Metal-semiconductor-metal photodetector with a-Ge:H absorption layer for 1.55μm optical communication wavelength
Bibliographic record
Abstract
Metal-Semiconductor-Metal photodetectors (MSM-PDs) have been demonstrated with ease of fabrication, low capacitance, and faster responses compared to PIN photodetectors. Si and Ge are two of the CMOS compatible materials for sensing area of the photodetector. Ge, because of its higher mobility and absorption at 1.55μm wavelength is an attractive material of choice. In the outlined work, an interdigitated electrode MSM photodetector with a-Ge:H (amorphous-Ge:hydrogenated) as the sensing material has been recognized as a promising candidate for near infrared photodetection. Hydrogenating Ge generally helps improve material characteristics because it increases life time of photocarriers. Ge was sputter deposited with different H2 concentrations of 0%, 5%, 10%, 15%, and 25% in the plasma gas. The highest hydrogen concentration showed the highest responsivity among other detectors showing that hydrogen helps to reduce the number of defects within the a-Ge film and therefore increase the life time of carriers. Results show that highest photocurrent belongs to a sample with 25% H2 concentration in the plasma with a responsivity of 2mA/W and dark current of 11.6μA at 5v for a device area of 95×110 (μm)2.
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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) | 0.003 | 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".