The effects of nanoclay on the extrusion foaming of wood fiber/polyethylene nanocomposites
Bibliographic record
Abstract
Abstract This article presents the foaming behaviors of wood fiber/high density polyethylene (HDPE) composites with small amounts of nanoclay. Melt compounding is used to prepare two types of clay‐filled wood fiber composites: intercalated and exfoliated clay composites. Their respective morphologies are determined using wide‐angle X‐ray diffraction (XRD) and transmission electron microscopy (TEM). We subsequently conduct an extrusion foaming experiment of the composites using N2 as the blowing agent. Varying the wood fiber content, as well as the processing parameters, such as temperature and pressure, the effects of different amounts of clay and the degree of exfoliation on the final cell morphology and the foam density of the wood fiber/HDPE/clay nanocomposite foams are studied. The results suggested that the addition of nanoclay improved the cell morphology of the wood fiber/HDPE composite foams as its content and degree of dispersion increased. POLYM. ENG. SCI., 2011. © 2011 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) | 0.000 | 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".