Nuclear Forensics Research Articles

Nuclear forensic signatures of UO2 fuel pellets for differentiation and provenance determination illustrated using synthetic database

This paper presents a comprehensive nuclear forensics signatures analysis of UO2 fuel pellets, allowing their provenance to specific manufacturers. The study is based on a synthetic database designed for the 4th international Galaxy Serpent exercise circulation, which mimics real fuel pellet characteristics. The scenario of the exercise is completely fictional, including the data used and manufacturers' names, locations, etc. The signatures investigated include chemical form, pellet dimensions, equivalent boron content, Gd additive, impurities distribution, and isotopic composition. The consistency levels of the results, which determine the confidence in the provenance process, were divided into four levels due to the varying resolving power of the signatures. The paper emphasizes the importance of a graphical representation of the results to simplify interpreting multi-degree-of-freedom data, typical to nuclear forensics investigations, including the amalgamation of quantitative and qualitative information. The analysis connects 11 orphan pellets and a single UO2 powder to five manufacturers. The presented methodology offers a straightforward approach to data interpretation in nuclear forensic investigations and highlights the need for continued research and development in this field.

Oxygen Isotope Alterations during the Reduction of U3O8 to UO2 for Nuclear Forensics Applications.

The fabrication of UO2 from U3O8 is an essential reaction in the nuclear fuel cycle. The oxygen isotope fractionation associated with this reaction has significant implications in the general field of nuclear forensics. Hence, the oxygen isotope fractionation during the reduction of U3O8 to UO2 was determined in the temperature range of 500-700 °C and for a duration of 2 to 6 h under a high-purity H2 atmosphere. Three U3O8 samples, possessing a different oxygen isotopic composition, were used to investigate key parameters involved with the fractionation during the reduction process. All UO2 products did not maintain the original isotope composition of the starting U3O8 under all conditions. The results show that the system UO2-H2O attains isotope equilibrium at 600 °C, provided the reduction process lasts at least 4 h or more. At 600 °C, UO2 was isotopically depleted by 2.89 ± 0.82‰ compared to the U3O8 from which it was produced. We find that the H2O formed during the reduction plays a major role in determining the final δ18O of UO2 prepared from U3O8. The isotope equilibrium of the system UO2-H2O at 600 °C was calculated, indicating that δ18O of the H2O was enriched by about 11‰ relative to the UO2 due to the uranium mass effect. These findings could potentially have important implications for nuclear forensics, as they provide a new method for determining the history of UO2 samples and tracing back their production process.

Prospective appraisal of a formative nuclear and radiation physics at Nairobi

We provide a prospective appraisal of the evolution of the graduate nuclear and radiation physics program at the University of Nairobi underscoring its unique growth in the framework of relevant knowledge networks and a nascent nuclear power program. Due to the distinctive characteristics of the nuclear fuel cycle, there arose in Kenya especially nuclear security educational requirements for a proliferation-free nuclear power program as well as the need for provision of a broad spectrum of technical capacities to plan, regulate, and safely handle a nuclear power infrastructure. We detail how the graduate program centres on our newly established research line in nuclear forensics. Learning from this experience we propose, as a result, moving into nuclear photonics enabled by accelerators so as to play more key roles in accelerating capacity building embracing both nuclear and laser physics.

Spatially Resolved Characterisation of Low Mass Fraction Uranium Glass Working Reference Materials

We present the results of a study to generate reference glasses that reflect an environment analogous to historic nuclear fallout samples of interest for post‐detonation nuclear forensics. The glasses were generated by melting and then quenching SiO2, Al2O3 and CaCO3 powders. Two suites of glasses with three distinct U isotopic ratios were successfully made with enrichments in the 235U isotope (~ natural [0.72%], ~ 53% and 94%), but the bulk elemental data showed heterogeneity (~ 10% RSD) with U mass fractions ranging from 331.47 to 373.63 μg g‐1. Spatially resolved U isotopic measurements were performed using three mass spectrometry techniques (secondary ion mass spectrometry‐single stage accelerator mass spectrometry [SIMS‐SSAMS], large geometry [LG] ‐ SIMS, and laser ablation‐inductively coupled plasma‐mass spectrometry [LA‐ICP‐MS]) across five National Laboratories. The results showed good agreement with the bulk U isotopic data for the low, medium, and high U mass fractions. We conclude that despite elemental heterogeneity, these samples can serve as useful working reference materials for spatially resolved nuclear fallout analyses, as well as for other related spatially resolved analyses.

