Impact of nitrogen doping on the linear and nonlinear terahertz response of graphene
Bibliographic record
Abstract
It is well known that impurities play a central role in the linear and nonlinear response of graphene at optical and terahertz frequencies. In this work, we calculate the bands and intraband dipole connection elements for nitrogen-doped monolayer graphene using a density functional tight-binding approach. Employing these results, we calculate the linear and nonlinear response of the doped graphene to terahertz pulses using a density-matrix approach in the length gauge. We present the results for the linear and nonlinear mobility as well as third-harmonic generation in graphene for adsorbed and substitutional nitrogen doping for a variety of doping densities. We show that the conduction bands are more parabolic in graphene structures with substitutional nitrogen doping than for those with adsorbed nitrogen. As a result, substitutional doping has a greater impact on the terahertz mobility and nonlinear response of graphene than adsorbed nitrogen does.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".