Effects of uniaxial strain on the performance of armchair graphene nanoribbon resonant tunneling diode
Bibliographic record
Abstract
Abstract Electronic performance of armchair graphene nanoribbon (AGNR) resonant tunneling diodes (RTDs) is influenced by strain effects, when they are mounted on the stretchable substrates or mechanically deformed due to real working conditions. Therefore, it is important to investigate how uniaxial strain can impact the performance of AGNR RTDs. In this paper, two platforms of AGNR RTD namely width-modified AGNR RTD and field-modified AGNR RTD are introduced and they are under both compressive and tensile uniaxial strain. It is found that the characteristics of AGNR RTD change considerably under either compressive or tensile strain. In particular, peak to valley ratio (PVR) can be totally deteriorated upon strong enough whole-body strain. However, local strain in the channel and barrier regions, in contrast to whole-body strain, can even improve the efficiency of AGNR RTD devices. Furthermore, the behavior of strained AGNR RTD is investigated while the width of device is modified. Numerical tight binding coupled with non-equilibrium Green’s function is derived for this study to calculate corresponding Hamiltonian matrices and transport properties.
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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".