Large-area ordered Ge-Si compound quantum dot molecules on dot-patterned Si (001) substrates
Bibliographic record
Abstract
We report on the formation of large-area ordered Ge-Si compound quantum dot molecules (CQDMs) in a combination of nanosphere lithography and self-assembly. Truncated-pyramid-like Si dots with {11n} facets are readily formed, which are spatially ordered in a large area with controlled period and size. Each Si dot induces four self-assembled Ge-rich dots at its base edges that can be fourfold symmetric along <110> directions. A model based on surface chemical potential accounts well for these phenomena. Our results disclose the critical effect of surface curvature on the diffusion and the aggregation of Ge adatoms and shed new light on the unique features and the inherent mechanism of self-assembled QDs on patterned substrates. Such a configuration of one Si QD surrounded by fourfold symmetric Ge-rich QDs can be seen as a CQDM with unique features, which will have potential applications in novel devices.
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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".