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Results for “URANIUM OXIDE”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Electronic and Geometric Contributors to Hydrogen Binding in Uranium Oxide Grain Boundaries

Hydrogen induced corrosion of uranium, which leads to the formation of toxic and pyrophoric UH 3 , raises significant safety concerns for long-term storage of nuclear materials. Previous work suggests hydrogen diffuses through the grain boundaries (GBs) of the passivating oxide layer to initiate hydriding reactions. However, the atomistic mechanisms underlying this phenomenon and the structural factors that control its initiation are not well understood. To address this knowledge gap, here we use a high-throughput density functional theory (DFT) workflow to investigate the adsorption of H and H 2 in the defective bulk UO 2 . Specifically, we have exhaustively investigated the adsorption of H (107 sites) and H 2 (26 sites) in three different coincident site lattice (CSL) GBs: Σ3, Σ5, and Σ9. Compared to the binding energies in pristine UO 2 , we observe significantly stronger hydrogen adsorption at these GB sites. Interestingly, we find that the trends in H and H 2 adsorption vary considerably across the three GB models. In particular, while a small number of sites in Σ5 and Σ9 show exothermic adsorption of H and H 2 , respectively, no such sites are found in Σ3. These results provide fundamental atomistic insights that could guide the development of future corrosion mitigation strategies for the storage of nuclear materials.

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

The influence of cooling rate on condensation of iron, aluminum, and uranium oxide nanoparticles

Fundamental observations of particle size distributions are needed to develop models that predict the fate and transport of radioactive materials in the atmosphere following a nuclear incident. The extent of material transport is influenced by the time scales of particle formation processes (e.g., condensation, coagulation). In this study, we investigated the influence of cooling time scales on size distributions of uranium, aluminum, and iron oxide particles that are synthesized separately under identical run conditions inside the controlled environment of an argon plasma flow reactor. Two distinct temperature distributions are imposed along the flow reactor by varying the argon flow rate downstream of the plasma torch. The vaporized reactants of uranium, aluminum, and iron are cooled from about 5000K to 1000K before they are collected on silicon wafers for ex situ scanning electron microscope analysis. The microscope images show that the sizes of the largest aluminum and iron oxide particles heavily depend on the cooling time scales, whereas significant size variation with cooling rate is not observed for uranium oxide particles. In addition, the size distribution of aluminum oxide particles exhibits the broadest range among all three metal oxides studied. We performed simulations of particle size distributions using a kinetic model that couples gas phase oxidation chemistry with particle formation processes, including nucleation, condensation, and coagulation. The model results demonstrate the strong sensitivity of particle size distribution to different cooling histories (i.e., temperature vs residence time) along the flow reactor. In conclusion, the kinetic model also helps identify directions for future research to improve the predictions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Exploring uranium oxidation in glue vapor to help avoid catastrophic slivers on NIF targets

Depleted uranium (DU) hohlraums are utilized for indirect drive fusion experiments at Lawrence Livermore National Laboratory. The production process for DU hohlraums is intricate, involving complex sputtering, machining, and leaching techniques. Achieving low-stress and defect-free hohlraums presents significant challenges. Recent failures have revealed that some uranium flakes, known as slivers, detach from the diagnostic windows and fall onto the capsule. These catastrophic failures were observed only after target assembly, leading to the hypothesis that oxidation of the DU by glue vapor might be the cause. A study investigating the impact of glue vapor on DU hohlraums found that spallation occurred in three out of seven sample hohlraums after three weeks. The slivers observed in these samples were consistent with those seen in assembled targets. This marks the first experimental reproduction of such catastrophic slivering failures. Consequently, future studies can now focus on sliver mitigation and the precise diagnosis of the failure mode.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Uranium Oxide Elutriation at Higher Flow Rates and Longer Times

