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At least 793 records · Page 44

Characterization of Preliminary Powder Production and Consolidation for Advanced LEU Fuel Concepts

A set of novel uranium-based alloys has been proposed for use in advanced LEU fuel systems that utilize powder metallurgical methods for fabrication of the fuel forms. This study seeks to evaluate the effectiveness of current fabrication methods to produce powder of each of the candidate alloys and consolidate composite systems. Powder samples were produced via atomization and analyzed for particle size, shape, and microstructure utilizing sieving methods and scanning electron microscopy (SEM). Preliminary pellet consolidation tests were conducted with the atomized powder using a press and sinter method. The resulting pellets were analyzed via SEM to evaluate the morphology of the composite system. These preliminary tests demonstrate the ability to produce powder but did not yield the desired quality of powder and impacted the ability to fabricate a fully dense pellet. A refined process is under development to produce a higher yield of small (<250 µm) spherical powder.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

New charged-particle transport computational capability: the SIT code An L-4 milestone

We have developed a new high-fidelity code for direct transport of charged particles using the simple integral transport method. The code can be coupled to the outputs of any hydrodynamical simulation code in 1-D, 2-D or 3-D. In this report we summarize the formalism involved in treating complex transport problems. We present physical examples wherein we have used the code to calculate the transport of alpha particles. Future work is planned to study the sensitivity of hydrodynamical mix to charged-particle radiochemistry and reaction-in-flight neutrons for the complex inertial confinement fusion problems encountered at NIF and at the Z-machine.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Powder spreading, densification, and part deformation in binder jetting additive manufacturing

Binder jetting additive manufacturing (AM) can print complex structures in economical and scalable manner. Binder jetting AM comprises of deposition and weak binding of particles, known as green part, at room temperature and subsequent binder removal and sintering densification at high temperatures. However, during the densification (i.e., sintering), the part significantly deforms due to volume shrinkage. The deformation during sintering is difficult to predict, which prevents the widespread application of this technology. In this research, powder spreading simulation using discrete element method (DEM) was performed first to capture local variations in powder bed configuration. Second, finite element method (FEM) with a phenomenological continuum constitutive model was used to predict part shrinkage during the sintering process. DEM simulation showed variations in packing density, particle segregation, formation of uneven powder bed surface, and shift in particle size distribution (PSD). The sintering simulation modeled part deformation with a reasonable accuracy of 3% for solid-state sintering and intermediate liquid phase sintering. A demonstration case with non-uniform initial packing density showed that inhomogeneous green part density and PSD should be accounted for prediction of part deformation in binder jetting AM.

36 MATERIALS SCIENCE↗

Programmable Anisotropy and Percolation in Supramolecular Patchy Particle Gels

Patchy particle interactions are predicted to facilitate the controlled self-assembly and arrest of particles into phase-stable and morphologically tunable "equilibrium" gels, which avoids the arrested phase separation and subsequent aging that is typically observed in traditional particle gels with isotropic interactions. Despite these promising traits of patchy particle interactions, such tunable equilibrium gels have yet to be realized in the laboratory due to experimental limitations associated with synthesizing patchy particles in high yield. Here, we introduce a supramolecular metal-coordination platform consisting of metallic nanoparticles linked by telechelic polymer chains, which validates the predictions associated with patchy particle interactions and facilitates the design of equilibrium particle hydrogels through limited valency interactions. We demonstrate that the interaction valency and self-assembly of the particles can be effectively controlled by adjusting the relative concentration of polymeric linkers to nanoparticles, which enables the gelation of patchy particle hydrogels with programmable local anisotropy, morphology, and low mechanical percolation thresholds. Moreover, by crowding the local environment around the patchy particles with competing interactions, we introduce an independent method to control the self-assembly of the nanoparticles, thereby enabling the design of highly anisotropic particle hydrogels with substantially reduced percolation thresholds. We thus establish a canonical platform that facilitates multifaceted control of the self-assembly of the patchy nanoparticles en route to the design of patchy particle gels with tunable valencies, morphologies, and percolation thresholds. These advances lay important foundations for further fundamental studies of patchy particle systems and for designing tunable gel materials that address a wide range of engineering applications.

