Thermally induced surface faceting on heteroepitaxial layers
Bibliographic record
Abstract
Heteroepitaxial semiconductors such as Ge-on-Si are widely used in current opto-electronic and electronic applications, and one of the most important challenges for epitaxial Ge-on-Si is threading dislocations (TDs) in Ge layers caused by lattice mismatch between Ge and Si. Here, apart from traditional wet chemical etching, we report a convenient approach to evaluate the threading dislocation densities in heteroepitaxial layers through vacuum thermal annealing. More importantly, the controversial origin of thermal annealing induced pits on a Ge surface was addressed in this work. By combining both experiments and density functional theory (DFT) calculations, we find that the {111} facets defined thermal pits on Ge (001) surfaces are mainly caused by threading dislocation activation. Ge adatoms at the TD segments sublimate preferentially than the ones on dislocation-free Ge (001) surface regions, and its further evolution is determined by surface energies of {111} facets, leading to a construction of inverted pyramid-shaped thermal pits.
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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".