Development of self‐healing coatings based on urea‐formaldehyde/polyurethane microcapsules containing epoxy resin
Bibliographic record
Abstract
Abstract In this study, the synthesis of urea‐formaldehyde/polyurethane (UF/PU) microcapsules containing epoxy resin for self‐healing and anti‐corrosion coatings with good stability has been reported. Spherical microcapsules were prepared with a diameter of about 50–720 μm and a shell thickness of 0.6–0.7 μm via in situ polymerization in an oil‐in‐water emulsion using 2,4‐toluene diisocyanate‐based pre‐polymer along with the urea‐formaldehyde. Scanning electron microscopy (SEM) and optical microscopy (OM) were employed to evaluate the shape and morphology of the microcapsules. Fourier transform infrared (FTIR) spectroscopy showed the absence of free isocyanate groups within the microcapsule shell confirming the completion of shell formation reactions. OM illustrated that the microcapsules were stable over a period of 30‐days in toluene and xylene. Increasing microcapsule loading improved crack repairing and anti‐corrosion performance of the coating layer. Low‐carbon steel coupons coated with an epoxy resin containing 10 wt% microcapsules and scribed using a scalpel blade showed no visible sign of corrosion after up to 5 weeks of exposure in a standard salt spray test chamber.
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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) | 0.000 | 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 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".