Novel silicon and nanophotonic components for emerging applications in optical short-reach interconnects
Bibliographic record
Abstract
In recent years, with the advantages of Complementary-Metal-Oxide-Semiconductor (CMOS) compatibility, high energy efficiency and high integration density, silicon photonics has been attracting ever-growing research interest as a promising platform for future optical short-reach interconnects. Because of the ultra-compact scale and ideal optical properties, nanophotonic microcavities are also of great research interest in applications for optical short-reach interconnects. In this thesis, we research on several novel silicon photonic and nanophotonic components for emerging applications in optical short-reach interconnects. Firstly, we propose a novel focusing-curved subwavelength grating coupler for wide-band optical interfaces of silicon photonics. An ultra-wide 1-dB bandwidth of over 100 nm (largest reported to date) near 1550 nm has been experimentally achieved for transverse-electric polarized light. Secondly, we report on the modeling and design of high-speed silicon microring modulators operating at both 1310 nm and 1550 nm. The modeling and simulation is validated by experimental results. At last, we present the characterization of a novel kind of nanophotonic microcavity - rolled-up semiconductor nanotube. The nanotube azimuthal and longitudinal optical modes were theoretically and experimentally investigated at 1550 nm. Counter-propagating whispering-gallery-modes in the nanotubes are experimentally demonstrated for the first time. The integration of nanotubes with silicon photonic chips is also demonstrated, based on which we achieve thermally controlled evanescent coupling, optical signal modulation and switching.
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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".