Improved thin film quality and photoluminescence of N-doped epitaxial germanium-on-silicon using MOCVD
Bibliographic record
Abstract
This paper addresses one of the key issues in the scientific community of Si photonics: thin-film quality and the light emission properties of band-engineered n+ Germanium-on-Silicon (Ge-on-Si). Compared to the traditional delta doping approach, which was utilized in the first electrically-pumped Ge-on-Si lasers, we offer an n+ Ge-on-Si thin film with better material quality and higher carrier injection efficiency grown by metal-organic chemical vapor deposition (MOCVD). The impacts of thermal cycle annealing and Si substrate offcut on the thin film quality were investigated, including surface roughness, strain, threading dislocation density, Si-Ge interdiffusion, and dopant diffusion. It was revealed that: 1) MOCVD overcomes the outdiffision issue of n-type dopants by having the dopant peaks at the bottom of the Ge films; 2) the characterization of the light emission properties of these MOCVD n+ Ge-on-Si samples (1.0 × 1019 cm−3 doped) compared to delta-doped ultra-high vacuum chemical vapor deposition (UHVCVD) Ge, showing comparable photoluminescence (PL) spectral intensity at 1/4 of the doping level; 3) Detailed PL spectral analyses showed that population inversion from the direct gap transition has been achieved, and the injected electron density in the direct Γ valley is comparable to that of the delta-doped sample even though the n-type doping level is 75% less; and 4) Experimental evidences that Si-Ge interdiffusion has a much larger impact on PL intensity than threading dislocation density in the range of 108-109/cm3. These results indicate that MOCVD n+ Ge is very promising to reduce the threshold of Ge gain media on Si notably.
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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) | 0.000 | 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 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".