Correlation Between Substrate Morphology and the Initial Stages of Epitaxial Organic Growth: PTCDA/Ag(111)
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide We have investigated the initial growth of the first two epitaxial layers of PTCDA on a Ag(111) surface consisting of a distribution of flat (111) terraces, separated by single atomic steps or step bunches with a few point defects. By utilizing the low-energy electron microscopy (LEEM) technique in both bright and dark field modes, we are able not only to follow the growth of the first layers but also to distinguish between different rotational and mirror domains and their influence on the growth of subsequent layers. Thus, we learn much about diffusion lengths and barriers, domain sizes, and about the influence of domain boundaries and nucleation centers. The results give deep insight into the growth dynamics, the influence of step orientation, and the quality of the resulting epitaxial layers and lead to the conclusion that the morphology of the substrate surface is likely to be the most influential parameter for the homogeneity of epitaxial layers.
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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".