Thermal annealing of birefringent TiO 2 thin films formed by oblique-angle deposition
Bibliographic record
Abstract
Titanium dioxide thin films were formed by electron-beam evaporation onto fused silica substrates using serial bideposition (SBD). The SBD technique combines rapid substrate rotation and oblique-angle physical vapor deposition (PVD) to create optical coatings that are composed of nanostructured columns which exhibit large birefringence values in the plane of the substrate. In this study, post-deposition annealing was used to crystallize amorphous TiO2 thin films formed by SBD to improve birefringence without significantly increasing optical absorption or scattering. Birefringent thin films were fabricated at deposition angles ranging from 60° to 75° and annealed in air at temperatures ranging from 200°C to 900°C to form anatase and rutile TiO2. Changes in the optical properties, crystallinity, and nanostructure were characterized by ellipsometry, x-ray diffraction, atomic force microscopy, and scanning electron microscopy. It was found that optical anisotropy increases strongly upon formation of anatase, yielding in-plane birefringence values that doubled from 0.11 to 0.22 in the case of TiO2 thin films deposited at 60° and annealed at 400°C. Raising the annealing temperature to 900°C to form rutile thin films increased the thin film birefringence further but also led to low optical transparency due to increased absorption and diffuse scattering.
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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 | 0.000 | 0.000 |
| 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".