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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

WALLABY Pre-pilot Survey: The Effects of Tidal Interaction on Radial Distribution of Color in Galaxies of the Eridanus Supergroup

We study the tidal interaction of galaxies in the Eridanus supergroup, using H i data from the pre-pilot survey of the Widefield ASKAP L-band Legacy All-sky Blind surveY. We obtain optical photometric measurements and quantify the strength of tidal perturbation using a tidal parameter S sum . For low-mass galaxies of M * ≲ 10 9 M ⊙ , we find a dependence of decreasing H i to optical disk size ratio with increasing S sum , but no dependence of H i spectral line asymmetry with S sum . This is consistent with the behavior expected under tidal stripping. We confirm that the color profile shape and color gradient depend on the stellar mass, but there is an additional correlation of low-mass galaxies having their color gradients within 2R 50 increasing with higher S sum . For these low-mass galaxies, the dependence of color gradients on S sum is driven by the color becoming progressively redder in the inner disk when tidal perturbations are stronger. For high-mass galaxies, there is no dependence of color gradients on S sum , and we find a marginal reddening throughout the disks with increasing S sum . Our result highlights tidal interaction as an important environmental effect in producing the faint end of the star formation suppressed sequence in galaxy groups.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

One Galaxy Sample to Rule Them All: Halo Occupation Distribution Modeling of DES Year 3 Source Galaxies

Abstract For the joint analysis of second-order weak-lensing and galaxy clustering statistics, so-called 3 × 2 analyses, the selection and characterization of optimal galaxy samples is a major area of research. One promising choice is to use the same galaxy sample as lenses and sources, which reduces the systematics parameter space that describes the uncertainties related to galaxy samples. Such a “lens-equal-source” analysis significantly improves the self-calibration of photo- z systematics, leading to improved cosmological constraints. With the aim of enabling a lens-equal-source analysis on small scales, we investigate the halo–galaxy connection of DES Year 3 source galaxies. We develop a technique to construct mock source galaxy populations by matching COSMOS/UltraVISTA photometry to U niverse M achine galaxies. These mocks predict a source halo occupation distribution (HOD) that exhibits significant redshift evolution, nontrivial central incompleteness, and galaxy assembly bias. We produce multiple realizations of mock source galaxies drawn from the U niverse M achine posterior, with added uncertainties in the measured Dark Energy Survey photometry and galaxy shapes. We fit a modified HOD formalism to these realizations to produce priors on the galaxy–halo connection for cosmological analyses. We additionally train an emulator that predicts this HOD to ∼2% accuracy from redshift z = 0.1−1.3 that models the dependence of this HOD on (1) observational uncertainties in galaxy size and photometry and (2) uncertainties in the U niverse M achine predictions.

Salcedo, Andrés N. (ORCID:000000031420527X)↗
DOE OSTI2026

What Shapes Transportation Charging Infrastructure Availability? Evidence from Tennessee

This study examines how community, travel, and freight characteristics relate to public charging infrastructure availability across Tennessee ZIP codes. We link Alternative Fuels Data Center station locations with traffic, socioeconomic, demographic, commuting, and freight employment data to build a ZIP code-level dataset. Ordinary least squares regression captures variation in chargers per 10,000 residents (R2=0.311). Quantile regressions at the 25th, 50th, and 75th percentiles, with pseudo R2 values up to 0.099, show that the determinants of infrastructure availability differ across low-, medium-, and high-availability areas. Percent female, percent car commuters, average household size, and median age are negatively associated with charging availability across much of the distribution. Truck traffic is positively associated only in lower-availability ZIP codes, while vehicle miles traveled shifts from a negative association at the lower end of the distribution to a positive association at the upper end. The results provide insight into how public charging deployment aligns with community characteristics, mobility demand, and freight activity across Tennessee. Future work can distinguish charger types and power levels, incorporate land-use and temporal rollout patterns, and examine how charging infrastructure needs differ across urban and rural contexts.

