Modeling fission product nucleation in molten NaCl using universal machine-learning potentials

Key Points

• To understand the formation and transport of solid fission products in molten salt nuclear reactors.
• Utilized machine-learning potentials to model fission product nucleation in NaCl
• Conducted simulations to analyze precipitation and transport patterns
• Applied various algorithms for data analysis
• Identified key parameters influencing fission product nucleation in molten salt
• Demonstrated improved predictive accuracy compared to traditional models
• Provided insights for better design and safety of molten salt reactors