Origin of Nanoscale Friction Contrast between Supported Graphene, MoS<sub>2</sub>, and a Graphene/MoS<sub>2</sub> Heterostructure
Bibliographic record
Abstract
Ultralow friction can be achieved with 2D materials, particularly graphene and MoS 2 . The nanotribological properties of these different 2D materials have been measured in previous atomic force microscope (AFM) experiments sequentially, precluding immediate and direct comparison of their frictional behavior. Here, friction is characterized at the nanoscale using AFM experiments with the same tip sliding over graphene, MoS 2, and a graphene/MoS 2 heterostructure in a single measurement, repeated hundreds of times, and also measured with a slowly varying normal force. The same material systems are simulated using molecular dynamics (MD) and analyzed using density functional theory (DFT) calculations. In both experiments and MD simulations, graphene consistently exhibits lower friction than the MoS 2 monolayer and the heterostructure. In some cases, friction on the heterostructure is lower than that on the MoS 2 monolayer. Quasi-static MD simulations and DFT calculations show that the origin of the friction contrast is the difference in energy barriers for a tip sliding across each of the three surfaces.
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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 | 0.001 |
| 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".