Impurity-induced spin gap asymmetry in nanoscale graphene
Bibliographic record
Abstract
We present a way to control both the band gap and the magnetic properties of nanoscale graphene, which might prove highly beneficial for application in nanoelectronic and spintronic devices. We have shown that chemical doping by nitrogen along a single zigzag edge lowers the symmetry from ${\text{D}}_{2h}$ (pure graphene) to ${\text{C}}_{2v}$, thereby accommodating the state with antiferromagnetic spin ordering of localized states between the zigzag edges. This leads to an increase in the gap in comparison to that of pure graphene in its highest possible symmetry of ${\text{D}}_{2h}$ and a shift of the molecular orbitals localized on the doped edge in such a way that the spin gap asymmetry, which can lead to half metallicity under certain conditions, is obtained. The doping in the middle of the graphene layer along the zigzag edge results in an impurity level between the highest occupied molecular orbital and lowest unoccupied molecular orbital of pure graphene (much like in semiconductor systems) thus decreasing the band gap and adding unpaired electrons, which can also be used to control the graphene conductivity.
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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".