Ion-beam etching for the precise manufacture of optical coatings
Bibliographic record
Abstract
We propose using ion-beam etching as an additional tool for the accurate control of the thickness of thin films during the manufacture of sensitive optical multilayer coatings. We use a dual ion-beam sputtering system in the deposition and etch modes. In the deposition mode both the assist and sputtering ion beams are used to produce dense films at deposition rates in the range of 0.1-0.3 nm/s. In the etch mode, only the assist ion beam is used to remove material at a rate of less than 0.1 nm/s. A very high precision in the layer thicknesses can be obtained by alternating between deposition and etch modes. We observed that etching did not significantly affect the surface quality and the uniformity of the coatings. We introduced etching into our current manufacturing process and demonstrated its potential for the fabrication of several optical multilayer systems with performances that are very sensitive to the thickness of their layers.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".