Pion transverse charge density from e+e− annihilation data and logarithmic dispersion relations
Not Available
SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Not Available
A program to collect extraterrestrial dust samples from the stratosphere using impactors mounted on NASA U-2 and WB-57F aircraft is discussed. Sample collection, preparation, and analysis techniques are described and the particle types found are reviewed. Preliminary examination of the particles indicates that they represent not only extraterrestrial material, but some fraction of terrestrial contamination from both natural and manmade sources. This examination involves a combination of optical microscopy, scanning electron microscopy (SEM) and qualitative bulk elemental analysis using an energy-dispersive X-ray spectrometer (EDS) to characterize each particle. The cosmic dust collection contains samples of at least three classes of material that may present some hazard to extended spacecraft operations in near-Earth orbit: (1) micrometeorites/cosmic dust, (2) aluminum oxide spheres, and (3) alloy spherules and fragments.
We used a plasma flow reactor (PFR) to generate synthetic fallout nanoparticles from vapor-phase condensation of two different input concentrations of uranium and iron analytes (U/Fe = 1:1 and 1:2). Synthetic fallout from complex chemical matrices (e.g., mixtures of U and Fe) has not been generated in this setup before and allows for the observation of relative condensation and fractionation of nuclear debris. Experiments were conducted under two different temperature histories with variations in particle flow patterns along the PFR. Transmission electron microscopy (TEM) observation and analysis of the nanoparticles revealed variations in speciation of uranium oxides (UO 2 and α-UO 3 ) depending on the competition between flow mixing and oxygen sequestration by iron. A ternary metal oxide, UFeO 4 , was observed in addition to iron oxides (e.g., FeO and Fe 3 O 4 ), which suggests that fallout models should account for chemical speciation of ternary metal oxides (i.e., UFeO 4 ) and their relative condensation behaviors in addition to those of singular metal oxides (e.g., FeO and UO 2 ). X-ray Energy Dispersive Spectroscopy (EDS) elemental maps showed that some particles had Fe-rich cores surrounded by U-rich regions. This suggests that either condensed U oxides coagulate onto molten Fe oxides or that the increase in iron analyte concentration might drive the system toward a higher degree of supersaturation, leading to earlier formation of iron oxide particles and providing an energetically favored pathway for nucleation of uranium oxides around iron oxide particles.
Meters-long oxide dispersion strengthened copper rods were manufactured directly from powder by a single-step process, called friction extrusion. The average grain size was 880 nm, which was refined 40 times from powder precursor due to extensive shear deformation. Meanwhile, the average size of alumina particles was 60 nm which retains a decent oxide dispersion strengthening. Here, mechanical properties, including hardness, tensile strength, and ductility, were tested and found to have better or similar values than conventional sintered-then-extruded oxide dispersion strengthened copper materials. The presented technique promises a convenient avenue for the fabrication of oxide dispersion strengthened copper from powder.
Wind observed long-lasting electromagnetic cyclotron waves near the proton cyclotron frequency on 11 March 2005, in the descending part of a fast wind stream. Bi-Maxwellian velocity distributions are fitted for core protons, beam protons, and alpha-particles. Using the fitted plasma parameters we conduct kinetic linear dispersion analysis and find ion cyclotron and/or firehose instabilities grow in six of 10 wave intervals. After Doppler shift, some of the waves have frequency and polarization consistent with observation, thus may be correspondence to the cyclotron waves observed.
