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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Charge influence on point defect interactions with xenon bubbles in uranium dioxide

The interaction of xenon (Xe) bubbles with small self-defects in uranium dioxide (UO2) has been studied using molecular statics simulations. The results show that the pressure and size of bubbles have a minimal impact on the heterogeneity of the interaction between a charge neutral Xe bubble and charged point defects, while the local charge distribution around the bubble overwhelmingly determines the interaction strength and critical interaction distance. The charge effect on the interactions between Xe bubbles and defects was further confirmed by assessing the point defect interaction energies with negatively or positively charged Xe bubbles. The Xe density, or pressure, has a much smaller effect on the interaction energy between charged bubbles and small defects at least for low and medium pressure bubbles. The interactions between charged Xe bubbles and point defects basically follow the Coulomb electrostatic interaction law, which is independent of the empirical potentials employed for the Xe–UO2 system in this work.

Yang, L. (ORCID:0000000322166071)↗
DOE OSTI2023

Schematic model for induced fission in a configuration-interaction approach

We model fission at barrier-top energies in a simplified model space that permits comparison of different components of the residual nucleon-nucleon interaction. The model space is built on particle-hole excitations of reference configurations. These are Slater determinants of uniformly spaced orbitals characterized only by their quantum numbers and orbital energies. The residual interaction in the Hamiltonian includes the diabatic interaction connecting similar orbitals at different deformations, the pairing interaction between like nucleons, and a schematic off-diagonal neutron-proton interaction. We find that the fission reaction probability is sensitive to the off-diagonal neutron-proton interaction much more than to the pairing and the diabatic interactions. In particular, the transmission coefficients become insensitive to the strength of the pairing interaction when the neutron-proton interaction is large. Here, we also find that the branching ratio is insensitive to the final-state scission dynamics, as is assumed in the well-known Bohr-Wheeler theory.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Modifying PyUltraLight to model scalar dark matter with self-interactions

Here we introduce a modification of the pysiultralight code that models the dynamical evolution of ultralight axionlike scalar dark matter fields. Our modified code, pysiultralight, adds a quartic, self-interaction term to reflect the one which arises naturally in axionlike particle models. Using a particle mass of 10−22 eV/c 2 , we show that pysiultralight produces spatially oscillating solitons, exploding solitons, and collapsing solitons which prior analytic work shows will occur with attractive self-interactions. Using our code we calculate the oscillation frequency as a function of soliton mass and equilibrium radius in the presence of attractive self-interactions. We show that when the soliton mass is below the critical mass ($M_c$ = $\frac{\sqrt{3}}{2} M_{max}$) described by Chavanis and the initial radius is within a specific range, solitons are unstable and explode. We test the maximum mass criteria described by Chavanis and Chavanis and Delfini for a soliton to collapse when attractive self-interactions are included. We also analyze both binary soliton collisions and a soliton rotating around a central mass with attractive and repulsive self-interactions. We find that when attractive self-interactions are included, the density profiles get distorted after a binary collision. We also find that a soliton is less susceptible to tidal stripping when attractive self-interactions are included. We find that the opposite is true for repulsive self-interactions in that solitons would be more easily tidally stripped. Including self-interactions might therefore influence the survival timescales of infalling solitons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Learning epistatic polygenic phenotypes with Boolean interactions

Detecting epistatic drivers of human phenotypes is a considerable challenge. Traditional approaches use regression to sequentially test multiplicative interaction terms involving pairs of genetic variants. For higher-order interactions and genome-wide large-scale data, this strategy is computationally intractable. Moreover, multiplicative terms used in regression modeling may not capture the form of biological interactions. Building on the Predictability, Computability, Stability (PCS) framework, we introduce the epiTree pipeline to extract higher-order interactions from genomic data using tree-based models. The epiTree pipeline first selects a set of variants derived from tissue-specific estimates of gene expression. Next, it uses iterative random forests (iRF) to search training data for candidate Boolean interactions (pairwise and higher-order). We derive significance tests for interactions, based on a stabilized likelihood ratio test, by simulating Boolean tree-structured null (no epistasis) and alternative (epistasis) distributions on hold-out test data. Finally, our pipeline computes PCS epistasis p-values that probabilisticly quantify improvement in prediction accuracy via bootstrap sampling on the test set. We validate the epiTree pipeline in two case studies using data from the UK Biobank: predicting red hair and multiple sclerosis (MS). In the case of predicting red hair, epiTree recovers known epistatic interactions surrounding MC1R and novel interactions, representing non-linearities not captured by logistic regression models. In the case of predicting MS, a more complex phenotype than red hair, epiTree rankings prioritize novel interactions surrounding HLA-DRB1 , a variant previously associated with MS in several populations. Taken together, these results highlight the potential for epiTree rankings to help reduce the design space for follow up experiments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Spontaneous bodily coordination varies across affective and intellectual child-adult interactions

