Mechanical and thermal properties of polyethylene/carbon nanofiber composites produced by rotational molding
Bibliographic record
Abstract
Abstract Nanocomposites based on carbon nanofibers (CNFs) and linear medium density polyethylene (LMDPE) were prepared by rotational molding. In particular, a simple dry‐blending process was used to add different CNF contents (0, 0.01, 0.1, and 1.0 wt%). To improve the fiber‐matrix adhesion, the CNF were treated by an oxygen cold plasma and the level of surface modification was analyzed by differential scanning calorimetry (DSC) and X‐ray photoelectron spectroscopy (XPS). From the samples produced a complete set of morphological, mechanical, rheological, and thermal characterization was performed. By following the internal air temperature while rotomolding, it was possible to detect the LMDPE melting and crystallization temperature and the values were confirmed by DSC. On the other hand, the XPS results show that the plasma treatment increased the CNF oxygen content and possibly the surface roughness. In general, the mechanical properties of the nanocomposites were improved by the addition of low CNF content: impact strength (30%), tensile modulus (20%), tensile strength (8%), elongation at break (35%), and toughness (70%).
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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 | 0.000 |
| 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".