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Title: Machine Learning Prediction of Nitric Acid Extraction Behavior in PUREX Process

Journal Article · · ACS Omega
ORCiD logo [1];  [2]; ORCiD logo [2]; ORCiD logo [2]; ORCiD logo [2]; ORCiD logo [2]; ORCiD logo [2]; ORCiD logo [2]
  1. Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); University of Washington, Seattle, WA (United States)
  2. Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
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Plutonium uranium reduction extraction (PUREX) is a liquid–liquid extraction process used to recover plutonium (Pu) and uranium (U) from irradiated uranium fuel for various nuclear-related applications. Despite extensive efforts, quantitative prediction of liquid–liquid extraction parameters, i.e., distribution ratios and separation factors, of the process remains challenging. Existing thermodynamic models are difficult to develop and often have limited utility due to the complexity of the aqueous feed. Nitric acid is a critical component of the PUREX system, both as a driving force for dissolving irradiated fuels in preprocessing stages, as well as being efficiently extracted by tributyl phosphate (TBP). Models to understand nitric acid’s distribution behavior is therefore a prerequisite to predict actinide extraction. In this work, we compiled a wealth of solvent extraction literature data and built machine learning (ML) models capable of predicting the organic phase nitric acid equilibrium concentration from initial acid and TBP concentrations across a variety of diluents. Our results demonstrate that ML is highly capable of predicting nitric acid extraction behavior in PUREX systems, and the resultant ML-aided response surfaces demonstrate promising progress as an in silico aid for optimizing the design of experiments for future work with the PUREX process.

Research Organization:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA); USDOE National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation; USDOE Office of Science (SC), Office of Workforce Development for Teachers & Scientists (WDTS); USDOE Office of Science (SC), Office of Workforce Development for Teachers & Scientists (WDTS)
Grant/Contract Number:
AC05-76RL01830
OSTI ID:
2483743
Report Number(s):
PNNL-SA--200530
Journal Information:
ACS Omega, Journal Name: ACS Omega Journal Issue: 51 Vol. 9; ISSN 2470-1343
Publisher:
American Chemical Society (ACS)Copyright Statement
Country of Publication:
United States
Language:
English

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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY
Equilibrium
Extraction
Fuels
Inorganic acids and bases
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