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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 325 records · Page 18

The Invariant Twist of Magnetic Fields in the Relativistic Jets of Active Galactic Nuclei

The origin of cosmic magnetic (B) fields remains an open question. It is generally believed that very weak primordial B fields are amplified by dynamo processes, but it appears unlikely that the amplification proceeds fast enough to account for the fields presently observed in galaxies and galaxy clusters. In an alternative scenario, cosmic B fields are generated near the inner edges of accretion disks in Active Galactic Nuclei (AGNs) by azimuthal electric currents due to the difference between the plasma electron and ion velocities that arises when the electrons are retarded by interactions with photons. While dynamo processes show no preference for the polarity of the (presumably random) seed field that they amplify, this alternative mechanism uniquely relates the polarity of the poloidal B field to the angular velocity of the accretion disk, resulting in a unique direction for the toroidal B field induced by disk rotation. Observations of the toroidal fields of 29 AGN jets revealed by parsec-scale Faraday rotation measurements show a clear asymmetry that is consistent with this model, with the probability that this asymmetry came about by chance being less than 1 %. This lends support to the hypothesis that the Universe is seeded by B fields that are generated in AGN via this mechanism

Contopoulos, Ioannis↗

On Acoustic Source Specification for Rotor-Stator Interaction Noise Prediction

This paper describes the use of measured source data to assess the effects of acoustic source specification on rotor-stator interaction noise predictions. Specifically, the acoustic propagation and radiation portions of a recently developed coupled computational approach are used to predict tonal rotor-stator interaction noise from a benchmark configuration. In addition to the use of full measured data, randomization of source mode relative phases is also considered for specification of the acoustic source within the computational approach. Comparisons with sideline noise measurements are performed to investigate the effects of various source descriptions on both inlet and exhaust predictions. The inclusion of additional modal source content is shown to have a much greater influence on the inlet results. Reasonable agreement between predicted and measured levels is achieved for the inlet, as well as the exhaust when shear layer effects are taken into account. For the number of trials considered, phase randomized predictions follow statistical distributions similar to those found in previous statistical source investigations. The shape of the predicted directivity pattern relative to measurements also improved with phase randomization, having predicted levels generally within one standard deviation of the measured levels.

Nark, Douglas M.↗

Moments of the Boltzmann collision operator for Coulomb interactions

Exact moments of the Boltzmann collision operator are calculated in the irreducible Hermitian moment expansion written in terms of the random-velocity variable of each species. The formulas are presented in closed, algebraic form and can be straightforwardly implemented in computer algebra systems. They are valid for two arbitrary masses, temperatures, and flow velocities, and hence include all other existing results derived for distribution functions expanded with respect to reference states of one temperature and flow velocity. In comparison, the Landau collisional moments are good approximations for large Coulomb logarithm and small relative flow velocity, but they fail to predict the correct behavior of most collisional moments for large relative flow even for weakly coupled plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Causal Inference Model Based on Random Forests to Identify the Effect of Soil Moisture on Precipitation

Soil moisture influences precipitation mainly through its impact on land–atmosphere interactions. Understanding and correctly modeling soil moisture–precipitation (SM–P) coupling is crucial for improving weather forecasting and subseasonal to seasonal climate predictions, especially when predicting the persistence and magnitude of drought. However, the sign and spatial structure of SM–P feedback are still being debated in the climate research community, mainly due to the difficulty in establishing causal relationships and the high degree of nonlinearity in land–atmosphere processes. To this end, we developed a causal inference model based on the Granger causality analysis and a nonlinear machine learning model. This model includes three steps: nonlinear anomaly decomposition, nonlinear Granger causality analysis, and evaluation of the quality of SM–P feedback, which eliminates the nonlinear response of interannual and seasonal variability and the memory effects of climatic factors and isolates the causal relationship of local SM–P feedback. We applied this model by using National Climate Assessment–Land Data Assimilation System (NCA-LDAS) datasets over the United States. Here, the results highlight the importance of nonlinear atmosphere responses in land–atmosphere interactions. In addition, the strong feedback over the southwestern United States and the Great Plains both highlight the impacts of topographic factors rather than only the sensitivity of evapotranspiration to soil moisture. Furthermore, the SM–P index defined by our framework is used to benchmark Earth system models (ESMs), which provides a new metric for efficiently identifying potential model biases in modeling local land–atmosphere interactions and may help the development of ESMs in improving simulations of water cycle variability and extremes.

