Ge-Ge$_{0.92}$Sn$_{0.08}$ core-shell single nanowire infrared photodetector with superior characteristics for on-chip optical communication
Bibliographic record
Abstract
Recent development on Ge$_{1-x}$Sn$_x$ nanowires with high Sn content, beyond its solid solubility limit, make them attractive for all group-IV Si-integrated infrared photonics at nanoscale. Herein, we report a chemical vapour deposition-grown high Sn-content Ge-Ge$_{0.92}$Sn$_{0.08}$ core-shell based single nanowire photodetector operating at the optical communication wavelength of 1.55 $\mu$m. The atomic concentration of Sn in nanowires has been studied using X-ray photoelectron and Raman spectroscopy data. A metal-semiconductor-metal based single nanowire photodetector, fabricated via electron beam lithography process, exhibits significant room-temperature photoresponse even at zero bias. In addition to the high-crystalline quality and identical shell composition of the nanowire, the efficient collection of photogenerated carriers under an external electric field result in the superior responsivity and photoconductive gain as high as ~70.8 A/W and ~57, respectively at an applied bias of -1.0 V. The extra-ordinary performance of the fabricated photodetector demonstrates the potential of GeSn nanowires for future Si CMOS compatible on-chip optical communication device applications.
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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".