Fabrication of silicon sharp nanocones using dry etch with periodic oxygen plasma shrinking and wet etch
Bibliographic record
Abstract
Silicon (Si) nanocones have a wide range of applications in microelectromechanical systems and nanoelectromechanical systems. There is an increasing demand for precise control over the size and shape of nanocones. This paper proposed a novel method combining Si dry etch with periodic oxygen plasma shrinking, wet etch, and oxidation sharpening to achieve well-defined sharp Si nanocones. First, the standard Bosch process was employed to create the base part of nanocones. Second, two alternating steps of etching with sulfur hexafluoride/octafluorocyclobutane plasma and photoresist shrinkage with oxygen plasma were used to form the cone-shaped structures on top of the cylindrical bases. Third, to obtain a sharp tip, wet etching was carried out in either potassium hydroxide or a nitric acid/hydrofluoric (HF) acid mixture. To further sharpen the Si tips, thermal oxidation and HF dipping were conducted and the apex of nanocones can be down to 20 nm. This technique provides a cost-effective way to manufacture nanocones for various applications.
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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".