This work supports the recovery of high-assay low-enriched uranium (i.e., U enriched in 235 U to >5% and <20%) from used nuclear fuel. One step includes elutriating triuranium octoxide (U 3 O 8 ) from a fluidized bed of alumina (Al 2 O 3 ) that fills the main reaction chamber. The experiments outlined in this report assessed the effects of the time and flow rate on the elutriation of U 3 O 8 powder from the reaction vessel. Testing at Oak Ridge National Laboratory (ORNL) was performed in a one-fourth scale experimental apparatus based on a pilot-scale system, which is the Material Recovery Pilot Plant (MRPP) at Idaho National Laboratory (INL). The experimental system comprises a supply of pressurized nitrogen (N 2 ), a gas heater, the reaction vessel, a knock-out pot, and a water trap where elutriated particles are collected for sampling. An Al 2 O 3 fluidized bed is contained within the reaction vessel. A bed of Al 2 O 3 with a nominal size of 180 µm and U 3 O 8 with a nominal size of 7 µm was fluidized at 2 different flow rates so the U 3 O 8 physically separated from the bed. The apparatus was simple and had no valves or sharp bends downstream from the reactor. The flow exited the reactor through a side port at the top. The flow passed through a knock-out vessel before the flow was passed through a bubbler to capture the U 3 O 8 . Seven tests were completed with U 3 O 8 using an elutriating gas of N 2 heated to 200°C. Tests were performed with bed loadings that comprise 25.0 g of U 3 O 8 , or 3.6 wt% of the bed mass. Except for one test performed at 12 SLPM, the gas flow rate through the bed for the other experiments was set at 10 SLPM as measured by the mass flow meter. Linear velocities through the bed were calculated as 28 and 34 cm/s, or 0.9 and 1.1 ft·s -1 . The duration of the tests ranged from 20 to 180 min, and one test had a flow cycled between 0 and 5 SLPM every 5 min for 40 min. The testing successfully demonstrated elutriation of U 3 O 8 from the fluidized bed as up to a 100% of the U 3 O 8 was transferred out of the bed. The removal of U 3 O 8 had a logarithmic dependence on flow rate. The design changes made the apparatus easier to clean, and the mass balances were better than those used in previous studies. Some elutriated Al 2 O 3 collected in the tubing that connected the reactor to the knock-out pot, but the amount of Al 2 O 3 was minimal for 10 SLPM. The flow at 12 SLPM showed considerable transport of Al 2 O 3 bed material into the reaction-vessel headspace and the transfer line to the knock-out pot.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Uranium Oxide Synthetic Pathway Discernment through Unsupervised Morphological Analysis

We present a novel unsupervised machine learning method for quantitative representation of scanning electron micrographs and its applications and performance for nuclear forensic analysis of uranium ore concentrates. The method uses a vector quantizing variational autoencoder followed by a histogram operation to encode a micrograph into a single dimensional representation, called the latent vector. The method requires no extant labeling of the data and can be applied over large datasets of micrographs with minimal human interaction. The representations generated are broadly descriptive of each micrograph and the microstructure of the material imaged. In the case of uranium ore concentrate analysis, the representations were amenable to processing reagent and ore concentrate species classification with accuracy of 81:8%, which is competitive with state-of-the-art supervised networks. The representations were also used to classify previously unseen processing routes, were able to classify imaging parameters such as magnification (to 76:0% accuracy), were able to classify fine grained process parameters such as calcining temperature (to 74:4% accuracy), and their informatic properties indicate that they are generally descriptive of the image represented. This method can be applied across microstructure analysis fields to perform quantitative analysis without the need for labor intensive and possibly biased human analysis.

Scanning Electron Microscopy, Vector Quantizing Va↗
DOE OSTI2020

Impact of uranium oxide (UO 2 ) fuel with molybdenum (Mo) inserts on pressurized water reactor performance and safety

This work investigates nuclear reactor performance and safety characteristics of UO 2 with high thermal conductivity Mo insert structures by using multiphysics modeling techniques. Additionally, the purpose of this study is to use scoping analyses to quantify the impact of using Mo inserts from neutronic and heat transfer standpoints. Attention is given to reactor performance parameters, such as cycle length, maximum fuel temperature, temperature gradients in the fuel, and stored energy in the fuel. The finite-element code BISON and the Monte Carlo particle transport code Serpent were used to perform sensitivity analyses on the Mo insert geometry to optimize the insert design and inform larger scale modeling that required the homogenization of the UO 2 and Mo. Although BISON is often used as a fuel performance analysis tool, it is used in this context for heat transfer analysis only. Fuel performance optimization is outside the scope of the current study, but would be important for future work focused on this concept. The results showed that the insert had little impact on neutronic performance and that homogenizing the UO 2 and Mo was acceptable for reactor physics calculations. Reactivity temperature coefficients calculated using homogeneous UO 2 -Mo were shown to be relatively similar to UO 2 , but higher Mo content and 235 U enrichment can reduce the worth of soluble boron and control rods. The effect of insert geometry on heat transfer was much greater, and an approximately 15–20% difference in maximum fuel temperature was predicted between the best and worst performing heat transfer geometries. Furthermore, thermal conductivity calibration based on the finite element analysis results was performed to improve the accuracy of temperature predictions in reactor analysis models that homogenized the UO 2 -Mo fuel. Compared with UO 2 in a pressurized water reactor (PWR), the optimized UO 2 -Mo design increased the margin to fuel melt by 13–32% across the fuel cycle, but it requires the 235U enrichment to exceed 5% to match the cycle length of conventional UO 2 .

