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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Micron Size NaCrO 2 Particles Enable High‐loading Dry‐processed Electrode for Sodium Ion Batteries

Dry-process fabrication using fibrillatable binder is emerging as a promising method to produce high-loading electrodes for energy storage applications, favored by its cost-efficiency and eco-friendliness. While previous studies have demonstrated the advantages of dry process over the traditional slurry method, there remains a gap in understanding how the particle size of active materials influences the mechanical and electrochemical performance of dry electrodes. In this study, four different particle size NaCrO 2 materials (Average size, S-NCO: 0.6 µm, M1-NCO 1.5 µm, M2-NCO: 4.4 µm, and L-NCO: 9.9 µm) are synthesized to investigate the effect of particle size on dry-processed high-loading electrodes. The findings reveal that the larger micron-sized (>4.4 µm) NCO dry films exhibit significantly improved tensile strength and electrochemical performance, primarily ascribed to the low film porosity, abundant inter-particle connection by the binder, comprehensive carbon coverage, and efficient percolation of the conductive pathway. Notably, a full cell incorporated with a high loading (5.2 mAh cm −2 ) and high active material ratio (96.5 wt.%) L-NCO film electrode demonstrates promising cycling stability and rate capability. Furthermore, these results provide valuable insights regarding the design and fabrication of dry-processed electrodes for future energy storage applications.

25 ENERGY STORAGE↗
DOE OSTI2023

A simple, validated approach for design of two-dimensional periodic particle patterns via acoustophoresis

Two-dimensional patterning of microparticles enables a wide range of functional materials, including patterned energy storage electrodes, flexible electronics, and sensor arrays. Particle patterning via acoustics offers an attractive path to generate a wide variety of 2D periodic patterns that introduce tailorable hierarchical porosity, useful for controlling surface area, transport distances, and other properties. This method is most effective with micron scale particles and patterns of tens to hundreds of microns. To enable systematic exploration of the broad design space for such patterns, this work develops a model of 2D and 3D assembly of particles at high loadings and validates the obtained patterns against both experiments and more computationally intensive modeling techniques. Using this simple model, connections are mapped between input parameters (like actuation conditions, particle volume fraction, material properties) and output geometrical features (like void size and shape, pattern connectivity, and surface area) so that they can be tailored to given applications. The utility of this simple model is illustrated by predicting and then experimentally demonstrating new hierarchical patterns resulting from multiple waves of different frequencies interacting. These multiscale patterns offer the potential to lift the limits on surface area, diffusion distances, and other features.

42 ENGINEERING↗
DOE OSTI2023

Studying the hadron structure with PANDA and CLAS using machine learning techniques

The hadron spectroscopy and structure are currently very active fields of research to study the non-perturbative regime of quantum chronodynamics. The first one studies the complex structure of excited hadrons by looking at their decay products, while the latter uses lepton scattering on nucleons. Both methods require reconstruction algorithms with great efficiency and good particle identification and background rejection rates. This work aims to provide these by either improving the existing methods or developing new ones. The first part of this document presents a feasibility study of a predicted hybrid charmonium state for the PANDA experiment. Lattice QCD calculations predict the ground state hybrid charmonium to be a spin exotic with quantum numbers of JP C = 1?+ at a mass of around 4.3 GeV with a width to be around 20 MeV. A machine learning based data analysis scheme is proposed to further improve the signal efficiency and the background reduction, alongside with improvements of the analysis software (PandaRoot), that are vital for this study. These improvements include a reworked clustering algorithm for the electromagnetic calorimeter (EMC) and an optimized monte carlo matching for neutral particles. The second part of this document is about studying the proton structure. A multidimensional study of the structure function ratio Fsin(?)LU /FUU has been performed for K±, based on the measurement of beam-spin asymmetries. It uses the high statistics data recorded with the CLAS12 spectrometer at Jefferson Laboratory. Fsin(?)LU is a twist-3 quantity that provides information about the quark gluon correlations in the proton. This document will present for the first time a simultaneous analysis of two kaon channels over a large kinematic range of z, xB , PT and Q2 with virtualities Q2 ranging from 1 GeV2 up to 8 GeV2 using machine learning techniques for improved particle identification.

