Thickness Dependent Interlayer Magnetoresistance in Multilayer Graphene Stacks
Bibliographic record
Abstract
Chemical Vapor Deposition grown multilayer graphene (MLG) exhibits large out-of-plane magnetoresistance due to interlayer magnetoresistance (ILMR) effect. It is essential to identify the factors that influence this effect in order to explore its potential in magnetic sensing and data storage applications. It has been demonstrated before that the ILMR effect is sensitive to the interlayer coupling and the orientation of the magnetic field with respect to the out-of-plane ( c -axis) direction. In this work, we investigate the role of MLG thickness on ILMR effect. Our results show that the magnitude of ILMR effect increases with the number of graphene layers in the MLG stack. Surprisingly, thicker devices exhibit field induced resistance switching by a factor of at least ~107. This effect persists even at room temperature and to our knowledge such large magnetoresistance values have not been reported before in the literature at comparable fields and temperatures. In addition, an oscillatory MR effect is observed at higher field values. A physical explanation of this effect is presented, which is consistent with our experimental scenario.
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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".