Etching mechanism of the single-step through-silicon-via dry etch using SF6/C4F8 chemistry
Bibliographic record
Abstract
A single-step etching method using the SF6/C4F8 chemistry is developed in this study as an alternative through-silicon-via (TSV) etching approach of the traditional Bosch process to realize ultrasmooth and vertical TSV profiles. Experimental results show that there is a profile discontinuity, or a “transition,” on the TSV profile produced by the single-step etching method at high bias voltages and high SF6 flow rates. Comparison between the intensity of the species generated in a pure SF6 or a pure C4F8 plasma and in a SF6/C4F8 plasma is investigated for better understanding interactions between SF6 and C4F8. The densities of all positive ions are reduced in the SF6/C4F8 plasma compared to a pure SF6 plasma and a pure C4F8 plasma at the same partial pressure, indicating a change of plasma chemistry when SF6 and C4F8 fluxes are mixed. The formation mechanism of the transition is proposed as a chemistry discontinuity caused by large-angle ion sputtering at the top part of the sidewalls and the polymer accumulation at the bottom part of the sidewalls. The formation of the transition has found to have an effect of improving the sidewall smoothness below the position where it is formed. Parameter study has shown that a decreased bias voltage and a reduced SF6/C4F8 ratio can help to improve the sidewall smoothness and eliminate the transition on the TSV profiles.
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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".