Deep germanium etching using time multiplexed plasma etching
Bibliographic record
Abstract
There is a growing need for patterning germanium for photonic and photovoltaics applications. In this paper, the authors use a time multiplexed plasma etch process (Bosch process) to deep etch a germanium substrate. They show that germanium etching presents a strong aspect ratio dependent etching and that patterns present scallops mostly on the upper part (aspect ratio below 0.8). Passivation layers are formed during the passivation step by neutrals' deposition and are reinforced during the etching step by the redeposition of sputtered fluorocarbon species from the etch front. When the sidewalls are passivated, reactive neutrals diffuse through Knudsen-like diffusion down to the bottom of the pattern to etch the germanium. The Knudsen-like diffusion is responsible for the aspect ratio dependent etching and makes difficult the etching of holes with aspect ratios above 10 while trenches with aspect ratio of 17 are still etched faster than 2 μm/min.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".