Vacancy complexes in nonequilibrium germanium-tin semiconductors
Bibliographic record
Abstract
Depth-profiled pulsed low-energy positron annihilation lifetime spectroscopy and Doppler broadening spectroscopy were combined to identify vacancy-related complexes and probe their evolution as a function of Sn content in GeSn epitaxial layers. Regardless of the Sn content in the 6.5–13.0 at. % range, all GeSn samples showed the same depth-dependent increase in the positron annihilation line broadening parameters, relative to that of epitaxial and bulk Ge references, thus confirming the formation of open volume defects during growth. The measured average positron lifetimes were found to be the highest (380–395 ps) in the region near the surface and monotonically decrease across the analyzed thickness but remain above 350 ps. All GeSn layers exhibit average lifetimes that are 20–160 ps higher than those recorded for the Ge reference. Surprisingly, these lifetimes were found to decrease as the Sn content increases in GeSn layers. These measurements indicate that divacancies are the dominant defect in the as-grown GeSn layers. However, their corresponding lifetime was found to be shorter than in epitaxial Ge, thus suggesting that the presence of Sn may alter the structure of divacancies. Additionally, GeSn layers were also found to contain a small fraction of vacancy clusters, which become less important as the Sn concentration increases. The interaction and possible pairing between Sn and vacancies have been proposed to explain the reduced formation of larger vacancy clusters in GeSn when the Sn content increases.
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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".