Evaluation of Polyester Resin as a New Compatibilizer for SBR/PVC Blends
Bibliographic record
Abstract
Abstract A polyester (PE) based on the glycolyzed products of PET was prepared and added in different concentrations to a series of SBR/PVC blends. The addition of the polyester showed that all properties of SBR/PVC blends were improved by incorporation of PE. Highest mechanical strength values were obtained at a polyester concentration of 7.5 phr. Thermal analysis as well as dynamic mechanical properties of SBR/PVC blends after the addition of 7.5 and 10 phr polyester indicated one single glass transition temperature. The dielectric losses (ϵ") were analyzed in the frequency domains in the two terms of Fröhlich related to the Maxwell Wagner effect and the orientation of the aggregates caused by the movement of the main chain. The permittivity (ϵ') values were found to increase by increasing the polyester content. This increase was followed by a decrease in the ϵ" up to a 7.5 phr polyester content after which no pronounced change was noticed.
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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 | 0.001 |
| 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 | 0.000 |
| 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".