Process design for reactive ion etching of silicones
Bibliographic record
Abstract
In this paper, reactive ion etch process of silicone materials, specifically polydimethylsiloxane (PDMS), was characterised using Plackett-Burman fractional factorial and Box-Behnken response surface designs. These design of experiment techniques allow for efficient analysis of input parameters and their effects on response parameters. The Plackett-Burman design was used in screening for critical factors in eight experiments. RF power, pressure and flow rate of sulphur hexafluoride were determined as critical parameters. Oxygen and nitrogen gas composition in plasma had little positive effect on etch rate. The three-critical parameter, three-level Box-Behnken design produced 15 experiments. Based on the data obtained, the effects of critical parameters on the etch rate and surface roughness were studied. Response surface plots along with a second order polynomial were derived using statistical analysis software yielding an approximated model with R² = 99.53%.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".