Butyl Acrylate/Vinyl Acetate Emulsion‐Based Pressure‐Sensitive Adhesives: Empirical Modelling of Final Properties
Bibliographic record
Abstract
Abstract The influence of the amounts of acrylic acid, chain transfer agent and anionic stabilizer on polymer microstructural properties and final adhesive performance of BA/VAc emulsion‐based PSAs on stainless‐steel and high‐density polyethylene substrates was investigated using a Box‐Behnken experimental design for 15 runs. The resulting data were empirically modelled. For each final adhesive property (i.e., loop tack, shear and peel strength), different models were found to fit the data. Similar models for loop tack and peel strength were found to be adequate for different PSA thicknesses on the same substrate. AA and SDS had significant effects on loop tack as did the AA‐SDS and CTA‐SDS two‐factor interactions. Quadratic peel strength models were found to adequately describe the data for SS substrate cases with a noticeable absence of any interaction parameters. The shear strength models were similar regardless of the substrate or thickness of the adhesive (e.g. in all models, AA and CTA, as well as their second‐order interactions, were the significant factors).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".