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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Multi-stage falling particle receivers

The present disclosure is directed to multi-stage falling particle receivers and methods of falling particle heating. As the particles fall through the receiver, the particles are periodically collected and released by flow retarding devices. The periodic catch-and-release of the particles falling through the receiver reduces particle flow dispersion, increases particle opacity and solar absorption, and reduces erosion and damage to surfaces caused by direct particle impingement.

Ho, Clifford K.↗
DOE OSTI2023

Volatility-resolved chemical characterization of airborne particles

A method and apparatus for evaluating the chemical composition of airborne particles by sequentially collecting and analyzing airborne particles in-situ. The method includes: collecting particles; enlarging the particles through water condensation; accelerating the enlarged particles onto a surface to collect enlarged particles; and analyzing the enlarged particles by: isolating the surface; passing a carrier gas over the surface; heating the surface to thermally desorb collected particles into the carrier gas; transporting this evolved vapor into detectors; and assaying the evolved vapor as a function of a desorption temperature. The apparatus includes: a sample flow inlet; a condensational growth tube; a collection and thermal desorption (CTD) cell; a carrier gas source; a heater coupled to the CTD; one or more gas detectors; and a controller configured to operate valves, the heater, the growth tube, and the CTD cell in at least an in-situ sequential collection mode and analysis mode.

Isaacman-VanWertz, Gabriel↗
DOE OSTI2016

The Countermeasure for the Noble Metal in the HLW Vitrification - the Behavior of the Needle Shape Ruthenium Particle - 16107

In this study, we investigated the generation factors and the influences for the glass fluidity of the needle shape ruthenium particles. We report the results described below. (1) About the influence of the ruthenium addition form for the generation of the needle shape ruthenium particles, we compared two forms which were the nitric acid nitrosyl ruthenium (III) solution and the powdered RuO{sub 2}. As a result, the needle shape ruthenium particles were formed from the nitric acid nitrosyl ruthenium (III) solution, but they were not formed from the RuO{sub 2}. (2) The needle shape ruthenium particles were formed, only the condition of the glass beads, the sodium nitrate and the nitric acid nitrosyl ruthenium (III) solution. (3) Rh and Pd which were the noble metal elements and Mo such as the coexistence elements did not have the influence for the needle shape ruthenium particles growth. (4) As the result of the generation examination of the needle shape ruthenium particles in the range of 700-1150 degrees Celsius, the generation temperature of the needle shape ruthenium particles were approximately 800 degrees Celsius. (5)Retention time in melting affected for the generation of the needle shape ruthenium particles, but cooling rate did not influence them. (6) As the result of comparing the fluidity between the nitric acid nitrosyl ruthenium (III) solution and the powdered RuO{sub 2} as ruthenium, the glass which added the ruthenium with the nitric acid nitrosyl ruthenium (III) solution was inferior to the fluidity. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Multi-stage falling particle receivers

The present disclosure is directed to multi-stage falling particle receivers and methods of falling particle heating. As the particles fall through the receiver, the particles are periodically collected and released by flow retarding devices. The periodic catch-and-release of the particles falling through the receiver reduces particle flow dispersion, increases particle opacity and solar absorption, and reduces erosion and damage to surfaces caused by direct particle impingement.

Ho, Clifford K.↗
DOE OSTI2025

Simulating Alpha Particles Incident on MKID Chips for Quantum Sensitivity Analysis

Superconducting quantum devices, such as microwave kinetic inductance detectors (MKIDs), are highly sensitive instruments used in quantum computing and advanced sensing technologies. However, their extreme sensitivity also makes them vulnerable to background noise from natural sources like radiation. One significant contributor to this noise is alpha particles emitted by 210Po, a radon decay daughter that accumulates on surfaces near the detector. This project investigates how alpha particles emitted from 210Po interact with MKID chips. These particles can deposit energy on the detector surface, disrupting its operation and generating false signals. Understanding the energy and behavior of these particles is crucial for improving the design and reliability of quantum devices. To explore this, we first modeled the decay chain starting from 210Pb to 210Po using differential equations. This allowed us to predict how the activity of alpha-emitting isotopes changes over time, reaching a steady state after about two years. Next, we simulated alpha particle interactions with the MKID chip using the Geant4 software toolkit. We built a detailed computer model of the detector housing, including the copper lid where alpha particles originate, the silicon chip, and a thin aluminum sensor layer. Alpha particles were emitted isotropically from just beneath the copper lid’s surface, mimicking natural decay conditions. The simulation tracked how these particles deposit energy on the chip, generating electron-hole pairs and phonons. The results provide insight into the behavior of the resultant electron-hole pairs and phonons, giving us a clear understanding of the energy deposition distribution on the chip. This work supports efforts to mitigate background noise in superconducting sensors, advancing their use in quantum computing and sensitive physics experiments.

