Degradation of thin carbon-backed lithium fluoride targets bombarded by 68 MeV 17O beams
Bibliographic record
Abstract
To analyze the cause of the destruction of thin, carbon-backed lithium fluoride targets during a measurement of the fusion of 7Li and 17O, we estimate theoretically the lifetimes of carbon and LiF films due to sputtering, thermal evaporation, and lattice damage and compare them with the lifetime observed in the experiment. Sputtering yields and thermal evaporation rates in carbon and LiF films are too low to play significant roles in the destruction of the targets. We estimate the lifetime of the target due to lattice damage of the carbon backing and the LiF film using a previously reported model. In the experiment, elastically scattered target and beam ions were detected by surface silicon barrier (SSB) detectors so that the product of the beam flux and the target density could be monitored during the experiment. The areas of the targets exposed to different beam intensities and fluences were degraded and then perforated, forming holes with a diameter around the beam spot size. Overall, the target thickness tends to decrease linearly as a function of the beam fluence. However, the thickness also exhibits an increasing interval after SSB counts per beam ion decreases linearly, extending the target lifetime. The lifetime of thin LiF film as determined by lattice damage is calculated for the first time using a lattice damage model, and the calculated lifetime agrees well with the observed target lifetime during the experiment. In experiments using a thin LiF target to induce nuclear reactions, this study suggests methods to predict the lifetime of the LiF film and arrange the experimental plan for maximum efficiency.
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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".