Oxide dispersion-strengthened (ODS) alloys are widely recognized for their exceptional high-temperature strength, creep resistance, and radiation tolerance, making them indispensable for advanced nuclear reactors, aerospace, and energy systems. Achieving a fine and stable dispersion of oxide nanoparticles is critical, as these particles act as strong barriers to dislocation motion and effective sinks for irradiation-induced defects, ensuring structural integrity under extreme conditions. Here, in this study, Fe–Cr–Mo-based ODS alloys were fabricated via mechanical alloying and consolidated using electric-field-assisted sintering (EFAS) with additions of Y 2 O 3 , La 2 O 3 , and CeO 2 . EFAS processing produced ultrafine-grained microstructures (average grain size <1 μm) with uniformly distributed oxide clusters (2–4 nm). Atom probe tomography revealed that La 2 O 3 -containing alloys exhibited the highest nanoparticle number density, resulting in superior tensile strength compared to yttria- and ceria-bearing counterparts. The combined effect of grain refinement and rare-earth oxide dispersion significantly enhanced mechanical performance, demonstrating the potential of EFAS for developing high-strength ferritic alloys for demanding environments such as nuclear systems.
Glaciation in mixed-phase clouds predominately occurs through the immersion freezing mode where ice nucleating particles (INPs) immersed within supercooled droplets induce nucleation of ice. Currently, model representations of this process are a large source of uncertainty in simulating cloud radiative properties, and to constrain these estimates, continuous flow diffusion chamber (CFDC)-style INP devices are commonly used to assess the immersion freezing efficiencies of INPs. In this study, a new approach was explored to operating such an ice chamber that provides maximum activation of particles without droplet breakthrough and correction factor ambiguity to obtain high-quality INP measurements in a manner that has not been demonstrated as possible previously. The conditioning section of the chamber was maintained at ~ –20 °C and water relative humidity (RH w ) ~ 113 % conditions to maximize the droplet activation, and the droplets were supercooled with an independently temperature-controlled nucleation section at a steady cooling rate (0.5 °C min –1 ) to induce the freezing of droplets and evaporation of unfrozen droplets. The performance of the modified ice chamber was evaluated using four INP species: K-feldspar, illite-NX, Argentinian soil dust, and airborne arable dust that had shown ice nucleation over a wide span of supercooled temperatures. Dry dispersed and size-selected K-feldspar particles were generated in the laboratory. Illite-NX and soil dust particles were sampled during the second phase of the Fifth International Ice Nucleation Workshop (FIN-02) campaign, and airborne arable dust particles were sampled from the aerosol inlet located on the rooftop of the laboratory. The measured ice nucleation efficiencies of model aerosols with a surface active site density (n s ) metric were higher, but mostly agreed within one order of magnitude compared to literature results.
Abstract. Glaciation in mixed-phase clouds predominantly occurs through the immersion-freezing mode where ice-nucleating particles (INPs) immersed within supercooled droplets induce the nucleation of ice. Model representations of this process currently are a large source of uncertainty in simulating cloud radiative properties, so to constrain these estimates, continuous-flow diffusion chamber (CFDC)-style INP devices are commonly used to assess the immersion-freezing efficiencies of INPs. This study explored a new approach to operating such an ice chamber that provides maximum activation of particles without droplet breakthrough and correction factor ambiguity to obtain high-quality INP measurements in a manner that previously had not been demonstrated to be possible. The conditioning section of the chamber was maintained at −20 ∘C and water relative humidity (RHw) conditions of 113 % to maximize the droplet activation, and the droplets were supercooled with an independently temperature-controlled nucleation section at a steady cooling rate (0.5 ∘C min−1) to induce the freezing of droplets and evaporation of unfrozen droplets. The performance of the modified compact ice chamber (MCIC) was evaluated using four INP species: K-feldspar, illite-NX, Argentinian soil dust, and airborne soil dusts from an arable region that had shown ice nucleation over a wide span of supercooled temperatures. Dry-dispersed and size-selected K-feldspar particles were generated in the laboratory. Illite-NX and soil dust particles were sampled during the second phase of the Fifth International Ice Nucleation Workshop (FIN-02) campaign, and airborne soil dust particles were sampled from an ambient aerosol inlet. The measured ice nucleation efficiencies of model aerosols that had a surface active site density (ns) metric were higher but mostly agreed within 1 order of magnitude compared to results reported in the literature.
