Technology platform for the fabrication of titanium nanostructures
Bibliographic record
Abstract
Abstract : This paper presents two approaches for the fabrication of top-down titanium nanostructures. The first approach involves electron beam lithography followed by a tailored titanium plasma etching. The two main challenges of this process lie in the optimization of the negative tone Ma–N electroresist resolution and in the definition of a controlled titanium etching process for titanium patterns less than 20 nm thick and wide. The second proposed approach is a damascene process where the titanium nanostructures are buried in the oxide. Very shallow and narrow (20 nm × 20 nm) trenches are first patterned in the oxide and nanostructures are obtained by planarization of an evaporated titanium film. The dimensions of the structures are defined by the electron beam lithography resolution and the etching recipe. The third dimension is given by the titanium or any other metal thickness and can be controlled down to few nanometers thanks to the planarization step.
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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 | 0.002 |
| 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 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".