Selective dry etching of TiN nanostructures over SiO2 nanotrenches using a Cl2/Ar/N2 inductively coupled plasma
Bibliographic record
Abstract
An inductively coupled plasma etch process for the fabrication of TiN nanostructures over nanotopography is presented. Using a Cl2/Ar/N2 plasma, a selectivity of 50 is achieved over SiO2. The effect of N2 flow rate on the etch rates and the nonvolatile residues on TiN sidewalls is investigated. As N2 flow rate is increased up to 50 sccm, a change in the deposition of the nonvolatile residues on TiN sidewalls is observed. The current density–voltage characterizations of TiN devices fabricated with TiN nanostructure sidewalls are presented. The measured current densities of two different samples etched with low and high N2 flow rate, respectively, demonstrated the presence after cleaning of an insulating layer deposited on the sidewalls for low N2 flow rate only.
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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 | 0.001 | 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 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".