Enhanced laser-driven radioisotope production using a helical coil target with tube
Bibliographic record
Abstract
We present a comprehensive study unveiling advancements in α particle spectra manipulation that can be achieved through the implementation of a helical coil target with tube (HCT). Leveraging particle-in-cell simulations, we demonstrate the ability to control the energy distribution of α particle bunches within a narrow range, down to a few MeV. This development marks the first instance of successful ion energy manipulation facilitated by the HCT configuration. Importantly, our investigations reveal a significant enhancement in radioisotope production, with yields ranging from 10 to 3000 times greater with an HCT than without. These findings underscore the transformative potential of the HCT approach in improving α particle production in the context of laser-plasma acceleration and its consequential impact on radioisotope production for diverse applications. We also investigate the production of radioisotopes using proton acceleration with the HCT configuration and demonstrate that the yield can be increased by a factor of 30.
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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 | 0.001 |
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".