Determining adhesion of nonuniform arrays of fibrils
Bibliographic record
Abstract
Dry adhesives containing nonuniform arrays of fibrils were tested for the uniformity of their adhesion strength. These arrays comprised fibrils with nanometer-scale dimensions and lengths tuned from 150 to 1500 nm. The surfaces of the fibrils were rendered hydrophobic through a vapor phase deposition of silane molecules to further tune the adhesion strength of the fibrillar structure. Adhesion force measurements over micrometer-length scales were obtained using a tipless cantilever controlled by a scanning probe microscope. Maps of the adhesion forces depicted diverse variations in adhesion strength with the nonuniform lateral changes in topography. Through an extensive data analysis, differences observed between samples were correlated to changes in processing conditions and surface chemistry modifications. The methods demonstrated in this paper are useful for identifying variations in the adhesion strength of dry adhesives made of nonuniform arrays of fibrils. These advancements are crucial for understanding the correlation between structure and function within nonuniform fibrillar adhesives.
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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 | 0.001 |
| 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 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".