Switchable Dry Adhesion with Step-like Micropillars and Controllable Interfacial Contact
Bibliographic record
Abstract
Dry adhesives have attracted much attention because of their repeatable and reversible attachment. Many research groups have made fruitful achievements in fabricating and designing various dry adhesives. However, most of these studies focus on imitating bioinspired geometry to achieve this smart adhesion, neglecting the contact interface control through their peeling motion. Here, we present an alternative design to achieve this switchable adhesion on the basis of controlling contact areas. This unique design includes micropillars array with large overhanging caps and a "step" located at the center line of the cap. When dragging the pillars in the direction of the upper surface of the step, the lower surface is brought into contact, rapidly yielding stronger adhesion (switched-on state). Alternatively, when dragging the pillars in the direction of the lower surface of the step, the contact areas decrease sharply, leading to weak adhesion (switched-off state). Such switchable property under strong adhesion force is exactly what many practical applications need, and the ability to achieve this property by controlling the adhesion area size presented here opens a new way to dry adhesives design.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".