Density Functional Theory Calculations of Mass Transport in UO2
Bibliographic record
Abstract
In this talk we present results of density functional theory (DFT) calculations of U, O and fission gas diffusion in UO{sub 2}. These processes all impact nuclear fuel performance. For example, the formation and retention of fission gas bubbles induce fuel swelling, which leads to mechanical interaction with the clad thereby increasing the probability for clad breach. Alternatively, fission gas can be released from the fuel to the plenum, which increases the pressure on the clad walls and decreases the gap thermal conductivity. The evolution of fuel microstructure features is strongly coupled to diffusion of U vacancies. Since both U and fission gas transport rates vary strongly with the O stoichiometry, it is also important to understand O diffusion. In order to better understand bulk Xe behavior in UO{sub 2{+-}x} we first calculate the relevant activation energies using DFT techniques. By analyzing a combination of Xe solution thermodynamics, migration barriers and the interaction of dissolved Xe atoms with U, we demonstrate that Xe diffusion predominantly occurs via a vacancy-mediated mechanism. Since Xe transport is closely related to diffusion of U vacancies, we have also studied the activation energy for this process. In order to explain the low value of 2.4 eV found for U migration from independent damage experiments (not thermal equilibrium) the presence of vacancy clusters must be included in the analysis. Next we investigate species transport on the (111) UO{sub 2} surface, which is motivated by the formation of small voids partially filled with fission gas atoms (bubbles) in UO{sub 2} under irradiation. Surface diffusion could be the rate-limiting step for diffusion of such bubbles, which is an alternative mechanism for mass transport in these materials. As expected, the activation energy for surface diffusion is significantly lower than for bulk transport. These results are further discussed in terms of engineering-scale fission gas release models. Finally, oxidation of UO{sub 2} and the importance of cluster formation for understanding thermodynamic and kinetic properties of UO{sub 2+x} are investigated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".