Influence of ion mixing on the energy dependence of the ion-assisted chemical etch rate in reactive plasmas
Bibliographic record
Abstract
Recently, Stafford et al. [Appl. Phys. Lett. 87, 071502 (2005)] have shown that in contrast to the etch yield on a saturated surface, the ion-assisted chemical etch rate cannot universally be modeled by a simple square-root energy dependence. This results from the surface coverage by reactive neutral species being also a function of the ion energy. In this work, we further point out that depending on the plasma-material combination, the etch rate can exhibit two regimes that are characterized by different dependences on the ion energy. While these results are inconsistent with currently available models, we show that they can be interpreted by taking into account ion mixing effects on the desorption rate of volatile reaction products involved in the model of Stafford et al. Application of this rate model to the etching of Si, SiO2, HfO2, and ZrO2 in chlorine and fluorine plasma chemistries provides an excellent description of the simultaneous dependence of the etch rate on ion energy and on ion and reactive neutral fluxes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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".