Effect of Hyperbranched Poly(butyl methacrylate) on Polymer Diffusion in Poly(butyl acrylate-<i>co</i>-methyl methacrylate) Latex Films
Bibliographic record
Abstract
Latex paint formulations normally contain volatile organic compounds (VOCs) to lower the modulus of the latex polymer and to enhance the rate of its diffusion in latex films. Here we show that hyperbranched poly(butyl methacrylate) (HB-PBMA) not only is miscible with poly(butyl acrylate- co -methyl methacrylate) [P(BA-MMA)] copolymers over a range of BA/MMA compositions but also acts as a diffusion promoter. At similar volume fractions (≤0.1), it is as effective at promoting P(BA-MMA) polymer diffusion as 2,2,4-trimethyl-1,3-pentanediol monoisobutyrate (Texanol, TPM), a classic coalescing aid. Unlike TPM, it does not cause a large decrease in the glass transition temperature of the polymer, and it has relatively little effect on the modulus of the polymer. Small molecule additives commonly lead to a reduction of useful mechanical properties of a polymer, such as tensile strength and toughness. Tensile tests show that P(BA-MMA) latex films containing HB-PBMA have better mechanical properties than the corresponding films containing TPM. Thus, this hyperbranched polymer represents a new kind of nonvolatile additive for latex that can promote the rate of polymer diffusion in latex films without significantly disrupting the desirable mechanical properties of the film.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 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".