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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 613 records · Page 34

On the relationship between the cosmic web and the alignment of galaxies and AGN jets

ABSTRACT The impact of active galactic nuclei (AGNs) on the evolution of galaxies explains the steep decrease in the number density of the most massive galaxies in the Universe. However, the fuelling of the AGN and the efficiency of this feedback largely depend on their environment. We use data from the Low Frequency Array Two-metre Sky Survey Data Release 2 (DR2), the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys, and the Sloan Digital Sky Survey DR12 to make the first study of the orientations of radio jets and their optical counterpart in relation to the cosmic web environment. We find that close to filaments ($\lesssim \!\! 11 \ \rm Mpc$), galaxies tend to have their optical major axes aligned with the nearest filaments. On the other hand, radio jets, which are generally aligned perpendicularly to the optical major axis of the host galaxy, show more randomized orientations with respect to host galaxies within ${\lesssim} 8 \, \rm Mpc$ of filaments. These results support the scenario that massive galaxies in cosmic filaments grow by numerous mergers directed along the orientation of the filaments while experiencing chaotic accretion of gas on to the central black hole. The AGN-driven jets consequently have a strong impact preferentially along the minor axes of dark matter haloes within filaments. We discuss the implications of these results for large-scale radio jet alignments, intrinsic alignments between galaxies, and the azimuthal anisotropy of the distribution of circumgalactic medium and anisotropic quenching.

Jung, S. Lyla (ORCID:0000000155123735)↗

Nuclear Waste Tank Emission Contributions to Particle Size Distribution

Pollutants from anthropogenic activities including industrial processes are ubiquitous to the environment. To understand the impact from industrial aerosol on climate and human health, industrial aerosol needs to be better characterized. Here, in this study, particle number concentrations were used as a proxy for atmospheric pollutants, which include both particles and gases. Particle concentration and size distribution were measured using a scanning mobility particle sizer (SMPS) approximately 4.5 km from primary industrial areas at the Savannah River Site in Aiken, SC. Industrial areas include numerous nuclear waste storage and processing tanks. The SMPS data were divided into two groups depending on the wind direction measured onsite to categorize transport from the industrial area or from elsewhere. Industrial contributions were found to have a higher concentration of particles with sizes less than 200 nm, 859 ± 564 cm -3 , in comparison to non-industrial attributed particles, 733 ± 495 cm -3 on average from March-July 2021. For sizes larger than 200 nm, industrial and non-industrial particles have a similar concentration, 89 ± 59 cm -3 and 99 ± 61 cm -3 , with non-industrial concentrations being slightly larger. To confirm that industrial particles could travel to the sampling location, air dispersion modeling was completed for specific case studies during the sampling period. The atmospheric dispersion modeling results confirmed that particles released at the industrial areas reached the sampling location when the wind direction was favorable for transport from the industrial areas. The greater concentration of smaller-sized particles in industrial emissions has implications for typical particulate measurements (PM2.5), heath impacts, and climatological influences.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

First measurement of symmetric cumulants of hexagonal flow harmonics in Pb-Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV

Correlations between event-by-event fluctuations of anisotropic flow harmonics are measured in Pb-Pb collisions at a center-of-mass energy per nucleon pair of 5.02 TeV, as recorded by the ALICE detector at the LHC. This study presents correlations up to the hexagonal flow harmonic 𝑣 6 , which was measured for the first time. The magnitudes of these higher-order correlations are found to vary as a function of collision centrality and harmonic order. These measurements are compared to viscous hydrodynamic model calculations with EKRT initial conditions and to the iEBE-VISHNU model with T R ⁢ENTo initial conditions. The observed discrepancies between the data and the model calculations vary depending on the harmonic combinations. Due to the sensitivity of model parameters estimated with Bayesian analyses to these higher-order observables, the results presented in this work provide new and independent constraints on the initial conditions and transport properties in theoretical models used to describe the system created in heavy-ion collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Meta-GGA performance in solids at almost GGA cost

