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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Review of Particle Physics

Abstract The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 2,143 new measurements from 709 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Among the 120 reviews are many that are new or heavily revised, including a new review on Machine Learning, and one on Spectroscopy of Light Meson Resonances. The Review is divided into two volumes. Volume 1 includes the Summary Tables and 97 review articles. Volume 2 consists of the Particle Listings and contains also 23 reviews that address specific aspects of the data presented in the Listings. The complete Review (both volumes) is published online on the website of the Particle Data Group (pdg.lbl.gov) and in a journal. Volume 1 is available in print as the PDG Book. A Particle Physics Booklet with the Summary Tables and essential tables, figures, and equations from selected review articles is available in print, as a web version optimized for use on phones, and as an Android app.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Measurement of the Sensitivity of Two-Particle Correlations in $\mathcal{pp}$ Collisions to the Presence of Hard Scatterings

A key open question in the study of multiparticle production in high-energy pp collisions is the relationship between the “ridge”—i.e., the observed azimuthal correlations between particles in the underlying event that extend over all rapidities—and hard or semihard scattering processes. In particular, it is not known whether jets or their soft fragments are correlated with particles in the underlying event. To address this question, two-particle correlations are measured in pp collisions at $\sqrt{s}$=13 TeV using data collected by the ATLAS experiment at the LHC, with an integrated luminosity of 15.8 pb -1 , in two different configurations. In the first case, charged particles associated with jets are excluded from the correlation analysis, while in the second case, correlations are measured between particles within jets and charged particles from the underlying event. Second-order flow coefficients, v2, are presented as a function of event multiplicity and transverse momentum. These measurements show that excluding particles associated with jets does not affect the measured correlations. Moreover, particles associated with jets do not exhibit any significant azimuthal correlations with the underlying event, ruling out hard processes contributing to the ridge.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

A Numerical Simulation of a Single Shock-Accelerated Particle

Particle drag models, which capture macro viscous and pressure effects, have been developed over the years for various flow regimes to enable cost effective simulations of particle-laden flows. The relatively recent derivation by Maxey and Riley has provided an exact equation of motion for spherical particles in a flow field based on the continuum assumption. Many models that have been simplified from these equations have provided reasonable approximations; however, the sensitivity of particle-laden flows to particle drag requires a very accurate model to simulate. To develop such a model, a 2D axisymmetric Navier-Stokes direct numerical simulation of a single particle in a transient, shock-driven flow field was conducted in the hydrocode FLAG. FLAG’s capability to run arbitrary Lagrangian-Eulerian hydrodynamics coupled with solid mechanic models makes it an ideal code to capture the physics of the flow field around and in the particle as it is shock-accelerated – a challenging regime to study. The goal of this work is twofold: to provide a validation for FLAG’s Navier-Stokes and heat diffusion solutions, and to provide a rationale for recent experimental particle drag measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

The Influence of Mesoscale Particle Structure on the Electrode Degradation and Resultant Electrochemistry of Lithium Ion Cells With Nickel Rich Lithium Nickel Manganese Cobalt Oxide Positive Electrodes

Nickel-rich lithium nickel manganese cobalt oxide, NMC (LiNi x Mn y Co z O 2 ), materials are desirable positive electrodes in lithium ion batteries, providing high capacity and energy density. The mesoscale structure of NMC materials is commonly a polycrystalline aggregate, providing opportunity for short lithium ion transport distance of the small primary particles, yet facile material handling due to the larger secondary particles. On (de)lithiation the NMC unit cell changes volume, where the anisotropic strain can result in secondary particle fracture. This secondary particle fracture process during cycling has been associated with several degradation modes of NMC materials in LIBs. In this work, a milling process was determined whereby the secondary particles could be pre-fractured with retention of the parent primary particle crystallographic structure, crystallite size, and morphology, providing the ability to unambiguously determine the influence of NMC secondary particle size and mesostructure on resultant functional behavior. The bulk and interfacial properties and electrochemistry of as-received commercially obtained polycrystal NMC811 (LiNi 0.8 Mn 0.1 Co 0.1 O 2 , PC NMC) and its milled MPC NMC counterpart were compared. The smaller secondary particle size, higher surface area MPC NMC was found to result in 1) greater cathode tortuosity, 2) reduced surface Ni on the cycled MPC cathodes consistent with surface reconstruction, and 3) increased Ni deposition on the anodes from cathode-anode crosstalk. These factors manifested in unfavorable electrochemical behavior of MPC with lower functional capacity at both 1C and C/10 rates and higher impedance over extended moderate voltage (dis)charge cycling.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Implementing the three-particle quantization condition for π + π + K + and related systems

