Nuclear forensics investigation of morphological signatures in the thermal decomposition of uranyl peroxide

Abstract

The analytical techniques typically utilized in a nuclear forensic investigation often provide limited information regarding the process history and production conditions of interdicted nuclear material. In this study, scanning electron microscopy (SEM) analysis of the surface morphology of amorphous-UO samples calcined at 250, 300, 350, 400, and 450°C from uranyl peroxide was performed to determine if the morphology was indicative of the synthesis route and thermal history for the samples. Thermogravimetic analysis-mass spectrometry (TGA-MS) and differential scanning calorimetry (DSC) were used to correlate transitions in the calcined material to morphological transformations. The high-resolution SEM images were processed using the Morphological Analysis for Material Attribution (MAMA) software. Morphological attributes, particle area and circularity, indicated significant trends as a result of calcination temperature. The quantitative morphological analysis was able to track the process of particle fragmentation and subsequent sintering as calcination temperature was increased. At the 90% confidence interval, with 1000 segmented particles, the use of Kolmogorov-Smirnov statistical comparisons allowed discernment between all calcination temperatures for the uranyl peroxide route.

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

“…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.…”

“…Baseline morphology and discussion of the technical production details for four precipitation conditions (ADU, AUC, SDU, and MDU) are provided in [1,2]. Subsequent studies have investigated the quantitative morphological variations for a selection of these materials due to processing, aging, and/or storage conditions [3,4,7]. One related inference goal is to determine factors that impact particle morphology, such as calcination temperature, production pathway involving UO3, U3O8, or UO2, at 400 • C, 800 • C, and 510 • C (in H2), respectively, and impurities for a given precipitation condition.…”

“…This review paper illustrates statistical issues using 22 quantitative morphological metrics (Appendix A describes these 22 metrics) derived from the analysis of scanning electron microscopy images (SEM) of each segmented particle [2,4,5]. Figure 1 highlights some example SEM images acquired from nuclear materials.…”

“…An alternative automated segmentation method using a deep learning model (a U-net based on convolutional neural networks) was shown in [8] to effectively segment fully visible particles (see also Reference [11] for another segmentation option); however, this paper's focus is on inferring processing conditions using currently-available segmentation software, such as MAMA, that can also provide the 22 quantitative particle morphological metrics. This review paper illustrates statistical issues using 22 quantitative morphological metrics (Appendix A describes these 22 metrics) derived from the analysis of scanning electron microscopy images (SEM) of each segmented particle [2,4,5]. Figure 1 highlights some example SEM images acquired from nuclear materials.…”

Construction of a developed software for nuclear forensics of micro particles

“…Validating analytical methods, sampling properly, and a quality control/assurance program lead to good analytical results. Nuclear forensic analysis uses elements, isotopes, physical and chemical signatures to get a clear technical insight into the nuclear materials source and history of an unknown origin (Schwerdt et al, 2018).…”