36 MATERIALS SCIENCE↗

Surface Functionalized Barium Titanate Nanoparticles: A Combined Experimental and Computational Study

Barium titanate (BTO) nanoparticles show great potential for use in electrostatic capacitors with high energy density. This includes both polymer composite and sintered capacitors. However, questions about the nanoparticles' size distribution, amount of agglomeration, and surface ligand effect on performance properties remain. Reducing particle agglomeration is a crucial step to understanding the properties of nanoscale particles, as agglomeration has significant effects on the composite dielectric constant. BTO surface functionalization using phosphonic acids is known reduce BTO nanoparticle agglomeration. We explore solution synthesized 10 nm BTO particles with tert-butylphosphonic acid ligands. Recent methods to quantifying agglomeration using an epoxy matrix before imaging shows that tert-butylphosphonic acid ligands reduce BTO agglomeration by 33%. Thermometric, spectroscopic, and computational methods provide confirmation of ligand binding and provide evidence of multiple ligand binding modes on the BTO particle surface.

36 MATERIALS SCIENCE↗

Seeing the whole picture: Methods for getting the most from micro X-ray computed tomography of TRISO nuclear fuel particles

Tristructural isotropic (TRISO) coated fuel particles are a nuclear fuel form under extensive study for use in advanced nuclear reactor concepts. TRISO fuels are subjected to high temperature neutron irradiations and then examined to assess their performance by determining fission product retention and studying morphological changes. Micro X-ray computed tomography is one method of nondestructively studying the effects of TRISO performance. This work addresses the need for image processing to remove X-ray tomographic reconstruction artifacts that prevent the study of TRISO features, as the TRISO particles’ high Z kernel can introduce metal artifacts that degrade the image quality in the surrounding low Z coating layers. These metal artifacts were reduced by imaging the TRISO particles with both high- and low-energy X-rays and applying a mask to the radiographs obtained with low-energy X-rays to digitally remove the dense fuel kernel region. These masked radiographs were then used to produce a tomographic reconstruction which was combined with the tomographic reconstruction of the high-energy data. This enabled the relatively-low-density TRISO buffer layer to be examined in more detail, providing information on irradiation induced dimensional changes of the coatings. This methodology, which helps see the full picture of a TRISO particle, is not limited to nuclear fuels but can be applied to systems that contain highly attenuating material surrounded by less dense materials.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Liquid-phase turbulence measurements in air-water two-phase flows using particle image velocimetry

Liquid-phase turbulence plays a vital role in determining various gas-liquid two-phase flow parameters, such as void fraction distribution, bubble morphology, bubble-bubble interactions, and interfacial area concentration. In this study, a two-phase flow database including both the gas- and liquid-phases measurements was developed focusing on three bubbly flow conditions in an air-water two-phase flow loop with a vertical one-inch diameter circular pipe test section. A particle image velocimetry (PIV) system integrating an optical phase separation method, i.e., the planar laser-induced fluorescence (PLIF) technique using fluorescent particles and optical filtration, was applied to measure the liquid-phase turbulence information, including the time-averaged velocity, Reynolds stress, and turbulent kinetic energy for the liquid phase. The PIV measurements were taken at three ports along the test section at 14.5, 51.5, and 88.5 pipe inner diameters downstream of a bubble injector. In addition, a double-sensor conductivity probe was used to measure radial distributions of the local time-averaged void fraction and gas velocity. The measured liquid-phase turbulence was used to benchmark Sato's turbulence model considering the bubble-induced shear stress for the three tested bubbly flows. The benchmark results showed good agreement between the PIV measurements and model predictions. Lastly, in the two bubbly flows tested that have low void fractions being less than 3%, the effect of the bubble-induced turbulence was found not significant. However, the bubble-induced shear stress becomes important with the increase of the void fraction.