Calderón, Oriana [University of Tennessee, Knoxvil↗
DOE OSTI2021

Deep learning inversion of gravity data for detection of CO 2 plumes in overlying aquifers

In this work, we developed an effective U-Net based deep learning (DL) model for inversion of surface gravity data on a rectangular grid to predict 2-D high-resolution subsurface CO 2 distribution along a vertical cross-section due to CO 2 leakage through a wellbore within a deep CO 2 storage reservoir. We used synthetic data to model two types of CO 2 leakage scenarios: one CO 2 plume in a shallow aquifer (single plume case), and two plumes present at different depths (double plume case). The 3-D synthetic plume samples were created by sampling among predetermined CO 2 plume depths, saturations, and volumes. The corresponding surface gravity data on a rectangular grid were generated by a 3-D forward model. The U-Net model detected 72% of single-plume samples, and one or both plumes in 75% of double-plume samples. Most of the undetected single plumes have small gravity field strengths below the typical noise level of 5 μGal. This model generated reproducible, reliable predictions with acceptable errors and demonstrated improved spatial resolution over the conventional least-squares inversion. In contrast to the conventional least-squares inversion, which often overestimates the size of its target and underestimates its density, this U-Net model accurately delineated the boundary of a target. Furthermore, this DL inversion detected deep, small, or low saturation CO 2 plumes that are often more difficult to resolve with conventional gravity inversion methods. We note the limitations of this feasibility study, including the use of synthetic data with regular CO 2 plume shapes, and the prediction of a 2-D plume cross-section rather than the full 3-D plume, as well, we recognize the lower detection fraction for double-plume scenarios. Nevertheless, this study demonstrates that DL gravity inversion is a promising and potentially superior method to conventional least-squares inversion. Our U-Net based deep learning inversion approach may be adapted for inversion of other types of geophysical data. DL inversion can facilitate near real-time monitoring of geologic carbon sequestration to provide site operators with prompt information about subsurface CO 2 distribution for risk management and mitigation.

58 GEOSCIENCES↗
DOE OSTI2020

Measurements of $\pi^-$ production in $^7$Be+$^9$Be collisions at beam momenta from 19$A$ to 150$A$GeV/$c$ in the NA61/SHINE experiment at the CERN SPS

The NA61/SHINE collaboration studies at the CERN Super Proton Synchrotron (SPS) the onset of deconfinement in hadronic matter by the measurement of particle production in collisions of nuclei with various sizes at a set of energies covering the SPS energy range. This paper presents results on inclusive double-differential spectra and mean multiplicities of $\pi^{-}$ mesons produced in the 5% most central $^7$Be + $^9$Be collisions at beam momenta of 19$A$, 30$A$, 40$A$, 75$A$ and 150$A$ GeV/$c$ obtained by the so-called $h^-$ method which does not require any particle identification. The shape of the transverse mass spectra differs from the shapes measured in central Pb + Pb collisions and inelastic p + p interactions. The normalized width of the rapidity distribution decreases with increasing collision energy and is in between the results for inelastic nucleon-nucleon and central Pb + Pb collisions. The mean multiplicity of pions per wounded nucleon in central $^7$Be + $^9$Be collisions is close to that in central Pb + Pb collisions up to 75$A$GeV/$c$. However, at the top SPS energy the result is close to the one for inelastic nucleon-nucleon interactions. The results are discussed in the context of predictions for the onset of deconfinement at the CERN SPS collision energies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Parameterizations of Entrainment-Mixing Mechanisms and their Effects on Cloud Droplet Spectral Width Based on Numerical Simulations

