Effects of band hybridization on electronic properties in tuning armchair graphene nanoribbons
Bibliographic record
Abstract
We explore a model of armchair graphene nanoribbons tuned by functionalizing the edge states. Edge modifications are modeled by changing the electronic energy of the edge states in specific periodic patterns. The model can be considered to mimic a controlled doping process with different elements. The band structure, density of states, conductance, and local density of states are calculated, using the tight binding approach, Green’s function methodology, and the Landauer formula. The results show interesting behaviors, which are considerably different from the properties of the perfect nanoribbons. The hybridization of conducting bands with non-conducting bands, which appear perfectly flat in the perfect ribbon, opens up and modifies gaps in conductance near the Fermi level. One particular pattern of edge functionalization causes a strong, symmetric, and systematic band gap change about the Fermi level, modifying the electronic characteristics in the energy dispersion, density of states, local density of states, and conductance.
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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".