42 ENGINEERING↗

Ultracold neutron storage simulation using the Kassiopeia software package

The Kassiopeia software package was originally developed to simulate electromagnetic fields and charged particle trajectories for neutrino mass measurement experiments. Recent additions to Kassiopeia also allow it to simulate neutral particle trajectories in magnetic fields based on their magnetic moments. Two different methods were implemented: an exact method that can work for arbitrary fields and an adiabatic method that is limited to slowly-varying fields but is much faster for large precession frequencies. Additional interactions to simulate reflection of ultracold neutrons (UCNs) from material walls and to allow spin–flip pulses were also added. These tools were used to simulate neutron precession in a room temperature neutron electric dipole moment experiment and predict the values of the longitudinal and transverse relaxation times as well as the trapping lifetime. All three parameters are found to closely match the experimentally determined values when simulated with both the exact and adiabatic methods, confirming that Kassiopeia is able to accurately simulate neutral particles. This opens the door for future uses of Kassiopeia to prototype the next generation of atomic traps and UCN experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Hybrid-gyrokinetic simulations of low- n toroidal Alfvén eigenmodes using gKPSP

Here, we report a benchmark study of toroidal Alfvén eigenmode (TAE) simulation using the hybrid-gyrokinetic code GyroKinetic Plasma Simulation Program (gKPSP). A simulation capability for energetic particles based on the gyrokinetic δf method has been newly implemented in the gKPSP code. Benchmark simulations have been performed in both circular and realistic tokamak geometries. Good agreement has been found with previously reported results, demonstrating the new capability of the gKPSP code. We have investigated the effects of the distribution function on TAE stability by examining both isotropic and anisotropic slowing-down distributions of energetic particles. The slowing-down distribution produces a higher linear growth rate than a Maxwellian distribution, while a growth rate scan with the anisotropy shows an opposite trend. This can be attributed to competition between Landau damping and the linear drive, which are correlated with the fraction of resonant passing particles and their distribution in phase space.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Spatially Aware Linear Transformer (SAL-T) for Particle Jet Tagging

Transformers are very effective in capturing both global and local correlations within high-energy particle collisions, but they present deployment challenges in high-data-throughput environments, such as the CERN LHC. The quadratic complexity of transformer models demands substantial resources and increases latency during inference. In order to address these issues, we introduce the Spatially Aware Linear Transformer (SAL-T), a physics-inspired enhancement of the linformer architecture that maintains linear attention. Our method incorporates spatially aware partitioning of particles based on kinematic features, thereby computing attention between regions of physical significance. Additionally, we employ convolutional layers to capture local correlations, informed by insights from jet physics. In addition to outperforming the standard linformer in jet classification tasks, SAL-T also achieves classification results comparable to full-attention transformers, while using considerably fewer resources with lower latency during inference. Experiments on a generic point cloud classification dataset (ModelNet10) further confirm this trend. Our code is available at https://github.com/aaronw5/SAL-T4HEP.

Wang, Aaron [Illinois U., Chicago] (ORCID:00000003↗

Solar receivers and methods for capturing solar energy

Thermal receivers, systems, and methods are disclosed that efficiently capture concentrated solar energy into a plurality of heat absorption bodies for conversion into thermal energy. In an embodiment, the thermal receivers, systems, and methods enable simultaneous electricity conversion and thermal energy capture. The receiver design enables a high penetration of concentrated sunlight deep into the thermal receiver to increase light trapping and reduce thermal losses. The thermal receiver is integrated with a photovoltaic (PV) receiver platform that converts some of the incident light to electricity while passing the remaining light to the thermal receiver. In another embodiment, other thermal receivers, systems, and methods are disclosed that efficiently capture concentrated solar energy into a sheet of falling particles. In an embodiment, the thermal receivers, systems, and methods enable simultaneous electricity conversion and thermal energy capture.

