Influence of the positive ion composition on the ion-assisted chemical etch yield of SrTiO3 films in Ar∕SF6 plasmas
Bibliographic record
Abstract
Langlois et al. [Appl. Phys. Lett. 87, 131503 (2005)] have demonstrated that the etch yield of SrTiO3 films in Ar∕SF6 plasmas decreases as the concentration fraction of molecular ions in the plasma increases. Introducing the concept of effective mass for both ions and SrTiO3, these experimental results have quantitatively been explained in the framework of a well-established model originally developed to describe the sputtering of single-atom materials by nonreactive monoatomic ions. This model has, however, ignored the dissociation of molecular ions occurring as these particles impact the material surface. In the present article, the influence of the positive ion composition on the ion-assisted chemical etch yield of SrTiO3 films in Ar∕SF6 plasmas is reexamined to the light of this consideration. A rate model accounting for the dissociation of the various molecular ions is proposed and validated using experimental data. It is found that even though a specific ion species may not be the most important charge carrier in the plasma, its contribution to the plasma etching dynamics may still be the most significant.
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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".