Recently, the formalism needed to relate the finite-volume spectrum of systems of nondegenerate spinless particles has been derived. In this work we discuss a range of issues that arise when implementing this formalism in practice, provide further theoretical results that can be used to check the implementation, and make available codes for implementing the three-particle quantization condition. Specifically, we discuss the need to modify the upper limit of the cutoff function due to the fact that the left-hand cut in the scattering amplitudes for two nondegenerate particles moves closer to threshold; we describe the decomposition of the three-particle amplitude K df,3 into the matrix basis used in the quantization condition, including both s and p waves, with the latter arising in the amplitude for two nondegenerate particles; we derive the threshold expansion for the lightest three-particle state in the rest frame up to O(1/L 5 ); and we calculate the leading-order predictions in chiral perturbation theory for K df,3 in the π + π + K + and π + K + K + systems. We focus mainly on systems with two identical particles plus a third that is different (“2+1” systems). We describe the formalism in full detail, and present numerical explorations in toy models, in particular checking that the results agree with the threshold expansion, and making a prediction for the spectrum of π + π + K + levels using the two- and three-particle interactions predicted by chiral perturbation theory.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Machine learning methods for particle stress development in suspension Poiseuille flows

Numerical simulations are used to study the dynamics of a developing suspension Poiseuille flow with monodispersed and bidispersed neutrally buoyant particles in a planar channel, and machine learning is applied to learn the evolving stresses of the developing suspension. The particle stresses and pressure develop on a slower time scale than the volume fraction, indicating that once the particles reach a steady volume fraction profile, they rearrange to minimize the contact pressure on each particle. Here we consider how the stress development leads to particle migration, time scales for stress development, and present a new physics-informed Galerkin neural network that allows for learning the particle stresses when direct measurements are not possible. The particle fluxes are compared with the Suspension Balance Model with good agreement. We show that when stress measurements are possible, the MOR-physics operator learning method can also capture the particle stresses.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

New electric force and charge exchange modules in discrete element model enables particle dynamics simulation in electric field

Discrete element modeling (DEM) is an important technique for particle dynamics simulation. The field of metal additive manufacturing often utilizes DEM to simulate the rheological behaviors of powder. Standard contact and short-range interactions are sufficient in most cases but insufficient to describe the particle dynamics with the influence of an electric field. Modeling such a system requires additional physics to describe the particle–field interactions. The relevant physics has been experimentally understood but is not yet available in DEM. Here, we develop a charge exchange and an electric force module. The electric force module governs particle response to the electric field, while the charge exchange module enables particles to acquire proper charge during contact with charged geometries. We validate the modules against analytical calculations and high-speed videos of electrostatic powder deposition experiments. Notably, the model struggles to capture the initial particle levitation. We later deploy a modified electric field, as supported by static electric field simulation, to better approximate the electric field penetration into the powder layer. This modification improves the model’s capability of simulating realistic particle levitation. The results highlight the challenges of modeling particle behaviors in the electric field while demonstrating the feasibility of obtaining quantitative results, which are difficult to measure experimentally.

charge exchange↗
DOE OSTI2020

Particle size effects in metallic microparticle impact-bonding

In cold spray processing of metals, the critical velocity for particle bonding is dependent on both intrinsic material properties, such as density and (spall) strength, and extrinsic process parameters, such as the powder particle size. Here, we specifically isolate and investigate particle size effects on the critical velocity for bonding through laser- induced single particle impact experiments and finite element simulations. We also present a predictive framework to correlate particle size and critical velocity. We show that an increase in particle size leads to an increase in the temperature of the jet formed at the interface of the particle and the substrate. This increased temperature locally decreases the spall strength of the material which, in turn, decreases the critical velocity for larger particles.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Experimental validation of the mechanistic scale-up methodology of gas–solid spouted beds using radioactive particle tracking (RPT)

