Advanced workflow detects and characterizes enriched uranium particles in environmental samples, suggesting improved monitoring for nuclear non-proliferation.
As part of a global initiative to detect and monitor uranium use in nuclear facilities, the International Atomic Energy Agency (IAEA) collects environmental samples from various countries and analyses them for the presence of man-modified uranium and other nuclear fuel cycle materials. For example, highly enriched uranium can be associated with undeclared nuclear material or activities, making its detection critical for nuclear non-proliferation efforts. The paper presents an advanced analytical workflow that combines automated mineralogy, FIB ToF-SIMS (focussed ion beam-time of flight secondary ion mass spectrometry), and LG SIMS (large geometry secondary ion mass spectrometry) to efficiently identify and characterise uranium-containing particles in field samples. This integrated workflow automates time-consuming aspects of particle analysis, significantly improving the speed and precision of detecting uranium. It also provides detailed, complementary data on particle morphology and the chemical elements associated with each particle. The approach was shown to effectively identify and characterise particles containing enriched uranium, offering an in-depth understanding of the material's composition. The workflow's efficiency and precision make it a potentially valuable tool for nuclear material monitoring and non-proliferation efforts.
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Rickard et al. (2026) studied this question.
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