Friction hysteretic behavior of supported atomically thin nanofilms
Bibliographic record
Abstract
Abstract Hysteretic friction behavior has been observed on varied 2D nanofilms. However, no unanimous conclusion has yet been drawn on to the exact mechanism or relative contribution of each mechanism to the observed behavior. Here we report on hysteretic friction behavior of supported atomically thin nanofilms studied using atomic force microscopy (AFM) experiments and molecular dynamics (MD) simulations. Load dependent friction measurements were conducted on unheated and heated samples of graphene, h-BN, and MoS 2 supported by silica substrates. Two diverging friction trends are reported: the unheated samples showed higher friction during unloading than during loading, and the heated samples showed a reversed hysteresis. Further, the friction force increased sub-linearly with normal force for heated samples, compared with unheated samples. Tapping mode AFM suggested that the interaction strength of the substrate was increased with heating. Roughened substrates in the MD simulations that mimicked strong/weak interaction forces reproduced the experimental observations and revealed that the evolution of real contact area in different interface interaction situation caused the diverging behaviors. Surface roughness and interaction strength were found to be the key parameters for controlling the out-of-plane deformation of atomically thin nanofilms.
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 | 0.000 | 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 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".