Raman investigation of hydrogen-implanted and DC hydrogen-plasma-treated Cz Si wafers
Bibliographic record
Abstract
The general goal of this work is to demonstrate that the buried defect layer created by hydrogen implantation can serve as a gettering region for hydrogen introduced from a DC plasma and to study the efficiency of this gettering affected by the implantation regimes. Standard n-type 4.5 Ω⋅cm Cz Si wafers were implanted by hydrogen ions with an energy of 100 keV and different doses of 1 × 1014, 1 × 1015, or 5 × 1015 atoms/cm2 at temperatures of 150, 300, 400, or 500 °C. After implantation, hydrogen was introduced to the wafers from the DC plasma at 150 °C. For a comparative estimation of the hydrogen concentration in the wafers implanted in different regimes Raman spectroscopy was used. The peaks of the Raman spectra associated with molecular hydrogen (H2), vacancy-hydrogen (V–H), and silicon–hydrogen (Si–H) complexes were studied depending on the implantation conditions. It is demonstrated that peaks of Raman spectra depend significantly on the dose and temperature of implantation. This means that the concentration of hydrogen in the wafers could be determined from the concentration and type of defects formed by hydrogen implantation. Maximum peaks associated with H2, Si–H, and V–H complexes were observed for the samples implanted at a temperature of 500 °C.
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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".