Research on child-adult interactions has identified that the morphology of bodily coordination seems to be sensitive to age and type of interaction. Mirror-like imitation emerges earlier in life and is more common during emotionally laden interactions, while anatomical imitation is acquired later and associated with cognitive tasks. However, it remains unclear whether these morphologies also vary with age and type of interaction during spontaneous coordination. Here we report a motion capture study comparing the spontaneous coordination patterns of thirty-five 3-year-old (20 girls; M age = 3.15 years) and forty 6-year-old children (20 girls; M age = 6.13 years) interacting with unacquainted adults during two storytelling sessions. The stories narrated the search of a character for her mother (Predominantly Affective Condition) or an object (Predominantly Intellectual Condition) inside a supermarket. Results show that children of both ages consistently coordinated their spontaneous movements towards adult storytellers, both in symmetric and asymmetric ways. However, symmetric coordination was more prominent in 3-year-old children and during predominantly emotional interactions, whereas asymmetric coordination prevailed in 6-year-old children and during predominantly intellectual interactions. These results add evidence from spontaneous interactions in favor of the hypothesis that symmetric coordination is associated with affective interactions and asymmetric coordination with intellectual ones.

Cornejo, Carlos↗
NASA NTRS1989

Near-planar TS waves and longitudinal vortices in channel flow: Nonlinear interaction and focusing

The nonlinear interaction between planar or near-planar Tollmien-Schlichting waves and longitudinal vortices, induced or input, is considered theoretically for channel flows at high Reynolds numbers. Several kinds of nonlinear interaction, dependent on the input amplitudes and wavenumbers or on previously occurring interactions, are found and inter-related. The first, Type 1, is studied the most here and it usually produces spanwise focusing of both the wave and the vortex motion, within a finite scaled time, along with enhancement of both their amplitudes. This then points to the nonlinear interaction Type 2 where new interactive effects come into force to drive the wave and the vortex nonlinearly. Types 3, 4 correspond to still higher amplitudes, with 3 being related to 2, while 4 is connected with a larger-scale interaction 5 studied in an allied paper. Both 3, 4 are subsets of the full three-dimensional triple-deck-lie interaction, 6. The strongest nonlinear interactions are those of 4, 5, 6 since they alter the mean-flow profile substantially, i.e., by an 0(1) relative amount. All the types of nonlinear interaction however can result in the formation of focussed responses in the sense of spanwise concentrations and/or amplifications of vorticity and wave amplitude.

Hall, P.↗
NASA NTRS1990

Hidden interaction in SBO galaxies

Galaxies, like plants, show a large variety of grafts: an individual of some type connects physically with a neighborhood of same or different type. The effects of these interactions between galaxies have a broad range of morphologies depending, among other quantities, on the distance of the closest approach between systems and the relative size of the two galaxies. A sketch of the possible situations is shown in tabular form. This botanical classification is just indicative, because the effects of interactions can be notable also at relatively large separations, when additional conditions are met, as for example low density of the interacting systems or the presence of intra-cluster gas. In spite of the large variety of encounters and effects, in the literature the same terms are often used to refer to different types of interactions. Analysis indicates that only few of the situations show evident signs of interaction. They appear to be most relevant when the size of the two galaxies is comparable. Bridges and tails, like the well known case of NGC 4038/39, the Antennae, are only observed for a very low percentage of all galaxies (approx. 0.38 percent, Arp and Madore 1977). In most cases of gravitational bond between two galaxies, the effects of interactions are not relevant or evident. For instance, the detection of stellar shells (Malin and Carter 1983), which have been attributed to the accretion of gas stripped from another galaxy or to the capture and disruption of a small stellar system (Quinn 1984), requires particular observing and reduction techniques. Besides these difficulties of detection, time plays an important role in erasing, within a massive galaxy, the effects of interactions with smaller objects. This can happen on a timescale shorter than the Hubble time, so the number of systems now showing signs of interaction suggests lower limits to the true frequency of interactions in the life-time of a stellar system.