Development of Fast Decay-Energy Spectroscopy With Magnetic Microcalorimeters

Decay energy spectroscopy (DES) is an increasingly important radiometric technique arising from the unique thermal detection physics and the precision of low-temperature microcalorimetry. DES can enable high-precision analysis of very small amounts of radioactive material with simple and rapid sample preparation, making it a key new tool for nuclear safeguards, nuclear forensics, the improvement of nuclear data, measurements of absolute activity, and other applications. For problems in nuclear safeguards and nuclear forensics it is highly desirable to increase the count rates achievable in DES, while maintaining simple and rapid sample preparation. In this report we describe progress in a new project to achieve high count rates in DES by taking advantage of the physics of magnetic microcalorimetry. We describe the results of initial modeling and experiment to validate the idea, a sample fabrication technique suitable for nuclear materials laboratories, the preparation and initial tests of paramagnetic Au-Er alloy in thin foil form, and the development of a sensing coil geometry that will perform well with the increased-thickness sensor used in the new technique.

Initial Characterization and Optimization of the Liquid Sampling-Atmospheric Pressure Glow Discharge Ionization Source Coupled to an Orbitrap Mass Spectrometer for the Determination of Plutonium.

Plutonium measurements are essential to the nuclear forensics and safeguards community. The liquid sampling-atmospheric pressure glow discharge (LS-APGD) microplasma ionization source coupled with an Orbitrap mass spectrometer is a proven platform for uranium isotope ratio determinations. This work expands the LS-APGD-Orbitrap platform capabilities by reporting the first-ever analysis of plutonium with the LS-APGD and the first-ever measurement of elemental plutonium with an Orbitrap mass spectrometer. This coupling has the potential to dramatically reduce the complex sample manipulations required for traditional analysis techniques employed for actinide isotope ratio determinations. As a first step toward the goal of simultaneous uranium and plutonium isotope ratio determinations, the initial characterization and optimization of the platform for the detection of plutonium are reported. Collision-induced dissociation modality settings were optimized to reduce water-related and other molecular clusters containing plutonium, maximizing 242Pu16O2+ responses. A design of experiments study was conducted to optimize the discharge conditions of the dual-electrode LS-APGD toward the responsivity of 242Pu16O2+. The measurement sensitivity was determined from a Pu response curve, yielding a limit of detection of 10 fg (absolute) of total analyte when data was collected and processed with a Spectroswiss FTMS Booster X2 data acquisition system. Additionally, plutonium and uranium were measured in a simultaneous acquisition, and each analyte remained unaffected by the other. It is believed that the LS-APGD-Orbitrap platform could be a valuable addition to the nuclear forensics' toolbox and, indeed, other scientific disciplines and regulatory communities in which rapid, high-resolution plutonium determinations are paramount.

An introduction to the significance of sample size in particle analyses for nuclear forensics and radiological investigations

Particulate isotopic analysis in nuclear forensics has developed rapidly during the past two decades due to technical advances in determining the isotopic composition of individual particles. This paper introduces basic statistical concepts that can be applied by analysts to understand the importance of statistical adequacy when interpretating particle data. While these basic statistical methods provide a useful point-of-entry to particle data analysis, more sophisticated statistical and modeling approaches are needed to extract maximal information from such datasets in the future.

A comparison of machine learning methods to classify radioactive elements using prompt-gamma-ray neutron activation data

The detection of illicit radiological materials is critical to establishing a robust second line of defence in nuclear security. Neutron-capture prompt-gamma activation analysis (PGAA) can be used to detect multiple radioactive materials across the entire Periodic Table. However, long detection times and a high rate of false positives pose a significant hindrance in the deployment of PGAA-based systems to identify the presence of illicit substances in nuclear forensics. In the present work, six different machine-learning algorithms were developed to classify radioactive elements based on the PGAA energy spectra. The model performance was evaluated using standard classification metrics and trend curves with an emphasis on comparing the effectiveness of algorithms that are best suited for classifying imbalanced datasets. We analyse the classification performance based on Precision, Recall, F1-score, Specificity, Confusion matrix, ROC-AUC curves, and Geometric Mean Score (GMS) measures. The tree-based algorithms (Decision Trees, Random Forest and AdaBoost) have consistently outperformed Support Vector Machine and K-Nearest Neighbours. Based on the results presented, AdaBoost is the preferred classifier to analyse data containing PGAA spectral information due to the high recall and minimal false negatives reported in the minority class.

