Carbon Fiber Composites of Pure Polypropylene and Maleated Polypropylene Blends Obtained from Injection and Compression Moulding
Bibliographic record
Abstract
A comparative study of the mechanical performance of PP and PP/PP-g-MAH blends reinforced with carbon fibre (CF) obtained by two different moulding techniques is presented. Three filler contents were used for fabricating the composites: 1, 3, and 5 pph (parts per hundred). The crystallisation behaviour of the composites was studied by differential scanning calorimetry. Morphological and structural features of these samples were observed by atomic field microscopy and Fourier-transform infrared spectroscopy, respectively. Mechanical properties of the injection and compression moulded composites were evaluated by means of tensile and impact resistance tests. The fracture surface of the impacted samples was observed by scanning electron microscopy. The processing method had a noticeable effect on the results obtained in these tests. Young’s modulus was enhanced up to 147% when adding 5 pph CF to a PP matrix when processed by compression moulding. Addition of PP-g-MAH and CF had a favourable effect on the tensile and impact strength properties in most samples; these composites showed improved performance as the filler content was increased.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".