Galletta, G.↗
NASA NTRS1990

Near-planar TS waves and longitudinal vortices in channel flow - Nonlinear interaction and focussing

The nonlinear interaction between planar or near-planar Tollmien-Schlichting waves and longitudinal vortices, induced or input, is considered theoretically for channel flows at high Reynolds numbers. Several kinds of nonlinear interaction, dependent on the input amplitudes and wavenumbers or on previously occurring interactions, are found and inter-related. The first, Type 1, is studied the most here and it usually produces spanwise focusing of both the wave and the vortex motion, within a finite scaled time, along with enhancement of both their amplitudes. This then points to the nonlinear interaction Type 2 where new interactive effects come into force to drive the wave and the vortex nonlinearly. Types 3, 4 correspond to still higher amplitudes, with 3 being related to 2, while 4 is connected with a larger-scale interaction 5 studied in an allied paper. Both 3, 4 are subsets of the full three-dimensional triple-deck-lie interaction, 6. The strongest nonlinear interactions are those of 4, 5, 6 since they alter the mean-flow profile substantially, i.e., by an O(1) relative amount. All the types of nonlinear interaction, however, can result in the formation of focused responses in the sense of spanwise concentrations and/or amplifications of vorticity and wave amplitude.

Hall, Philip↗
NASA NTRS1993

Deep H alpha images of interacting galaxies

Gravitational interactions between galaxies are believed to increase star formation activity dramatically, and most of the brightest starburst galaxies show clear signs of recent interactions. However, it is still not known how interaction triggers star formation, nor are there models to relate the type or strength of interaction to the location or amount of star formation. We report on a series of deep H alpha images of interacting and post-interaction galaxies which we took with the purpose of finding the young stars and ionized gas in these objects. We were motivated in part by the hope that by studying the very recently formed stars we could see how the interaction process had affected the star formation. We observed the galaxies through 50 A-wide filters, one on the redshifted H alpha line and one off, and a standard R filter. Depending on the galaxy and conditions, images in the B, V, and I filters were also obtained. The images were recorded with a 4x7 ft. or 17 ft. diameter CCD at the 1-meter telescope of the Wise Observatory in Mitzpe Ramon. The H alpha and continuum images are used, together with observations at other wavelengths, to put together as complete a picture as possible of star formation and interactions in each galaxy. The complete observation set is not yet available for all the galaxies but certain results are already clear. There do not seem to be any correlations between H 1 and H alpha structures. In some H 1 plume galaxies H alpha extensions were seen on the other side of the galaxy from the H 1; in others extensive H alpha filaments have been found but not H 1. The preliminary results agree with the simplest model that interaction-induced star formation will be concentrated in the system center, since that is where the mass ends up.

Beck, S. C.↗
DOE OSTI2020

Deep Learning Prediction of Interspecies Interactions from Self-organized Spatiotemporal Patterns of Co-evolving Organisms

