Effect of dynamic vulcanization on the microstructure and performance of polyethylene terephthalate/elastomer blends
Bibliographic record
Abstract
Abstract Blends of polyethylene terephthalate (PET) and ethylene‐ethyl acrylate‐maleic anhydride terpolymer (E‐EA‐MAH) were dynamically crosslinked in a one‐step extrusion process. An amine‐terminated glycol reacting with MAH moieties was used as the crosslinking agent. The effect of blend composition and dynamic crosslinking on the microstructure and mechanical properties were investigated. Blend ratios ranging from 80:20 to 20:80 PET/E‐EA‐MAH were studied. The region of phase inversion was located for uncrosslinked and dynamically crosslinked blends. The rheological characterization was also carried out for these blends in comparison with the neat materials. After dynamic crosslinking, the phase inversion is shifted from the 30–40% range to the 70–80% range of elastomer content. This shift is induced by the increase of viscosity and elasticity of the network formed. Dynamically crosslinked blends show significant improvements in impact strength but also exhibit a decrease in elongation at break.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".