Quantifying Morphological Features of α-U<sub>3</sub>O<sub>8</sub> with Image Analysis for Nuclear Forensics

Olsen, Adam M.; Richards, Bryony; Schwerdt, Ian J.; Heffernan, Sean; Lusk, Robert; Smith, Braxton; Jurrus, Elizabeth; Ruggiero, Christy E.; McDonald, Luther W.

doi:10.1021/acs.analchem.6b05020

Cited by 52 publications

(36 citation statements)

References 38 publications

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“…Control samples were synthesized through the same procedure without the addition of impurities. The synthesis of studtite, (UO 2 )O 2 (H 2 O) 2 ·2H 2 O, from UNH and a molar excess of H 2 O 2 was described previously . Six total replicates were synthesized, and replicates 1–3 were filtered and washed with three aliquots of 50 mL of Millipore water to remove any residual nitrates .…”

Section: Methodsmentioning

confidence: 99%

“…Morphological features of U oxides have been previously shown to be a result of processing parameters including dependence on the starting material, intermediate material, oxidation rates, precipitation conditions, and thermal history . These were the first studies to successfully quantify morphological analysis of nuclear material and were essential to advancements in nuclear forensics and the nuclear fuels community.…”

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confidence: 98%

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Quantifying Impurity Effects on the Surface Morphology of α-U₃O₈

Hanson

Lee

Vachet³

et al. 2019

Anal. Chem.

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The morphological effect of impurities on α-U3O8 has been investigated. This study provides the first evidence that the presence of impurities can alter nuclear material morphology, and these changes can be quantified to aid in revealing processing history. Four elements: Ca, Mg, V, and Zr were implemented in the uranyl peroxide synthesis route and studied individually within the α-U3O8. Six total replicates were synthesized, and replicates 1–3 were filtered and washed with Millipore water (18.2 MΩ) to remove any residual nitrates. Replicates 4–6 were filtered but not washed to determine the amount of impurities removed during washing. Inductively coupled plasma mass spectrometry (ICP-MS) was employed at key points during the synthesis to quantify incorporation of the impurity. Each sample was characterized using powder X-ray diffraction (p-XRD), high-resolution scanning electron microscopy (HRSEM), and SEM with energy dispersive X-ray spectroscopy (SEM-EDS). p-XRD was utilized to evaluate any crystallographic changes due to the impurities; HRSEM imagery was analyzed with Morphological Analysis for MAterials (MAMA) software and machine learning classification for quantification of the morphology; and SEM-EDS was utilized to locate the impurity within the α-U3O8. All samples were found to be quantifiably distinguishable, further demonstrating the utility of quantitative morphology as a signature for the processing history of nuclear material.

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Section: Methodsmentioning

confidence: 99%

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confidence: 98%

Quantifying Impurity Effects on the Surface Morphology of α-U₃O₈

Hanson

Lee

Vachet³

et al. 2019

Anal. Chem.

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“…In particular, recent research has examined the morphology of various uranium oxides, with a focus on discerning process history or process conditions for a particular sample of material. [20][21][22][23][24][25][26][27][28][29][30][31][32]46 One outcome of these efforts was a lexicon to standardize descriptions of material images for nuclear forensics, indicating a likely increasing role for morphology within nuclear forensics. 33 Recent research has also investigated elemental and chemical impurities present in process samples of uranium compounds, also with a focus of discerning process history as well as the origin of the uranium.…”

Section: ■ Introductionmentioning

confidence: 99%

Progress in Uranium Chemistry: Driving Advances in Front-End Nuclear Fuel Cycle Forensics

et al. 2021

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The front-end of the nuclear fuel cycle encompasses several chemical and physical processes used to acquire and prepare uranium for use in a nuclear reactor. These same processes can also be used for weapons or nefarious purposes, necessitating the need for technical means to help detect, investigate, and prevent the nefarious use of nuclear material and nuclear fuel cycle technology. Over the past decade, a significant research effort has investigated uranium compounds associated with the front-end of the nuclear fuel cycle, including uranium ore concentrates (UOCs), UF 4 , UF 6 , and UO 2 F 2 . These efforts have furthered uranium chemistry with an aim to expand and improve the field of nuclear forensics. Focus has been given to the morphology of various uranium compounds, trace elemental and chemical impurities in process samples of uranium compounds, the degradation of uranium compounds, particularly under environmental conditions, and the development of improved or new techniques for analysis of uranium compounds. Overall, this research effort has identified relevant chemical and physical characteristics of uranium compounds that can be used to help discern the origin, process history, and postproduction history for a sample of uranium material. This effort has also identified analytical techniques that could be brought to bear for nuclear forensics purposes. Continued research into these uranium compounds should yield additional relevant chemical and physical characteristics and analytical approaches to further advance front-end nuclear fuel cycle forensics capabilities.

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“…References [1][2][3][4][5][6][7] describe pre-detonation nuclear forensics goals. Pre-detonation nuclear forensics focuses on determining the source and route of nuclear materials and devices prior to their use in an improvised nuclear device or radiological dispersal device.…”

Section: Introductionmentioning

confidence: 99%

Overview of Algorithms for Using Particle Morphology in Pre-Detonation Nuclear Forensics

et al. 2021

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A major goal in pre-detonation nuclear forensics is to infer the processing conditions and/or facility type that produced radiological material. This review paper focuses on analyses of particle size, shape, texture (“morphology”) signatures that could provide information on the provenance of interdicted materials. For example, uranium ore concentrates (UOC or yellowcake) include ammonium diuranate (ADU), ammonium uranyl carbonate (AUC), sodium diuranate (SDU), magnesium diuranate (MDU), and others, each prepared using different salts to precipitate U from solution. Once precipitated, UOCs are often dried and calcined to remove adsorbed water. The products can be allowed to react further, forming uranium oxides UO3, U3O8, or UO2 powders, whose surface morphology can be indicative of precipitation and/or calcination conditions used in their production. This review paper describes statistical issues and approaches in using quantitative analyses of measurements such as particle size and shape to infer production conditions. Statistical topics include multivariate t tests (Hotelling’s T2), design of experiments, and several machine learning (ML) options including decision trees, learning vector quantization neural networks, mixture discriminant analysis, and approximate Bayesian computation (ABC). ABC is emphasized as an attractive option to include the effects of model uncertainty in the selected and fitted forward model used for inferring processing conditions.

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Quantifying Morphological Features of α-U₃O₈ with Image Analysis for Nuclear Forensics

Cited by 52 publications

References 38 publications

Quantifying Impurity Effects on the Surface Morphology of α-U₃O₈

Quantifying Impurity Effects on the Surface Morphology of α-U₃O₈

Progress in Uranium Chemistry: Driving Advances in Front-End Nuclear Fuel Cycle Forensics

Overview of Algorithms for Using Particle Morphology in Pre-Detonation Nuclear Forensics

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Quantifying Morphological Features of α-U3O8 with Image Analysis for Nuclear Forensics

Cited by 52 publications

References 38 publications

Quantifying Impurity Effects on the Surface Morphology of α-U3O8

Quantifying Impurity Effects on the Surface Morphology of α-U3O8

Progress in Uranium Chemistry: Driving Advances in Front-End Nuclear Fuel Cycle Forensics

Overview of Algorithms for Using Particle Morphology in Pre-Detonation Nuclear Forensics

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Product

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Quantifying Morphological Features of α-U₃O₈ with Image Analysis for Nuclear Forensics

Quantifying Impurity Effects on the Surface Morphology of α-U₃O₈

Quantifying Impurity Effects on the Surface Morphology of α-U₃O₈