Preparation and thermal and thermo‐oxidative stability of vinylidene chloride‐<i>co</i>‐vinyl chloride copolymer/synthetic hectorite nanocomposites
Bibliographic record
Abstract
Abstract Poly(vinylidene chloride‐co‐vinylchloride)/organically modified hectorite (VDC‐VC/SPN) nanocomposites were prepared by melt blending VDC‐VC copolymer with SPN in the presence of dioctyl phthalate, which acted as a plasticizer. As a result, the exfoliated structure was found in the VDC‐VC/SPN nanocomposites. In nitrogen atmosphere, VDC‐VC/SPN nanocomposites exhibited a single‐step thermal degradation. The thermal stability of VDC‐VC/SPN nanocomposites is significantly influenced by the SPN, which was modified with long alkyl ternary ammonium salt. In air atmosphere, VDC‐VC/SPN nanocomposites revealed a two‐step thermo‐oxidative degradation behavior. At the first degradation stage, the weight loss pattern is similar to that of VDC‐VC composites in nitrogen, in which the thermo‐oxidative stability of VDC‐VC/SPN nanocomposites is affected by the ternary ammonium salt and oxygen rather than its morphology. At the second degradation stage, both the enhanced thermo‐oxidative stability and the flame‐retardation ability of VDC‐VC composites are strongly and closely related to the morphology of nanocomposites. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci ,2009
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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) | 0.000 | 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".