Role of contact electrification and electrostatic interactions in gecko adhesion
Bibliographic record
Abstract
Geckos, which are capable of walking on walls and hanging from ceilings with the help of micro-/nano-scale hierarchical fibrils (setae) on their toe pads, have become the main prototype in the design and fabrication of fibrillar dry adhesives. As the unique fibrillar feature of the toe pads of geckos allows them to develop an intimate contact with the substrate the animal is walking on or clinging to, it is expected that the toe setae exchange significant numbers of electric charges with the contacted substrate via the contact electrification (CE) phenomenon. Even so, the possibility of the occurrence of CE and the contribution of the resulting electrostatic interactions to the dry adhesion of geckos have been overlooked for several decades. In this study, by measuring the magnitude of the electric charges, together with the adhesion forces, that gecko foot pads develop in contact with different materials, we have clarified for the first time that CE does contribute effectively to gecko adhesion. More importantly, we have demonstrated that it is the CE-driven electrostatic interactions which dictate the strength of gecko adhesion, and not the van der Waals or capillary forces which are conventionally considered as the main source of gecko adhesion.
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 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".