The very high-temperature reactors (VHTRs) are highly ranked among candidates of Generation IV of nuclear reactors due to their high efficiency, safety, the resistance to proliferation, and reliability. The VHTRs are preferentially fueled by Tristructural-isometric (TRISO) coated fuel particles which has fuel kernels of fissile material coated by four coating layers: a porous buffer pyrolysis carbon layer (buffer PyC), an inner dense pyrolysis carbon layer (IPyC), a silicon carbide layer (SiC) and an outer dense pyrolysis carbon layer (OPyC). The heart of the operation and safety of the VHTRs significantly depends on the reliability of the coating layers of TRISO particles to retain metallic and gaseous fission products within the particles. The technique used for coating TRISO particles are gas-solids spouted beds via chemical vapor deposition (CVD). Fabrication of high-quality low-defect TRISO fuel particles fuel at larger scale spouted beds is required to support the commercialization of the VHTRs. In this work, our new developed mechanistic scale-up methodology of gas-solids spouted beds based on matching the radial profile of gas-holdup has been demonstrated and validated using radioactive particle tracking (RPT). Two spouted beds of small and larger scales were used in the study. Three sets of conditions were carried out which include the conditions of the reference case in the large scale, conditions that provide similar gas holdup radial profile to that of the reference case and conditions that provided dissimilar gas holdup radial in the small-scale spouted beds. The results confirm the validation of the scale-up methodology in terms of the dimensionless values of the spout diameter, cumulative probability distribution of the solids particles penetration into the spout, fraction of cycle time in each region of the bed, the radial profiles of the dimensionless values of the root-mean-square particle velocities and solids eddy diffusivity. Finally, the results further advance the knowledge and understanding of the gas-solids spouted beds provide deeper insight into their solids dynamics and presenting important benchmarking data for validating computational fluid dynamics codes and models. At last, procedures are established for the implementation of the new scale-up methodology.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Influence of Initial fabric and water-wetting on particle fracture and force chain evolution in natural silica sand

Particle fracture has a significant influence on the engineering behavior of granular materials. However, the combined influence of the initial fabric and wetting on particle fracture and force chain evolution in granular materials, particularly in sands, remains insufficiently explored in the current literature. Here, in this paper, one-dimensional (1D) confined compression experiments were conducted on dry and wet specimens, and particle-level fracture was captured using three-dimensional (3D) in-situ Synchrotron Micro-Computed Tomography (SMT). A quantitative assessment of particle fracture revealed that wet specimens, which have disturbed fabric, exhibited a higher fracture percentage in comparison to dry specimens. Complementary 3D finite element (FE) simulations were performed using dry and wet (only solid fabric was considered and the influence of pore water is not considered) sand assemblies to assess interparticle contact forces and particle-scale stress distributions within the specimens. Force chain analysis was subsequently conducted, encompassing quantification of interparticle forces, characterization of force network structures, and monitoring the dynamic evolution of force chains under different strain levels. The results show that the specimens with disturbed fabric led to a more dynamic and less persistent force network, more fabric instability, and thus more reorganization of force chain structures. In addition, the frequent rearrangement of the force network in the presence of water (with reduced inter-particle contact friction) likely exacerbates localized stress concentrations, promoting failure in previously unengaged or weakly connected particles. The results reported in this paper offer a new insight into how the initial fabric and wetting cause different fracture behavior. The findings can also pave the way for more in-depth future investigations into the mechanics governing particle fracture in granular assemblies.

Finite element analysis↗
DOE OSTI2024

Understanding particle size effect on fast-charging behavior of graphite anode using ultra-thin-layer electrodes

Extreme fast charging (≤ 15 min) of lithium-ion batteries is highly desirable to accelerate mass-market adoption of electric vehicles. However, significant capacity fading, as well as safety issues due to the lithium plating caused by the fast charging rate, limit its implementation. In this study, we investigated the fast-charging capability of graphite materials with various particle sizes. To eliminate the Li + ion concentration gradient effect across the thickness of the electrode, ultra-thin-layer graphite electrodes were developed to investigate the "real" fast-charging capability of graphite at the particle level. Electrochemical assessments as well as microscopic characterizations revealed that smaller particles exhibited superior fast-charging performance, featuring enhanced capacity reversibility, faster charging rate, and less lithium plating under the same fast-charging conditions. It is shown that small-particle graphite (mean radius of 3.3 μm) could withstand a 4C charge (to 80 % state-of-charge) without plating, with minimal plating occurring at 6C. Thicker particles exhibited plating at lower C-rates. Since the experimental data could not directly explain whether intra-particle diffusion limitations or interfacial reaction limitations dominated the plating mechanism, the pseudo-2-dimensional model was used to evaluate the most likely plating mechanism. The model suggested that particle-level diffusion is the dominant mechanism contributing to plating at high rates. Finally, this work provides comprehensive insights into the particle size effects on fast-charging capability, offering a better understanding of fast-charging behavior and valuable guidance for designing optimal electrode architecture for high-rate lithium-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2021