Microorganisms colonizing natural habits such as soils co-evolve to form specific spatial patterns through interspecies interactions. These self-organized patterns are a key ecological phenotype, which provides critical information on their interaction mechanisms. However, conventional network inference techniques that analyze species population data in bulk have yet to be extended to account for such spatial heterogeneity. Here we proposed supervised deep learning as a new network inference tool for predicting interspecies interactions from spatiotemporal patterns of microbial evolution. Due to lack of biological imaging data that can be used for training deep learning networks, we used in silico data generated from high-fidelity agent-based models to determine model structure and parameters. Even though networks were trained under simple configurations where interaction coefficients are assumed to be spatially invariant, we demonstrated that the resulting model can be utilized to successfully predict spatial variation of interactions in more complex domains (i.e., configured with a context-dependent mixture of interaction coefficients) as well as in simple domains without further training. In the further test against real biological data obtained through imaging experiments of a binary consortium (Pseudomonas fluorescens and a mutant of Escherichia coli), our model also predicted the dramatic shifts in interactions of the two organisms across different environmental contexts. Through various successful demonstrations in this work, the combined use of the agent-based model and machine learning algorithm provides a means to use new type of data - microscopic images - for extracting microbial interactions, therefore presenting itself as a useful tool for the analysis of more complex microbial community interactions.

Lee, Joon-Yong↗
DOE OSTI2024

Investigating Electro-Nuclear Interactions in a New Dark Matter Search

Electro-nuclear (EN) interactions are interactions in which an incident electron collides with a nucleus, scattering the electron and creating byproduct particles. Such interactions are of interest to neutrino physicists, who use EN interactions to inform model building of neutrino-nucleus interactions. The Light Dark Matter Experiment (LDMX) is a small-scale, fixed-target, electron beam experiment which seeks to probe for dark matter and mediator particle production in the sub-GeV mass region. The 8GeV LDMX electron beam will serve as an opportunity to study electro-nuclear interactions in final states in the multi-GeV region. LDMX s missing energy trigger for dark matter interactions however, will not be sufficient to efficiently capture EN interactions. An additional trigger is needed. Using simulated events, that included background and EN interactions, a trigger on momentum was developed.

Croteau, Beatrice↗
DOE OSTI2021

Material Interactions in Severe Accidents – Benchmarking the MELCOR V2.2 Eutectics Model for a BWR-3 MARK-I Station Blackout: Part I – Single Case Analysis

Here in this analysis, the two material interaction models available in the MELCOR code are benchmarked for a severe accident at a BWR under representative Fukushima Daiichi boundary conditions. This part of the benchmark investigates the impact of each material interaction model on accident progression through a detailed single case analysis. It is found that the eutectics model simulation exhibits more rapid accident progression for the duration of the accident. The slower accident progression exhibited by the interactive materials model simulation, however, allows for a greater degree of core material oxidation and hydrogen generation to occur, as well as elevated core temperatures during the ex-vessel accident phase. The eutectics model simulation exhibits more significant degradation of core components during the late in-vessel accident phase – more debris forms and relocates to the lower plenum before lower head failure. The larger debris bed observed in the eutectics model simulation also reaches higher temperatures, presenting a more significant thermal challenge to the lower head until its failure. At the end of the simulated accident scenario, however, core damage is comparable between both simulations due to significant core degradation that occurs during the ex-vessel phase in the interactive materials model simulation. A key difference between the two models’ performance is the maximum temperatures that can be reached in the core and therefore the maximum ΔT between any two components. When implementing the interactive materials model, users have the option to modify the liquefaction temperature of the ZrO 2 -interactive and UO 2 -interactive materials as a way to mimic early fuel rod failure due to material interactions. Through modification of the liquefaction of high melting point materials with significant mass, users may inadvertently limit maximum core temperatures for fuel, cladding, and debris components.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Assembly of Building Blocks by Double-End-Anchored Polymers in the Dilute Regime Mediated by Hydrophobic Interactions at Controlled Distances

