Sensitivity Comparison between Monolayer Graphene and Multilayer Graphene
Bibliographic record
Abstract
Graphene is an excellent piezoresistive material. The gauge factor of graphene mirrors the sensitivity of electromechanical devices. This paper mainly studies the gauge factors of different layers of graphene under different deformation conditions. Specifically, a theoretical model was combined with linearized Boltzmann transport equation, and the density function theory (DFT) to explore how the layer number of graphene affects sensitivity. The results show that monolayer graphene is slightly more sensitive than two-layer graphene, and significantly more sensitive than three-layer graphene and four- layer graphene. In particular, monolayer graphene remains highly sensitive under large deformation conditions, which gives monolayer graphene a significant advantage over other layers of graphene. Furthermore, a microelectromechanical system (MEMS) pressure sensor was proposed with monolayer graphene, and compared with previous similar sensors with multilayer graphene in terms of sensitivity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".