Design of gecko-inspired fibrillar surfaces with strong attachment and easy-removal properties: a numerical analysis of peel-zone
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
Despite successful fabrication of gecko-inspired fibrillar surfaces with strong adhesion forces, how to achieve an easy-removal property becomes a major concern that may restrict the wide applications of these bio-inspired surfaces. Research on how geckos detach rapidly has inspired the design of novel adhesive surfaces with strong and reversible adhesion capabilities, which relies on further fundamental understanding of the peeling mechanisms. Recent studies showed that the peel-zone plays an important role in the peeling off of adhesive tapes or fibrillar surfaces. In this study, a numerical method was developed to evaluate peel-zone deformation and the resulting mechanical behaviour due to the deformations of fibrillar surfaces detaching from a smooth rigid substrate. The effect of the geometrical parameters of pillars and the stiffness of backing layer on the peel-zone and peel strength, and the strong attachment and easy-removal properties have been analysed to establish a design map for bio-inspired fibrillar surfaces, which shows that the optimized strong attachment and easy-removal properties can vary by over three orders of magnitude. The adhesion and peeling design map established provides new insights into the design and development of novel gecko-inspired fibrillar surfaces.
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