The dynamical properties of a prolate bar have been studied by means of a three-dimensional computer model. The bar pattern rotates in the sense of the total angular momentum. The mean particle motion is a rapid streaming in the direction of pattern rotation as seen from a frame that rotates with the bar. Rotation rates that would be inferred from observation are significantly (2-3 times) faster than the pattern rotation speed. Velocity dispersions are anisotropic with the largest component along the bar. Particles oscillate in the bar potential significantly faster than pattern rotation. About 25% of the star orbits are near 2:2:1 resonance with the slow motion along the bar. Particle motion is highly ordered in the bar. Observable properties are described; where comparisons can be made, observable properties are in agreement with observations of brightness contours, velocity fields, and velocity dispersions. The bar has nearly exponential density profiles.
Laser anemometry enables the measurement of complex flow fields via the light scattered from small particles entrained in the flow. In the study of turbomachinery, refractory seed materials are required for seeding the flow due to the high temperatures encountered. In this work we present a pH stabilization technique commonly employed in ceramic processing to obtain stable dispersions for generating aerosols of refractory seed material. By adding submicron alumina particles to a preadjusted pH solution of ethanol, a stable dispersion is obtained which when atomized, produces a high quality aerosol. Commercial grade alumina powder is used with a moderate size distribution. Other metal oxide powders in various polar solvents could also be used once the point of zero charge (pH(pzc)) of the powder in the solvent has been determined. Laser anemometry measurements obtained using the new seeding technique are compared to measurements obtained using Polystyrene Latex (PSL) spheres as the seed material.
In this work, we develop a machine learning (ML) model with aleatoric uncertainty for the low energy beam transport (LEBT) region of the LANSCE linear accelerator in which we model the transport of a space-charge-dominated 750 keV proton beam through a lattice of 22 quadrupole magnets. Our ML model is developed based on data generated by a Kapchinsky–Vladimirsky (KV) envelope model of beam transport. We show that a recurrent neural network can be used as a dynamical surrogate model for fast prediction of the LEBT beam envelope. Furthermore, we endow the model with the prediction of aleatoric uncertainty and compare three different approaches. We demonstrate that the ML-based uncertainty quantification models are well calibrated and produce good estimates of the regions where the model is less certain about its predictions. This ML framework is a necessary step in the development of a real-time virtual diagnostic tool with uncertainty quantification that can be integrated into more complex downstream tasks (e.g., adaptive control or learning flexible control policies via reinforcement learning) for improved efficiency in beam operations. In future work, we plan to expand on this preliminary study by considering more realistic envelope models that include longitudinal momentum spread and dispersive effects in bending magnets, as well as particle tracking codes with 3D space charge (such as and ). Published by the American Physical Society 2024
Developing deterministic neighborhood-informed point-particle closure models using machine learning has garnered interest recently from the dispersed multiphase flow community. The robustness of neural models for this complex multibody problem is hindered by the availability of particle-resolved data. Here, the present work addresses this unavoidable limitation of data paucity by implementing two strategies: (1) by using a rotation and reflection equivariant neural network and (2) by pursuing a physics-based hierarchical machine learning approach. The resulting machine-learned models are observed to achieve a maximum accuracy of 85% and 96% in the prediction of neighbor-induced force and torque fluctuations, respectively, for a wide range of Reynolds number and volume fraction conditions considered. Furthermore, we pursue force and torque network architectures that provide universal prediction spanning a wide range of Reynolds number (0.25 ≤ Re ≤250) and particle volume fraction (0 ≤ φ ≤0.4). The hierarchical nature of the approach enables improved prediction of quantities such as streamwise torque, by going beyond binary interactions to include trinary interactions.