Kripko, Aron↗
DOE OSTI2023

Energy calibration of germanium detectors for the Majorana Demonstrator

The Majorana Demonstrator was a search for neutrinoless double-beta decay (0νββ) in the 76 Ge isotope. It was staged at the 4850-foot level of the Sanford Underground Research Facility (SURF) in Lead, SD. The experiment consisted of 58 germanium detectors housed in a low background shield and was calibrated once per week by deploying a 228 Th line source for 1 to 2 hours. The energy scale calibration determination for the detector array was automated using custom analysis tools. We describe the offline procedure for calibration of the Demonstrator germanium detectors, including the simultaneous fitting of multiple spectral peaks, estimation of energy scale uncertainties, and the automation of the calibration procedure.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Identification and reconstruction of low-energy electrons in the ProtoDUNE-SP detector

Measurements of electrons from 𝜈𝑒 interactions are crucial for the Deep Underground Neutrino Experiment (DUNE) neutrino oscillation program, as well as searches for physics beyond the standard model, supernova neutrino detection, and solar neutrino measurements. This article describes the selection and reconstruction of low-energy (Michel) electrons in the ProtoDUNE-SP detector. ProtoDUNE-SP is one of the prototypes for the DUNE far detector, built and operated at CERN as a charged particle test beam experiment. A sample of low-energy electrons produced by the decay of cosmic muons is selected with a purity of 95%. This sample is used to calibrate the low-energy electron energy scale with two techniques. An electron energy calibration based on a cosmic ray muon sample uses calibration constants derived from measured and simulated cosmic ray muon events. Another calibration technique makes use of the theoretically well-understood Michel electron energy spectrum to convert reconstructed charge to electron energy. In addition, the effects of detector response to low-energy electron energy scale and its resolution including readout electronics threshold effects are quantified. Finally, the relation between the theoretical and reconstructed low-energy electron energy spectra is derived, and the energy resolution is characterized. The low-energy electron selection presented here accounts for about 75% of the total electron deposited energy. After the addition of lost energy using a Monte Carlo simulation, the energy resolution improves from about 40% to 25% at 50 MeV. These results are used to validate the expected capabilities of the DUNE far detector to reconstruct low-energy electrons.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Computational Modeling, Simulation, and Potential Applications of Optical Stochastic Cooling

With the rising demand for intense particles beams, much research is being conducted in the area of particle beam cooling. One of these methods, called Stochastic Cooling (SC) (developed at CERN in the 1970's), delivered a feedback method to improve the quality and lifetime of circulating proton beams by reducing their 6D phase-space and has been widely implemented in a number of hadron machines. However, traditional stochastic cooling schemes are limited by the bandwidth of microwave frequency systems. Optical Stochastic Cooling (OSC) is a promising extension of the stochastic cooling beam cooling technique. OSC instead uses optical wavelengths which allows for improved control and increased cooling but creates its own technical challenges. This lays out work conducted toward the experimental demonstration of OSC at Fermilab's Integrable Optics Test Accelerator (IOTA) storage ring. This includes the design and characterization of parts of the optical delay system, the development and validation of a high-fidelity computational model of the OSC process, and the investigations into possible applications of the OSC mechanism to advanced beam manipulations.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Concentrating lithium carbonate after regeneration of lithium sorbent

A system and method that includes flowing brine containing a metal ion through a reactor that includes porous particles having metal ion imprinted polymer having selective binding sites. The system and method further include discharging the brine from the reactor, contacting the porous particles with water, and pressurizing the reactor with carbon dioxide. The carbon dioxide reacts with the adsorbed metal ions to form a metal carbonate solution, where the metal carbonate solution can then be continuously purified with ion exchange. The method can include recycling eluent from the ion exchange back into the system for re-use. The method further includes depressurizing the reactor to precipitate metal carbonate from the metal carbonate solution and discharging the metal carbonate solution from the reactor.

