Reversible adhesives with controlled wrinkling patterns for programmable integration and discharging
Bibliographic record
Abstract
Switchable and minimally invasive tissue adhesives have great potential for medical applications. However, on-demand adherence to and detachment from tissue surfaces remain difficult. We fabricated a switchable hydrogel film adhesive by designing pattern-tunable wrinkles to control adhesion. When adhered to a substrate, the compressive stress generated from the bilayer system leads to self-similar wrinkling patterns at short and long wavelengths, regulating the interfacial adhesion. To verify the concept and explore its application, we established a random skin flap model, which is a crucial strategy for repairing severe or large-scale wounds. Our hydrogel adhesive provides sufficient adhesion for tissue sealing and promotes neovascularization at the first stage, and then gradually detaches from the tissue while a dynamic wrinkling pattern transition happens. The gel film can be progressively ejected out from the side margins after host-guest integration. Our findings provide insights into tunable bioadhesion by manipulating the wrinkling pattern transition.
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.
How this classification was reachedexpand
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 | 0.001 |
| 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 teacher head, 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".