Studies of an improved system for the radial implantation of radio-isotopes
Bibliographic record
Abstract
We report on experiments undertaken to clarify the implantation process of a coaxial plasma-based ion implanter designed for the implantation of radio-isotopes into small, cylindrical metal surfaces. Mapping the distribution of the radioactive fragments on the reactor's surfaces allows us to verify several aspects that impact the implantation efficiency. First, by a careful design of the radioactive deposit support, we eliminated the generation of radioactive 'flakes', thus removing a source of possible contamination. Second, we verified that the material is ejected from the radioactive source (RS) in a cosine distribution. Third, we clearly demonstrated that the ionization mean free path of the radioactive fragments is only a few centimetres, much shorter than our original estimates based on an electron impact ionization model. From these results, we believe that the dominant ionization process is Penning ionization. The measurements undertaken in this study were only possible through the use of radioactive atoms and the associated radiographic mapping techniques that we developed. We have also studied a new configuration, with the RS situated on the reactor's axis, and where the implantation process depends explicitly on the potential barrier generated by the plasma. Using this new configuration with optimized parameters we believe an implantation efficiency of the order of 20% is achievable.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".