Lasing in a Hybrid Rare‐Earth Silicon Microdisk
Bibliographic record
Abstract
Abstract Silicon photonics is an ideal platform for low‐cost, energy‐efficient, and high‐performance optical microsystems. However, because silicon is an inefficient light emitting material, the development of simple, inexpensive, and scalable monolithic amplifiers and light sources has been a significant challenge. Here, optical gain and lasing in an ultra‐compact hybrid rare‐earth silicon microdisk resonator are reported. The microdisk design is straightforward and compatible with the fabrication steps and device dimensions available in all silicon photonics foundries, while the thulium‐doped tellurite gain medium is added in a low‐temperature single‐step sputter deposition. This approach allows for low‐cost and high‐volume wafer‐scale manufacturing and co‐integration of rare‐earth amplifiers and light sources with silicon passive and active devices with no adjustment to standard process flows. The hybrid laser is pumped at standard telecom wavelengths around 1.6 µm and exhibits stable single‐mode emission at 1.9 µm, with an internal slope efficiency of 60% and >1 mW on‐chip output power. The laser is highly promising for emerging communications and sensing applications and opens new possibilities for the development of monolithic rare‐earth optical amplifiers and lasers directly on silicon.
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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".