Synthesis and Morphological Control of UO2F2 Particulates.

Uranium-based microspheres are of interest due to their potential applications as targets for medical isotopes production, as fuel for nuclear reactors, and as standardized materials for nuclear forensics. Here, for the first time, UO2F2 microspheres (1-2 μm) have been prepared from the reaction between UO3 microspheres and AgHF2 in an autoclave. In this preparation, a new fluorination method has been applied, and HF(g)-produced in situ from the thermal decomposition of AgHF2 and NH4HF2-was used as the fluorinating agent. The microspheres were characterized by powder X-ray diffraction (PXRD) and scanning electron microscopy (SEM). Diffraction results indicated that the reaction performed with AgHF2 at 200 °C led to anhydrous UO2F2 microspheres, while at 150 °C, hydrated UO2F2 microspheres were obtained. Meanwhile, NH4HF2 led to the formation of contaminated products as driven by the formation of volatile species.

Development of a new approach for rapid identification and classification of uranium ore concentrate powders using textural and spectroscopy signatures

Recently, a concept for a new approach for rapid identification of uranium ore concentrate (UOC) powders using colour, textural and spectroscopy signatures was developed using a sample dataset consisting of 79 industrial uranium ore concentrate powders produced by different production routes at different facilities. The samples were first grouped into six different predefined colour categories using a colour-based classification model previously developed. In this study, a machine learning approach was used to develop supervised texture- and spectroscopy-based classification models for each colour category of uranium ore concentrates.Scanning electron microscopy images of the UOC samples were collected at 100x, 250x, 500x/1000× magnifications. A total of 524 texture features describing sample morphology were extracted from each image using First Order Statistics (FOS), Grey Level Co-Occurrence Matrix (GLCM), Grey Level Run Length Matrix (GLRLM), Grey Level Size Zone Matrix (GLSZM), Locally Binary Pattern (LBP) and Angle Measure Technique (AMT) textural feature extraction algorithms. Hyperspectral images of the samples were collected in the wavelength range 900–1700 nm and the mean spectrum of each sample was calculated, giving the spectral features of the UOCs. The texture and spectral features were used as input to the machine learning approach which consisted of a feature reduction step to identify discriminatory features and a classification step to provide the texture- and spectroscopy-based models. An average prediction accuracy of 82% and 97% were obtained for the texture- and spectral-based classification models, respectively, on hold-out test sets. The feature reduction step identified two new nuclear forensics signatures, consisting of 3–7 texture (morphological) characteristics and 2–6 characteristic wavelengths, respectively.This new approach enables rapid classification of unknown uranium ore concentrate powders using only their textural and hyperspectral images. By combining the classification results from the two models, the most probable production process and chemical composition can be identified, and the provenience of the seized sample can be narrowed down to a few matching possibilities. Moreover, after the image acquisition, the models can provide results in less than 2 min speeding up the investigation procedure, a key factor when a nuclear security event occurs.

A possible novel method in nuclear forensics: positron annihilation spectroscopy

Positron Annihilation Spectroscopy (PAS) is a non-destructive technique used mostly in material science for studying open spaces/free volumes in materials. In this work, several different nuclear materials originating from the nuclear fuel cycle or round-robin exercises are analyzed by PAS. Our goal was, as for a first test of applicability, to check whether the technique is potentially suitable in a nuclear forensic examination for origin assessment of nuclear materials in order to support investigation. The results, presented below are promising and can certainly be further improved by analyzing larger sets of samples.

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

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 (UF6). This work synthesizes uranium oxides from uranyl fluoride (UO2F2) 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 UO2F2 to UO2 and may provide a novel nuclear forensics morphology signature for nuclear fuel and U metal precursors.

Microscopic calculation of fission product yields for odd-mass nuclei

Fission data are essential inputs to reaction networks involved in nucleosynthesis simulations and nuclear forensics. In such applications as well as in the description of multi-chance fission, the characteristics of fission for odd-mass nuclei are just as important as those for even-even nuclei. The fission theories that aim at explicitly describing fission dynamics are typically based on some variant of the nuclear mean-field theory. In such cases, the treatment of systems with an odd number of particles is markedly more involved, both formally and computationally. In this article, we use the blocking prescription of the Hartree-Fock-Bogoliubov theory with Skyrme energy functionals to compute the deformation properties of odd-mass uranium isotopes. We show that the resulting fission fragment distributions depend quite significantly on the spin of the odd neutron. By direct calculation of the spin distribution of the fissioning nucleus, we propose a methodology to rigorously predict the charge and mass distributions in odd-mass nuclei.

