Nanowire array based photonic crystal devices
Bibliographic record
Abstract
Photonic crystals consisting of semiconductor nanowire arrays grown using a metal catalyzed vapor-liquid-solid (VLS) method are excellent candidates for photonic elements and devices, such as micro-cavities, due to the high dielectric constant contrast and high aspect ratio. In addition, it is easy to control the crystal structure by patterning the metal catalysis, and the versatility of composition of nanowires (including II-VI, III-V and ternary III-V) makes the integration of optical components in diversified wavelength ranges possible. Here we use a Plane-Wave-Expansion (PWE) method and Finite Difference Time Domain (FDTD) technique toinvestigate the optical properties of nanowire based photonic crystals. It is found that arrays consisting of nanowires with radius at or below the edge of the effective single-wire confining range for a stand alone Fabry-Perot cavity can still form a high-Q value cavity with single mode operation. Our results will help to extend the concept of the-state-of-art 1-D distributed bragg reflector (DBR) and distributed feedback (DFB) lasers into 2-D ones with a working range from ultraviolet to near infrared.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".