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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Why does the apparent mass of a coronal mass ejection increase?

Mass is one of the most fundamental parameters characterizing the dynamics of a coronal mass ejection (CME). It has been found that CME apparent mass measured from the brightness enhancement in coronagraphs increases during its evolution in the corona. However, the physics behind it is not clear. Does the apparent mass gain come from the outflow from the dimming regions in the low corona, or from the pileup of the solar wind plasma around the CME? Here we analyze the mass evolution of six CME events. Based on the coronagraph observations from the Solar Terrestrial Relations Observatory, we find that their masses increased by a factor of 1.3–1.7 from 7 to 15 R{sub S}, where the occulting effect is negligible. We then adopt the “snow-plow” model to calculate the mass contribution of the piled-up solar wind. The result gives evidence that the solar wind pileup probably makes a non-negligible contribution to the mass increase. In the height range from about 7 to 15 R{sub S}, the ratio of the modeled to the measured mass increase is roughly larger than 0.55 though the ratios are believed to be overestimated. It is not clear yet whether the solar wind pileup is a major contributor to the final mass derived from coronagraph observations, but it does play an increasingly important role in the mass increase as a CME moves further away from the Sun.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

ON THE INTRINSIC CONTINUUM LINEAR POLARIZATION OF CLASSICAL Be STARS: THE EFFECTS OF METALLICITY AND ONE-ARMED DENSITY PERTURBATIONS

We report on the effects of two disk properties on the continuum linear polarization signature of classical Be stars. First, we investigate the effect of including metallicity in computing the thermal structure of the circumstellar gas on the resulting polarimetric Balmer jump. The Balmer jump is a distinguishing feature of the polarization signature in these objects and, as such, can be used as a tool for differentiating classical Be stars from similar H{alpha}-emitters identified through conventional photometric techniques. We find that although low-metallicity environments will have hotter disk temperatures on average, the temperature change alone cannot account for the discrepancy in the frequency of Balmer jumps between low-metallicity and solar-metallicity stellar populations. Second, we investigate the effect of including a global one-armed oscillation in the gas density distribution of the modeled disk. We find that a non-axisymmetric perturbation pattern yields discernible variations in the predicted polarization level. If these density oscillations are present in the inner region of classical Be star disks, the polarimetric variations should produce a periodic signature which can help characterize the dynamical nature of the gas near the star.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Linking stem rehydration kinetics to hydraulic traits using a novel method and mechanistic model

Background: Despite the recognized importance of hydraulic capacitance as a mechanism used by plants to maintain hydraulic functioning during high transpiration, characterizing the dynamics of capacitance remains a challenge. Methods: For this work, we used a novel ‘two-balance method’ to investigate relationships between stem rehydration kinetics and other hydraulic traits in multiple tree species, and we developed a model to explore stem rehydration kinetics further. Key Results: We found that: (1) rehydration time constants and the amount of water uptake occurring during rehydration differed significantly across species; (2) time constants did not change with declining water potential (Ψ), while water uptake increased at lower Ψ in some species; (3) longer time constants were associated with lower wood density, higher capacitance and less negative stem pressures causing 50 % loss of hydraulic conductivity (P 50 ); (4) greater water uptake occurred in stems with lower wood density and less negative P 50 values; and (5) the model could estimate the total hydraulic resistance of the rehydration path, which cannot be measured directly. Conclusions: Overall, the two-balance method can be used to examine rehydration dynamics quickly and thoroughly in detached woody stems. This method has the potential to improve our understanding of how capacitance functions across tree species, which is an often-overlooked component of whole-plant hydraulics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Synthetic soils for ecological and synthetic biology applications