Linear Regression and Machine Learning for Nuclear Forensics of Spent Fuel from Six Types of Nuclear Reactors

The illicit trafficking of radioactive materials, especially weapon-grade uranium or plutonium, is a significant security threat. Nuclear forensics helps trace the illicit trafficking of radioactive materials. The present study develops the methods for the forensics of the possible origins of fuels irradiated in nuclear reactors, which are the most powerful sources producing radioactive materials, including plutonium. Three key factors are significant for irradiated fuel forensics, namely, initial 235U enrichment, burnup, and the type of irradiation nuclear reactors. The methods for the first two are determined based on experimental data of six nuclear-reactor technologies and are further verified using the neutron-transport-depletion coupling simulation of the two major commercial reactor technologies, a pressurized-water reactor (PWR) and a boiling-water reactor (BWR). In addition, three machine-learning techniques are applied to discriminate between a PWR and a BWR, which are quite similar in neutronic properties, with nice accuracy and generalization ability. In summary, the presently determined methods provide a reliable pathway to predict the origins of spent nuclear fuels.3 MoreReceived 18 August 2022Revised 7 November 2022Accepted 1 February 2023DOI:https://doi.org/10.1103/PhysRevApplied.19.034028© 2023 American Physical SocietyPhysics Subject Headings (PhySH)Research AreasFissionNeutron physicsNuclear decayNuclear powerRadioactive wasteTheory, design & simulation of reactorsTechniquesNuclear data analysis & compilationNuclear PhysicsEnergy Science & Technology

Flow Injection Electrochemical Quartz Crystal Microbalance with ICP-OES Detection: Electroprecipitation and Stripping of Lanthanum and Neodymium in a Flow Cell

We used an improved version of our hyphenated analysis technique, flow injection electrochemical quartz crystal microbalance with inductively coupled optical emission spectroscopy (FI-EQCM-ICP-OES), to investigate the electroprecipitation of lanthanum and neodymium from flowing solutions. The improved version has two independent flow injection circuits, allowing different conditions for electrochemical precipitation (pH = 4.3 or 2.6) and quick stripping (2% HNO3) with EQCM mass detection and ICP-OES elemental analysis. Lanthanum or neodymium ions in a 500 μl sample were injected into a carrier stream and deposited onto an electrochemical quartz crystal microbalance (EQCM) housed in a micro flow cell, owing to a localized high-pH layer. The deposits are subsequently stripped from the electrode using HNO3 and analyzed downstream using an ICP-OES. We found that using acidic solutions without supporting electrolyte leads to an increase of the amount of lanthanum detected by 4-fold. The enhanced deposition can be attributed to enhanced mass transfer by migration. Moreover, we showed that by applying chronopotentiometry, we can detect a change in the hydrogen evolution reaction mechanism that enables the precipitation of lanthanides on the surface of the electrode. Understanding and enhancing the deposition of lanthanides is relevant for elemental or isotopic detection in nuclear forensics.

Determination of inorganic anions in uranium ore concentrate reference materials

The determination of inorganic anions in uranium ore concentrates (UOCs) is useful to nuclear forensics for establishing the provenance of sample materials. In this collaborative study, quantitation of inorganic anions was carried out on three UOC reference materials from the National Research Council Canada: UCLO-1 (https://doi.org/10.4224/crm.2020.uclo-1), UCHI-1 (https://doi.org/10.4224/crm.2020.uchi-1), and UPER-1 (https://doi.org/10.4224/crm.2020.uper-1). The analytes were extracted into water and characterized by ion chromatography with combined standard uncertainties (uc) between 1.6 and 11%. The highest contributor to uc was homogeneity. Sulfate was the most abundant anion (2000–12,000 mg/kg SO42−). Other anions were in the 15–500 mg/kg range.

