Silicon photonic resonator-enhanced defect-mediated photodiode for sub-bandgap detection
Bibliographic record
Abstract
We describe, model and demonstrate a tunable micro-ring resonator integrated monolithically with a photodiode in a silicon waveguide device. The photodiode is made sensitive to wavelengths at and around 1550nm via the introduction of lattice damage through selective ion implantation. The ring resonator enhances detector responsivity in a 60 mum long waveguide photodiode such that it is 0.14 A/W at -10Vbias with less than 0.2 nA leakage current. The device is tunable such that resonance (and thus detection) can be achieved at any wavelength from 1510 - 1600 nm. We also demonstrate use of the device as a digital switch with integrated power monitoring, 20 dB extinction, and no optical power tapped from the output path to the photodiode. A theoretical description suggests that for a critically coupled resonator where the round trip loss is dominated by the excess defects used to mediate detection, the maximum responsivity is independent of device length. This leads to the possibility of extremely small detector geometries in silicon photonics with no requirement for the use of III-V materials or germanium.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".