The development of uranium foil farication technology utilizing twin roll method for Mo-99 irradiation target
Bibliographic record
Abstract
MDS Nordion in Canada, occupying about 75% of global supply of Mo-99 isotope, has provided the irradiation target of Mo-99 using the rod-type UAl sub x alloys with HEU(High Enrichment Uranium). ANL (Argonne National Laboratory) through co-operation with BATAN in Indonesia, leading RERTR (Reduced Enrichment for Research and Test Reactors) program substantially for nuclear non-proliferation, has designed and fabricated the annular cylinder of uranium targets, and successfully performed irradiation test, in order to develop the fabrication technology of fission Mo-99 using LEU(Low Enrichment Uranium). As the uranium foils could be fabricated in laboratory scale, not in commercialized scale by hot rolling method due to significant problems in foil quality, productivity and economic efficiency, attention has shifted to the development of new technology. Under these circumstances, the invention of uranium foil fabrication technology utilizing twin-roll casting method in KAERI is found to be able to fabricate LEU or HEU foils. Uranium and uranium alloy foils are fabricated through twin-roll casting of a uranium melt without a hot-rolling process and heat-treatment process. An improvement in productivity and process economics due to process simplification and better quality from the absence of any residual stress on the foil are expected through this research project.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".