Postfabrication fine-tuning of photonic crystal microcavities in InAs∕InP quantum dot membranes
Bibliographic record
Abstract
A method to fine-tune photonic crystal defect cavities is developed based on successive oxidation and wet etching cycles. Photonic crystal microcavities based on InP membranes are oxidized using an ultraviolet (UV)/ozone treatment, and the oxide is subsequently removed using a hydrofluoric acid solution. Each oxidation/etch cycle consumes a thin layer of InP directly exposed to the UV/ozone, enlarging the radius of holes in the photonic crystal and decreasing the membrane thickness. The method is applied to single missing air-hole defect cavities with embedded InAs quantum dots, permitting measurement of the resonant frequency tuning in emission. Defect mode energies were found to blueshift 1.74meVpercycle, consistent with finite-difference time-domain simulations. A tuning range of 33meV was obtained after 20cycles.
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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) | 0.000 | 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".