Original synthesis of polyvinyl butyral with a green deep eutectic solvent and a weakly polyacrylic acid from polyvinyl alcohol and the impacts of the chains structures of polyvinyl alcohol
Bibliographic record
Abstract
Abstract In this work, an environmentally‐friendly deep eutectic solvent (DES) was employed as a catalyst to generate polyvinyl butyral (PVB) resins from polyvinyl alcohol (PVA) with a weakly acidic polymer (polyacrylic acid [PAA]) as an emulsifier. Finally, high viscosity PVB resins with molecular weight of 110,000–200,000 g · mol−1 and acetalization degree above 83% were successfully synthesized, which was found to satisfy the requirements for interlayer films between safety glass. Furthermore, it was well proved that the properties of PVB resins immensely depend on the molecular structures of the PVA. The molecular weight of the PVB, independent of alcoholic degrees of the PVA, indicated an upward trend with the increase of the molecular weight of the PVA. As for these four PVBs with high molecular weight, the Tg was sensitive to the content of hydroxyl and acetal groups rather than molecular weight, associated with the inter‐ or intra‐molecule hydrogen bond between OH. PVB‐1799 and PVB‐1797 had higher Ti and Tg than that of PVB‐1788 and PVB‐1795 because the former had low contents of vinyl acetate group (VAc) and alcohol hydroxyl group (VOH). The tensile strength of PVBs was all higher than 30 Mpa, and the elongation at break was about 300% due to their high molecular weights.
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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".