Evaluating the Performance of a Semiaromatic/Aliphatic Polyamide Blend: The Case for Polyphthalamide (PPA) and Polyamide 4,10 (PA410)
Bibliographic record
Abstract
This paper studies the structure-property-processing relationship of polyphthalamide (PPA) PPA/polyamide 4,10 (PA410) blends, via co-relating their thermal-mechanical properties with their morphology, crystallization, and viscoelastic properties. When compared to neat PPA, the blends show improved processability with a lower processing temperature (20 °C lower than neat PPA) along with a higher modulus/strength and heat deflection temperature (HDT). The maximum tensile modulus is that of the 25PPA/75PA410 blend, ~3 GPa, 25% higher than neat PPA (~2.4 GPa). 25PPA/75PA410 also exhibits the highest HDT (136 °C) among all the blends, being 11% more than PPA (122 °C). The increase in the thermo-mechanical properties of the blends is explained by the partial miscibility between the two polymers. The blends improve the processing performance of PPA and broaden its applicability.
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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 | 0.001 |
| 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".