54 ENVIRONMENTAL SCIENCES↗

Modeling 2p-2h Interactions in Neutrino-Nucleus Scattering: A Comparative Overview of the Valencia and SuSAv2-MEC Models

2p-2h interactions are crucial for describing ν-A scattering, especially in the "dip region" between the Quasi-Elastic (QE) peak and Δ-resonance production. They involve the ejection of two nucleons, leading to two holes in the nuclear ground state. The underlying nuclear dynamics involve short-range correlations (SRC), long-range correlations (Random Phase Approximation, RPA), and the interplay of one- and two-body currents. Several models attempt to describe 2p-2h interactions, including Microscopic Models (e.g., Valencia), Scaling-Based Models (e.g., SuSAv2-MEC), and Transport Models (e.g., GiBUU). Despite progress, discrepancies exist between models and with data. I Will give an overview of 2p2h from the perspective of two Models Valencia and SuSAv2-MEC.

Hassinin, Karim [Houston U.]↗

MEC modeling

2p-2h interactions are crucial for describing ν-Ar scattering, especially in the "dip region" between the Quasi-Elastic (QE) peak and Δ-resonance production. They involve the ejection of two nucleons, leading to two holes in the nuclear ground state. The underlying nuclear dynamics involve short-range correlations (SRC), long-range correlations (Random Phase Approximation, RPA), and the interplay of one- and two-body currents. Several models attempt to describe 2p-2h interactions like Valencia and SuSAv2-MEC. Despite progress, discrepancies exist between models and with data. I Will give an overview of 2p2h from the perspective of two Models Valencia and SuSAv2-MEC. I will introduce my current work to apply reweighting from SuSAv2 to Valencia on argon which will help improving the systematic uncertainty on MEC for SBN and DUNE.

Hassinin, Karim [Houston U.] (ORCID:00090009778353↗

Dual transposon sequencing profiles the genetic interaction landscape in bacteria

Gene redundancy complicates systematic characterization of gene function as single-gene deletions may not produce discernible phenotypes. We report dual transposon sequencing (dual Tn-seq), a platform for assaying the fitness of a comprehensive double mutant pool in parallel. Dual Tn-seq couples random barcode transposon site sequencing with the Cre-lox system, enabling deep sampling of 73% of the 1.3 million possible double gene deletions in Streptococcus pneumoniae. The genetic interactions identified span a wide range of biochemical processes, revealing new factors in presumably well-studied pathways, exemplified by a cytidine triphosphate synthase PyrJ. Moreover, this approach should permit further investigation of growth condition–specific genetic interactions. Because dual Tn-seq does not require the construction of a large array of single mutants, it should be readily adaptable to various microorganisms.

CTP synthesis↗

Entanglement and confinement in coupled quantum systems

We study some general properties of coupled quantum systems. We consider simple interactions between two copies of identical Hamiltonians such as the SYK model, Pauli spin chains with random magnetic field and harmonic oscillators. Such couplings make the ground states close to the thermofield double states of the uncoupled Hamiltonians. For the coupled SYK model, we push the numerical computation further towards the thermodynamic limit so that an extrapolation in the size of the system is possible. We find good agreement between the extrapolated numerical result and the analytic result in the large-q limit. We also consider the coupled gauged matrix model and vector model, and argue that the deconfinement is associated with the loss of the entanglement, similarly to the previous observation for the coupled SYK model. The understanding of the microscopic mechanism of the confinement/deconfinement transition enables us to estimate the quantum entanglement precisely, and backs up the dual gravity interpretation which relates the deconfinement to the disappearance of the wormhole. Our results demonstrate the importance of the entanglement between the color degrees of freedom in the emergence of the bulk geometry from quantum field theory via holography.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Graph neural networks for CO 2 solubility predictions in Deep Eutectic Solvents