Hierarchical assembly of building blocks via competing, orthogonal interactions is a hallmark of many of nature’s composite materials that do not require highly specific ligand-receptor interactions. To mimic this assembly mechanism requires the development of building blocks capable of tunable interactions. In the present work, we explored the interplay between repulsive (steric and electrostatic) and attractive hydrophobic forces. The designed building blocks allow hydrophobic forces to effectively act at controlled, large distances, to create and tune the assembly of membrane-based building blocks under dilute conditions and affect their interactions with cellular membranes via physical cross-bridges. Specifically, we employed double-end-anchored poly(ethylene glycol)s (DEA-PEGs)—hydrophilic PEG tethers with hydrophobic tails on both ends. Using differential-interference-contrast optical microscopy, synchrotron small angle X-ray scattering (SAXS), and cryogenic electron microscopy, we investigated the ability of DEA-PEGs to mediate assembly in the dilute regime on multiple length scales and on practical time scales. The PEG length, anchor hydrophobicity, and molar fraction of DEA-PEG molecules within a membrane strongly affect the assembly properties. Additional tuning of the intermembrane interactions can be achieved by adding repulsive interactions via PEG-lipids (steric) or cationic lipids to the DEA-PEG-mediated attractions. Further, while the optical and electron microscope imaging methods provided qualitative evidence of the ability of DEA-PEGs to assemble liposomes, the SAXS measurements and quantitative line-shape analysis in dilute preparations demonstrated that the ensemble average of loosely organized liposomal assemblies maintains DEA-PEG concentration-dependent tethering on defined nanometer length scales. For cationic liposome–DNA nanoparticles (CL–DNA NPs), aggregation induced by DEA-PEGs decreased internalization of NPs by cells, but tuning the DEA-PEG-induced attractions by adding repulsive steric interactions via PEG-lipids limited aggregation and increased NP uptake. However, confocal microscopy imaging together with colocalization studies with Rab11 and LysoTracker as markers of intracellular pathways showed that modifying CL–DNA NPs with DEA-PEGs alters their interactions with the plasma and endosomal membranes.

- x-ray scattering↗
DOE OSTI2020

Self-interaction error overbinds water clusters but cancels in structural energy differences

Here, we gauge the importance of self-interaction errors in density functional approximations (DFAs) for the case of water clusters. To this end, we used the Fermi–Löwdin orbital self-interaction correction method (FLOSIC) to calculate the binding energy of clusters of up to eight water molecules. Three representative DFAs of the local, generalized gradient, and metageneralized gradient families [i.e., local density approximation (LDA), Perdew–Burke–Ernzerhof (PBE), and strongly constrained and appropriately normed (SCAN)] were used. We find that the overbinding of the water clusters in these approximations is not a density-driven error. We show that, while removing self-interaction error does not alter the energetic ordering of the different water isomers with respect to the uncorrected DFAs, the resulting binding energies are corrected toward accurate reference values from higher-level calculations. In particular, self-interaction–corrected SCAN not only retains the correct energetic ordering for water hexamers but also reduces the mean error in the hexamer binding energies to less than 14 meV/ H 2 O from about 42 meV/ H 2 O for SCAN. By decomposing the total binding energy into many-body components, we find that large errors in the two-body interaction in SCAN are significantly reduced by self-interaction corrections. Higher-order many-body errors are small in both SCAN and self-interaction–corrected SCAN. These findings suggest that orbital-by-orbital removal of self-interaction combined with a proper DFA can lead to improved descriptions of water complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Understanding the dynamic interactions of root-knot nematodes and their host: role of plant growth promoting bacteria and abiotic factors

Root-knot nematodes (Meloidogyne spp., RKN) are among the most destructive endoparasitic nematodes worldwide, often leading to a reduction of crop growth and yield. Insights into the dynamics of host-RKN interactions, especially in varied biotic and abiotic environments, could be pivotal in devising novel RKN mitigation measures. Plant growth-promoting bacteria (PGPB) involves different plant growth-enhancing activities such as biofertilization, pathogen suppression, and induction of systemic resistance. We summarized the up-to-date knowledge on the role of PGPB and abiotic factors such as soil pH, texture, structure, moisture, etc. in modulating RKN-host interactions. RKN are directly or indirectly affected by different PGPB, abiotic factors interplay in the interactions, and host responses to RKN infection. We highlighted the tripartite (host-RKN-PGPB) phenomenon with respect to (i) PGPB direct and indirect effect on RKN-host interactions; (ii) host influence in the selection and enrichment of PGPB in the rhizosphere; (iii) how soil microbes enhance RKN parasitism; (iv) influence of host in RKN-PGPB interactions, and (v) the role of abiotic factors in modulating the tripartite interactions. Furthermore, we discussed how different agricultural practices alter the interactions. Finally, we emphasized the importance of incorporating the knowledge of tripartite interactions in the integrated RKN management strategies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Mass Spectral Imaging to Map Plant–Microbe Interactions

