Injection and waveguiding properties in SU8 nanotubes for sub-wavelength regime propagation and nanophotonics integration
Bibliographic record
Abstract
We report photonic concepts related to injection and sub-wavelength propagation in nanotubes, an unusual but promising geometry for highly integrated photonic devices. Theoretical simulation by the finite domain time-dependent (FDTD) method was first used to determine the features of the direct light injection and sub-wavelength propagation regime within nanotubes. Then, the injection into nanotubes of SU8, a photoresist used for integrated photonics, was successfully achieved by using polymer microlensed fibers with a sub-micronic radius of curvature, as theoretically expected from FDTD simulations. The propagation losses in a single SU8 nanotube were determined by using a comprehensive set-up and a protocol for optical characterization. The attenuation coefficient has been evaluated at 1.25 dB mm(-1) by a cut-back method transposed to such nanostructures. The mechanisms responsible for losses in nanotubes were identified with FDTD theoretical support. Both injection and cut-back methods developed here are compatible with any sub-micronic structures. This work on SU8 nanotubes suggests broader perspectives for future nanophotonics.
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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".