Mechanics of vitrimer particle compression and fusion under heat press

The compression and fusion of vitrimer particles is a fundamental problem underlying the recycling of vitrimers. Incomplete particle compression can lead to voids in the fused vitrimer, thereby impacting its mechanical property. In this work, we present a two-dimensional finite element model to capture the interplay of multiple complex mechanisms including random particle packing, large deformation, inter-particle contact, thermally activated bulk stress relaxation, and interface healing. Specifically, we focus on understanding two key components of this problem: i) evolution of porosity during compression and fusion of randomly packed vitrimer particles, and ii) effective tensile modulus and strength of fused vitrimer. Using the finite element model, we first show that using smaller particles can reduce the porosity in the fused vitrimer, which only slightly increases the effective modulus, but the increase in tensile strength is more pronounced. In addition, under the same processing conditions, particles with mixed sizes can achieve better densification and higher tensile strength after fusion than uniformly sized particles with the same average radius. Regarding the effects of processing conditions, we discuss how the porosity and effective modulus of the fused vitrimer depend on the processing time, temperature and pressure, and find a general trend consistent with experimental observations, i.e. longer processing time, higher temperature or higher pressure can lead to lower porosity and higher modulus of the fused vitrimer. Finally, the theoretical insights towards the compression and fusion process as well as the simulation framework can be useful in optimizing the powder-based heat press process of vitrimer and its composites.

42 ENGINEERING↗
DOE OSTI2020

Microanalysis of Primary Biological Particles from Model Grass over Its Life Cycle

Airborne biological aerosols are an integral part of the atmosphere–biosphere interface and significantly impact the environment and Earth’s climate. Primary biological particles such as fungal spores, bacteria, and fragments of plant debris are emitted directly from the biosphere into the atmosphere. The phyllosphere (aboveground plant surfaces) is one of the major habitats for different microbes. Here, atmospheric emissions of primary biological particles from model grass Brachypodium distachyon were monitored by online particle number concentration counting at eight principal growth stages starting from leaf development to senescence. Particles collected at each of the growth stages were then characterized using microspectroscopy techniques. Our findings indicate that the morphological and compositional characteristics of emitted biological particles are highly variable at the different growth stages. We identified fungal spores as the most abundant biological particles in the heading stage, while bacteria were most abundant in the flowering and fruit development stages. Understanding differences in the composition and morphology of biological particles during the plant life cycle provides more accurate and reliable insights on structural, functional, and biochemical properties of plant systems, as well as their interactions with microbial communities. This study also provides insights into Earth geoscience system models that represent primary biological particle emissions from the biosphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Chemical Imaging of Fine Mode Atmospheric Particles Collected from a Research Aircraft over Agricultural Fields

Vegetation and crops in agricultural areas are a significant source of both biogenic secondary organic aerosols and of directly emitted primary biological atmospheric particles (PBAPs) composed of plant fragments/debris, fungal spores, pollen, and bacteria among others. Seasonal crop harvesting significantly intensifies regional PBAP emissions and aerosolizes soil organic matter and dust particulates. In this paper, the atmospheric contributions and impact of PBAPs have been insufficiently investigated due to limited real-time observations and ambiguity in their detection by existing measurement techniques. We collected ambient particles on-board an instrumented Beechcraft BE76 Duchess research aircraft flying above actively harvested agriculture fields of corn and soybean crops. In this work, particle samples were analyzed using complementary chemical imaging techniques, including computer-controlled scanning electron microscopy coupled with elemental microanalysis to describe particle-type population and scanning transmission X-ray microscopy to provide quantitative metrics on particle internal heterogeneity. We show the particle-class contribution is consistent between corn and soybean harvesting across altitudes of 100–300 m AGL. The contribution of PBAPs in the size range of 0.15–1.25 μm is estimated to be 10–12% of ~39,000 analyzed particles. Determining viscosity with X-ray microanalysis has shown that the fine-mode organic particles collected are viscous/semisolid (10 2 –10 12 Pa s) while the majority of PBAP fragments are solid (>10 12 Pa s). The observation of submicrometer, solid carbonaceous fragments of biogenic origin has implications for the regional cloud condensation nuclei and ice nuclei budget. Therefore, seasonal harvesting of crops may play an important, yet unrecognized, role in regional cloud formation and climate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Correlating the Viscosity and Rate of Water Diffusion in Semisolid Gel-Forming Aerosol Particles

