Abstract
The development and qualification of silicide-based nuclear fuel would significantly benefit from an adequate understanding of the U–Si phase space, yet issues remain with respect to confidence in the phase diagram, especially in the USi–USi2 composition range. Experimental investigations have shown the existence of hexagonal and tetragonal phases in the USix 1.5 < x < 2 region, as well as possible miscibility gaps among the phases. To support the experimental work, we performed computational modeling, first applying cluster expansion CE) coupled with relaxation using molecular dynamics. The stable phases found using the CE were then subjected to more rigorous density functional theory (DFT) calculations, to determine the most stable phases in the USi–USi2 phase space. We subsequently performed a detailed analysis of the dependence of the U–Si convex hull on values of the on-site Coulomb correction, Ueff, (DFT + U) using the U-ramping method. This information allowed us to study the influence of electron correlation, and to find Ueff values that best represents the U–Si convex hull. Lastly, the temperature dependence was calculated using determined Gibbs energies of the phases. In the USi–USi2 phase space, two stable phases were observed up to 1200 °C, with a possible hexagonal to tetragonal phase transition at 580 °C for one of the phases.
| Original language | English |
|---|---|
| Pages (from-to) | 157-163 |
| Number of pages | 7 |
| Journal | Journal of Nuclear Materials |
| Volume | 524 |
| DOIs | |
| State | Published - Oct 2019 |
| Externally published | Yes |
Funding
This research was supported by the DOE Office of Nuclear Energy's Nuclear Energy University Programs . This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1548562 , and the HPC clusters Hyperion and Bolden, within the Division of Information Technology at University of South Carolina . This research was supported by the DOE Office of Nuclear Energy's Nuclear Energy University Programs. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1548562, and the HPC clusters Hyperion and Bolden, within the Division of Information Technology at University of South Carolina.
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