Novel waveguide MSM photodetectors on SOI substrates using silicides
Bibliographic record
Abstract
Novel Si waveguide MSM photodetector suitable for high speed/high quantum efficiency applications is proposed and demonstrated. Silicides are formed on a silicon-on-insulator (SOI) substrate through metal/Si reaction under heat treatment, in two areas separated by a narrow gap. The silicide sidewalls on the two sides of the narrow gap provide lateral waveguide confinement, and also serve as electrodes. The silicide/Si interface forms a Schottky junction, making the structure a MSM diode. The waveguide structure provides a long optical path length to increase the quantum efficiency at near infrared wavelengths. The distance between electrodes can be changed easily through photolithography, and can be made very small to reduce the transit time between electrodes for high-speed operation. Since the devices are made on SOI substrates, the drift component of the photocurrent can be eliminated, further facilitating high-speed operation. First set of photodetectors was made using PtSi on commercially available SOI substrates with 0.34micrometers Si layer. Initial experiments have demonstrated a responsivity of near 200mA/W at (lambda) equals980 nm for a detector with 486micrometers long electrodes and 2 micrometers gap size. The dark current was on the order of 0.1 nA/micrometers 2 at 5V bias.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".