A recent modification, r 2 SCAN, of the strongly constrained and appropriately normed (SCAN) meta-generalized gradient approximation (GGA) exchange-correlation functional mostly eliminates numerical instabilities and attendant integration grid sensitivities exhibited by SCAN. Here, we show that the successful deorbitalization of SCAN to SCAN-L (SCAN with density Laplacian dependence) carries over directly to yield r 2 SCAN-L. A major benefit is that the high iteration counts that hindered the use of SCAN-L are eliminated in r 2 SCAN-L. It therefore is a computationally much faster meta-GGA than its orbital-dependent antecedent. In this work, validation data for molecular heats of formation, bond lengths, and vibration frequencies (G3/99X, T96-R, and T82-F test sets, respectively) and on lattice constants, and cohesive energies (for 55 solids) and bulk moduli (for 40 solids) are provided. In addition, we show that the overmagnetization of bcc Fe, hcp Co, and fcc Ni persists in r 2 SCAN but does not appear in r 2 SCAN-L. Distinct from SCAN, both r 2 SCAN and r 2 SCAN-L give the correct nonmagnetic ground state for bcc V.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Quantum magnetism in the frustrated square lattice oxyhalides YbBi 2 IO 4 and YbBi 2 ClO 4

Square-lattice systems offer a direct route for realizing two-dimensional (2D) quantum magnetism with frustration induced by competing interactions. In this work, the square lattice materials YbBi 2 IO 4 and YbBi 2 ClO 4 were investigated using a combination of magnetization and specific-heat measurements on polycrystalline samples. Specific-heat measurements provide evidence for long-range magnetic order below $T$ N = 0.21 K (0.25 K) for YbBi 2 IO 4 (YbBi 2 ClO 4 ). On the other hand, a rather broad maximum is found in the temperature-dependent magnetic susceptibility, located at $T$ max = 0.33 K (0.38 K) in YbBi 2 IO 4 (YbBi 2 ClO 4 ), consistent with the quasi-2D magnetism expected for the large separation between the magnetic layers. Estimation of the magnetic entropy supports the expected Kramers' doublet ground state for Yb 3+ and the observed paramagnetic behavior is consistent with a well-isolated doublet. Roughly two-thirds of the entropy is consumed above $T$ N , due to a combination of the quasi-2D behavior and magnetic frustration. The impact of frustration is examined from the viewpoint of a simplified $J$ 1 -$J$ 2 square lattice model, which is frustrated for antiferromagnetic interactions. Specifically, a high-temperature series expansion analysis of the temperature-dependent specific-heat and magnetization data yields $J$ 2 /$J$ 1 = 0.30 (=0.23) for YbBi 2 IO 4 (YbBi 2 ClO 4 ). In conclusion, this simplified analysis suggests strong frustration that should promote significant quantum fluctuations in these compounds, and thus motivates future work on the static and dynamic magnetic properties of these materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Multiscale structural analysis of polymorphic phase boundaries in doped antiferroelectric sodium niobate

In the current work, we have performed multiscale structural analysis of a Pb-free sodium niobate-based smart system, i.e., 0.9⁢NaNbO 3 –0.1⁢Ba 0.9 ⁢Ca 0.1 ⁢TiO 3 (NN-10BCT) reported earlier for its high ferroelectric response. We have investigated the temperature-dependent evolution of crystal structure at long, medium, and short ranges using synchrotron x-ray diffraction (SXRD), Raman scattering, and pair distribution function(PDF) techniques in conjunction with dielectric studies. Temperature-dependent synchrotron x-ray diffraction data combined with dielectric analysis suggest two unique polymorphic phase boundaries (PPB) with two coexisting ferroelectric phases stable in the wide temperature ranges. These PPBs are stable in different regions viz. (i) cryogenic temperatures with coexisting R3c and Pmc⁢2 1 phases (ii) vicinity of room temperatures with coexisting Pmc⁢2 1 and Amm2 phases. In contrast to the conclusions drawn from SXRD, PDF reveals structures having lower symmetry (with coexisting Cc+ Pmc2 1 phases at 1.7 ≤r≤ 20 Å) at short ranges for these PPBs. In conclusion, the presence of different long- and short-range symmetries (accommodating tilt-oriented ferroelectric phases) in the unique polymorphic phase boundaries makes them thermally stable and advantageous for technological applications.

