Flame retarding effects of nanoclay on wood–fiber composites
Bibliographic record
Abstract
Abstract This research article focuses on investigating the effects of nanoclay particles on the flame retarding characteristics of wood–fiber/plastic composites (WPC) using ASTM D635. The processing aspects of nanocomposites with WPC are presented. The processing techniques for controlling the degree of exfoliation and the cost aspect are also described. It turns out that the coupling agent used for wood–fibers is also effective for the exfoliation of clay, and therefore, no additional cost is required. This research indicates that the structure of nanocomposites (i.e., the degree of exfoliation) and the clay content used have a large impact on the flame retardancy of WPC. The flame retardancy is investigated as a function of these parameters. Based on this, a cost‐effective way to improve flame retardancy of WPC is presented. POLYM. ENG. SCI., 47:308–313, 2007. © 2007 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".