Multi-step plasma etching of high aspect ratio silicon nanostructures for metalens fabrication
Bibliographic record
Abstract
Inductively coupled plasma etching of silicon nanostructures for metalens applications using a continuous, multi-step C4F8/SF6 plasma was investigated to achieve high aspect ratio (HAR) features down to tens of nanometers with smooth sidewalls. In the process, the ion bombardment and the free radical transport significantly change among HAR nanostructures as the etching progresses, posing challenges to profile control. With a fixed gas ratio, a change in the profile angle occurs at a depth of approximately 400 nm, transitioning from a positive taper to a negative one. Additionally, a wave-like pillar profile is produced when using three separate (i.e., plasma turned off after each step) etching processes with varying gas ratios. To optimize passivation and etching, we adopt a three-step C4F8/SF6 plasma etching process with varying gas ratios at different etching depths. By keeping the plasma on after each step, the continuous, three-step process provides more flexibility for tuning the etching of HAR nanostructures with smooth and vertical profiles. Metalens nanostructures with 71 nm diameter and 1 μm height were created using the appropriate gas ratio. The feature size variation is less than 10 nm. This proposed continuous, multi-step process improves the controllability of silicon etching in C4F8/SF6 plasma, facilitating the nanofabrication of silicon metalens and other nanodevices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".