Mid-infrared group IV nanowire laser
Bibliographic record
Abstract
Semiconductor nanowires have shown great potential for enabling ultracompact lasers for integrated photonics platforms. Despite the impressive progress in developing nanowire lasers, their integration into Si photonics platforms remains challenging largely because of the use of III-V and II-VI semiconductors as gain media. Recently, group IV nanowires, particularly direct bandgap GeSn nanowires capable of emitting above 2 μm, have emerged as promising cost-effective gain media for Si-compatible nanowire lasers, but there has been no successful demonstration of lasing from this seemingly promising nanowire platform. Herein, we report the experimental observation of lasing above 2 μm from a single bottom-up grown GeSn nanowire. By harnessing strain engineering and optimized cavity designs simultaneously, the single GeSn nanowire achieves an amplified material gain that can sufficiently overcome minimized optical losses, resulting in single-mode lasing with an ultralow threshold of ~5.3 kilowatts per square centimeter. Our finding paves the way for all-group IV mid-infrared photonic-integrated circuits with Si-compatible lasers for on-chip classical and quantum 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) | 0.002 | 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".