CHARACTERIZATION OF PLUTONIUM DISTRIBUTION IN THO<sub>2</sub>–PUO<sub>2</sub> MIXED OXIDES BY ELECTRON PROBE MICROANALYSIS
Bibliographic record
Abstract
Thoria–plutonia (ThO2–PuO2) pellets with a nominal composition of 9.0 wt% PuO2 were prepared using a fabrication route similar to an industrial process for production of urania–plutonia (UO2–PuO2) mixed oxide fuel. The green fuel pellets were separated into 2 batches and the sintering of each batch was carried out under a reducing atmosphere at 1820 °C or 1750 °C. The distribution of plutonium (Pu) in the sintered pellets was investigated by electron probe microanalysis using X-ray mapping and quantitative point analyses. The results show that the pellet samples consist of Pu-rich agglomerates with Pu content close to that of the mastermix blend and a thorium (Th)-rich matrix. The matrix and the Pu-rich agglomerates are separated by a transition zone with Pu content varying from practically nil to the Pu content of the Pu-rich agglomerates. X-ray maps taken from random regions of the centre of the pellets show different sizes of Pu-rich agglomerates irregularly dispersed in the Th-rich matrix. Image analysis of the Pu X-ray maps indicate that the average diameter of the Pu-rich agglomerates of the material sintered at 1820 °C and 1750 °C were 68 μm and 161 μm, respectively.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".