Ho, Clifford K.↗

Impacts of Biomass Feedstock Pre-Processing on Heat and Mass Transfer During Pyrolysis Using X-Ray Computed Tomography and Multiscale Modeling

Knowledge of the transport properties of biomass particles such as porosity, tortuosity, and permeability is paramount for high-fidelity modeling of biomass pyrolysis due to the heat and mass transfer limitations imposed by particle microstructure. X-ray computed tomography (XCT) is a non-destructive imaging method that enables full 3D reconstructions of the biomass particle microstructure with high resolution, permitting direct calculation of porosity, tortuosity, and permeability from real particle geometries. In this study, XCT imaging revealed the 3D microstructures of particles and chars from pyrolytic conversion of cylindrically cut or milled/pelletized loblolly pine samples. The porosity, tortuosity, and permeability were calculated directly from the XCT geometries via open-source microstructural analysis tool MATBOX+TauFactor (https://github.com/NREL/MATBOX_Microstructure_analysis_toolbox) and computational fluid dynamics (CFD) simulations using our solver, Mesoflow (https://github.com/NREL/mesoflow). These properties were used in a reactor scale model developed in COMSOL of the single particle reactor at NREL to investigate the impact of feedstock pre-processing on biomass conversion during pyrolysis with rigorous experimental validation.

biomass↗

Extending TOUGH + HYDRATE with a parallel particle transport simulator: numerical investigation of sand production during gas production from hydrate deposits

A new parallel code for simulating particle transport in porous media is integrated with the TOUGH + HYDRATE simulator to investigate sand production associated with gas production from unconsolidated gas hydrate-bearing sediments (HBS). Here, the parallel coupled simulator is named THMPT and uses the integral finite difference method to describe the Darcian and non-Darcian flow of fluids and heat transport, the finite element method to describe the associated geomechanical changes, and the discrete element method to track the trajectory of individual sand particles within the HBS. The THMPT simulator is written in Fortran, incorporates multiple optimized algorithms, and can comprehensively address the coupled flow, thermal, chemical, geomechanical, and particle transport processes that characterize the system behaviors during gas production from HBS. The simulator can capture all processes involved in sand particle transport in porous media, including sand detachment, collision, clogging (i.e., bridging), and migration. A benchmark case study of sand production in the course of depressurization-induced gas production from a representative HBS reveals various distinct microscopic particle migration mechanisms and the adverse impact of sand particle detachment, transport, and clogging. The numerical investigation also examines the effect of bottomhole pressure on mitigating sand production. The simulation results indicate that sand clogging near the wellbore significantly reduces permeability, decreasing gas production by at least 50%. Lastly, the efficiency of gravel packing in mitigating sand production is numerically evaluated, revealing that the structure of the porous media appears to profoundly influence the macroscopic motion behavior of sand particles and sand clogging characteristics.

discrete element method↗

Low Energy Neutron-induced Charged-particle (Z) (LENZ) instrument development with a focus on pulse shape discrimination for low-energy charged particles

To study neutron-induced charged-particle reactions with high precision, the Low Energy Neutron-induced Charged-particle (Z) instrument (LENZ) was developed at the Los Alamos Neutron Science Center. For the interest of measuring (n,p) and (n, α) reactions simultaneously, Pulse Shape Discrimination methods were investigated to identify different charged particles in the energy range of 3 - 20 MeV and improve signal-to-background ratios using Double-sided Silicon Strip Detectors and waveform digitizers. The risetime and pulse shape properties of detected charged particles were characterized for various silicon detector’s thickness with different orientations. During the post-processing of waveforms, we implemented different digital filters for effective particle identifications and improved energy- and timing- resolutions. We validated the optimized digital filters and pulse shape analyses, via measurements with 228 Th and 229 Th calibration sources, proton-induced reactions on a 7 LiF target, and neutron-induced reactions on CH 2 , Ta 2 O 5 , 58 Ni, and 6 LiF/ 59 Ni targets at the time-of-flight facility, LANSCE. In conclusion, the summary of effective thresholds and Figure of Merits on separating different charged particles is reported.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Studying fast-ion populations using oscillations in solid-state neutral-particle analyzer signal and neutral-beam injection power

A method for determining the fast-ion population density in magnetically confined plasmas as a function of pitch-radius, (λ, R), using a solid-state neutral-particle analyzer (ssNPA) signal and neutral-beam injection (NBI) power-output data has been developed. Oscillations in the NBI power output are replicated only in the active part of the ssNPA signal, allowing this to be separated from the passive and background signals, which usually complicate data from this diagnostic. Results obtained using this method are compared with those from standard techniques using data from the Mega-Amp Spherical Tokamak Upgrade spherical tokamak.

