Zipping and unzipping of nanoscale carbon structures
Bibliographic record
Abstract
We demonstrate theoretically that hydrogenation and annealing applied to nanoscale carbon structures play a crucial role in determining the final shape of the system. In particular, graphene flakes characterized by linear and nonhydrogenated zigzag or armchair edges have a high propensity to merge into a bigger flake or a nanotube (the formation of a single carbon-carbon bond lowers the total energy of the system by up to 6.22 eV). Conversely, a line of ${\mathit{sp}}^{2}$ carbon bonds (common for pure carbon structures such as graphene or a carbon nanotube) converted into ${\mathit{sp}}^{3}$ type by hydrogenation shows an ability to disassemble the original structure by cutting it along the line of the modified bonds. These structural transformations provide us with an understanding of the behavior of mobile carbon structures in solution and a distinct scenario for how to preserve the original structure, which is a crucial issue for their application in carbon-based electronics.
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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) | 0.002 | 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".