Deep Eutectic Solvents (DESs) are a promising class of solvents for CO 2 capture. DESs are complex mixtures that can be designed to optimize CO solubility and overall capture process efficiency. However, the vast design landscape of DES mixtures makes experimental investigation prohibitive; as such, there is a need for computational models that can quickly and efficiently navigate the design space and inform data collection efforts. In this work, we propose Graph Neural Network (GNN) models for predicting CO 2 solubility for DESs; the GNN leverages a mixture graph representation that captures the molecular structure of the DES components as well as their intermolecular interactions. Here, we compare the GNN framework against alternative architectures (neural networks, graph convolution networks, and random forests) and data representations (molecular fingerprints, sigma profiles, and graphs). We show that the proposed approach offers superior predictive performance; specifically, we show that solubility can be predicted reliably directly from molecular structure (without the need of using sigma profiles as proposed in previous studies). This result is important, as obtaining sigma profiles requires expensive density functional theory computations. We also explored the ability of GNNs to predict solubility for new DES mixtures and operating conditions. We found that the model extrapolates across temperature reliably. However, we also found deficiencies in the ability of the model to predict solubility for DES mixtures, pressures, and molar ratio not included in the training sets; we show that this is due to an inherent lack of chemical diversity in datasets available in the literature. The proposed computational capabilities can thus help navigate the design space of DES and inform data collection efforts. Our models, data, and benchmarks are shared as Python code implemented in Jupyter notebooks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evidence of Skewness and Sub-Gaussian Character in Temperature-Dependent Distributions of One Million Electronic Excitation Energies in PbS Quantum Dots

Obtaining statistical distributions by sampling a large number of conformations is vital for an accurate description of temperature-dependent properties of chemical systems. However, constructing distributions with 105??106 samples is computationally challenging because of the prohibitively high computational cost of performing rst-principles quantum-mechanical calculations. In this work, we present a new technique called the Eective Stochastic Potential Conguration Interaction Singles (ESP-CIS) method to obtain excitation energies. The ESP-CIS method uses random matrix theory for the construction of an eective stochastic representation of the Fock operator and combines it with linear-response theory. Here, we perform excitation calculations on PbS quantum dots (0.75-1.75 nm) at temperatures of 200-400 K. Results from a total of 15 million excitation energy calculations (1 million samples for each of the three dots at ve dierent temperatures) revealed the distributions to be sub-Gaussian in nature with negative skewness. The distributions progressively became red-shifted with increasing temperature. The study shows that random distortions in structure from the minimum-energy geometry of these quantum dots are more likely to lower the excitation energies.

Scher, Jeremy A.↗

First-principles study of electron transport in ScN

We investigate the conduction-band structure and electron mobility in rocksalt ScN based on density functional theory. The first-principles band structure allows us to obtain band velocities and effective masses as a function of energy. Electron-phonon scattering is assessed by explicitly computing the q-dependent electron-phonon matrix elements, with the inclusion of the long-range electrostatic interaction. The influence of free-carrier screening on the electron transport is assessed using the random phase approximation. We find a notable enhancement of electron mobility when the carrier concentration exceeds 10 20 cm -3 . We calculate the room-temperature electron mobility in ScN to be 587 cm2 /Vs at low carrier concentrations. When the carrier concentration is increased, the electron mobility starts to decrease significantly around n = 10 19 cm -3 , and drops to 240 cm 2 /Vs at n = 10 21 cm -3 . We also explore the influence of strain in (111)- and (100)-oriented ScN films. For (111) films, we find that a 1.0% compressive epitaxial strain increases the in-plane mobility by 72 cm 2 /Vs and the out-of-plane mobility by 50 cm 2 /Vs. For (100) films, a 1.0% compressive epitaxial strain increases the out-of-plane mobility by as much as 172 cm2 /Vs, but has a weak impact on the in-plane mobility. Our study sheds light on electron transport in ScN at different electron concentrations and shows how strain engineering could increase the electron mobility.

36 MATERIALS SCIENCE↗

Model Exploration of an Information-Based Healthcare Intervention Using Parallelization and Active Learning

This paper describes the application of a large-scale active learning method to characterize the parameter space of a computational agent-based model developed to investigate the impact of CommunityRx, a clinical information-based health intervention that provides patients with personalized information about local community resources to meet basic and self-care needs. Additionally, the diffusion of information about community resources and their use is modeled via networked interactions and their subsequent effect on agents' use of community resources across an urban population. A random forest model is iteratively fitted to model evaluations to characterize the model parameter space with respect to observed empirical data. We demonstrate the feasibility of using high-performance computing and active learning model exploration techniques to characterize large parameter spaces; by partitioning the parameter space into potentially viable and non-viable regions, we rule out regions of space where simulation output is implausible to observed empirical data. We argue that such methods are necessary to enable model exploration in complex computational models that incorporate increasingly available micro-level behavior data. We provide public access to the model and high-performance computing experimentation code.

