Electronic and transport properties of zigzag carbon nanotubes with the presence of periodical antidot and boron/nitride doping defects
Bibliographic record
Abstract
Abstract Electronic and transport properties of Carbon nanotubes (CNTs) are affected by the presence of physical or chemical defects in their structures. In this paper, we present novel platforms of defected zigzag CNTs (Z-CNTs) in which two topologies of antidot and Boron/Nitride (BN) doping defects are periodically imposed throughout the length of perfect tubes. Using the tight binding model and the non-equilibrium Green’s function method, it is realized that the quantum confinement of Z-CNTs is modified by the presence of such defects. This new quantum confinement results in the appearance of mini bands and mini gaps in the transmission spectra, as well as a modified band structure and band gap size. The modified band gap could be either larger or smaller than the intrinsic band gap of a perfect tube, which is determined by the category of Z-CNT. The in-depth analysis shows that the size of the modified band gap is the function of several factors consisting of: the radii of tube ( D r ), the distance between adjacent defects ( d d ), the utilized defect topology, and the kind of defect (antidot or BN doping). Furthermore, taking advantage of the tunable band gap size of Z-CNT with the presence of periodical defects, new platforms of defect-based Z-CNT resonant tunneling diode (RTD) are proposed for the first time. Our calculations demonstrate the apparition of resonances in transmission spectra and the negative differential resistance in the I-V characteristics for such RTD platforms.
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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".