Theoretical Studies of Transition-Metal-Doped Single-Walled Carbon Nanotubes
Bibliographic record
Abstract
We have studied single-walled carbon nanotubes (SWCNTs) doped with transition metal (TM) atoms with both exo and endo doping configurations. The electronic and geometric properties of these TM-doped SWCNTs were calculated within density functional theory. It was found that the endo-doped SWCNTs are less stable than the exo-doped counterparts due to the large geometric strain of the deformation in the endo-doped nanotubes. On the basis of partial charge analysis, the TM-doped SWCNTs have localized net charge distributions, whereas the spin densities in Sc-, Co-, and Cu-doped SWCNTs are delocalized over the entire nanotubes. The TM-doped SWCNTs are mostly metallic or narrow-gap semiconductive. With highly localized frontier molecular orbitals, the exo-doped SWCNTs are better electron donors than the corresponding endo-doped systems. As the dopant TM changes from Sc to Zn in the same row of the periodic table or from the top to the bottom in the same Pt group, the energy of the highest occupied crystal orbital of the TM-doped SWCNTs decreases, indicating a reduced electron donating ability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".