DFT+U investigation of local configurations and oxidation states of Cr in Cr-doped UO2
Bibliographic record
Abstract
Doping UO2 with Cr modifies the material’s microstructure, enhancing its properties and making Cr-doped UO2 a promising candidate as accident-tolerant nuclear fuel (ATF). Numerous studies have examined the oxidation state and localization of Cr in UO2 but often yield inconsistent results, identifying either Cr2+ or Cr3+ as the most stable oxidation state. In the present study, DFT+U is employed to model the incorporation of Cr in the UO2 matrix, providing insights into the oxidation state of Cr in UO2, in relation to the local atomic configurations. In particular, we investigate the $${{{\rm{Cr}}}}_{{{{\rm{x}}}}}^{3+}$$ $${{{\rm{U}}}}_{1-{{{\rm{x}}}}}^{4+}$$ O2−0.5x local configuration recently proposed by EPR and XANES experiments, alongside other theoretical configurations. Cr3+ is found to be the most favorable oxidation state in this configuration, agreeing with the most recent experimental data. This work clarifies the controversy over Cr oxidation states and incorporation sites within UO2, offering critical data for developing efficient and safer nuclear fuels. Doping UO2 with Cr enhances its properties and makes it a promising accident-tolerant nuclear fuel, yet the stable oxidation state of Cr in Cr-doped UO2 remains debated. Here, the authors use DFT+U modeling to reveal Cr3+ as the most favorable oxidation state in Cr-doped UO2, aligning with the most recent experimental results.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".