Adhesion and Surface Interactions of a Self‐Healing Polymer with Multiple Hydrogen‐Bonding Groups
Bibliographic record
Abstract
The surface properties and self‐adhesion mechanism of self‐healing poly(butyl acrylate) (PBA) copolymers containing comonomers with 2‐ureido‐4[1 H ]‐pyrimidinone quadruple hydrogen bonding groups (UPy) are investigated using a surface forces apparatus (SFA) coupled with a top‐view optical microscope. The surface energies of PBA–UPy4.0 and PBA–UPy7.2 (with mole percentages of UPy 4.0% and 7.2%, respectively) are estimated to be 45–56 mJ m −2 under dry condition by contact angle measurements using a three probe liquid method and also by contact and adhesion mechanics tests, as compared to the reported literature value of 31–34 mJ m −2 for PBA, an increase that is attributed to the strong UPy–UPy H‐bonding interactions. The adhesion strengths of PBA–UPy polymers depend on the UPy content, contact time, temperature and humidity level. Fractured PBA–UPy films can fully recover their self‐adhesion strength to 40, 81, and 100% in 10 s, 3 h, and 50 h, respectively, under almost zero external load. The fracture patterns (i.e., viscous fingers and highly “self‐organized” parallel stripe patterns) have implications for fabricating patterned surfaces in materials science and nanotechnology. These results provide new insights into the fundamental understanding of adhesive mechanisms of multiple hydrogen‐bonding polymers and development of novel self‐healing and stimuli‐responsive 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".