Bioinspired Functionally Graded Adhesive Materials: Synergetic Interplay of Top Viscous–Elastic Layers with Base Micropillars
Bibliographic record
Abstract
Inspired by the amazing adhesion abilities of the toe pads of geckos and tree frogs, we report an experimental study on the integration of a dissipative material (resembling the dissipative and wet nature of the tree frog toe pads) to an elastic fibrillar interface (resembling the dry and fibrillar nature of the gecko foot pads). Accordingly, a new type of functionally graded adhesive is introduced, which is composed of an array of elastic micropillars at the base, a thin elastic intermediate layer and a viscoelastic top layer. A systematic investigation of this bioinspired graded adhesive structure was performed in comparison with three control adhesive materials: a viscoelastic film, a viscoelastic film coated on a soft elastomer, and elastic film-terminated micropillars. The results showed that this graded structure bestows remarkable adhesive properties in terms of pull-off force, work of adhesion, and structural integrity (i.e., inhibited cohesive failure). Moreover, an extraordinary compliance was observed, which is attributed to the polymer slippage at the top layer. Overall, we attribute the improved adhesive properties to the synergetic interplay of top viscous–elastic layers with the base biomimetic micropillars.
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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) | 0.001 | 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 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".