Mechanical properties of carbon black‐filled polypropylene/polystyrene blends containing styrene‐butadiene‐styrene copolymer
Bibliographic record
Abstract
Abstract Mechanical properties and morphology of carbon black (CB)‐filled polypropylene/polystyrene (PP/PS) blends with and without styrene‐butadiene‐styrene (SBS) tri‐block copolymer were studied as a function of PP/PS volume ratio and CB content. Blends were prepared by melt mixing in a batch mixer followed by compression molding. Incompatibility of the PP/PS blends was found to negatively influence the blends' tensile properties. Addition of 5 vol% SBS to the CB‐filled PP/PS blends was found to compatibilize the blends by reducing the interfacial tension and enhancing the interfacial adhesion. In general, SBS addition enhanced the yield stress of the co‐continuous CB‐filled PP/PS blends, reduced the Young's modulus and enhanced the elongation at yield for all blends studied. For the (70/30) PP/PS blends with and without SBS, yield stress of the blends filled with up to 3 vol% CB is close to that of the unfilled (70/30) PP/PS blends. Increasing CB loading to 5 vol% considerably increased the yield stress for the blends with and without SBS. A gradual increase in Young's modulus was reported with increasing CB content in the (70/30) PP/PS blends with and without SBS. Increasing CB loading up to 5 vol% did not influence the elongation at yield of the (70/30) PP/PS blend without SBS. POLYM. ENG. SCI., 2009. © 2009 Society of Plastics Engineers
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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 | 0.000 |
| 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".