Effect of oxygen plasma cleaning on nonswitching pseudo-Bosch etching of high aspect ratio silicon pillars
Bibliographic record
Abstract
In dry plasma silicon etching, it is desired to have a high etching rate, a high etching selectivity to mask material, a vertical or controllable sidewall profile, and a smooth sidewall. Since the standard Bosch process (switching between SF6 and C4F8 gases) leads to a wavy/rough sidewall profile, the nonswitching pseudo-Bosch process is developed to give a smooth sidewall needed for nanostructure fabrication. In the process, SF6 and C4F8 gases are introduced to the chamber simultaneously. Here, the authors show that by introducing a periodic oxygen (O2) plasma cleaning step, that is, switching between SF6/C4F8 etching and O2 cleaning, the silicon etching rate can be significantly improved (by up to ∼55%, from 139 to 216 nm/min) without any adverse effect. This is mainly because O2 plasma can remove the fluorocarbon polymer passivation layer at the surface. The etching and cleaning step durations were varied from 5 s to 40 min and from 0 to 60 s, respectively. The fastest etching rates were obtained when the cleaning step takes roughly 10% of the total etching time.
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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 | 0.001 |
| 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".