Hornbostel, Marc↗
DOE OSTI2020

Almost medium-free measurement of the Hoyle state direct-decay component with a TPC

The structure of the Hoyle state, a highly α -clustered state at 7.65 MeV in 12 C, has long been the subject of debate. Understanding if the system comprises of three weakly interacting α particles in the 0s orbital, known as an α-condensate state, is possible by studying the decay branches of the Hoyle state. The direct decay of the Hoyle state into three α particles, rather than through the 8 Be ground state, can be identified by studying the energy partition of the three α particles arising from the decay. This paper provides details on the breakup mechanism of the Hoyle stating using a new experimental technique. Method: By using β-delayed charged-particle spectroscopy of 12 N using the Texas active target time-projection chamber, a high-sensitivity measurement of the direct 3α decay ratio can be performed without contributions from pileup events. A Bayesian approach to understanding the contribution of the direct components via a likelihood function shows that the direct component is <0.043% at the 95% confidence level. This value is in agreement with several other studies, and, here, we can demonstrate that a small nonsequential component with a decay fraction of about 10 –4 is most likely. Here, the measurement of the non-sequential component of the Hoyle state decay is performed in an almost medium-free reaction for the first time. The derived upper limit is in agreement with previous studies and demonstrates sensitivity to the absolute branching ratio. Further experimental studies would need to be combined with robust microscopic theoretical understanding of the decay dynamics to provide additional insight into the idea of the Hoyle state as an α condensate.

6 ≤ A ≤ 19↗
DOE OSTI2023

Rotating spokes, potential hump and modulated ionization in radio frequency magnetron discharges

Here, in this work, the transition from the gradient drift instability (GDI) into an m = 1 rotating spoke in the radio frequency magnetron discharge was studied by means of the two-dimensional axial-azimuthal (z–y) particle-in-cell/Monte Carlo collision method. The kinetic model combined with the linear analysis of the perturbation revealed that the cathode sheath (axial) electric field E z triggers the GDI, deforming the local potential until the instability condition is not fulfilled and the fluctuation growth stops in which moment the instability becomes saturated. The potential deformation consequently leads to the formation of the potential hump, surrounding which the azimuthal electric field E y is present. The saturation level of E y was found to be synchronized with and proportional to the time-changing voltage applied at the cathode, resulting in the RF-modulation of the electron heating in the E y due to $\nabla B$ drift. In the saturated stage of the instability, it was shown that the rotation velocity and direction of the spoke present in the simulations agree well with the experimental observation (Panjan 2019 J. Appl. Phys.125 203303). In the instability linear stage, the instability mode wavelength and the growth rate were also found to be in good agreement with the prediction of the GDI linear fluid theory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Rolling Behavior of Surface Tagged Aluminum 6061 using Photoluminescent Oxides

Physical tagging of nuclear fuel is potentially one way of tracking throughout the fuel lifecycle. The process of tagging can take many forms, but one promising method is to embed a small amount of photoluminescent particles in the surface of a material which are not detectable under normal illumination but are readily visible under excitation by ultraviolet light. The goal of this project was to explore the potential to tag simulated nuclear fuel cladding with small ceramic particles, via laser beam welding or gas tungsten arc welding, and measure the photoluminescent response. Surface tagging using this method has demonstrated viability and detectability throughout this project; work in FY24 focused on the survivability of these tags through subsequent deformation processing similar to what taggants in a fuel manufacturing environment would be subjected to. This work demonstrated that particles are readily visible in the as-welded state (i.e., before subsequent rolling treatment to represent mechanical processing of a fuel material), but visibility is reduced as the deformation is induced. Despite the reduction in photoluminescence, the taggants are still visible after rolling processes are performed, making this surface tagging technique a promising candidate for nuclear fuel cladding tagging. This work demonstrated, though, that targeted optimization work would be necessary to develop a robust taggant depending on the fidelity and luminescent properties required.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Coregistered positron emission particle tracking (PEPT) and X-ray computed tomography (CT) for engineering flow measurements

