Effects of dry plasma releasing process parameters and induced in-plane stress on MEMS devices yield
Bibliographic record
Abstract
An investigation into the effects of dry plasma etching release process parameters, local wafer position and induced inplane stress on the yield of MEMS devices is presented. Several identical wafer quarters, each subjected to different releasing process conditions, are studied. Yield is evaluated by observational measurements of the stiction of MEMS nanocantilevers fabricated alongside with bent beam strain sensors. Results show that lower yield is found for larger processing times as well as higher releasing temperatures. On the other hand, yield improves when thicker nanocantilevers are released using the same processing parameters. The distribution of process-induced in-plane stress of PECVD silicon nitride films is shown to change widely from compressive to tensile based on the local wafer position, whereas no clear correlation between stiction and stress distribution is found. Viability of determining MEMS yield at the wafer-level based on process-induced residual stress is discussed. Other possible root causes of yield in MEMS due to dry plasma release etching are also briefly touched.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".