Entrainment-mixing mechanisms significantly affect cloud droplet number concentration, radius, and spectral shape. Quantitative examination of entrainment-mixing effects on cloud droplet spectral width is lacking. Here, we examine the effects of entrainment-mixing processes on cloud microphysics by 12,218 different setups, each simulated 10 times using the Explicit Mixing Parcel Model (EMPM) driven by the observational data from the Third Tibetan Plateau Atmospheric Scientific Experiment (TIPEX-III) campaign. Parameterizations of entrainment-mixing mechanisms are developed by relating homogeneous mixing degree to transition scale number that depends on the dissipation rate and droplet evaporation time scale. The correlation between relative dispersion of cloud droplet size distribution and homogeneous mixing degree changes from negative to positive with the decreasing homogeneous mixing degree. The different relationships are closely related to the competition between complete and partial droplet evaporation and the number concentration of small droplets, which are quantitatively described by two newly introduced dimensionless numbers. The competition is significantly affected by relative humidity and mixing fraction of entrained air as well as turbulence dissipation rate, but not much by cloud droplet number concentration. Especially, when relative humidity and dissipation rate are high, there is only a negative correlation. This study sheds new light on generalizing the homogeneous/inhomogeneous concept by considering relative dispersion, and also provides parameterizations of entrainment-mixing processes and relative dispersion for atmospheric models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Fully Distributed Multi-Material Magnetic Sensing Structures for Multiparameter DAS Applications

This dissertation demonstrates the first of its kind distributed magnetic field sensor based on a fiber optic distributed acoustic sensing (DAS) scheme. Ferromagnetic nickel and Metglas® were dispersed internally within a fiber optic preform and then drawn on an in-house fiber optic draw tower to lengths in the kilometers. Due to the close proximity of the ferromagnetic metals and fiber optic core, the magnetostrictive strain response of the ferromagnetic materials when exposed to a magnetic field would perturbate within the fiber cladding and transfer that strain, internally, to the fiber optic core. Strain resulting from the magnetostrictive effect allows the DAS based sensor to accurately translate strain into readable magnetic field data. Due to the high sensitivity seen in this sensor design, multiparameter sources, acoustic and magnetic fields, were tested and validated and a three dimensional magnetic-field vector sensor was proposed. Numerical analysis of the novel sensor design was first implemented using COMSOL Multiphysics, where inputs such as magnetostrictive element shape, size, distance, and number were first investigated. Upon optimizing system constraints, the sensor design was further modified such that single mode operation was consistent across multiple fiber draws while retaining high strain transfer from the ferromagnetic elements to the fiber optic core. Ferromagnetic material selection was evaluated as a function of the saturation magnetostriction constants and a total of 4 modules were used to fully characterize the complex physics involved in this sensor design. All fabrication and testing were performed in-house using a full scale 3-story fiber draw tower and custom environmental testing stations to imitate naturally occurring events such as magnetic or acoustic point sources. A unique stacking method was used to embed ferromagnetic nickel and Metglas® into a fiber optic preform which when combined with a custom fiber draw process resulted in consistent multi-material fibers drawn to lengths of 1-km. In-house testing facilities included different types of electromagnetic generators, in addition to a soil test bed, and an outdoor test bed which allowed 100 meters of fiber to be tested simultaneously. All tested sensors demonstrated high strain transfer capabilities on the order of 0.01-10 μϵ depending on the materials used, ferromagnetic rod number, and core to metal spacing. Due to the sensitivity of the system the difference between AC and DC was distinct, and directional magnetostriction was studied. Transverse and longitudinal magnetic wave propagation was controlled through a solenoid and rectangular Helmholtz coil, both built in-house. A three-dimensional magnetic field vector sensor was proposed due to the success of the magnetic field sensor, and a design was proposed and initially tested to validate direction as a function of field strength and distance. To summarize, this dissertation explores the first fully distributed magnetic field sensor using DAS based techniques and one of the first multi-material fiber draw processes which can produce consistent single mode fiber up to 1-km. Due to extensive FEA modeling, multiple iterations of the magnetic sensor were fully characterized and an equation describing the relationship between sensor design and strain transfer has been created and validated experimentally. Multi-parameter tests including acoustic and magnetic fields were implemented and an algorithm was developed to separate the mixed signals. Finally, a test was performed to demonstrate the feasibility of sensing magnetic fields directionally. Cumulative results demonstrate a high-quality sensor alternative to current designs which may surpass other magnetic sensors due to innate multi-parameter capabilities, in addition to the inexpensive production cost and extremely long operating lengths.

