Measuring Shear‐<scp>I</scp>nduced Adhesion of Gecko‐<scp>I</scp>nspired Fibrillar Arrays Using Scanning Probe Techniques
Bibliographic record
Abstract
Abstract The natural ability of geckos and spiders to climb almost all surfaces using the compliant, nano‐structured components on their feet provides motivation for making bio‐inspired adhesives. The goal of the studies in this paper is to create an analytical technique for improving the ability to characterize dry adhesives modeled after these biological systems. The technique described herein uses a scanning probe microscope to manipulate a flat test surface in contact with biomimetic fibrillar arrays while monitoring the adhesion forces. Adhesion forces were measured after both normal contact and shear‐induced contact between the nano‐structured fibrils and the test surface. Results confirm that the adhesion forces are higher for bio‐inspired adhesives after a shear‐induced contact. Variations in these forces can be measured across the sample with micrometer‐scale lateral resolution. This method of analysis can be extended to evaluate bio‐inspired dry adhesives with realistic mechanisms of attachment utilized in robotic and similar applications of these materials.
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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 | 0.000 | 0.000 |
| 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".