Increasingly, fully 3D experimental measurements of flow in complex engineering geometries are required to validate computational fluid dynamics models that support and inform reactor design and licensing. One barrier to such measurements is the complexity of typical reactor components and subsequent lack of optical access in these systems. To overcome this, the deployment of coregistered positron emission particle tracking (PEPT) and X-ray computed tomography (CT) is explored for flow measurement in reactor thermal hydraulic components and model (scaled) systems. Through this methodology, fully 3D flow information (via PEPT) and detailed internal geometry (via CT) are captured in opaque systems such as pipes, rod bundles, packed beds, etc. The reconstructed flow field and geometry can then be overlain to reveal detailed flow features around internal structures within a given test section. This is enabled through the use of a combined preclinical PET/CT scanner with overlapping PET and CT fields of view. Such measurements are useful for characterizing flow inside such intricate nuclear thermal hydraulic components as core geometries and heat exchangers, among others, and providing valuable 3D validation data for CFD models. In this work, basic tests of this 3D flow/geometry mapping are presented, and the implications of such measurements are discussed. Further, preliminary measurements are made with both point sources and flow in a simple pipe flow geometry to evaluate the capabilities of this technique. PEPT and CT features are coregistered with up to 0.1 mm precision, and pipe flow mean velocity and Reynolds stresses are reconstructed with similar accuracy to previous PEPT demonstrations. The utility of PEPT/CT is shown herein, and suggestions for future measurements are made.

3D flow measurement↗
DOE OSTI2025

Evaluation of current density measurement methods for high-current, low-beta electron beams

Recent current density measurements with a low-beta electron beam (β=0.5-0.75) are strongly affected by electron scatter and Cherenkov limits. These invasive measurements are heavily influenced by the electron energy and the intercepting material properties: density, index of refraction, and atomic number. We evaluate various measurement methods, including x-ray scintillation and Cherenkov emission. To optimize the x-ray scintillation technique for this energy regime, metal foils of differing atomic number (Z) and thickness were placed upstream of a scintillation screen. We have selected Cherenkov emitters, based on a material refractive index, in order to differentiate the contributions from electron scatter and produced fluorescence, Cherenkov emission, and total internal reflection. The observed distributions for both approaches are verified through MCNP6®. Additionally, the simulations provide insight as to what physical processes dominate the measured distribution. We conclude by determining the limits and optimal measurement range for each measurement technique.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

The discrete Green's function paradigm for two-way coupled Euler–Lagrange simulation

We outline a methodology for the simulation of two-way coupled particle-laden flows. The drag force that couples fluid and particle momentum depends on the undisturbed fluid velocity at the particle location, and this latter quantity requires modelling. We demonstrate that the undisturbed fluid velocity, in the low particle Reynolds number limit, can be related exactly to the discrete Green's function of the discrete Stokes equations. In addition to hydrodynamics, the method can be extended to other physics present in particle-laden flows such as heat transfer and electromagnetism. The discrete Green's functions for the Navier–Stokes equations are obtained at low particle Reynolds number in a two-plane channel geometry. We perform verification at different Reynolds numbers for a particle settling under gravity parallel to a plane wall, for different wall-normal separations. Compared with other point-particle schemes, the Stokesian discrete Green's function approach is the most robust at low particle Reynolds number, accurate at all wall-normal separations. To account for degradation in accuracy away from the wall at finite Reynolds number, we extend the present methodology to an Oseen-like discrete Green's function. The extended discrete Green's function method is found to be accurate within 6% at all wall-normal separations for particle Reynolds numbers up to 24. Furthermore, the discrete Green's function approach is well suited to dilute systems with significant mass loading and this is highlighted by comparison against other Euler–Lagrange as well as particle-resolved simulations of gas–solid turbulent channel flow. Strong particle–turbulence coupling is observed in the form of turbulence modification and turbophoresis suppression, and these observations are placed in context of the different methods.