Analyses were obtained on more than 2400 randomly selected particles from the sub-37 micron (ultrafine) fraction of ten Apollo 14 regolith samples. The analyses were conducted with an energy dispersive electron microprobe system. The semiquantitative data were used to group the particles into ten categories. The pyroxene/plagioclase and olivine/plagioclase ratios are inconsistent with those ratios in the Apollo 14 breccias and rocks. The data suggest that fragmented basalts similar to Apollo 12 olivine basalts may have made significant contributions to the ultrafine fraction of the Fra Mauro regolith. Among a number of unusual particles encountered are brown, birefringent lath-shaped grains with 60 wt % SiO2 and 34 wt % FeO(FeSi2O5) and a glass with 20 to 25 wt % CaO, 0 to 8 wt % MgO, 40 to 45 wt % Al2O3 and approximately 30 wt % SiO2.
The rapidly warming Arctic has transitioned to thinner sea ice which fractures, producing leads. Few studies have investigated Arctic sea spray aerosol (SSA) produced from open ocean, leads, and melt ponds, which vary in salinity and organic and microbial community composition. A marine aerosol reference tank was deployed aboard an icebreaker to the Arctic Ocean during August–September 2018 to study SSA generated from locally collected surface waters. Aerosol generation experiments were carried out using water collected from the marginal ice zone, a human-made hole in sea ice near the North Pole, and both lead and melt pond water during an ice floe drift period. Salinity, chlorophyll a, organic carbon, nitrogen, and microbial community composition were measured. Eukaryotic plankton and bacterial abundance were elevated in experimental water from the marginal ice zone, but the relative contributions from major eukaryotic taxonomic groups varied little across the experiments. The chemical composition of individual SSA particles was analyzed using Raman microspectroscopy and computer-controlled scanning electron microscopy with energy-dispersive X-ray spectroscopy. Individual sea salt aerosol, primary organic aerosol, and mineral dust particles were observed. Sea salt aerosol constituted 44–95% of individual submicrometer and 68–100% of supermicrometer particles, by number, generated during each experiment. Carbon was detected in 85%, by number, of the individual sea salt particles, with visible organic coatings. Carbohydrates were detected in 72% of particles, by number, with smaller contributions from long-chain fatty acids (13%) and siliceous material (15%). SSA generated from melt pond water contained only long-chain fatty acids and siliceous material. Quantification of the ice-nucleating activity showed that locally produced SSA may define the High Arctic background ice-nucleating particle population, but cannot account for the peak atmospheric concentrations observed. As the Arctic warms, the increasing SSA emissions have a complex dependence on changing biological and physical processes.
Nanoparticle aggregates in solution controls surface reactivity and function. Complete dispersion often requires additive sorbents to impart a net repulsive interaction between particles. Facet engineering of nanocrystals offers an alternative approach to produce monodisperse suspensions simply based on facet-specific interaction with solvent molecules. Here, we measure the dispersion/aggregation of three morphologies of hematite (α-Fe 2 O 3 ) nanoparticles in varied aqueous solutions using ex situ electron microscopy and in situ small-angle x-ray scattering. We demonstrate a unique tendency of (104) hematite nanoparticles to maintain a monodisperse state across a wide range of solution conditions not observed with (001)- and (116)-dominated particles. Density functional theory calculations reveal an inert, densely hydrogen-bonded first water layer on the (104) facet that favors interparticle dispersion. Results validate the notion that nanoparticle dispersions can be controlled through morphology for specific solvents, which may help in the development of various nanoparticle applications that rely on their interfacial area to be highly accessible in stable suspensions.