Soils are heterogeneous and dynamic systems characterized by complex physical, chemical, and biological interactions. Understanding these interactions is critical, as they influence plant productivity, global biogeochemical cycles, and ecosystem resilience. While ecologists have long studied soils in field, greenhouse, and laboratory settings, their complexity and heterogeneity make it challenging to pinpoint key properties driving biological processes and derive mechanistic insights. Advancements in synthetic biology, which seeks to engineer and control biological processes in soils, have increased the demand for standardized and controllable experimental platforms. These platforms, referred to here as ‘synthetic soils’, are systems designed to reproduce selected physicochemical characteristics of natural soils in a simplified and defined format, allowing scientists to systematically change soil physicochemical properties (i.e. texture, mineralogy, pH) to study how biological components (i.e. microbes, plants, soil fauna, etc.) respond to, modify, or interact within these controlled environments. This review explores existing synthetic soils, their advantages, limitations, and applications in ecology and synthetic biology, and discusses potential directions for their future development.

artificial soils↗
DOE OSTI2022

SEED LIPID DROPLET PROTEIN1, SEED LIPID DROPLET PROTEIN2, and LIPID DROPLET PLASMA MEMBRANE ADAPTOR mediate lipid droplet–plasma membrane tethering

Membrane contact sites (MCSs) are interorganellar connections that allow for the direct exchange of molecules, such as lipids or Ca 2+ between organelles, but can also serve to tether organelles at specific locations within cells. Here, we identified and characterized three proteins of Arabidopsis thaliana that form a lipid droplet (LD)–plasma membrane (PM) tethering complex in plant cells, namely LD-localized SEED LD PROTEIN (SLDP) 1 and SLDP2 and PM-localized LD-PLASMA MEMBRANE ADAPTOR (LIPA). Using proteomics and different protein–protein interaction assays, we show that both SLDPs associate with LIPA. Disruption of either SLDP1 and SLDP2 expression, or that of LIPA, leads to an aberrant clustering of LDs in Arabidopsis seedlings. Ectopic co-expression of one of the SLDPs with LIPA is sufficient to reconstitute LD–PM tethering in Nicotiana tabacum pollen tubes, a cell type characterized by dynamically moving LDs in the cytosolic streaming. Furthermore, confocal laser scanning microscopy revealed both SLDP2.1 and LIPA to be enriched at LD–PM contact sites in seedlings. These and other results suggest that SLDP and LIPA interact to form a tethering complex that anchors a subset of LDs to the PM during post-germinative seedling growth in Arabidopsis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Sendai virus intra-host population dynamics and host immunocompetence influence viral virulence during in vivo passage

In vivo serial passage of non-pathogenic viruses has been shown to lead to increased viral virulence, and although the precise mechanism(s) are not clear, it is known that both host and viral factors are associated with increased pathogenicity. Under- or overnutrition leads to a decreased or dysregulated immune response and can increase viral mutant spectrum diversity and virulence. The objective of this study was to identify the role of viral mutant spectra dynamics and host immunocompetence in the development of pathogenicity during in vivo passage. Because the nutritional status of the host has been shown to affect the development of viral virulence, the diet of animal model reflected two extremes of diets which exist in the global population, malnutrition and obesity. Sendai virus was serially passaged in groups of mice with differing nutritional status followed by transmission of the passaged virus to a second host species, guinea pigs. Viral population dynamics were characterized using deep sequence analysis and computational modeling. Histopathology, viral titer and cytokine assays were used to characterize viral virulence. Viral virulence increased with passage and the virulent phenotype persisted upon passage to a second host species. Additionally, nutritional status of mice during passage influenced the phenotype. Sequencing revealed the presence of several non-synonymous changes in the consensus sequence associated with passage, a majority of which occurred in the hemagglutinin-neuraminidase and polymerase genes, as well as the presence of persistent high frequency variants in the viral population. In particular, an N1124D change in the consensus sequences of the polymerase gene was detected by passage 10 in a majority of the animals. In vivo comparison of an 1124D plaque isolate to a clone with 1124N genotype indicated that 1124D was associated with increased virulence.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Repulsively bound exciton-biexciton states in high-spin fermions in optical lattices