Plant–microbe interactions are of rising interest in plant sustainability, biomass production, plant biology, and systems biology. These interactions have been a challenge to detect until recent advancements in mass spectrometry imaging. Plants and microbes interact in four main regions within the plant, the rhizosphere, endosphere, phyllosphere, and spermosphere. This mini review covers the challenges within investigations of plant and microbe interactions. We highlight the importance of sample preparation and comparisons among time-of-flight secondary ion mass spectroscopy (ToF-SIMS), matrix-assisted laser desorption/ionization (MALDI), laser desorption ionization (LDI/LDPI), and desorption electrospray ionization (DESI) techniques used for the analysis of these interactions. Using mass spectral imaging (MSI) to study plants and microbes offers advantages in understanding microbe and host interactions at the molecular level with single-cell and community communication information. More research utilizing MSI has emerged in the past several years. We first introduce the principles of major MSI techniques that have been employed in the research of microorganisms. An overview of proper sample preparation methods is offered as a prerequisite for successful MSI analysis. Traditionally, dried or cryogenically prepared, frozen samples have been used; however, they do not provide a true representation of the bacterial biofilms compared to living cell analysis and chemical imaging. New developments such as microfluidic devices that can be used under a vacuum are highly desirable for the application of MSI techniques, such as ToF-SIMS, because they have a subcellular spatial resolution to map and image plant and microbe interactions, including the potential to elucidate metabolic pathways and cell-to-cell interactions. Promising results due to recent MSI advancements in the past five years are selected and highlighted. The latest developments utilizing machine learning are captured as an important outlook for maximal output using MSI to study microorganisms.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Graphical and Numerical Description of Strain-Gage Balance Interactions

A new approach for the graphical and numerical description of balance interactions is presented. The approach uses data from single-component loads as input. This choice has the two advantages. First, the number of applied loads is at the minimum needed for interactions to be observed. In addition, the loads used for the description of interactions can easily be repeated at different sites. Output differences relative to the outputs of the zero load point of a load series are used for the description of interactions. Similarly, load differences relative to the loads of the zero load point of a load series are used for the description of the loads. Interactions are plotted versus the load differences for each load component while omitting the outputs of the primary gage of the chosen load component. The resulting plots have a characteristic star pattern as interactions are zero at zero load. Numerical estimates of the slopes of the interactions can be reverse-engineered from the load prediction equations of a balance if calibration data is examined. The slopes are the off-diagonal coefficients of the inverse of the matrix that has the coefficients of the linear terms of the fitted loads if the Non-Iterative Method is used for the analysis. Similarly, the slopes are the off-diagonal coefficients of the inverse of the matrix that is the non-iterative part of the primary load iteration equation if the Iterative Method is used for the analysis. Data from the calibration of a force balance is processed to illustrate the proposed graphical and numerical description of interactions.

wind tunnel test↗
NASA NTRSDate not supplied

Graphical and Numerical Description of Strain-Gage Balance Interactions

A new approach for the graphical and numerical description of strain-gage balance interactions is presented. The approach uses data from single-component loads as input. This choice has the two advantages. First, the number of applied loads is at the minimum needed for interactions to be observed. In addition, the loads used for the description of interactions can easily be repeated at different sites. Output differences relative to the outputs of the zero load point of a load series are used for the description of interactions. Similarly, load differences relative to the loads of the zero load point of a load series are used for the description of the loads. Interactions are plotted versus the load differences for each load component while omitting outputs of the primary gage of the chosen load component. The resulting plots have a star pattern as all interactions are zero at zero load. Estimates of the slopes of the interactions can be obtained from the load prediction equations of a balance if calibration data is examined. The slopes are the off-diagonal coefficients of the inverse of the matrix that has the coefficients of the linear terms of the fitted loads if the Non-Iterative Method is used for the analysis. Similarly, the slopes are the off-diagonal coefficients of the inverse of the matrix that is the non-iterative part of the primary load iteration equation if the Iterative Method is used for the analysis. Data sets from a manual and a machine calibration of a force balance are processed to illustrate the proposed description of interactions.

strain-gage balance↗