02 PETROLEUM↗
DOE OSTI2023

SootLib: A soot model library for combustion simulation

Soot formation in combustion is an important process that affects radiative heat transfer, flame temperatures, and emissions with health and environmental impacts. Soot formation involves complex chemistry for nucleation, growth, oxidation, and coagulation processes. The soot particles vary widely in size and accurate modeling requires representation of the particle size distribution (PSD). Modeling soot is not trivial, and is only one of several physical processes active in combustion systems. This paper presents a software package called SootLib, which is an open-source library for modeling soot formation and other aerosol systems. SootLib is written in C++, is documented with Doxygen, and is available on GitHub. The library includes several models for soot chemistry and coagulation, and it represents the PSD using either a sectional model or the method of moments (MOM). Four closure approaches for the MOM are implemented allowing up to eight moments: monodispersed, an assumed-shape lognormal distribution, the quadrature method of moments, and the method of moments with interpolative closure. SootLib provides an interface for inclusion in other combustion packages including CFD or reacting flow solvers. The range of models allows comparisons and sensitivity studies, and the modularity facilitates extension to other soot models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Sensitivity of puff dynamics and airborne droplet nuclei distribution to variations in violent expiration events

Here, we use large eddy simulations to investigate the puff and droplet dynamics from violent expiratory events such as coughs and sneezes in the first few seconds following an ejection. For each of the eleven simulations considered, over 60,000 droplets are ejected and individually tracked using the point-particle Euler–Lagrange approach. We test the sensitivity of the puff and droplet dynamics to various parameters including the ejection volume, momentum, and orientation. We also explore the effect of the mouth shape on the aforementioned dynamics by considering elliptical and circular inlet cross-sections. The results from the simulations compare favorably with a recent theoretical framework put forth by Balachandar et al. in terms of the puff size and propagation velocity. More importantly however, the theory is able to accurately predict the number and size spectra of the potentially virus-laden droplet nuclei that remain airborne within the puff. We observe that the ejection angle and mouth shape do not significantly affect the puff and droplet dynamics. Additionally, we quantify the carrying capacity of the detached puff portions in terms of the number and size spectra of droplets/droplet nuclei suspended within.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

3D pore structure reconstruction of fluff region in top of EBR-II irradiated fuel by X-ray micro-computed tomography

Metallic fuels comprised of U-Zr binary and U-Pu-Zr ternary alloys are a promising fuel candidate for sodium-cooled fast reactors and possess many advantages over ceramic fuels such as higher uranium density and improved thermal conductivity. Fluff is a highly porous structure forming at the top of metallic fuel slugs during irradiation and was extensively observed in past sodium-cooled fast reactor (SFR) experiments such as Idaho National Laboratory’s Experimental Breeder Reactor II (EBR-II). Previous investigations have shown that fluff is rich in fissile atoms and hence could have neutronics implications, but its formation mechanisms are not understood. In this work, two cube-shaped lift outs were taken from the fluff and bulk fuel regions of a high burnup U-19Pu-10Zr composition EBR-II fuel slug and characterized by micro computed tomography (Micro-CT) and energy dispersive x-ray spectroscopy (EDS). This was used to characterize differences in microscale porosity and composition between fluff and bulk fuel, and to support or oppose postulated fluff formation mechanisms. Surface EDS showed minimal differences between the elemental compositions of the fluff and fuel cubes. However, three-dimensional (3D) pore analysis from the tomography scans showed significant differences between the fluff and fuel cube pore size distributions at the microscale level. The high porosity and irregular pore distribution seen in macroscale fluff was also present within the micro-scale fluff cube, having a much higher porosity than the fuel cube which was concentrated in a few large pore networks. In conclusion, these results indicate support for a creep driven mechanism of fluff formation.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Bootstrapping outperforms community‐weighted approaches for estimating the shapes of phenotypic distributions

