Multiscale, mechanistic modeling of cesium transport in silicon carbide for TRISO fuel performance prediction

Understanding cesium (Cs) transport in TRistructural ISOtropic (TRISO) particle fuel is crucial for predicting fission product release in high-temperature reactors. However, current challenges include significant scatter in diffusivity data and unexplained temperature-dependent diffusion regimes in the silicon carbide layer. This study addresses these challenges by developing a multiscale, mechanistic Cs transport model integrating atomistic simulations and phase field modeling. Our model quantifies temperature and grain size effects on Cs diffusivity, attributing experimentally observed regimes to a transition from bulk-dominated diffusivity at high temperatures to grain boundary-dominated diffusivity at lower temperatures. The model, validated against diffusion measurements and advanced gas reactor (AGR)-1 and AGR-2 post-irradiation fission product release data, enhances the predictive capability of the BISON fuel performance code. This study advances our understanding of Cs release from TRISO particles and its dependence on temperature and silicon carbide grain size, with implications for the safety and efficiency of high-temperature nuclear reactors.

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Publication Details

Journal
npj Computational Materials
Published
2025-07-19
DOI
https://doi.org/10.1038/s41524-025-01734-y
Citations
3
Primary Topic
Nuclear Materials and Properties
Type
article
Field-Weighted Citation Impact
1.55

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article

Multiscale, mechanistic modeling of cesium transport in silicon carbide for TRISO fuel performance prediction

Wen Jiang, Jia-Hong Ke, Pierre-Clément A. Simon, Stephen Novascone et al.
3 citations
npj Computational Materials
Nuclear Materials and Properties
1.55
article

Multiscale, mechanistic modeling of cesium transport in silicon carbide for TRISO fuel performance prediction

Wen Jiang, Jia-Hong Ke, Pierre-Clément A. Simon, Stephen Novascone, Larry K. Aagesen, Chao Jiang
article en
3 citations

Abstract

Understanding cesium (Cs) transport in TRistructural ISOtropic (TRISO) particle fuel is crucial for predicting fission product release in high-temperature reactors. However, current challenges include significant scatter in diffusivity data and unexplained temperature-dependent diffusion regimes in the silicon carbide layer. This study addresses these challenges by developing a multiscale, mechanistic Cs transport model integrating atomistic simulations and phase field modeling. Our model quantifies temperature and grain size effects on Cs diffusivity, attributing experimentally observed regimes to a transition from bulk-dominated diffusivity at high temperatures to grain boundary-dominated diffusivity at lower temperatures. The model, validated against diffusion measurements and advanced gas reactor (AGR)-1 and AGR-2 post-irradiation fission product release data, enhances the predictive capability of the BISON fuel performance code. This study advances our understanding of Cs release from TRISO particles and its dependence on temperature and silicon carbide grain size, with implications for the safety and efficiency of high-temperature nuclear reactors.

npj Computational MaterialsVol. 11(1)
Pennsylvania State University (US), North Carolina State University (US), Idaho National Laboratory (US)
U.S. Department of Energy
Openalex Percentile: Top 17%
Nuclear Materials and Properties
1.55
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