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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Electric charging particle heater for thermal energy storage

The disclosure relates to particle heaters for heating solid particles to store electrical energy as thermal energy. Thermal energy storage directly converts off-peak electricity into heat for thermal energy storage, which may be converted back to electricity, for example during peak-hour power generation. The particle heater is an integral part of an electro-thermal energy storage system, as it enables the conversion of electrical energy into thermal energy. As described herein, particle heater designs are described that provide efficient heating of solid particles in an efficient and compact configuration to achieve high energy density and low cost.

Ma, Zhiwen↗
DOE OSTI2026

Impact of front-end parameters of the ARCADIA MD3 on charged particle detection

The ARCADIA INFN R&D project developed a Fully Depleted Monolithic Active Pixel Sensor (FD-MAPS) using a customized LFoundry 110 nm CIS process. The first in-beam characterization of the ARCADIA Main Demonstrator 3 (MD3) sensor with 200 $μ$m active thickness has been performed at the Fermilab Test Beam Facility with a 120 GeV proton beam. The Device Under Test (DUT) is tested with a trigger-less telescope composed of two ARCADIA MD3 tracking planes. This early study investigates the effect of the front-end parameters on the tracking performance.

Pantouvakis, C. [Padua U.; INFN, Padua]↗
NASA NTRS2010

Particle Access and Charging Environments in the Lunar Wake

A plasma wake a region of low density, high temperature plasma forms on the far side of the Moon when solar wind, magnetosheath, and magnetotail plasma flows past the Moon [Manka, 1973; Ogilvie et al., 1996; Farrell et al., 1998; Halekas et al., 2005]. Ion populations in these flows typically have much smaller thermal velocity than bulk speed and are therefore excluded from the plasma wake while the large thermal electron velocity allows the lighter negatively charged particles to stream ahead of the ions into the wake. Charge separation due to electrons streaming ahead of the ions into the wake from the wake boundary establishes an ambipolar electric field which impedes the motion of electron flow and accelerates ions into the wake [Ogilvie et al., 1996; Farrell et al., 1997]. We have conducted a theoretical study of acceleration (and deceleration) of charged particles in lunar plasma environments, which investigated the mechanisms responsible for allowing solar wind entry into the lunar wake, and for producing energetic particle distributions observed within the lunar wake. To this end, the investigation utilized a macroscale 3D hybrid particle-in-cell numerical model of the interaction of the Moon with external plasma environments to compute electric fields in the lunar environment for a variety of external plasma conditions and interplanetary magnetic field orientations. Ion dynamics were attained from the hybrid code while electron dynamics were determined by considering electron test particle trajectories through the fields established in the hybrid code. Results from the code will be presented to evaluate charging environments within the lunar wake.

Parker, Linda↗
DOE OSTI2020

Underlying event properties in pp collisions at $ \sqrt{s} $ = 13 TeV

This article reports measurements characterizing the Underlying Event (UE) associated with hard scatterings at midrapidity (|η| < 0.8) in pp collisions at √s = 13 TeV. The hard scatterings are identified by the leading particle, the charged particle with the highest transverse momentum ( p T l e a d i n g ) in the event. Charged-particle number-densities and summed transverse-momentum densities are measured in different azimuthal regions defined with respect to the leading particle direction: Toward, Transverse, and Away. The Toward and Away regions contain the fragmentation products of the hard scatterings in addition to the UE contribution, whereas particles in the Transverse region are expected to originate predominantly from the UE. The study is performed as a function of p T l e a d i n g with three different p T thresholds for the associated particles, $p^{track}_T$ > 0.15, 0.5, and 1.0 GeV/c. The charged-particle density in the Transverse region rises steeply for low values of $p^{leading}_T$ and reaches a plateau. The results confirm the trend that the charged-particle density in the Transverse region shows a stronger increase with $\sqrt{s}$ an the inclusive charged-particle density at midrapidity. The UE activity is increased by approximately 20% when going from 7 TeV to 13 TeV pp collisions. The plateau in the Transverse region (5 < $p^{leading}_T$ < 40 GeV/c) is further characterized by the probability distribution of its charged-particle multiplicity normalized to its average value (relative transverse activity, R T ) and the mean transverse momentum as a function of R T Experimental results are compared to model calculations using PYTHIA 8 and EPOS LHC. The overall agreement between models and data is within 30%. These measurements provide new insights on the interplay between hard scatterings and the associated UE in pp collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Active learning of polarizable nanoparticle phase diagrams for the guided design of triggerable self-assembling superlattices

Polarizable nanoparticles are of interest in materials science because of their rich and complex phase behavior that can be used to engineer nanostructured materials with long-range crystalline order. To understand and rationally navigate the design space of polarizable nanoparticles for self-assembling highly ordered superlattices, we developed a coarse-grained computational model to describe the nanoparticle-nanoparticle interactions in implicit solvent and employ the computationally efficient image method to model many-body polarization interactions. We conducted high-throughput virtual screening over a five-dimensional particle design space spanned by temperature, particle size, particle charge, particle dielectric, and solvent dielectric using enhanced sampling molecular dynamics calculations within an active learning framework to efficiently map out the regions of thermodynamic stability of the self-assembled aggregates. We validate our predictions in comparisons against small angle x-ray scattering measurements of gold nanoparticles surface functionalized with metal chalcogenide ligands. Lastly, we use our validated phase maps to computationally design switchable nanostructured materials capable of triggered assembly and disassembly as a function of temperature and solvent dielectric with potential applications as sensors, smart windows, optoelectronic devices, and in medical diagnostics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Physics-tailored machine learning reveals unexpected physics in dusty plasmas

