Fabrication of <scp> CeO <sub>2</sub> </scp> microspheres by internal gelation process using flow‐focusing droplet generator
Bibliographic record
Abstract
Abstract Sphere‐pac fuel is an alternative nuclear fuel technology in which microspheres of two or more sizes are utilized to fill the cladding tube in place of the more conventional single‐size fuel pellets. This provides leeway for adjusting the fuel pellet packing density and resulting cladding tube porosity. The current investigation makes use of a flow‐focusing droplet generator made from stainless steel (S.S.) 316 L, with a channel internal diameter (I.D.) of 0.5, 0.8, 1, and 3 mm. These microspheres were supposed to be of actinide oxide but here, cerium has been chosen as a surrogate of plutonium. Detailed information about the flow‐focusing droplet generator, internal gelation process, and sphere‐pac fuel has been provided. The size and size distribution of ceria microspheres were investigated by varying the flow rates of the continuous and dispersed phase. The characterization of ceria microspheres has been conducted using techniques such as scanning electron microscope (SEM), X‐ray diffraction (XRD), Fourier‐transform infrared spectroscopy (FTIR), and Brunauer–Emmett–Teller (BET) analyses. The size of prepared monodisperse microspheres was controlled precisely (within ±2%) in the range of 498–2888 μm using four S.S. 316 L flow‐focusing droplet generators with channel I.D. 0.5, 0.8, 1, and 3 mm, respectively, and the coefficient of variation of the size distribution was found to be less than 2%.
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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 | 0.000 | 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".