Butyl acrylate/methyl methacrylate latexes: adhesive properties
Bibliographic record
Abstract
Abstract In this study, butyl acrylate/methyl methacrylate (BA/MMA) latexes of bimodal molecular weight and particle size distribution were prepared in a multi‐step process by seeded conventional emulsion and seeded miniemulsion polymerization. For the conventional emulsion case, a BA/MMA batch copolymerization was conducted as a first step (seed generation) and was followed by a monomer addition step to ensure particle growth. In a third step, a BA/MMA pre‐emulsified mixture was added to generate a second particle population. For the miniemulsion case, a BA/MMA copolymerization was carried out as a first step (seed generation) and was followed by a monomer addition step. The addition of a BA/MMA miniemulsion served to generate a bimodal particle size and molecular weight distribution. The final latexes were coated onto a polyethylene terephthalate carrier, dried and their performance as pressure‐sensitive adhesives was evaluated using tack, peel and shear adhesion measurements. Structure‐property relationships between the adhesive properties and the weight‐average molecular weight and average particle size were examined. Even though the polymers obtained by miniemulsion showed better shear resistance, their shear resistance was low. There was no statistically significant difference in peel resistance of the polymers obtained by the two reactions. While a significant difference in tackiness between the two emulsion procedures was found when the adhesives were tested using the less sensitive, rolling ball test, no differences were found when they were tested using a loop tack test.
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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".