Extended-SWIR GeSn LEDs with Reduced Footprint and Efficient Operation Power
Bibliographic record
Abstract
Complementary metal oxide semiconductor-compatible short- and midwave infrared emitters are highly coveted for the monolithic integration of silicon-based photonic and electronic integrated circuits to serve a myriad of applications in sensing and communication. In this regard, the group IV germanium–tin (GeSn) material epitaxially grown on silicon (Si) emerges as a promising platform to implement tunable infrared light emitters. Indeed, upon increasing the Sn content, the bandgap of GeSn narrows and becomes direct, making this material system suitable for developing an efficient silicon-compatible emitter. With this perspective, microbridge PIN GeSn LEDs with a small footprint of 1520 μm 2 are demonstrated, and their operation performance is investigated. The spectral analysis of the electroluminescence emission exhibits a peak at 2.31 μm, and it red-shifts slightly as the driving current increases. It is found that the microbridge LED operates at a dissipated power as low as 10.8 W at room temperature and just 3 W at 80 K. This demonstrated low operation power is comparable to that reported for LEDs having a significantly larger footprint reaching 10 6 μm 2 . The efficient thermal dissipation of the current design helped reduce the heat-induced optical losses, thus enhancing light emission. Further performance improvements are envisioned through thermal and optical simulations of the microbridge design. These simulations indicate that the use of GeSn-on-insulator substrate for developing a similar microbridge device is expected to improve the optical confinement toward the realization of electrically driven GeSn lasers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".