Abstract Estimating phenotypic distributions of populations and communities is central to many questions in ecology and evolution. These distributions can be characterized by their moments (mean, variance, skewness and kurtosis) or diversity metrics (e.g. functional richness). Typically, such moments and metrics are calculated using community‐weighted approaches (e.g. abundance‐weighted mean). We propose an alternative bootstrapping approach that allows flexibility in trait sampling and explicit incorporation of intraspecific variation, and show that this approach significantly improves estimation while allowing us to quantify uncertainty. We assess the performance of different approaches for estimating the moments of trait distributions across various sampling scenarios, taxa and datasets by comparing estimates derived from simulated samples with the true values calculated from full datasets. Simulations differ in sampling intensity (individuals per species), sampling biases (abundance, size), trait data source (local vs. global) and estimation method (two types of community‐weighting, two types of bootstrapping). We introduce the traitstrap R package, which contains a modular and extensible set of bootstrapping and weighted‐averaging functions that use community composition and trait data to estimate the moments of community trait distributions with their uncertainty. Importantly, the first function in the workflow, trait_fill , allows the user to specify hierarchical structures (e.g. plot within site, experiment vs. control, species within genus) to assign trait values to each taxon in each community sample. Across all taxa, simulations and metrics, bootstrapping approaches were more accurate and less biased than community‐weighted approaches. With bootstrapping, a sample size of 9 or more measurements per species per trait generally included the true mean within the 95% CI. It reduced average percent errors by 26%–74% relative to community‐weighting. Random sampling across all species outperformed both size‐ and abundance‐biased sampling. Our results suggest randomly sampling ~9 individuals per sampling unit and species, covering all species in the community and analysing the data using nonparametric bootstrapping generally enable reliable inference on trait distributions, including the central moments, of communities. By providing better estimates of community trait distributions, bootstrapping approaches can improve our ability to link traits to both the processes that generate them and their effects on ecosystems.

Maitner, Brian S.↗
DOE OSTI2020

Concept Design of Active Shielding for Dynamic Wireless Charging of Light-duty EV

Dynamic wireless charging of electric vehicles is a flexible and state of the art charging technology with the potential capability of enabling fully automated in-motion charging. With charging power increasing to more than 100 kW for light duty vehicles, electromagnetic field (EMF) emission becomes a critical challenge. Due to the high costs of ferrite materials, this paper proposes an active shielding solution with multiple canceling coils installed on the ground side to supplement ferrite passive shielding to ensure electromagnetic safety. Two canceling coils are designed on two sides of the ground side coil. The canceling coils are small in size and 180 degree opposite in phase to the ground coil. Simulation and modeling shows that the canceling coils can reduce EMF emission from 37.2 µT to 18.2 µT at 0.8 m during 100 kW operation with only 2.5% of ground side current flowing in the canceling coils. These results have been preliminarily verified by inductance measurements and magnetic field measurement at 1.1 m distance without canceling coils. By further increasing the canceling coils’ currents to 4%, EMF emission can also be mitigated at 200 kW, although the canceling coils’ shape, position, and phase angle can be further optimized to improve the three-dimensional field distribution.

25 ENERGY STORAGE↗
DOE OSTI2025

Symmetry breaking during low-temperature domain formation in micron-sized magnetite crystals

We report the results of synchrotron Bragg Coherent x-ray Diffraction Imaging (BCDI) experiments to investigate domain formation in a micron-sized magnetite crystal undergoing the Verwey transition at low temperature. A strong splitting of the measured 311 Bragg reflection was observed in the low-temperature phase, indicating the formation of domains. BCDI revealed pronounced strain distributions, characterized by a clear layered stripe domain structure in real-space. Stripes were seen only along the [001] crystallographic direction, normal to the substrate surface direction, breaking the symmetry of the cubic high-temperature phase. It is argued that other domain directions were suppressed by the sample mounting orientation. More surprisingly, only a single domain orientation was observed, suggesting an additional symmetry-breaking influence originating from the shape of the crystal. Gaining insight into how thermal effects induce the formation of layered or striped phases offers a valuable framework for understanding the development of mesoscopic domains and strain patterns in functional materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Quantitative Evaluation of Top Coal Caving Methods at the Working Face of Extra‐Thick Coal Seams Based on the Random Medium Theory

