Investigation of Nd<sub><i>x</i></sub>Y<sub>0.25–</sub><sub><i>x</i></sub>Zr<sub>0.75</sub>O<sub>1.88</sub> inert matrix fuel materials made by a co-precipitation synthetic route
Bibliographic record
Abstract
Yttria-stabilized zirconia (YSZ) is a material that is being considered for use as an inert matrix fuel in nuclear reactors, but a complete characterization of these materials is required for them to be licensed for use. A series of NdxY0.25–xZr0.75O1.88 materials have been synthesized using a co-precipitation method, and the thermal stability of these materials has been studied by annealing them at 1400 and 1500 °C. (Nd was used as surrogate for Am.) The long-range and local structures of the materials were characterized via powder X-ray diffraction, scanning electron microscopy, wavelength dispersive spectroscopy, and X-ray absorption spectroscopy at the Zr K- and Y K-edges. These results were compared with the previous characterization of Nd-YSZ materials synthesized using a ceramic method. The results indicated that the ordering in the local metal–oxygen polyhedral remains relatively unaffected by the synthetic method, but there was increased long-range disorder in the materials prepared by the co-precipitation method. Further, it was found that the materials produced by the co-precipitation method were unexpectedly unstable when annealed at high temperature. This study highlights the importance of determining the effect of synthetic method on material properties and demonstrates how the co-precipitation route could be used to produce inert matrix fuels.
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 | 0.000 | 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) | 0.001 | 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".