Hall, Matthew [Fermilab; UCLA]↗
DOE OSTI2021

A machine learning-based interaction force model for non-spherical and irregular particles in low Reynolds number incompressible flows

In this study, interaction force of non-spherical particles in low Reynolds number gas-solid flow is investigated by neural network approaches. An artificial neural network (ANN) model is developed to correlate the non-spherical particle shape and the flow conditions with the interaction force. To define the particle shape, spherical harmonic expansion is applied. Furthermore, variational autoencoder model is then used to extract latent geometric features. The latent vector is utilized as an input with the Reynolds number for the ANN. The interaction force data, which is used as output data of the ANN, is obtained by particle resolved direct numerical simulation for 5200 non-spherical particles. The proposed model enables unsupervised extraction for non-spherical particle shapes and accurate predictions on the interaction force without heavy computation. This study provides the model that can explain complicated shapes of particles and be applied to a large scale, computational fluid dynamics simulation.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2014

On geometric factors for neutral particle analyzers

Neutral particle analyzers (NPA) detect neutralized energetic particles that escape from plasmas. Geometric factors relate the counting rate of the detectors to the intensity of the particle source. Accurate geometric factors enable quick simulation of geometric effects without the need to resort to slower Monte Carlo methods. Previously derived expressions [G. R. Thomas and D. M. Willis, “Analytical derivation of the geometric factor of a particle detector having circular or rectangular geometry,” J. Phys. E: Sci. Instrum. 5(3), 260 (1972); J. D. Sullivan, “Geometric factor and directional response of single and multi-element particle telescopes,” Nucl. Instrum. Methods 95(1), 5–11 (1971)] for the geometric factor implicitly assume that the particle source is very far away from the detector (far-field); this excludes applications close to the detector (near-field). The far-field assumption does not hold in most fusion applications of NPA detectors. We derive, from probability theory, a generalized framework for deriving geometric factors that are valid for both near and far-field applications as well as for non-isotropic sources and nonlinear particle trajectories.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

The effect of non-uniform mass loading on the linear, temporal development of particle-laden shear layers

The effect of non-uniformity in bulk particle mass loading on the linear development of a particle-laden shear layer is analyzed by means of a stochastic Eulerian-Eulerian model. From the set of governing equations of the two-fluid model, a modified Rayleigh equation is derived that governs the linear growth of a spatially periodic disturbance. Eigenvalues for this Rayleigh equation are determined numerically using proper conditions at the co-flowing gas and particle interface locations. For the first time, it is shown that non-uniform loading of small-inertia particles (Stokes number (St) <0.2) may destabilize the inviscid mixing layer development as compared to the pure-gas flow. The destabilization is triggered by an energy transfer rate that globally flows from the particle phase to the gas phase. For intermediate St (1 < St < 10), a maximum stabilizing effect is computed, while at larger St, two unstable modes may coexist. The growth rate computations from linear stability analysis are verified numerically through simulations based on an Eulerian-Lagrangian (EL) model based on the inviscid Euler equations and a point particle model. The growth rates found in numerical experiments using the EL method are in very good agreement with growth rates from the linear stability analysis and validate the destabilizing effect induced by the presence of particles with low St.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Oleic acid coated magnetic nano-particles: Synthesis and characterizations

Magnetic nano particles of Fe{sub 3}O{sub 4} coated with oleic acid were synthesized using wet chemical route, which involved co-precipitation of Fe{sup 2+} and Fe{sup 3+} ions. The nano particles were characterized using XRD, TEM, FTIR, TGA and VSM. X-ray diffraction studies showed that nano particles consist of single phase Fe{sub 3}O{sub 4} having inverse spinel structure. The particle size obtained from width of Bragg peak is about 12.6 nm. TEM analysis showed that sizes of nano particles are in range of 6 to 17 nm with a dominant population at 12 - 14 nm. FTIR and TGA analysis showed that -COOH group of oleic acid is bound to the surface of Fe{sub 3}O{sub 4} particles and one has to heat the sample to 278° C to remove the attached molecule from the surface. Further it was seen that Fe{sub 3}O{sub 4} particles exhibit super paramagnetism with a magnetization of about 53 emu/ gm.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Lagrangian velocity and acceleration correlations of large inertial particles in a closed turbulent flow

We investigate the response of large inertial particle to turbulent fluctuations in an inhomogeneous and anisotropic flow. We conduct a Lagrangian study using particles both heavier and lighter than the surrounding fluid, and whose diameters are comparable to the flow integral scale. Both velocity and acceleration correlation functions are analyzed to compute the Lagrangian integral time and the acceleration time scale of such particles. The knowledge of how size and density affect these time scales is crucial in understanding particle dynamics and may permit stochastic process modelization using two-time models (for instance, Sawford’s). As particles are tracked over long times in the quasi-totality of a closed flow, the mean flow influences their behaviour and also biases the velocity time statistics, in particular the velocity correlation functions. By using a method that allows for the computation of turbulent velocity trajectories, we can obtain unbiased Lagrangian integral time. This is particularly useful in accessing the scale separation for such particles and to comparing it to the case of fluid particles in a similar configuration.

