(Digital Presentation) Gesnoi Laser Technology for Photonic-Integrated Circuits
Bibliographic record
Abstract
GeSn alloys have been regarded as a promising material for creating a complementary metal-oxide-semiconductor (CMOS)-compatible light source. Despite the remarkable progress in demonstrating GeSn lasers, an unavoidable intrinsic compressive strain introduced during epitaxial growth has prevented researchers from pushing the directness of GeSn gain media to the limit and realizing practical GeSn lasers. In this paper, we demonstrate a GeSn-based 1D photonic crystal nanobeam laser on a high-quality GeSn-on-insulator (GeSnOI) substrate which allows releasing the limiting compressive strain, thus improving the threshold and operating temperature. Pump-power-dependent photoluminescence measurements show a lasing threshold density of 18.2 kW cm−2 at 4 K for the released strain-free GeSn nanobeam, which is ~2 times lower than that of the unreleased GeSn nanobeam with compressive strain. The improved bandgap directness in the released GeSn nanobeam also allows achieving lasing action at higher operating temperatures up to 90 K compared to the unreleased laser device (<70 K). We also report a straightforward geometric strain-inversion technique that harnesses the harmful compressive strain to achieve ultrahigh tensile strain in GeSnOI nanowire, drastically improving the directness of the bandstructure. We achieve ~2.67% uniaxial tensile strain in ~120 nm wide nanowires, surpassing other values reported thus far. We also demonstrate unique superlattices comprising of indirect and direct bandgap GeSn are demonstrated in a single material only by applying a periodic tensile strain. Increased directness in tensile-strained GeSn significantly enhances the photoluminescence intensity by a factor of ~2.5. Our demonstration offers an avenue toward developing practical CMOS compatible light sources.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.411 | 0.161 |
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".