Effect of intercalating agents on clay dispersion and thermal properties in polyethylene/montmorillonite nanocomposites
Bibliographic record
Abstract
Abstract Alkyl pyridinium, 1‐vinyl alkyl imidazolium, 1,3‐dialkyl imidazolium, and tetraalkyl phosphonium bromides were successfully used as intercalants for the preparation of highly thermally stable organophilic montmorillonites. Nanocomposites of linear low density polyethylene (LLDPE) and linear low density polyethylene grafted with maleic anhydride (LLDPE/LLDPE‐g‐MAH) were prepared from those organoclays. The micro‐ and nano‐dispersions were analyzed through X‐ray diffraction (XRD), scanning electron microscopy (SEM), and transmission electron microscopy (TEM): intercalation and/or partial exfoliation were found to occur only for formulations based on organoclays having an initial basal distance higher than 20 Å, suggesting the existence of a critical interfoliar distance for the delamination of silicate layers in a noninteracting polymer matrix. The properties of the nanocomposites were analyzed through differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), and oscillatory rheometry. The dynamic crystallization of LLDPE was not significantly affected by the presence of clay. TGA in oxidative atmosphere proved to be very sensitive to the dispersion state of the organoclay: the thermal stability was drastically enhanced for intercalated and partially exfoliated formulations. However, the inherent thermal stability of the organoclay did not appear to influence significantly the overall thermal stability of the composite in the range of temperatures investigated (160–230°C). POLYM. ENG. SCI., 2008. © 2008 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".