Mikhail Finko

Lawrence Livermore National Laboratory

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Davide Curreli

University of Illinois Urbana-Champaign

Kim B. Knight

Lawrence Livermore National Laboratory

Harry B. Radousky

Lawrence Livermore National Laboratory

Jonathan C. Crowhurst

Lawrence Livermore National Laboratory

Timothy P. Rose

Lawrence Livermore National Laboratory

Batikan Köroğlu

Lawrence Livermore National Laboratory

Chiara Saggese

Lawrence Livermore National Laboratory

David G. Weisz

Lawrence Livermore National Laboratory

D. D. Lucas

Lawrence Livermore National Laboratory

Samuel Foster

Lawrence Livermore National Laboratory

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Lawrence Livermore National Laboratory

University of Illinois Urbana-Champaign

Lawrence Livermore National Security

University of California, Berkeley

University of California System

Planetary Science Institute

West Virginia University

National Center for Supercomputing Applications

Max Planck Society

Max Planck Institute for Plasma Physics

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Stochastic optimization of a uranium oxide reaction mechanism using plasma flow reactor measurements

Scientific Reports (2023)

Mikhail Finko Batikan Köroğlu Kate Rodriguez Timothy P. Rose Jonathan C. Crowhurst

Abstract In this work, a coupled Monte Carlo Genetic Algorithm (MCGA) approach is used to optimize a gas phase uranium oxide reaction mechanism based on plasma flow reactor (PFR) measurements. The PFR produces a steady Ar plasma containing U, O, H, and N species with high temperature regions (3000–5000 K) relevant to observing UO formation via optical emission spectroscopy. A global kinetic treatment is used to model the chemical evolution in the PFR and to produce synthetic emission signals for direct comparison with experiments. The parameter space of a uranium oxide reaction mechanism is then explored via Monte Carlo sampling using objective functions to quantify the model-experiment agreement. The Monte Carlo results are subsequently refined using a genetic algorithm to obtain an experimentally corroborated set of reaction pathways and rate coefficients. Out of 12 reaction channels targeted for optimization, four channels are found to be well constrained across all optimization runs while another three channels are constrained in select cases. The optimized channels highlight the importance of the OH radical in oxidizing uranium in the PFR. This study comprises a first step toward producing a comprehensive experimentally validated reaction mechanism for gas phase uranium molecular species formation.

Oxidizing agent

Uranium oxide

Reaction rate

10.1038/s41598-023-35355-6

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Citations (1)

The influence of cooling rate on condensation of iron, aluminum, and uranium oxide nanoparticles

Journal of Aerosol Science (2022)

Batikan Köroğlu Mikhail Finko Chiara Saggese Scott W. Wagnon Samuel Foster

Particle (ecology)

10.1016/j.jaerosci.2022.105959

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Citations (6)