42 ENGINEERING↗
DOE OSTI2016

Effect of erodent particles on the erosion of metal specimens

This paper presents the experimental results of the measurement of erosion rate of carbon steel specimens in sand water slurry system in a slurry pot tester. Sylhet sand has been sieved to get three sizes of erodent particles; namely, less than 250 micron, 250 to 590 micron and 590 to 1190 micron. Experiments are done with three sand concentrations (10%, 15% and 20%). The rate of erosion of the carbon steel specimens is measured as the loss of weight per unit surface area per unit time under the dynamic action of solid particles. The eroded surfaces of the specimens are examined using Scanning Electron Microscopy (SEM) to visualize the impact of the slurry of various conditions. It is seen that irrespective of the particle size the rate of erosion increases with the increase of slurry concentration. This increment of erosion rate at high concentration is high for large particles. High erosion rate is observed in case of large sand particles. In case of small and fine particles erosion rate is small because of low impact energy as well as the wastage of energy to overcome the hindrance of the finer particles before striking on the specimen surface.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Response of alpha particles in hexagonal boron nitride neutron detectors

Here, thermal neutron detectors were fabricated from 10 B enriched h-BN epilayers of different thicknesses. The charge carrier generation and energy loss mechanisms as well as the range of alpha daughter particles generated by the nuclear reaction between thermal neutrons and 10 B atoms in hexagonal boron nitride (h-BN) thermal neutron detectors have been investigated via their responses to alpha particles from a 210 Po source. The ranges of alpha particles in h-BN were found to be anisotropic, which increase with the angle (θ) between the trajectory of the alpha particles and c-axis of the h-BN epilayer following (cos θ) -1 and are 4.6 and 5.6 μm, respectively, for the alpha particles with energies of 1.47 MeV and 1.78 MeV at θ = 0. However, the energy loss of an alpha particle inside h-BN is determined by the number of layers it passes through with a constant energy loss rate of 107 eV per layer due to the layered structure of h-BN. Roughly 5 electron-hole pairs are generated when an alpha particle passes through each layer. It was also shown that the durability of h-BN thermal neutron detectors is excellent based on the calculation of boron vacancies generated (or 10 B atoms consumed) by neutron absorption. Finally, the results obtained here provide useful insights into the mechanisms of energy loss and charge carrier generation inside h-BN detectors and possible approaches to further improve the overall performance of h-BN thermal neutron detectors, as well as the ultimate spatial resolution of future neutron imaging devices or cameras based on h-BN epilayers.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

The Acceleration of Charged Particles and Formation of Power-law Energy Spectra in Nonrelativistic Magnetic Reconnection

Magnetic reconnection is a primary driver of particle acceleration processes in space and astrophysical plasmas. Understanding how particles are accelerated and the resulting particle energy spectra is among the central topics in reconnection studies. We review recent advances in addressing this problem in nonrelativistic reconnection that is relevant to space and solar plasmas and beyond. We focus on particle acceleration mechanisms, particle transport due to 3D reconnection physics, and their roles in forming power-law particle energy spectra. We conclude by pointing out the challenges in studying particle acceleration and transport in a large-scale reconnection layer and the relevant issues to be addressed in the future.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Shape-driven, emergent behavior in active particle mixtures

Abstract Active particle systems can vary greatly from one-component systems of spheres to mixtures of particle shapes at different composition ratios. We investigate computationally the combined effect of anisotropy and stoichiometry on the collective behavior of two-dimensional active colloidal mixtures of polygons. We uncover three emergent phenomena not yet reported in active Brownian particle systems. First, we find that mixtures containing hexagons exhibit micro-phase separation with large grains of hexagonal symmetry. We quantify a measurable, implicit ‘steric attraction’ between the active particles as a result of shape anisotropy and activity. This calculation provides further evidence that implicit interactions in active systems, even without explicit attraction, can lead to an effective preferential attraction between particles. Next, we report stable fluid clusters in mixtures containing one triangle or square component. We attribute the fluidization of the dense cluster to the interplay of cluster destabilizing particles, which introduce grain boundaries and slip planes into the system, causing solid-like clusters to break up into fluid clusters. Third, we show that fluid clusters can coexist with solid clusters within a sparse gas of particles in a steady state of three coexisting phases. Our results highlight the potential for a wide variety of behavior to be accessible to active matter systems and establish a route to control active colloidal systems through simple parameter designs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Neural Networks for Modeling and Control of Particle Accelerators

