Self‐healing polyacrylate coatings with dynamic H‐bonds between urea groups
Bibliographic record
Abstract
Abstract Adding self‐healing properties to coatings is a promising way to increase their lifetime. Despite an increasing popularity, lots of self‐healing polymers are not suited for commercial coatings because they exhibit poor mechanical properties or require expensive products or high healing temperature (> 100°C). One way to obtain self‐healing abilities with good mechanical properties is by using dynamic H‐bonds as they also limit the healing temperature. To do so, urea groups are used since they are well‐known for their bonding capacity and can be readily synthesized. In this study, several methacrylate monomers containing urea groups in their side‐chain were synthesized from easily accessible amines and isocyanates in a one‐step, high‐yield synthesis. They were afterwards used in a copolymer containing methyl methacrylate and butyl acrylate monomers. The self‐healing properties of the resulting coatings were evaluated with gloss recovery and optical microscopy and the presence of H‐bonds in the most promising polymer was investigated with FTIR. The mechanical properties of the coatings as a function of time were checked by nanoindentation creep test. We were able to obtain an affordable, easily prepared polymer that suits the requirements for protective coating applications and shows a complete healing after heating at 75°C for 1 h.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".