We show that the interplay between spin-changing collisions and quadratic Zeeman coupling provides a mechanism for the formation of repulsively bound composites in high-spin fermions, which we illustrate by considering spin flips in an initially polarized hard-core one-dimensional Mott insulator of spin-3/2 fermions. We show that after the flips the dynamics is characterized by the creation of two types of exciton-biexciton composites. We analyze the conditions for the existence of these bound states and discuss their intriguing properties. In particular we show that the effective mass and stability of the composites depends nontrivially on spin-changing collisions, on the quadratic Zeeman effect, and on the initial exciton localization. Finally, we show that the composites may remain stable against inelastic collisions, opening the possibility of interesting quantum composite phases.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Operator dynamics in Floquet many-body systems

We study operator dynamics in many-body quantum systems, focusing on generic features of systems that are ergodic, spatially extended, and lack conserved densities. Quantum circuits of various types provide simple models for such systems. We focus on Floquet quantum circuits, comparing their behavior with what has been found previously for circuits that are random in time. Floquet circuits, which have discrete time-translation symmetry, represent an intermediate case between circuits that are random in time and lack any symmetry, and systems with a time-independent Hamiltonian and continuous time-translation invariance. By making this comparison, one of our aims is to identify signatures of time-translation symmetry in Floquet operator dynamics. To characterize behavior we examine a variety of quantities in solvable models and numerically: operator autocorrelation functions; the partial spectral form factor; the out-of-time-order correlator (OTOC); and the paths in operator space that make the dominant contributions to the ensemble-averaged autocorrelation functions. Our most striking result is that ensemble-averaged autocorrelation functions show behavior that is distinctively different in Floquet systems compared to systems in which successive time-steps are independent. Specifically, while average autocorrelation functions decay on a microscopic timescale for circuits that are random in time, in Floquet systems they have a late-time tail with a duration that grows parametrically with the size of the operator support. In the simplest models this tail is separated from the initial decay by a minimum, so that the average autocorrelation function has an intermediate-time peak. The existence of these tails provides a way to understand deviations of the spectral form factor from random matrix behavior at times shorter than the Thouless time. In contrast to this feature in autocorrelation functions, we find no new aspects to the behavior of OTOCs for Floquet models compared to random-in-time circuits. We show that this difference between averaged autocorrelation functions and OTOCs can be understood in terms of the paths in operator space that contribute to the two quantities: paths for the former retain a limited support at late times, while paths for the latter are dominated by operator spreading. Published by the American Physical Society 2025

Yoshimura, Takato (ORCID:0000000309159846)↗
DOE OSTI2019

Operator spreading in quantum maps

Operators in ergodic spin chains are found to grow according to hydrodynamical equations of motion. The study of such operator spreading has aided our understanding of many-body quantum chaos in spin chains. Here we initiate the study of “operator spreading” in quantum maps on a torus, systems which do not have a tensor-product Hilbert space or a notion of spatial locality. Using the perturbed Arnold cat map as an example, we analytically compare and contrast the evolutions of functions on classical phase space and quantum operator evolutions, and identify distinct timescales that characterize the dynamics of operators in quantum chaotic maps. Until an Ehrenfest time, the quantum system exhibits classical chaos, i.e., it mimics the behavior of the corresponding classical system. After an operator scrambling time, the operator looks “random” in the initial basis, a characteristic feature of quantum chaos. These timescales can be related to the quasienergy spectrum of the unitary via the spectral form factor. Furthermore, we show examples of “emergent classicality” in quantum problems far away from the classical limit. Lastly, we study operator evolution in nonchaotic and mixed quantum maps using the Chirikov standard map as an example.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Solving nuclear structure problems with the adaptive variational quantum algorithm