Propagation and variation of material characteristics during the uranium ore concentrate production at Dolní Rožinka, Czech Republic

In the framework of the European Commission Support Programme to the International Atomic Energy Agency (EC SP task A1753) 20 samples were obtained from the Dolní Rožínka (DIAMO, Czech Republic) uranium milling facility. The sampling procedure followed stepwise the uranium production and purification from the U ore to uranium ore concentrate (yellow cake) end-product. Elemental concentrations, rare-earth elemental pattern, anion concentrations, morphology and isotope abundance ratios of S, Sr, Pb and U were measured at each sampling stage. The purpose of the measurements was to investigate the applicability of various material characteristics for authentication, propagation and variation of these parameters, and to identify the relevant signatures for nuclear forensics and safeguards during the uranium production.

Diffuse Reflectance Spectroscopy and Principal Component Analysis to Retrospectively Determine Production History of Plutonium Dioxide.

Diffuse reflectance spectroscopy measurements in the shortwave infrared (930-1600 nm) spectral region were acquired for Pu2(C2O4)3•9H2O and its thermal decomposition product, PuO2. We analyzed a total of eight PuO2 samples that were produced at different calcination temperatures (300, 350, 450, 525, 600, 675, 750, and 900°C). Our goal was to identify spectroscopic fingerprints that could be used to gain retrospective information regarding the production parameters of these important nuclear compounds. The diffuse reflectance spectrum of Pu2(C2O4)3•9H2O features several broad bands that currently preclude detailed analysis. However, all PuO2 samples produced relatively sharp spectral features that got sharper and more intense for samples that were produced at higher calcination temperatures. The electronic band observed at 1433 nm in the diffuse reflectance spectra of PuO2 was found to be a sensitive indicator of crystallinity; a result that is corroborated by ancillary Raman spectroscopy measurements. Principal component analysis of diffuse reflectance spectra was able to clearly rank and categorize PuO2 samples based on the calcination temperature that was employed during their production. Thus, we show herein that important retrospective information pertaining to the process history of PuO2 can be gained through the relatively simplistic combination of diffuse reflectance spectroscopy and principal component analysis. This discovery presents a new method for determining the provenance and process history of PuO2 and should have an impact in the fields of nuclear forensics and nuclear nonproliferation.

Machine learning in analytical spectroscopy for nuclear diagnostics [Invited

Analytical spectroscopy methods have shown many possible uses for nuclear material diagnostics and measurements in recent studies. In particular, the application potential for various atomic spectroscopy techniques is uniquely diverse and generates interest across a wide range of nuclear science areas. Over the last decade, techniques such as laser-induced breakdown spectroscopy, Raman spectroscopy, and x-ray fluorescence spectroscopy have yielded considerable improvements in the diagnostic analysis of nuclear materials, especially with machine learning implementations. These techniques have been applied for analytical solutions to problems concerning nuclear forensics, nuclear fuel manufacturing, nuclear fuel quality control, and general diagnostic analysis of nuclear materials. The data yielded from atomic spectroscopy methods provide innovative solutions to problems surrounding the characterization of nuclear materials, particularly for compounds with complex chemistry. Implementing these optical spectroscopy techniques can provide comprehensive new insights into the chemical analysis of nuclear materials. In particular, recent advances coupling machine learning methods to the processing of atomic emission spectra have yielded novel, robust solutions for nuclear material characterization. This review paper will provide a summation of several of these recent advances and will discuss key experimental studies that have advanced the use of analytical atomic spectroscopy techniques as active tools for nuclear diagnostic measurements.

Simultaneous Determination of Transuranium Radionuclides for Nuclear Forensics by Compact Accelerator Mass Spectrometry.

Accelerator mass spectrometry (AMS) is one of the most sensitive techniques used to measure the long-lived actinides. This is particularly of interest for determination of ultra-trace transuranium nuclides and their isotopic fingerprints for nuclear forensics. In this work, a new method was developed for simultaneous determination of transuranium nuclides (Np, Pu, Am, and Cm isotopes) by using 300 kV AMS after a sequential chemical separation of each group of actinides. 242Pu and 243Am were utilized as tracers for Np/Pu and Am/Cm yield monitoring. The results show that the chemical behaviors of Np and Pu on the TK200 column and those of Am and Cm on the DGA column were very consistent in 8-9 mol/L of HNO3 and 0.015-0.03 mol/L of NaNO2 media during the radiochemical separation. The AMS detection efficiencies for transuranium nuclides were also evaluated. The detection limits for all radionuclides are below femtogram level and even in attogram level for Pu and Cm isotopes. The established method has been successfully applied to accurately measure various transuranium nuclides in a single actinide radionuclide solution, demonstrating its feasibility for nuclear forensic investigation.