Fullerene on Nitrogen-Adsorbed Cu(001) Nanopatterned Surfaces: From Preferential Nucleation to Layer-by-Layer Growth
Bibliographic record
Abstract
Nitrogen (N)-adsorbed Cu(001)− c (2 × 2) nanopatterned surfaces are used as templates to guide the growth of low-dimensional C 60 molecular nanostructures. At room temperature and during the initial stages of growth, C 60 molecules preferentially adsorb on the bare Cu regions on a partially N-covered grid surface. Subsequently, a two-dimensional molecular nanomesh is formed at low (∼0.28 monatomic layer) C 60 coverages. Further deposition leads to C 60 growth on the c (2 × 2)−N surface until the first molecular layer is completed. For a N-saturated surface with trench structures, the <010> steps of these structures serve as initial anchoring sites for C 60 growth. From there, the growth proceeds two-dimensionally until a single C 60 layer is achieved due to island coalescence. In contrast, no nucleation site was observed when the <110> steps were predominant on the surface. At least up to 6 monatomic layers, the growth proceeds layer-by-layer (i.e., the overlayer morphologies are directed by the underlying substrate pattern). Four rotational domains are observed for the quasi-hexagonally close-packed C 60 overlayer with a nearest-neighbor C 60 −C 60 distance of 1.02 nm. It was found that the interaction between C 60 and the c (2 × 2)−N surface is fairly weak, likely dominated by van der Waals forces, whereas the C 60 −Cu interface is chemisorbed. Site-specific electronic effects between these two regions can be resolved by STM even for thick films.
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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".