Here we use the Lipkin-Meshkov-Glick (LMG) model and the valence-space nuclear shell model to examine the likely performance of variational quantum eigensolvers in nuclear-structure theory. The LMG model exhibits both a phase transition and spontaneous symmetry breaking at the mean-field level in one of the phases, features that characterize collective dynamics in medium-mass and heavy nuclei. We show that with appropriate modifications, the ADAPT-VQE algorithm, a particularly flexible and accurate variational approach, is not troubled by these complications. We treat up to 12 particles and show that the number of quantum operations needed to approach the ground-state energy scales linearly with the number of qubits. We find similar scaling when the algorithm is applied to the nuclear shell model with realistic interactions in the sd and pf shells. Although most of these simulations contain no noise, we use a noise model from real IBM hardware to show that for the LMG model with four particles, weak noise has no effect on the efficiency of the algorithm.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2011

Configurational subdiffusion of peptides: A network study

Molecular dynamics (MD) simulation of linear peptides reveals configurational subdiffusion at equilibrium extending from 10-12 to 10-8 s. Rouse chain and continuous-time random walk models of the subdiffusion are critically discussed. Network approaches to analyzing MD simulations are shown to reproduce the time dependence of the subdiffusive mean squared displacement, which is found to arise from the fractal-like geometry of the accessible volume in the configuration space. Convergence properties of the simulation pertaining to the subdiffusive dynamics are characterized and the effect on the subdiffusive properties of representing the solvent explicitly or implicitly is compared. Non-Markovianity and other factors limiting the range of applicability of the network models are examined.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Quantifying hydrodynamic collective states of magnetic colloidal spinners and rollers

Ferromagnetic microparticles energized by an alternating magnetic field exhibit fascinating collective behavior ranging from the emergent self-assembled spinners to a variety of self-organized rolling states. Despite their simplicity, quantifying their essentially multibody collective behavior remains elusive due to a multitude of relevant interactions, from short-range collisions to long-range magnetic and hydrodynamic forces. Here we develop a high-performance computational algorithm based on smoothed particle hydrodynamics to quantify the role of individual interactions in the emergent collective state. The computational model provides insight into the role of hydrodynamic interaction on the onset of collective behavior and allows characterization of dynamic regimes that are hard to access experimentally. Comparison with high-resolution experimental data allows validation of the algorithm. Our work expands the scope of modern computational tools for predictive modeling of microscopic active systems and provides insight into the intricate role of hydrodynamic interactions on the onset of collective behavior in living and synthetic active matter.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Distributed X-ray photon correlation spectroscopy data reduction using Hadoop MapReduce

Multi-speckle X-ray photon correlation spectroscopy (XPCS) is a powerful technique for characterizing the dynamic nature of complex materials over a range of time scales. XPCS has been successfully applied to study a wide range of systems. Recent developments in higher-frame-rate detectors, while aiding in the study of faster dynamical processes, creates large amounts of data that require parallel computational techniques to process in near real-time. Here, an implementation of the multi-tau and two-time autocorrelation algorithms using the Hadoop MapReduce framework for distributed computing is presented. In conclusion, the system scales well with regard to the increase in the data size, and has been serving the users of beamline 8-ID-I at the Advanced Photon Source for near real-time autocorrelations for the past five years.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Novel Technique for Developing Linearized Convex System Models from Experimentally Derived Data

This paper presents a novel technique for generating a convex system model from an experimentally derived data set which features variance among repeated measurements. The convex system model developed as a test case characterizes the dynamic system losses of a vanadium redox flow battery as a function of the active power output and the battery state of charge. The technique hinges on a pre-cleaning via clustering procedure which precedes the formation of a planar convex hull comprised of triangular simplices. The clustering procedure efficiently reduces the experimental data set while mitigating variance among repeated measurements and removes outliers. Ultimately, the lower evelope of the planar convex hull serves as the desired convex system model. The proposed technique reduces systematic model error which is otherwise present when directly developing a planar convex hull model based on an unreduced data set.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

Fundamental radiological and geometric performance of two types of proton beam modulated discrete scanning systems

