Bibliographic record
Abstract
The blistering of Si wafers with (100), (110), and (111) orientations, induced by implantation of low energy (5–8 keV) H and/or He ions, was studied. Our earlier work had used either pure H implants at high dose (5×1016 cm−2) or low dose coimplantation (1×1016 H cm−2+1×1016 He cm−2). Here we study pure He implantation, and coimplantation with variable He/H dose ratio, in order to understand the roles of H and He, in the hope of improving the blistering efficiency (as used, e.g., in the Smart-cut® process). After room temperature implantation, the samples were vacuum annealed in three steps at 500, 550, and 600 °C. At each step, the development of blistering and exfoliation was quantified by scanning electron microscopy (“exfoliation” is here used to mean blister explosion). We found that the thermal budget required for blistering is higher than for comparable doses of high energy (>30 keV) ions. On the Si(110) surface, H blistering is very weak, He blistering is the strongest, but exfoliation absent. On Si(111), H blistering is the strongest, He the weakest, but exfoliation a maximum. Si(100) shows intermediate behavior. Weak H blistering correlates with premature H2 desorption. H+He coimplantation efficiently increases the degree of blistering and, to some extent, exfoliation.
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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".