97 MATHEMATICS AND COMPUTING↗

Costs of symmetric strategic games with defenses

A companion note discusses the crisis stability of symmetric offensive missile forces. This note extends the analysis to include symmetric defensive forces. It derives Nash equilibrium optimal missile defenses, which are used to study the impact of varying defenses on strike costs and stability. It treats the option to strike first as a random decision by nature, which is consistent with previous experience and provides a rational basis for interaction and deterrence without which the study of stability is vacuous.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

On the magnon interaction in haematite. I - Magnon energy of optical mode.

The effect of magnon interaction on the magnon energies of haematite was studied by the use of a recently developed random phase approximation. In this study, the spin Hamiltonian and the magnon energy were written in a power series of (1/S), where S denotes the magnitude of spin. It is known that the expression of magnon energy is rigorous up to the second term of this series. It is found that the optic mode energy is small if the free optic mode energy is small, which is contrary to Herbert's (1969) conclusion. This direct proportionality between the optic mode energy and the free optic mode energy was not confirmed in the higher order terms of 1/S.

Nagai, O.↗

Factors limiting the discrimination and quantification of terrestrial features using remotely sensed radiance

In this paper, factors controlling the radiance incident on a remote-sensing device and the interaction of the sensor with upwelling radiance are considered. Attention is also given to systematic and random radiance variations across an image: while the former may be corrected for (to an extent) the latter may not, so that it is necessary to be aware of the impact of random variations on target identification, discrimination and quantification. Both the optical reflective and the thermal-infrared parts of the spectrum are considered. Equations are presented to concisely illustrate the processes involved.

Duggin, M. J.↗

Rationale for two phase polymer system microgravity separation experiments

The two-phase systems that result when aqueous solutions of dextran and poly(ethylene glycol) are mixed at concentrations above a few percent are discussed. They provide useful media for the partition and isolation of macromolecules and cell subpopulations. By manipulating their composition, separations based on a variety of molecular and surface properties are achieved, including membrane hydrophobic properties, cell surface charge, and membrane antigenicity. Work on the mechanism of cell partition shows there is a randomizing, nonthermal energy present which reduces separation resolution. This stochastic energy is probably associated with hydrodynamic interactions present during separation. Because such factors should be markedly reduced in microgravity, a series of shuttle experiments to indicate approaches to increasing the resolution of the procedure are planned.

Brooks, D. E.↗

Fragmented molecular complexes: The role of the magnetic field in feeding internal supersonic motions

A hierarchical structure for molecular complexes in their cold phase i.e., preceeding the formation of massive stars, was derived from extensive large scale CO(13)(J=1=0) observations: the mass is found to be distributed into virialized clouds which fill only a very low fraction approx. 01 of the volume of the complex and are supported against gravity by internal supersonic motions. An efficient mechanism was found to transfer kinetic energy from the orbital motions of the clouds to their internal random motions. The large perturbations of the magnetic field induced at the cloud boundaries by their interactions with their neighbors generate systems of hydromagnetic waves trapped inside the clouds. The magnetic field lines being closely coupled to the gas at the densities which prevail in the bulk of the clouds volume, internal velocity dispersion is thus generated. Some conclusions derived from this data are given.

Falgarone, E.↗

HD 43246 and HD 127208 - Two unusual F-G + B binary systems

New optical spectroscopic observations along with ultraviolet IUE observations have been obtained for the two interacting F or G III + B V binaries: HD 43246 and HD 127208. Photometric observations indicate random changes superimposed on regular ellipsoidal light variations, the latter probably the result of tidal distortion of the giant primaries. Mass transfer and loss is apparent in inverted mass ratios derived from orbital analysis, strong wind features present in the spectra, and the presence of circumsystem shells. Regular and irregular changes in the spectral features are discussed in this context.

Dempsey, Robert C.↗