Purpose: The purpose of this investigation was to compare and contrast the measured fundamental properties of two new types of modulated proton scanning systems. This provides a basis for clinical expectations based on the scanned beam quality and a benchmark for computational models. Because the relatively small beam and fast scanning gave challenges to the characterization, a secondary purpose was to develop and apply new approaches where necessary to do so.Methods: The following performances of the proton scanning systems were investigated: beamlet alignment, static in-air beamlet size and shape, scanned in-air penumbra, scanned fluence map accuracy, geometric alignment of scanning system to isocenter, maximum field size, lateral and longitudinal field uniformity of a 1 l cubic uniform field, output stability over time, gantry angle invariance, monitoring system linearity, and reproducibility. A range of detectors was used: film, ionization chambers, lateral multielement and longitudinal multilayer ionization chambers, and a scintillation screen combined with a digital video camera. Characterization of the scanned fluence maps was performed with a software analysis tool.Results: The resulting measurements and analysis indicated that the two types of delivery systems performed within specification for those aspects investigated. The significant differences were observed between the two types of scanning systems where one type exhibits a smaller spot size and associated penumbra than the other. The differential is minimum at maximum energy and increases inversely with decreasing energy. Additionally, the large spot system showed an increase in dose precision to a static target with layer rescanning whereas the small spot system did not.Conclusions: The measured results from the two types of modulated scanning types of system were consistent with their designs under the conditions tested. The most significant difference between the types of system was their proton spot size and associated resolution, factors of magnetic optics, and vacuum length. The need and benefit of mutielement detectors and high-resolution sensors was also shown. The use of a fluence map analytical software tool was particularly effective in characterizing the dynamic proton energy-layer scanning.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Hydroxide films on mica form charge-stabilized microphases that circumvent nucleation barriers

Crystal nucleation is facilitated by transient, nanoscale fluctuations that are extraordinarily difficult to observe. Here, we use high-speed atomic force microscopy to directly observe the growth of an aluminum hydroxide film from an aqueous solution and characterize the dynamically fluctuating nanostructures that precede its formation. Nanoscale cluster distributions and fluctuation dynamics show many similarities to the predictions of classical nucleation theory, but the cluster energy landscape deviates from classical expectations. Kinetic Monte Carlo simulations show that these deviations can arise from electrostatic interactions between the clusters and the underlying substrate, which drive microphase separation to create a nanostructured surface phase. This phase can evolve seamlessly from a low-coverage state of fluctuating clusters into a high-coverage nanostructured network, allowing the film to grow without having to overcome classical nucleation barriers.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Plateau Phenomenon in Gradient Descent Training of RELU Networks: Explanation, Quantification, and Avoidance

The ability of neural networks to provide ‘best in class’ approximation across a wide range of applications is well-documented. Nevertheless, the powerful expressivity of neural networks comes to naught if one is unable to effectively train (choose) the parameters defining the network. In general, neural networks are trained by gradient descent type optimization methods,a stochastic variant thereof. In practice, such methods result in the loss function decreases rapidly at the beginning of training but then, after a relatively small number of steps, significantly slow down. The loss may even appear to stagnate over the period of a large number of epochs, only to then suddenly start to decrease fast again for no apparent reason. This so-called plateau phenomenon manifests itself in many learning tasks. The present work aims to identify and quantify the root causes of plateau phenomenon.analysis is carried out in the setting of univariate ReLU networks. No assumptions are made on the number of neurons relative to the number of training data, and our results hold for both the lazy and adaptive regimes. Here, the main findings are: plateaux correspond to periods during which activation patterns remain constant, where activation pattern refers to the number of data points that activate a given neuron; quantification of convergence of the gradient flow dynamics; and, characterization stationary points in terms solutions of local least squares regression lines over subsets of the training data. Based on these conclusions, we propose a new iterative training method, the Active Neuron Least Squares (ANLS), characterised by the explicit adjustment of the activation pattern at each step, which is designed to enable a quick exit from a plateau. Illustrative numerical examples are included throughout.

97 MATHEMATICS AND COMPUTING↗