Adopting an effective top coal caving method is the key to enhancing coal recovery and reducing gangue content for the fully mechanized top coal caving working face with extra‐thick coal seams. In this study, the movement of coal particles generated during top coal caving is considered to follow a normal distribution. Then, the caving body and coal‐rock settlement along the working face during the caving process are studied based on both the random media theory and probability theory. Accordingly, the optimal caving interval and caving sequences are determined, and a novel interval symmetrical coal caving method is proposed. The proposed method is systematically verified with results from physical similarity tests, and different caving methods are assessed by field tests. The results show the following: (1) The coal‐rock settlement and the caving body demonstrate clear axial symmetrical features along the working face; the size of the caving body increases as the caving height grows and its shape turns progressively from semicircular to semielliptical with a lower foot of the coal‐rock settlement. (2) The caving interval is derived using the sum of the radii of the coal‐rock settlement curves formed by the two largest caving bodies. (3) The symmetrical caving approach provides a symmetrical space for the subsequent movement of the broken top coal, which enables a uniform development of the caving body. (4) Compared with the traditional sequential coal caving method with the same number of supports, the interval symmetrical caving method results in a 21.7% of coal production increase, 17% caving rate promotion, and a shortened caving time by 23.4%. (5) The interval symmetrical caving method is found to improve the controllability of the caving process at the fully mechanized top coal caving working face. In general, this work presents a theoretical approach to select the optimal caving methods for the fully mechanized caving working face in extra‐thick coal seams for an improved production efficiency of the work face. The results of this study can also provide theoretical significance and referencing value for quantitative analyses of the coal caving methods for work faces with similar geological conditions.

Jiulin, Shi (ORCID:0000000155819062)↗
DOE OSTI2021

Effects of the large-scale circulation on temperature and water vapor distributions in the Π Chamber

Abstract. Microphysical processes are important for the development of clouds and thus Earth's climate. For example, turbulent fluctuations in the water vapor mixing ratio, r, and temperature, T, cause fluctuations in the saturation ratio, S. Because S is the driving factor in the condensational growth of droplets, fluctuations may broaden the cloud droplet size distribution due to individual droplets experiencing different growth rates. The small-scale turbulent fluctuations in the atmosphere that are relevant to cloud droplets are difficult to quantify through field measurements. We investigate these processes in the laboratory using Michigan Tech's Π Chamber. The Π Chamber utilizes Rayleigh–Bénard convection (RBC) to create the turbulent conditions inherent in clouds. In RBC it is common for a large-scale circulation (LSC) to form. As a consequence of the LSC, the temperature field of the chamber is not spatially uniform. In this paper, we characterize the LSC in the Π Chamber and show how it affects the shape of the distributions of r, T, and S. The LSC was found to follow a single roll with an updraft and downdraft along opposing walls of the chamber. Near the updraft (downdraft), the distributions of T and r were positively (negatively) skewed. At each measuring position, S consistently had a negatively skewed distribution, with the downdraft being the most negative.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Shapes of rotating normal fluid He-3 versus superfluid He-4 droplets in molecular beams

Previous single-pulse extreme ultraviolet and X-ray coherent diffraction studies revealed that superfluid 4He droplets obtained in free jet expansion acquire sizable angular momentum, resulting in significant centrifugal distortion. Similar experiments with normal fluid 3He droplets may help elucidating the origin of the of the large degree of rotational excitation and highlight similarities and differences of dynamics in normal and superfluid droplets. Here, we present the first comparison of the shapes of isolated 3He and 4He droplets following expansion of the corresponding fluids in vacuum at temperatures as low as ~ 2 K. Large 3He and 4He droplets with average radii of ~160 nm and ~350 nm, respectively, were produced. We find that the majority of the 3He droplets in the beam correspond to rotating oblate spheroids with reduced average angular momentum ($\Lambda$) and reduced angular velocities ($\Omega$) similar to that of 4He droplets. Given the different physical nature of 3He and 4He, this similarity in $\Lambda$ and $\Omega$ may be surprising and suggest that similar mechanisms induce rotation regardless of the isotope. We hypothesized that the observed distribution of droplet sizes and angular momenta stem from processes in the dense region close to the nozzle. In this region, the significant velocity spread and collisions between the droplets induce excessive rotation followed by droplet fission. The process may repeat itself several times before the droplets enter the collision-fee high vacuum region further downstream.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Characterization of ceramic fuel powder packing fractions to support INFLUX

