Mechanical, thermal, and rheological properties of polypropylene hybrid composites based clay and graphite
Bibliographic record
Abstract
Polypropylene hybrid composites based on a mixture of graphite and clay were compounded by twin-screw extrusion and injection molded. In particular, the effect of reinforcement content and ratio of each particle was studied via morphological, mechanical, rheological, and thermal properties. The properties were evaluated in both solid and melt state to determine the mechanical performance of these materials. The results showed that these composites have excellent mechanical properties when compared to the neat polymer matrix. For example, the tensile moduli are 1607 and 1445 MPa for 30 wt% of clay and graphite respectively, while a 10:10 ratio of clay/graphite produced a value of 1500 MPa. Morphological analyses showed good adhesion/dispersion of both particles in the matrix, which was confirmed by good tensile strength results. Also, thermal stability was improved by adding clay and graphite particles, the results showing between 40℃ and 50℃ increased at 20 wt% content. Finally, a combination of graphite and clay is shown to produce hybrid composites with improved performances.
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".