Aerosol particles are known to exist in highly viscous amorphous states at a low relative humidity and temperature. The slow diffusion of molecules in viscous particles impacts the uptake and loss of volatile and semivolatile species and the rate of heterogeneous chemistry. Recent work has demonstrated that in particles containing organic molecules and salts, the formation of two-phase gel states is possible, leading to observations of rigid particles that resist coalescence. The way that molecules diffuse and transport in gel systems is not well-characterized. In this work, we use an electrodynamic balance to levitate sample particles containing a range of organic compounds in mixtures with calcium chloride and measure the rate of water diffusion. Particles of the pure organics have been shown to form viscous amorphous states, while in mixtures with divalent salts, coalescence measurements have revealed the apparent solidification of particles, consistent with the formation of a gel state facilitated by ion–molecule interactions. We report in several cases that water transport can actually be increased in the rigid gel state relative to the pure compound that forms a viscous state under similar conditions. These measurements reveal the limitations of using viscosity as a metric for predicting molecular diffusion and that the gel structure that forms is a much stronger controlling factor in the rate of diffusion. In conclusion, this underscores the need for diffusion measurements as well as a deeper understanding of noncovalent molecular assembly that leads to supramolecular structures in aerosol particles.

organic-inorganic mixtures↗
DOE OSTI2021

Artificial generation of representative single Li-ion electrode particle architectures from microscopy data

Accurately capturing the architecture of single lithium-ion electrode particles is necessary for understanding their performance limitations and degradation mechanisms through multi-physics modeling. Information is drawn from multimodal microscopy techniques to artificially generate LiNi 0.5 Mn 0.3 Co 0.2 O 2 particles with full sub-particle grain detail. Statistical representations of particle architectures are derived from X-ray nano-computed tomography data supporting an ‘outer shell’ model, and sub-particle grain representations are derived from focused-ion beam electron backscatter diffraction data supporting a ‘grain’ model. A random field model used to characterize and generate the outer shells, and a random tessellation model used to characterize and generate grain architectures, are combined to form a multi-scale model for the generation of virtual electrode particles with full-grain detail. This work demonstrates the possibility of generating representative single electrode particle architectures for modeling and characterization that can guide synthesis approaches of particle architectures with enhanced performance.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Particle resonances in stellarators

Resonances of high energy particles in magnetic confinement devices due to electromagnetic instabilities can strongly modify the particle distribution, leading to a reduction in fusion power and even discharge termination and particle loss to the device walls through an avalanche. The existence of a mode particle resonance depends on the properties of the equilibrium and particle parameters, and their number, location, and density can vary with device design. Recently, the advent of more powerful computing capabilities and advanced theoretical understanding has led to the design of non-axisymmetric devices or stellarators, which could prove to be more advantageous than tokamaks. Stellarators have the advantage of being immune to major disruptions because of the very low plasma current. One of the problems shared by both types of devices is the existence of resonances in particle orbits, which can lead to large amplitude high frequency instabilities and subsequent induced particle loss. We examine the number of resonances, their location, and dependence on particle energy for some stellarator designs.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

CryoSegNet: accurate cryo-EM protein particle picking by integrating the foundational AI image segmentation model and attention-gated U-Net

Picking protein particles in cryo-electron microscopy (cryo-EM) micrographs is a crucial step in the cryo-EM-based structure determination. However, existing methods trained on a limited amount of cryo-EM data still cannot accurately pick protein particles from noisy cryo-EM images. The general foundational artificial intelligence–based image segmentation model such as Meta’s Segment Anything Model (SAM) cannot segment protein particles well because their training data do not include cryo-EM images. Here, we present a novel approach (CryoSegNet) of integrating an attention-gated U-shape network (U-Net) specially designed and trained for cryo-EM particle picking and the SAM. The U-Net is first trained on a large cryo-EM image dataset and then used to generate input from original cryo-EM images for SAM to make particle pickings. CryoSegNet shows both high precision and recall in segmenting protein particles from cryo-EM micrographs, irrespective of protein type, shape and size. On several independent datasets of various protein types, CryoSegNet outperforms two top machine learning particle pickers crYOLO and Topaz as well as SAM itself. The average resolution of density maps reconstructed from the particles picked by CryoSegNet is 3.33 Å, 7% better than 3.58 Å of Topaz and 14% better than 3.87 Å of crYOLO. It is publicly available at https://github.com/jianlin-cheng/CryoSegNet

59 BASIC BIOLOGICAL SCIENCES↗