Triply periodic minimal surface (TPMS)-based structures show marked potential in novel nuclear reactor fuel designs, as their high surface area-to-volume ratio increases the efficiency of heat transfer out of the fuel, enabling safer, more innovative reactor designs. This milestone report addresses the role of dUO 2 powder processing route on the fill behavior of TPMS-based cladding shells to understand and advance the feasibility of manufacturing TPMS-based nuclear fuel forms. dUO 2 powder was processed through either a dry granulation route, varying consolidation pressure, or through milling, varying milling time, milling method and milled size distribution. The lowest tapped bulk densities (TBD), but best powder flowabilities, were obtained when testing unprocessed dUO 2 powder which was prone to self-agglomeration and formed low-density spheroids. The highest TBD and lowest flowabilities were obtained when using powder produced by hammer-milling dUO 2 powder to pass through a 200-mesh sieve, which led to particles with angular morphologies. Powder produced by dry granulation exhibited TBD that varied according to the consolidation pressure used to form the initial pellets and exhibited improved flowabilities when compared to hammer-milled material. Because of the large span of granule sizes formed as well as the irregular shape associated with the granules, a packing fraction of 0.69 was achieved, exceeding the analytical solution for random close packing of mono-sized spheres. TPMS polymer shells were loaded with unprocessed, granulated, and hammer-milled dUO 2 powders, and their qualitative packing behaviors were analyzed using x-ray computed tomography (xCT). TBDs calculated after loading TPMS polymer shells were 10-20% lower when compared to tapped bulk density measurements taken in a glass graduated cylinder, indicating a non-trivial impact on the tapped bulk density of either the TPMS channel size, TPMS channel surface material, powder cohesiveness, or a combination of the two parameters. A metallic zircaloy-4 TPMS shell will be loaded with hammer-milled dUO 2 powder upon receipt of the shell from Oak Ridge National Laboratory (ORNL) and shipped to Idaho National Labs (INL) for subsequent hot isostatic pressing (HIP) densification experiments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Automated Gold Nanorod Spectral Morphology Analysis Pipeline

The development of a colloidal synthesis procedure to produce nanomaterials with high shape and size purity is often a time-consuming, iterative process. This is often due to quantitative uncertainties in the required reaction conditions and the time, resources, and expertise intensive characterization methods required for quantitative determination of nanomaterial size and shape. Absorption spectroscopy is often the easiest method for colloidal nanomaterial characterization. However, due to the lack of a reliable method to extract nanoparticle shapes from absorption spectroscopy, it is generally treated as a more qualitative measure for metal nanoparticles. This work demonstrates a gold nanorod (AuNR) spectral morphology analysis tool, called AuNR-SMA, which is a fast and accurate method to extract quantitative structural information from colloidal AuNR absorption spectra. To demonstrate the practical utility of this model, we apply it to three distinct applications. First, we demonstrate this model's utility as an automated analysis tool in a high-throughput AuNR synthesis procedure by generating quantitative size information from optical spectra. Second, we use the predictions generated by this model to train a machine learning model to predict the resulting AuNR size distributions under specified reaction conditions. Third, we apply this model to spectra extracted from the literature where no size distributions are reported and impute unreported quantitative information on AuNR synthesis. This approach can potentially be extended to any other nanocrystal system where absorption spectra are size dependent, and accurate numerical simulation of absorption spectra is possible. In addition, this pipeline could be integrated into automated synthesis apparatuses to provide interpretable data from simple measurements, help explore the synthesis science of nanoparticles in a rational manner, or facilitate closed-loop workflows.

36 MATERIALS SCIENCE↗