Dusty plasma is a mixture of ions, electrons, and macroscopic charged particles that is commonly found in space and planetary environments. The particles interact through Coulomb forces mediated by the surrounding plasma, and as a result, the effective forces between particles can be nonconservative and nonreciprocal. Machine learning (ML) models are a promising route to learn these complex forces, yet their structure should match the underlying physical constraints to provide useful insight. Here, we demonstrate and experimentally validate an ML approach that incorporates physical intuition to infer force laws in a laboratory dusty plasma. Trained on 3D particle trajectories, the model accounts for inherent symmetries, nonidentical particles, and learns the effective nonreciprocal forces between particles with exquisite accuracy (R 2 > 0.99). We validate the model by inferring particle masses in two independent yet consistent ways. The model’s accuracy enables precise measurements of particle charge and screening length, identifying large deviations from common theoretical assumptions. Our ability to identify unknown physics from experimental data demonstrates how ML-powered approaches can guide new routes of scientific discovery in many-body systems. Furthermore, we anticipate our ML approach to be a starting point for inferring laws from dynamics in a wide range of many-body systems, from colloids to living organisms.

Science & Technology - Other Topics↗
DOE OSTI2022

Extracting forces from noisy dynamics in dusty plasmas

Extracting environmental forces from noisy data is a common yet challenging task in complex physical systems. Machine learning (ML) represents a robust approach to this problem, yet is mostly tested on simulated data with known parameters. Here we use supervised ML to extract the electrostatic, dissipative, and stochastic forces acting on micron-sized charged particles levitated in an argon plasma (dusty plasma). By tracking the sub-pixel motion of particles in subsequent images, we successfully estimated these forces from their random motion. The experiments contained important sources of non-Gaussian noise, such as drift and pixel-locking, representing a data mismatch from methods used to analyze simulated data with purely Gaussian noise. Our model was trained on simulated particle trajectories that included all of these artifacts, and used more than 100 dynamical and statistical features, resulting in a prediction with 50\% better accuracy than conventional methods. Lastly, in systems with two interacting particles, the model provided non-contact measurements of the particle charge and Debye length in the plasma environment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1975

Micrometeoroid composition analyzer

Technique has been developed to detect moving charged particles and to determine their positions and/or their velocity vectors, relative to three mutually orthogonal axes, without particle impact or any elements of detector and without changing particle charge or motion.

Auer, S. O.↗
NASA NTRS1989

Returned Solar Max hardware degradation study results

The Solar Maximum Repair Mission returned with the replaced hardware that had been in low Earth orbit for over four years. The materials of this returned hardware gave the aerospace community an opportunity to study the realtime effects of atomic oxygen, solar radiation, impact particles, charged particle radiation, and molecular contamination. The results of these studies are summarized.

Triolo, Jack J.↗
NASA NTRS2012

Imposing a Lagrangian Particle Framework on an Eulerian Hydrodynamics Infrastructure in Flash

In many astrophysical simulations, both Eulerian and Lagrangian quantities are of interest. For example, in a galaxy cluster merger simulation, the intracluster gas can have Eulerian discretization, while dark matter can be modeled using particles. FLASH, a component-based scientific simulation code, superimposes a Lagrangian framework atop an adaptive mesh refinement Eulerian framework to enable such simulations. The discretization of the field variables is Eulerian, while the Lagrangian entities occur in many different forms including tracer particles, massive particles, charged particles in particle-in-cell mode, and Lagrangian markers to model fluid structure interactions. These widely varying roles for Lagrangian entities are possible because of the highly modular, flexible, and extensible architecture of the Lagrangian framework. In this paper, we describe the Lagrangian framework in FLASH in the context of two very different applications, Type Ia supernovae and galaxy cluster mergers, which use the Lagrangian entities in fundamentally different ways.

Dubey, A.↗
NASA NTRSDate not supplied

Developing Materials and Coating Technologies for Mitigation of Lunar Dust Adhesion and Abrasion

Lunar regolith was first identified as a major issue during the Apollo missions. There are three characteristics of lunar regolith that cause issues: small size, rough surface topology, and particle charge. The lack of a magnetosphere allows solar wind to bombard the lunar surface which results in the regolith becoming charged. These charged particles will adhere to most surfaces and degrade thermal control systems. The lack of atmosphere and surface liquids on the lunar surface results in the regolith’s small particle size, abrasive topology, and chemical reactivity. When the dust adheres to a surface, or the lunar lander exhaust kicks up dust regolith, it can impair instrument or thermal control system function, abrade optical surfaces, diminish range of motion, and mechanically degrade soft-goods such as gloves and astronaut suits. All of these examples were experienced during the Apollo missions. The objective of this study was to select and evaluate abrasion-resistant ceramic materials for application on the lunar landing equipment.

materials↗