36 MATERIALS SCIENCE↗

Improved limits on Fierz interference using asymmetry measurements from the Ultracold Neutron Asymmetry (UCNA) experiment

The Ultracold Neutron Asymmetry (UCNA) experiment was designed to measure the β-decay asymmetry parameter, A 0 , for free neutron decay. In the experiment, polarized ultracold neutrons are transported into a decay trap, and their β-decay electrons are detected with ≈4π acceptance into two detector packages which provide position and energy reconstruction. The experiment also has sensitivity to b n , the Fierz interference term in the neutron β-decay rate. In this work, we determine bn from the energy dependence of A 0 using the data taken during the UCNA 2011–2013 run. In addition, we present the same type of analysis using the earlier 2010 A dataset. Furthermore, motivated by improved statistics and comparable systematic errors compared to the 2010 data-taking run, we present a new b n measurement using the weighted average of our asymmetry dataset fits, to obtain b n = 0.066 ± 0.041 stat ± 0.024 syst which corresponds to a limit of -0.012 < b n < 0.144 at the 90% confidence level.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A simple solution to the Rietveld refinement recipe problem

Rietveld refinements are widely used for many purposes in the physical sciences. Conducting a Rietveld refinement typically requires expert input because correct results may require that parameters be added to the fit in the proper order. This order will depend on the nature of the data and the initial parameter values. A mechanism for computing the next parameter to add to the refinement is shown. The fitting function is evaluated with the current parameter value set and each parameter incremented and decremented by a small offset. This provides the partial derivatives with respect to each parameter, along with information to discriminate meaningful values from numerical computational errors. The implementation of this mechanism in the open-source GSAS-II program is discussed. This new method is discussed as an important step towards the development of automated Rietveld refinement technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accelerating Scientific Simulations with Bi-Fidelity Weighted Transfer Learning

High-fidelity modeling is an essential design tool for many engineering applications. However, for complex systems, computational cost can be a limiting factor. Analyzing parameter sensitivity, uncertainty quantification, and design optimization require many model evaluations. Surrogate models are often used to develop the relationship between model parameters and quantities of interest. However, in the case of complex systems, surrogate models require several degrees of freedom and, thus, a large number of data points to determine the correct dependencies. For many applications, this may be prohibitively expensive. The reduction of computational requirements can be achieved by leveraging low-fidelity models. Low-fidelity models represent the system at a coarser resolution with the advantage of computational efficiency. Therefore, a bi-fidelity modeling paradigm, which augments the accuracy of a low-fidelity model in a computationally efficient manner by invoking limited runs of a high-fidelity model, can be leveraged to sufficiently balance the accuracy and computational requirements. In this work, a bi-fidelity weighted transfer learning method using neural networks was applied to a computational fluid dynamics heat transfer modeling problem. The transfer learning advantage was investigated as a function of hyperparameters. Our main finding is that the use of a bi-fidelity modeling paradigm achieves accuracy close to that of a high-fidelity Gaussian process model while significantly reducing computational cost. The bi-fidelity model achieves comparable performance with 90 high-fidelity samples-that is, 60% less than the samples needed to achieve similar accuracy without the use of bi-fidelity modeling,

Borowiec, Katarzyna↗

ADC Nonlinearity Correction for the Majorana Demonstrator

Imperfections in analog-to-digital conversion cannot be ignored when signal digitization requirements demand both wide dynamic range and high resolution, as is the case for the MAJORANA DEMONSTRATOR 76 Ge neutrinoless double beta decay search. Enabling the experiment's high-resolution spectral analysis and efficient pulse shape discrimination required careful measurement and correction of ADC nonlinearites. Here, a simple measurement protocol was developed that did not require sophisticated equipment or lengthy data taking campaigns. A slope-dependent hysteresis was observed and characterized. A correction applied to digitized waveforms prior to signal processing reduced the differential and integral nonlinearites by an order of magnitude, eliminating these as dominant contributions to the systematic energy uncertainty at the double-beta decay Q value.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Inhibition of nitrous oxide reduction in forest soil microcosms by different forms of methanobactin

Copper plays a critical role in controlling greenhouse gas emissions as it is a key component of the particulate methane monooxygenase and nitrous oxide reductase. Some methanotrophs excrete methanobactin (MB) that has an extremely high copper affinity. As a result, MB may limit the ability of other microbes to gather copper, thereby decreasing their activity as well as impacting microbial community composition. Here, we show using forest soil microcosms that multiple forms of MB; MB from Methylosinus trichosporium OB3b (MB-OB3b) and MB from Methylocystis sp. strain SB2 (MB-SB2) increased nitrous oxide (N 2 O) production as well caused significant shifts in microbial community composition. Such effects, however, were mediated by the amount of copper in the soils, with low-copper soil microcosms showing the strongest response to MB. Furthermore, MB-SB2 had a stronger effect, likely due to its higher affinity for copper. The presence of either form of MB also inhibited nitrite reduction and generally increased the presence of genes encoding for the iron-containing nitrite reductase (nirS) over the copper-dependent nitrite reductase (nirK). Lastly, these data indicate the methanotrophic-mediated production of MB can significantly impact multiple steps of denitrification, as well as have broad effects on microbial community composition of forest soils.