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Raman spectroscopic investigation of ianthinite [U$_2^{4+}$(UO$_2$)$_4$O$_6$(OH)$_4$(H$_2$O)$_4$]·$5$H$_2$O, a rare mixed-valence uranium oxide hydrate

Ianthinite ([[U$_2^{4+}$(UO$_2$)$_4$O$_6$(OH)$_4$(H$_2$O)$_4$]·$5$H$_2$O) is an exotic mineral that possesses U in both tetravalent and hexavalent oxidation states and is structurally related to the U 3 O 8 polymorphs, which are commonly encountered technogenic materials in the nuclear fuel cycle. Despite the similarities between U 3 O 8 and ianthinite, and the importance of ianthinite in U paragenesis, no Raman spectra have been reported for this mineral. Here, to gain a more complete understanding of how structural attributes of ianthinite give rise to observable spectroscopic features and how these may relate to important materials in the nuclear fuel cycle, we provide, for the first time, Raman spectra of ianthinite. Ianthinite readily oxidizes at ambient conditions, complicating analysis of phase-pure material. Several analytical methods are employed herein to decouple the Raman features of ianthinite from its alteration product(s). First, a simple difference spectrum is presented, then results of Raman spectroscopic mapping are employed, and finally, we use a novel processing and analysis method. Each analysis method provides different insight into structural features that are unique to ianthinite, in particular, features that are attributable to U(IV) in distorted octahedral coordination in both ianthinite and U 3 O 8 phases.

Spano, Tyler L. [Oak Ridge National Laboratory (OR↗
DOE OSTI2022

Irradiation of MiniFuel Targets Bearing TRISO Fuel Compacts (Status Report)

Irradiation testing of MiniFuel compacts bearing tristructural isotropic (TRISO) fuel particles was performed at Oak Ridge National Laboratory (ORNL) to support the development of Kairos Power’s (KP’s) fluoride salt–cooled high-temperature reactor concept. The fuel compacts were fabricated with TRISO fuel particles of different types—including low-enriched uranium oxide, uranium carbide (LEUCO), natural uranium oxide, uranium carbide (NUCO), and low-enriched uranium dioxide (LEUO 2 )—and inserted into MiniFuel irradiation targets. Five targets were assembled and inserted in the High Flux Isotope Reactor (HFIR) for four cycles. The data collected post-irradiation will provide experimental input to validate TRISO fuel performance models for high particle power operations. This report summarizes the completion of the HFIR irradiation, the as-irradiated numerical analysis, and the post-irradiation work performed to date. This work was performed under the Nuclear Science User Facility program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Improving robustness for model discerning synthesis process of uranium oxide with unsupervised domain adaptation

The quantitative characterization of surface structures captured in scanning electron microscopy (SEM) images has proven to be effective for discerning provenance of an unknown nuclear material. Recently, many works have taken advantage of the powerful performance of convolutional neural networks (CNNs) to provide faster and more consistent characterization of surface structures. However, one inherent limitation of CNNs is their degradation in performance when encountering discrepancy between training and test datasets, which limits their use widely. The common discrepancy in an SEM image dataset occurs at low-level image information due to user-bias in selecting acquisition parameters and microscopes from different manufacturers. Therefore, in this study, we present a domain adaptation framework to improve robustness of CNNs against the discrepancy in low-level image information. Furthermore, our proposed approach makes use of only unlabeled test samples to adapt a pretrained model, which is more suitable for nuclear forensics application for which obtaining both training and test datasets simultaneously is a challenge due to data sensitivity. Through extensive experiments, we demonstrate that our proposed approach effectively improves the performance of a model by at least 18% when encountering domain discrepancy, and can be deployed in many CNN architectures.

scanning electron microscopy↗