Frictional Adhesion of Patterned Surfaces and Implications for Gecko and Biomimetic Systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Geckos and smaller animals such as flies, beetles, and spiders have extraordinary climbing abilities: They can firmly attach and rapidly detach from almost any kind of surface. In the case of geckos, this ability is attributed to the surface topography of their attachment pads, which are covered with fine columnar structures (setae). Inspired by this biological system, various kinds of regularly structured or "patterned" surfaces are being fabricated for use as responsive adhesives or in robotic systems. In this study, we theoretically analyze the correlated adhesion and friction (frictional adhesion) of patterned surfaces against smooth (unstructured) surfaces by applying well-established theories of van der Waals forces, together with the classic Johnson-Kendall-Roberts (JKR) theory of contact (or adhesion) mechanics, to recent theories of adhesion-controlled friction. Our results, when considered with recent experiments, suggest criteria for simultaneously optimizing the adhesion and friction of patterned surfaces. We show that both the van der Waals adhesion and the friction forces of flexible, tilted, and optimally spaced setal stalks or (synthetic) pillars are high enough to support not only a large gecko on rough surfaces of ceilings (adhesion) and walls (friction) but also a human being if the foot or toe pads-effectively the area of the hands-have a total area estimated at approximately 230 cm2.
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.
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 it