Fabrication of substrates for photonic band gap crystals growth
Bibliographic record
Abstract
We present a technical processing to fabricate substrates (fused silica) for 3-D photonic bandgap material. The potential surface was modified to improve the colloidal method for nanoparticles assembly. This method allows orientating the growth of the colloidal crystals in a specific way; the crystalline plans growth is parallel to the surface of the substrate, and we can eliminate stacking defects and polycrystallinity. The substrate is obtained with ions beam engraving, according to the following process: A layer of photoresist is deposited on the substrate; we write two identical holographic gratings on the photoresist with 90° angle; After the development of photoresist, we obtain a profile which corresponds to one of the crystalline plans of the face centered cubic lattice; This profile will be transferred on the substrate by RIE (reactive ion etching). This substrate has many advantages: it is reusable because it is easily cleaned with solvents like acetone; the same substrate will be easy to use in order to make several growth tests and to optimize physicochemical parameters during artificial opals fabrication.
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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) | 0.001 | 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".