In an earlier paper, I recounted an exploratory analysis, using Gaussian windows, of a data set derived from the Infrared Astronomical Satellite. Here, my goals are to develop strategies for finding structural features in a data set in a many-dimensional space, and to find ways to describe the shape of such a data set. After a brief review of Gaussian windows, I describe the current implementation of the method. I give some ways of describing features that we might find in the data, such as clusters and saddle points, and also extended structures such as a 'bar', which is an essentially one-dimensional concentration of data points. I then define a distance function, which I use to determine which data points are 'associated' with a feature. Data points not associated with any feature are called 'outliers'. I then explore the data set, giving the strategies that I used and quantitative descriptions of the features that I found, including clusters, bars, and a saddle point. I tried to use strategies and procedures that could, in principle, be used in any number of dimensions.

Jaeckel, Louis A.↗