Comparison of two encapsulation systems of UV stabilizers on the UV protection efficiency of wood clear coats
Bibliographic record
Abstract
Abstract One of the major issues in the wood industry is the durability of clear coatings. The addition of organic ultraviolet absorbers (UVAs) improves coating resistance by the absorption and conversion of UV radiation into harmless heat. Organic UVAs are, however, easily degraded by free radicals produced by photodegradation inside the polymer matrix and are prone to migration in the coating. In this study, commercial UVAs and hindered amine light stabilizers (HALS) entrapped into poly(methyl methacrylate) (PMMA) microspheres and CaCO3 templates coated with UV-responsive polymers were added into clear acrylic water-based coating formulation. Artificial accelerated weathering experiments were performed on each formulation. Raman spectroscopy mapping was performed to visualize the concentration and distribution of UVAs and HALS. This study also presents a comparison of the mechanical properties of coatings obtained by dynamic mechanical analysis. Results showed that coating mechanical properties were improved when using encapsulated UVAs and HALS inside PMMA microspheres. The color change of the wood and coating system was minimized and the production of photo-oxidation compounds in the binder was also limited.
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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".