54 ENVIRONMENTAL SCIENCES↗

Impact of aqueous solution pH on network structure of corrosion–induced surface layers of boroaluminosilicate glass

Understanding of the long-term stability of vitrified nuclear waste glass is critical to its safe storage, but knowledge gaps remain regarding the corrosion mechanism, especially with respect to surface alteration layers whose presence changes the observed corrosion rates. Here, we report the aqueous corrosion of a model boroaluminosilicate glass at ground water relevant pHs as investigated by vibrational spectroscopy to understand the network structure of the alteration layer that we hypothesize controls the corrosion rates. Both specular reflection infrared spectroscopy and infrared variable angle spectroscopic ellipsometry were used to elucidate details of the structure of the alteration layers formed at pH 7 and pH 9. After 2312 days, the thickness of the alteration layer is found to be ~2000 nm for corrosion at pH 7 and ~300 nm for corrosion at pH 9. Here, the interpretation of the vibrational spectra suggests that alteration layers formed at pH 7 and pH 9 both exhibit a porous network with "silica-like" structures, but with differences in the bond lengths and bond angles in the glass network. Moreover, the relative abundance of the hydrous species within the porous network appears to be dependent on pH. Additionally, the spectroscopic data suggest that the B and Ca trapped in the alteration layer during the secondary corrosion of the pH 9 pre-corroded sample in pH 3 solution are hydrated within the nano-porous layer and not bound to the silicate network. However, the precise chemical form remains to be determined. Based on these findings, we propose that the combination of the network structure of the alteration layer and the relative abundance of hydrous species within the alteration layer act to control the transport of ionic species dissolved from the reaction front to the aqueous solution outside the glass.

36 MATERIALS SCIENCE↗

Genetic and biochemical characterization of a radical SAM enzyme required for post-translational glutamine methylation of methyl-coenzyme M reductase

ABSTRACT Methyl-coenzyme M reductase (MCR), the key catalyst in the anoxic production and consumption of methane, contains an unusual 2-methylglutamine residue within its active site. In vitro data show that a B12-dependent radical SAM (rSAM) enzyme, designated MgmA, is responsible for this post-translational modification (PTM). Here, we show that two different MgmA homologs are able to methylate MCR in vivo when expressed in Methanosarcina acetivorans , an organism that does not normally possess this PTM. M. acetivorans strains expressing MgmA showed small, but significant, reductions in growth rates and yields on methylotrophic substrates. Structural characterization of the Ni(II) form of Gln-methylated M. acetivorans MCR revealed no significant differences in the protein fold between the modified and unmodified enzyme; however, the purified enzyme contained the heterodisulfide reaction product, as opposed to the free cofactors found in eight prior M. acetivorans MCR structures, suggesting that substrate/product binding is altered in the modified enzyme. Structural characterization of MgmA revealed a fold similar to other B12-dependent rSAMs, with a wide active site cleft capable of binding an McrA peptide in an extended, linear conformation. IMPORTANCE Methane plays a key role in the global carbon cycle and is an important driver of climate change. Because MCR is responsible for nearly all biological methane production and most anoxic methane consumption, it plays a major role in setting the atmospheric levels of this important greenhouse gas. Thus, a detailed understanding of this enzyme is critical for the development of methane mitigation strategies.

Rodriguez Carrero, Roy J. (ORCID:0000000184475641)↗

Prediction of microstructure formation in laser powder bed fusion process.

