Factors Affecting Gloss and Color of Decorative Pressure Sensitive Adhesive Films During Thermomechanical Deformation
Bibliographic record
Abstract
Decorative polymer films are finding applications in processes that require forming at elevated temperatures and significant strain. In order to satisfy their function in these applications, the appearance of these films must remain unaltered or at least any changes must be predictable. This paper examines four different high gloss decorative films comprised of different materials in the layers of their construction. The films were uniaxially stretched up to failure (which was up to 75% strain) at isothermal conditions of 25, 40, or 75°C and then examined. Gloss (at 20°) was the most strongly altered parameter concerning the appearance of the films after thermomechanical deformation while color intensity was relatively unaffected. The change in gloss was higher for the two amorphous films compared to the two that exhibited crystallinity. The films were analyzed for their surface roughness using a white light interferometer, for their crystallinity by X‐ray diffraction and for their morphology by atomic force microscopy (AFM). Surface roughness increased with crystallinity for the two films that exhibited crystals but overall showed no correlation to the gloss measurements. Only evidence of altered domain morphology in the films as determined by AFM appeared to correlate with the changes in gloss reported. POLYM. ENG. SCI., 56:1357–1365, 2016. © 2016 Society of Plastics Engineers
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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".