42 ENGINEERING↗
DOE OSTI2024

Discrete-Element and Material-Point Method (DEM and MPM) Based Solvers for Sustainable Technologies

We present the use of discrete element method (DEM) and material point method (MPM) in three relevant green technology applications that include biomass feedstock handling, lithium-ion battery manufacturing, and high-pressure reverse osmosis. Our open-source DEM and MPM solvers are developed using performance portable grid and particle management library, AMReX, thus enabling superior performance on NVIDIA and AMD GPUs with > 100 million particles. Our DEM solver resolves the motion of individual particles in a granular system and includes a bonded sphere method for modeling non-spherical particles along with Hertzian and liquid bridge-based contact models. We simulate highly variable biomass feedstock flows in large-scale hoppers for biofuel production and electrode calendering in battery manufacturing using DEM. Our simulations predict flow blockage in large scale biomass hoppers and electrode microstructure variations, thus providing valuable information for biofuel and battery manufacturers, respectively. The second half of the talk will be on MPM and its application towards pore resolved simulations of reverse osmosis membranes under compressive loads. We present a validation study of our MPM simulations with membrane microscopy imaging thus providing useful insights on membrane stability under high pressure conditions. We also present a spectral stability analysis of using linear hat, quadratic and cubic spline basis in MPM indicating regions of numerical stability.

BIOMASS FUELS,MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Hydrodynamic Characterization of a Shallow Rectangular Spouted Bed Using Bed Pressure Signals and Image Processing Methods

To support the design of spouted bed reactors, experiments are performed in a rectangular spouted bed to measure the peak pressure drop (Δ P max ) and the internal and external spouting velocities ( U is and U es ). Four particle types spanning under Geldart D and B are used. U is and U es are measured from bed pressure drop and expansion ratio profiles, respectively, with the U es / U is ratio of each particle type obtained. Additionally, correlations predicting the Δ P max of Geldart D and B particles are developed by reviewing published correlations and investigating the nozzle effect. Good prediction is achieved with a slope of 0.997 and an adjusted R 2 of 0.998 in a 95% confidence interval. U es is predicted through correlations developed by adding effects of d p / D i and H 0 in the Mathur–Gishler equation. The calculated U es agrees well with the experimental data, achieving a slope of 0.998 and an adjusted R 2 of 0.998 in a 95% confidence interval.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Silicon nanocluster anion-argon cation recombination via hybrid continuum-molecular dynamics calculations

Prediction of the charge distribution on particles in an aerosol is critical not only in electrical mobility based characterization methods, but also in understanding the role that charging plays in particle growth in gas phase synthesis reactors. The latter is particularly important in non-thermal plasma synthesis reactors, wherein nanoclusters form and grow from vapor phase precursors in a high electron and high ion density environment. In plasmas, because free electrons are much less massive and much more mobile than positive gas ions, nanocluster charge distributions are biased negative. Furthermore, neutral or even positively charged nanoclusters may exist, depending on the rate of nanocluster-gas ion recombination, and nanocluster-nanocluster collisions may greatly contribute to nanocluster growth if not Coulombically suppressed.

42 ENGINEERING↗
DOE OSTI2025

Aerosol size determination via light scattering of viruses and protein complexes

Abstract The study of ultrafine particle aerosols, those with particle diameters of 100 nm or less, is important due to their impact on our health and environment. However, given their small sizes, such particles can be difficult to measure and trace. Most common optical methods are unable to reach this size range. Other methods exist but incur other limitations, such as the need for electrically charged particles. Here we show how light scattering can be used to detect and measure the size and location of single viruses and protein complexes forming an aerosol beam, as well as trace their path. We were able to detect individual particles down to 16 nm in diameter. The primary purpose of our instrument is to monitor the delivery of single bioparticles to the focus of an X-ray laser to image those particles, but it has the potential to study any other aerosols such as those resulting from ultrafine sea spray, with important consequences for cloud formation and climate modeling, or from combustion, responsible for most air pollution and resulting health impacts.

Physics↗