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Mannion, Joseph M.

Publications and source records attributed to Mannion, Joseph M..

Rapid 235 U/ 238 U determination by matrix assisted ionization–time-of-flight mass spectrometry

Matrix-assisted ionization (MAI) of inorganic analytes is a nascent research domain that holds promise for rapid, potentially facility-deployable analytical applications. Here, we present results of MAI uranium isotopic analysis ( 235 U/ 238 U) obtained on the timescale of minutes utilizing simple sample preparation and an ambient ionization time-of-flight mass spectrometer (ToF MS). Experimental MAI-ToF MS characterization of uranium Certified Reference Materials (CRMs) was used to establish method calibration and validate quantitative 235 U/ 238 U determination spanning depleted, natural, and low-enriched uranium isotopic compositions. Secondary standard analyses with total uranium mass loadings of 5–500 ng per analysis yield accurate calibrated 235 U/ 238 U results and relative uncertainties of 4.7–17.2% (approx. ±95% confidence level), with weighted-mean uncertainties approaching 1.5%. This method permits accurate determination of uranium isotopic composition in a sample with uranium content as low as 200 pg for equal atom 235 U: 238 U. Instrument detection limits constrain the minimum uranium mass required to identify the presence of highly enriched uranium (HEU ≥20% 235 U) as only 500 pg using the method presented here. MAI-ToF MS quantitation of relatively extreme isotope ratios ( 235 U/ 238 U ≤ 0.01) is limited by detection of minor 235 U (LoD 100 pg 235 U/analysis ≈ 10 ng total U/analysis), and subsequent method optimization is anticipated to further reduce these limits. These findings underscore the potential of MAI-ToF MS for isotopic characterization of uranium and other inorganic species for both basic and applied science.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND

Advanced Method Optimization for Sampling and Analysis Instrumentation

This work presents a generalized approach for analytical method optimization that branches the gap between techniques historically employed and accurate modern optimization techniques suitable for various applications. The novelty of the described strategy is the utilization of multivariate, multiobjective optimization with Karush-Kuhn-Tucker conditions to bound the optimization space to solutions within the physical limitations of instrumentation. Briefly, the basic steps outlined in this paper are to (1) determine the objective(s) that should be maximized or minimized based on the goals of the analytical application, (2) conduct a screening experiment, (3) perform ANOVA to determine the parameters which have a statistically significant effect on the objective, (4) conduct an experiment (e.g., Box-Behnken design) to collect data for fitting the objective equation, and (5) determine the physical constraints of the parameters and solve the Lagrangian to determine the optimal method parameters. A broad approach to optimization target selection allows for robust method tuning to develop improved data sets amenable for chemometrics and machine learning algorithm development. Gas chromatography-mass spectrometry was selected as a use case due to its broad use across scientific fields and time-consuming method development involving numerous parameters. In conclusion, this strategy can reduce the cost of research, improve data quality, and enable the rapid development of new analytical technique.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH