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Title: Morphology and particle size (MaPS) exercise: testing the applications of image analysis and morphology descriptions for nuclear forensics

Journal Article · · Journal of Radioanalytical and Nuclear Chemistry
ORCiD logo [1];  [2];  [3];  [4];  [1];  [2];  [2];  [4];  [3];  [3];  [5];  [1]
  1. Atomic Weapons Establishment (AWE), Reading (United Kingdom)
  2. Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
  3. Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
  4. Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
  5. Missouri Univ. of Science and Technology, Rolla, MO (United States)
+ Show Author Affiliations

Image analysis techniques have been applied and shown to be a valuable tool in nuclear forensics analysis. The interlaboratory exercise reported here has tested quantitative and qualitative approaches for characterizing nuclear materials. Particle size, surface features and morphology descriptions were compared by four laboratories on a common image set generated by Scanning Electron Microscopy and Digital Light Microscopy. Quantitative analysis of the image sets through the Morphological Analysis for MAterials software highlighted the strength of image analysis, but also that the application of the software alone can introduce significant bias in the analysis. Qualitative morphology descriptions following the process outlined by Tamasi et al. (J Radioanal Nuclear Chem 307:1611–1619, 2015) were compared with a discussion on the robustness and reproducibility of the results. Finally, future work should continue to focus on proficiency and standardization of image analysis through continued exercises within the extended nuclear forensics community.

Research Organization:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation
Grant/Contract Number:
AC52-07NA27344
OSTI ID:
2333089
Report Number(s):
LLNL--JRNL-860159; 1091290
Journal Information:
Journal of Radioanalytical and Nuclear Chemistry, Journal Name: Journal of Radioanalytical and Nuclear Chemistry Journal Issue: 4 Vol. 333; ISSN 0236-5731
Publisher:
SpringerCopyright Statement
Country of Publication:
United States
Language:
English

References (17)

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Qualitative assessment of uranium ore concentrates and related materials using scanning electron microscopy journal October 2022
Classification of uranium ore concentrates applying support vector machine to spectrophotometric and textural features journal November 2022
A new approach for quantifying morphological features of U3O8 for nuclear forensics using a deep learning model journal April 2019
Nuclear forensics investigation of morphological signatures in the thermal decomposition of uranyl peroxide journal January 2018
Nuclear proliferomics: A new field of study to identify signatures of nuclear materials as demonstrated on alpha-UO3 journal August 2018
Trends and perspectives in Nuclear Forensic Science journal January 2022
Quantifying Morphological Features of α-U 3 O 8 with Image Analysis for Nuclear Forensics journal February 2017
Impact of Controlled Storage Conditions on the Hydrolysis and Surface Morphology of Amorphous-UO 3 journal March 2021
Effect of Diel Cycling Temperature, Relative Humidity, and Synthetic Route on the Surface Morphology and Hydrolysis of α-U3O8 journal July 2021
Effects of process history on the surface morphology of uranium ore concentrates extracted from ore other January 2020
Segmentation and learning in the quantitative analysis of microscopy images conference February 2015
Interactive image quantification tools in nuclear material forensics conference February 2011
A response surface model of morphological changes in UO₂ and U₃O₈ following high temperature aging journal June 2019
MAMA User Guide v2.0.1 report July 2016
Uncertainty in the use of MAMA software to measure particle morphological parameters from SEM images report June 2017
Overview of Algorithms for Using Particle Morphology in Pre-Detonation Nuclear Forensics journal November 2021

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