Stimulation Modulates Adhesion and Mechanics of Hydrogel Adhesives
Bibliographic record
Abstract
The ability to modulate the adhesion of soft materials on-demand is desired for broad applications ranging from tissue repair to soft robotics. Research effort has been focused on the chemistry and architecture of interfaces, leaving the mechanics of soft adhesives overlooked. Stimuli-responsive mechanisms of smart hydrogels could be leveraged for achieving stimuli-responsive hydrogel adhesives that respond mechanically to external stimuli. Such stimuli-responsive hydrogel adhesives involve complex chemomechanical coupling and interfacial fracture phenomena, calling for mechanistic understanding to enable rational design. Here, we combine experimental, computational, and analytical approaches to study a thermo-responsive hydrogel adhesive. Experimentally, we show that the adhesion and mechanical properties of a stimuli-responsive hydrogel adhesive are both enhanced by the application of a stimulus. Our analysis further reveals that the enhanced adhesion stems from the increased fracture energy of the bulk hydrogel and the insignificant residual stress on the adhesive-tissue interface. This study presents a framework for designing stimuli-responsive hydrogel adhesives based on the modulation of bulk properties and sheds light on the development of smart adhesives with tunable mechanics.
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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 | 0.000 |
| 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 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".