Identification and Elemental Impurity Analysis of Heterogeneous Morphologies in Uranium Oxides Synthesized from Uranyl Fluoride Precursors

Abstract

The surface morphology characteristics of postenrichment deconversion products in the nuclear fuel cycle are important for producing nuclear fuel pellets. They also provide the first opportunity for a microstructural signature after conversion to gaseous uranium hexafluoride (UF 6 ). This work synthesizes uranium oxides from uranyl fluoride (UO 2 F 2 ) starting solutions by the wet ammonium diuranate route and a modification of the dry route. Products are reduced under a nitrogen/hydrogen atmosphere, with and without water vapor in the reducing environment. The crystal structures of the starting materials and resulting uranium oxides are characterized by powder X-ray diffraction. Scanning electron microscopy (SEM) and focused ion beam SEM with energy-dispersive X-ray spectroscopy (EDX) are used to investigate microstructural properties and quantify fluorine impurity concentrations. Heterogeneous distributions of fluorine with unique morphology characteristics were identified by backscatter electron imaging and EDX; these regions had elevated concentrations of fluorine impurities relating to the incomplete reduction of UO 2 F 2 to UO 2 and may provide a novel nuclear forensics morphology signature for nuclear fuel and U metal precursors.

Oxygen Isotope and Fluorine Impurity Signatures during the Conversion of Uranium Ore Concentrates to Nuclear Fuel

“…The other half of the UO 2 F 2 was directly dried and again split in half for reductions with or without steam. 19 Reduction of MDU, ADU, and UO 2 F 2 to UO x . The reduction of MDU, ADU, and UO 2 F 2 to UO x was reported previously.…”

“…The average water vapor concentration in a 50 mL min −1 wet N 2 stream coupled with a 440 mL min −1 dry UHP N 2 stream was 5240 ± 40 ppm, analyzed by cavity ring down spectroscopy (CRDS) measurements taken over 30 min. 19 For a flow of 60 mL•min −1 , the water vapor concentration was 6290 ± 50 ppm; 19 the δ 18 O value of the water vapor was −25.11 ± 0.36‰. 19 We did not measure the δ 18 O value of the liquid water from which the vapor was generated; however, 13 tap water samples collected between 2013 and 2023 from the University of Utah campus near the lab discussed herein have an average δ 18 O value of −15.86‰ (±0.41‰) (waterisotopes.org, projects 00058, 00059, 00064).…”

“…19 For a flow of 60 mL•min −1 , the water vapor concentration was 6290 ± 50 ppm; 19 the δ 18 O value of the water vapor was −25.11 ± 0.36‰. 19 We did not measure the δ 18 O value of the liquid water from which the vapor was generated; however, 13 tap water samples collected between 2013 and 2023 from the University of Utah campus near the lab discussed herein have an average δ 18 O value of −15.86‰ (±0.41‰) (waterisotopes.org, projects 00058, 00059, 00064). 21 Based on H 2 O liquid−vapor oxygen isotope fractionation, the theoretical δ 18 O value of the vapor in equilibrium with this water (liquid) at 25 °C is −25.16‰; 22 the calculated water vapor δ 18 O value closely approximates the measured water vapor δ 18 O value.…”

“…For each analysis, the primary ion beam was rastered over a 150 × 150 μm area, using a 10 pA primary ion beam current. Secondary ion signals from 18 O (50−500 cps), 19 F (500−400,000 cps), and 238 U 16 O (50−1000 cps) were measured by hopping the magnet and detecting with one axial EM. Note that the measured 18 O signal was only used to confirm the spatial locations of 238 U 16 O signal from particles.…”

In Situ Liquid Cell Transmission Electron Microscopy Study of Studtite Particle Formation and Growth via Electron Beam Radiolysis

“…Controlling particle morphology is of great importance to many industries including semiconductors, nanomaterials, and steel fabrication. − Levlev et al showed that a mechanistic understanding of nucleation and growth mechanisms can lead to improved modeling of material properties and future material discovery . In the nuclear industry, particle morphology can impact the environmental transport of uranium, nuclear fuel performance in reactors, long-term storage of spent nuclear fuel, and support nuclear forensics and nuclear safeguards in identifying the processing history of nuclear materials. ,, Prior studies have identified many variables including pH, temperature, reaction time, and calcination temperature that impact the final particle morphology. − Advancements in particle segmentation and machine learning enable quantification of even subtle morphology changes. , The challenge, however, has been in understanding the fundamental principles that result in unique particle morphologies based on the chemical and physical processing conditions. In situ liquid phase transmission electron microscopy can help reveal the underlying mechanisms of particle formation, particularly when the impacts of radiolysis can be mitigated. , In the case of studtite, electron beam radiolysis of uranyl solutions enables the controlled in situ precipitation of particles under different reaction conditions.…”