The datasets are results analyzing the predicted microstructures in a single track during the laser powder bed fusion additive manufacturing process. They are the outputs by running the opensource code, muMatScale (The code can be cited at: Yuan, Lang, Fattebert, Jean-Luc, and Sabau, Adrian. (2023, August 03). muMatScale. [Computer software]. https://github.com/lang-yuan/muMatScale. https://doi.org/10.11578/dc.20240112.2.) For each set of data, it contains the time-dependent information of Temperature, Fraction Solid, Grain ID, Grain Angle ( crystallographic orientations by Euler angles), and solute Composition. The dataset can be visualized by Paraview (https://www.paraview.org/ ). The 6 datasets are: 1. Baseline_base1_n4e14_dt20: baseline case with bulk nucleation density of 4E+14/m^3, undercooling of 20K, substrate nucleation density of 1.5E+15/m^3 2. Nuc_n4e15_dt20: case with bulk nucleation density of 4E+15/m^3, undercooling of 20K, substrate nucleation density of 1.5E+15/m^3 3. Nuc_n4e15_dt50: case with bulk nucleation density of 4E+15/m^3, undercooling of 50K, substrate nucleation density of 1.5E+15/m^3 4. Nuc_n6e15_dt20: case with bulk nucleation density of 4E+16/m^3, undercooling of 20K, substrate nucleation density of 1.5E+15/m^3 5. Base4_n4e14_dt20: case with bulk nucleation density of 4E+14/m^3, undercooling of 20K, substrate nucleation density of 6.0E+15/m^3 6. Base16_n4e14_dt20: case with bulk nucleation density of 4E+14/m^3, undercooling of 20K, substrate nucleation density of 2.4E+16/m^3

36 MATERIALS SCIENCE↗

Real-time structural motif searching in proteins using an inverted index strategy

Biochemical and biological functions of proteins are the product of both the overall fold of the polypeptide chain, and, typically, structural motifs made up of smaller numbers of amino acids constituting a catalytic center or a binding site that may be remote from one another in amino acid sequence. Detection of such structural motifs can provide valuable insights into the function(s) of previously uncharacterized proteins. Technically, this remains an extremely challenging problem because of the size of the Protein Data Bank (PDB) archive. Existing methods depend on a clustering by sequence similarity and can be computationally slow. We have developed a new approach that uses an inverted index strategy capable of analyzing >170,000 PDB structures with unmatched speed. The efficiency of the inverted index method depends critically on identifying the small number of structures containing the query motif and ignoring most of the structures that are irrelevant. Our approach (implemented at motif.rcsb.org ) enables real-time retrieval and superposition of structural motifs, either extracted from a reference structure or uploaded by the user. Herein, we describe the method and present five case studies that exemplify its efficacy and speed for analyzing 3D structures of both proteins and nucleic acids.

59 BASIC BIOLOGICAL SCIENCES↗

SAR Geolocation Using Range-Only Multilateration

Radar is by its basic nature a ranging instrument. If radar range measurements from multiple directions can be made and assembled, then multilateration allows locating a feature common to the set of Synthetic Aperture Radar (SAR) images to an accurate 3-D coordinate. The ability to employ effective multilateration algorithms is highly dependent on the geometry of the data collections, and the accuracy with which relative range measurements can be made. The problem can be cast as a least-squares exercise, and the concept of Dilution of Precision can describe the accuracy and precision with which a 3-D location can be made.

47 OTHER INSTRUMENTATION↗

SAR Geolocation Using Range-Doppler Multilateration

Radar is by its basic nature a ranging instrument. If radar range and range-rate measurements from multiple directions can be made and assembled, then multilateration allows locating a feature common to the set of Synthetic Aperture Radar (SAR) images to an accurate 3-D coordinate. The ability to employ effective multilateration algorithms is highly dependent on the geometry of the data collections, and the accuracy with which relative range measurements can be made. The problem can be cast as a least-squares exercise, and the concept of Dilution of Precision can describe the accuracy and precision with which a 3-D location can be made.

42 ENGINEERING↗

Offloading Calculations to Computational Storage Devices: Spark and HDFS [Slides]

The objective is to evaluate the capabilities of multiple CSDs (provided by NDG Systems) using Hadoop Filesystem and Apache Spark. The independent variables are: number of CSDs, 0, 1, 2, 4, or 6; size of dataset, 1 GB, 5 GB, 10 GB; type of dataset, one large file with all of the data, 10 files, 100 files. The dependent variables are: job time; execution time. the constants are operations on the dataset.

97 MATHEMATICS AND COMPUTING↗