Evolution of Gesn Lasers Towards Photonic Integration into Practical Applications
Bibliographic record
Abstract
GeSn alloys have emerged as a promising material for group IV light sources because alloying Ge with Sn increases the directness of the bandstructure, thus improving the efficiency of light emission. Despite several years of progress in GeSn lasers, however, the integration of such lasers into practical applications still faces challenges such as high threshold, low operating temperature, and large device footprint. In this report, we address these challenges via each of the studies containing thermal management, defect reduction, and nanowire growth approach. First, we demonstrate improved lasing characteristics including reduced threshold and increased operating temperature in GeSn microdisks directly sitting on Si, which is allowed by the enhanced thermal management over the conventional suspended microdisks. Although there is a concern about poor optical confinement of the sitting approach, we confirm the simultaneous achievement of excellent heat dissipation and superior optical confinement from the microdisk released on Si through experiments and theoretical simulations. We also demonstrate a decreased threshold in microdisk lasers fabricated using a high-quality GeSn-on-insulator (GeSnOI) substrate. Photoluminescence measurements show that the reduction of defects in GeSnOI leads to enhancement of spontaneous emission and reduction of the lasing threshold. Lastly, we present the potential for GeSn nanowire lasers having smaller footprints by observing clear cavity resonances in a single nanowire grown by a bottom-up growth approach. Our demonstrations provide guiding principles to push the performance of GeSn lasers to the limit towards a realization of practical group IV 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) | 0.000 | 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".