Biological lignin valorization represents an emerging green approach to upgrade lignin for sustainable and economic biorefineries. However, lignin generally exhibits poor water solubility and inhomogeneous distribution in an aqueous medium, significantly limiting its bioconversion efficiency. Herein, we develop a novel alkali sterilization strategy to effectively enhance the dispersion and fermentation performance of lignin substrates. The colloidal particle size and molecular structure variations of lignin during the sterilization were thoroughly investigated to reveal the mechanisms of enhanced fermentation performance. Results showed that alkali sterilization achieved a completely aseptic effect when mixing lignin medium at an initial pH of 12.7 for 24 h. Dynamic light scattering (DLS) analysis demonstrated that the hydrodynamic volume of colloidal lignin particles decreased by 96.3% by alkali sterilization compared with the conventional thermal sterilization. Moreover, lignin characterizations by nuclear magnetic resonance (NMR) spectroscopy and gel permeation chromatography (GPC) suggested that alkali sterilization modified the lignin molecular structure by generating 50% more hydrophilic carboxyl groups, reducing the weight-average molecular weight (M w ) by 23.0%, and narrowing the molar-mass dispersity (D M ) by 23.8%. The generation of lignin substrates with more uniform distribution and lower molecular weight improved Rhodococcus opacus PD630 cell growth and metabolism. Microbial cell amount, lignin degradation, and lipid production in alkali sterilized medium increased by 309%, 30.3%, and 48.3%, respectively, compared to those in thermally sterilized medium. These results clearly demonstrated that alkali sterilization dramatically improved the lignin bioconversion performance. Furthermore, this work presents a facile and effective sterilization strategy to overcome inhomogeneous lignin distribution in aqueous fermentation media, showing great potentials as a platform technique for promoting biological lignin valorization.
Abstract Nonlinear coupling of cold and hot waves in a flowing magnetized plasma is analyzed with the Vlasov equation. An analytical solution is obtained for cold waves of a small amplitude (weak flow) and a long wavelength. The distribution function is obtained by integrating the kinetic equation along a perturbed phase-space trajectory for a time-varying plasma flow. The kinetic description presents a generalized dispersion relation that involves resonances depending on cold and hot wave dispersions. Coherent fluid motion leads to radiation peaks in addition to the cyclotron harmonics, where the wavenumber of the cold wave determines the peak frequencies. The peaks appear narrow when the wave propagates perpendicular to the time-averaged flow while they become broad due to the Doppler effect when the wave propagates parallel to the flow. Fully kinetic particle-in-cell simulations corroborate the theoretical predictions. The dispersion relation and resulting wave spectra provide information about plasma parameters and flow properties.
Abstract. Atmospheric ice nucleation impacts the hydrological cycle and climate by modifying the radiative properties of clouds. To improve our predictive understanding of ice formation, ambient ice-nucleating particles (INPs) need to be collected and characterized. Measurements of INPs at lower latitudes in a remote marine region are scarce. The Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) campaign, in the region of the Azores islands, provided the opportunity to collect particles in the marine boundary layer (MBL) and free troposphere (FT) by aircraft during the campaign's summer and winter intensive operation period. The particle population in samples collected was examined by scanning transmission X-ray microscopy with near-edge X-ray absorption fine structure spectroscopy. The identified INPs were analyzed by scanning electron microscopy with energy-dispersive X-ray analysis. We observed differences in the particle population characteristics in terms of particle diversity, mixing state, and organic volume fraction between seasons, mostly due to dry intrusion events during winter, as well as between the sampling locations of the MBL and FT. These differences are also reflected in the temperature and humidity conditions under which water uptake, immersion freezing (IMF), and deposition ice nucleation (DIN) proceed. Identified INPs reflect typical particle types within the particle population on the samples and include sea salt, sea salt with sulfates, and mineral dust, all associated with organic matter, as well as carbonaceous particles. IMF and DIN kinetics are analyzed with respect to heterogeneous ice nucleation rate coefficients, Jhet, and ice nucleation active site density, ns, as a function of the water criterion Δaw. DIN is also analyzed in terms of contact angles following classical nucleation theory. Derived MBL IMF kinetics agree with previous ACE-ENA ground-site INP measurements. FT particle samples show greater ice nucleation propensity compared to MBL particle samples. This study emphasizes that the types of INPs can vary seasonally and with altitude depending on sampling location, thereby showing different ice nucleation propensities, which is crucial information when representing mixed-phase cloud and cirrus cloud microphysics in models.