Particle accelerators are host to myriad nonlinear and complex physical phenomena. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems, as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. The purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

WE-H-BRA-08: A Monte Carlo Cell Nucleus Model for Assessing Cell Survival Probability Based On Particle Track Structure Analysis

Purpose: To correlate the damage produced by particles of different types and qualities to cell survival on the basis of nanodosimetric analysis and advanced DNA structures in the cell nucleus. Methods: A Monte Carlo code was developed to simulate subnuclear DNA chromatin fibers (CFs) of 30nm utilizing a mean-free-path approach common to radiation transport. The cell nucleus was modeled as a spherical region containing 6000 chromatin-dense domains (CDs) of 400nm diameter, with additional CFs modeled in a sparser interchromatin region. The Geant4-DNA code was utilized to produce a particle track database representing various particles at different energies and dose quantities. These tracks were used to stochastically position the DNA structures based on their mean free path to interaction with CFs. Excitation and ionization events intersecting CFs were analyzed using the DBSCAN clustering algorithm for assessment of the likelihood of producing DSBs. Simulated DSBs were then assessed based on their proximity to one another for a probability of inducing cell death. Results: Variations in energy deposition to chromatin fibers match expectations based on differences in particle track structure. The quality of damage to CFs based on different particle types indicate more severe damage by high-LET radiation than low-LET radiation of identical particles. In addition, the model indicates more severe damage by protons than of alpha particles of same LET, which is consistent with differences in their track structure. Cell survival curves have been produced showing the L-Q behavior of sparsely ionizing radiation. Conclusion: Initial results indicate the feasibility of producing cell survival curves based on the Monte Carlo cell nucleus method. Accurate correlation between simulated DNA damage to cell survival on the basis of nanodosimetric analysis can provide insight into the biological responses to various radiation types. Current efforts are directed at producing cell survival curves for high-LET radiation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Is it possible to discover a dark matter particle with an accelerator?

The paper contains description of the main properties of the galactic dark matter (DM) particles, available approaches for detection of DM, main features of direct DM detection, ways to estimate prospects for the DM detection, the first collider search for a DM candidate within an Effective Field Theory, complete review of ATLAS results of the DM candidate search with LHC RUN I, and less complete review of “exotic” dark particle searches with other accelerators and not only. From these considerations it follows that one is unable to prove, especially model-independently, a discovery of a DM particle with an accelerator, or collider. One can only obtain evidence on existence of a weakly interacting neutral particle, which could be, or could not be the DM candidate. The current LHC DM search program uses only the missing transverse energy signature. Non-observation of any excess above Standard Model expectations forces the LHC experiments to enter into the same fighting for the best exclusion curve, in which (almost) all direct and indirect DM search experiments permanently take place. But this fighting has very little (almost nothing) to do with a real possibility of discovering a DM particle. The true DM particles possess an exclusive galactic signature—annual modulation of a signal, which is accessible today only for direct DM detection experiments. There is no way for it with a collider, or accelerator. Therefore to prove the DM nature of a collider-discovered candidate one must find the candidate in a direct DM experiment and demonstrate the galactic signature for the candidate. Furthermore, being observed, the DM particle must be implemented into a modern theoretical framework. The best candidate is the supersymmetry, which looks today inevitable for coherent interpretation of all available DM data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Shock Propagation and Associated Particle Acceleration in the Presence of Ambient Solar-Wind Turbulence

The topic of this review paper is on the influence of solar wind turbulence on shock propagation and its consequence on the acceleration and transport of energetic particles at shocks. As the interplanetary shocks sweep through the turbulent solar wind, the shock surfaces fluctuate and ripple in a range of different scales. We discuss particle acceleration at rippled shocks in the presence of ambient solar-wind turbulence. This strongly affects particle acceleration and transport of energetic particles (both ions and electrons) at shock fronts. In particular, we point out that the effects of upstream turbulence is critical for understanding the variability of energetic particles at shocks. Moreover, the presence of pre-existing upstream turbulence significantly enhances the trapping near the shock of low-energy charged particles, including those near the thermal energy of the incident plasma, even when the shock propagates normal to the average magnetic field. Pre-existing turbulence, always present in space plasmas, provides a means for the efficient acceleration of low-energy particles and overcoming the well known injection problem at shocks.

, solar wind↗