Triboelectrification and Unique Frictional Characteristics of Germanium‐Based Nanofilms
Bibliographic record
Abstract
In this study, germanium arsenide (GeAs) is investigated as a promising nanomaterial for application in triboelectric nanogenerators and green energy harvesting. The mechanical and electrical properties of mechanically exfoliated GeAs on silica substrates are evaluated through friction force microscopy and Kelvin probe force microscopy, respectively. First, it is observed that the surface potential/work function of GeAs varied with thickness. Second, thickness-dependent friction on GeAs films is found. However, the variation of friction with GeAs thickness followed an inverse trend typically observed for most other 2D material systems: larger friction is measured on thicker GeAs films. The higher friction is attributed to the higher surface potential of thicker GeAs, resulting from the accumulation of electrons on the GeAs surface that also resulted in higher adhesion between GeAs surface and the tip. Finally, history-dependent friction is observed and resulted from a continual increase in the friction force as the surface is scanned and originated from the triboelectrification of the surface. The dynamic triboelectrification behavior of thick GeAs during the scanning process is further verified and visualized by a serial experiment, where the GeAs is tribo-electrified through scanning and gradually de-electrified/discharged upon ceasing the scan.
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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) | 0.000 | 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".