Recent Advances in Uranium Particle Analyses by LG-SIMS

We present on the analysis of uranium particles by large-geometry secondary ion mass spectrometry (LG-SIMS) using three primary ion species, (O- , O2 - , O3 - ), and two sample substrates (graphite, silicon). The study shows that the primary species result in different magnitudes of mass fractionation, which are potentially driven by characteristics of the sputtering process and not by differences in the secondary ion energy distributions of U+ . O3 - was found to yield consistently less mass fractionation across the secondary energy distribution compared to O- . The shapes of the energy distributions do not account for the cumulative difference in fractionation. We also found that O3 - improves the detection limits of 236U compared to Oby reducing the UH+ signal for particles on a graphite substrate. The particle-to-particle hydride scatter was also reduced using O3 - . We present on the development of an efficient, open-source Python tool, FCpy, for calculating Feldman-Cousins confidence intervals on low-count Poisson processes in the presence of a nonnegligible, but known, average detector background signal. These methods and tools positively impact the analysis of environmental sampling and Nuclear Safeguards-related actinide particles. This work and other recent studies highlight important considerations for sample preparation and measurement design, particularly for inter-element analyses of individual atom-limited samples and separating different populations of particle data generated by large-area mapping.