Injection molded self‐hybrid composites based on polypropylene and natural fibers
Bibliographic record
Abstract
Self‐hybrid thermoplastic composites (combination of two fiber sizes) were obtained by injection molding using pine or agave fibers with polypropylene (PP). The effect of self‐hybridization was determined through mechanical properties and water absorption for different total fiber contents between 10 and 30% wt. The results showed that impact strength (30% of fiber) and tensile modulus (20% of fiber) were improved by self‐hybridization compared with composites formulated with only one fiber size. Flexural properties were not improved by self‐hybridization. On the other hand, the combination of two fiber sizes had no effect on the water absorption behavior of these composites. Overall, the total fiber content was found to be an important parameter with 20% being the optimum condition where self‐hybridization provides the best mechanical properties. POLYM. COMPOS., 35:1798–1806, 2014. © 2013 Society of Plastics Engineers
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".