Instruments & Instrumentation↗

Identification of uranium oxidation states using oxygen K-edge scanning transmission X-ray microscopy

The field of nuclear forensics is growing in importance, and the increasing capabilities at synchrotron radiation light sources enable non-destructive characterization of oxide particles with better spatial, compositional, and oxidation state speciation resolution than ever before. Here, uranium oxide particles derived from multiple wet chemical processing methods were examined using a scanning transmission X-ray microscope (STXM), and a weakly-supervised method was developed to automatically analyze the collected data. Multiple uranium oxidation states were observed and quantified within and between samples, yielding information about differences between particles produced via the various processing routes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A large expert-curated cryo-EM image dataset for machine learning protein particle picking

Cryo-electron microscopy (cryo-EM) is a powerful technique for determining the structures of biological macromolecular complexes. Picking single-protein particles from cryo-EM micrographs is a crucial step in reconstructing protein structures. However, the widely used template-based particle picking process is labor-intensive and time-consuming. Though machine learning and artificial intelligence (AI) based particle picking can potentially automate the process, its development is hindered by lack of large, high-quality labelled training data. To address this bottleneck, we present CryoPPP, a large, diverse, expert-curated cryo-EM image dataset for protein particle picking and analysis. It consists of labelled cryo-EM micrographs (images) of 34 representative protein datasets selected from the Electron Microscopy Public Image Archive (EMPIAR). The dataset is 2.6 terabytes and includes 9,893 high-resolution micrographs with labelled protein particle coordinates. The labelling process was rigorously validated through 2D particle class validation and 3D density map validation with the gold standard. The dataset is expected to greatly facilitate the development of both AI and classical methods for automated cryo-EM protein particle picking.

42 ENGINEERING↗

Direct cross section measurement of 102 Pd ⁢(𝛾,𝑝) and 102 Pd ⁢(𝛾,𝛼) for the astrophysical 𝑝 process

Background: A handful of neutron-deficient stable nuclei, known as the “p nuclei,” cannot be produced through astrophysical neutron capture processes. Instead, some of these nuclei are proposed to be produced by 𝛾-induced reactions on existing r- and s-process seeds. The specific astrophysical site or sites are not yet identified, however, with uncertainties in the cross sections of these 𝛾-induced reactions playing a role. Databases of reaction rates for astrophysical simulations often rely on theoretical statistical model calculations, such as Hauser-Feshbach, for rates where no experimental information is known. However, reasonable variations in the choice of parametrizations of various nuclear properties can create order-of-magnitude variations in the final predicted cross sections and reaction rates, which are then propagated through the models to the predicted final abundances. Purpose: To better constrain these statistical model calculations and ultimately reduce the uncertainties from the nuclear physics on our understanding of the p nuclei, a measurement of the cross sections of 𝛾-induced reactions on the p-nucleus 102 Pd was undertaken. This work represents the first measurement of its kind, using segmented silicon detectors to measure prompt charged particle emission from 𝛾-induced reactions. Methods: Quasimonoenergetic gamma beams from the High Intensity 𝛾 Source facility bombarded an enriched 102 Pd target. A segmented silicon array was arranged to detect the particles emitted from (𝛾,𝑝) and (𝛾,𝛼) reactions. Results: Reaction cross sections were deduced at multiple 𝛾-beam energies between 10 and 19 MeV, and compared to statistical model calculations using talys-1.96. The 102 Pd ⁢(𝛾,𝑝)⁢ 101 Rh reaction cross section was reasonably well reproduced by a subset of photon strength functions and level densities, though the strength to the ground state of 101 Rh was underestimated at higher incident gamma energies. The 102 Pd ⁢(𝛾,𝛼)⁢ 98 Ru was in general overpredicted by the various alpha-nucleus optical model potentials. Conclusions: While the theoretical cross sections used to model the (𝛾,𝑝) reactions for the p process may be reasonable, a more careful approach is needed in the case of (𝛾,𝛼). Further work to probe gamma-induced reaction cross sections at and near the p nuclei is warranted.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