Synthesis of poly(arylene disulfide)–vermiculite nanocomposites via <i>in situ</i> ring‐opening polymerization of macrocyclic oligomers
Bibliographic record
Abstract
Abstract Exfoliated poly(4, 4′‐oxybis(benzene)disulfide)/vermiculite (POBDS/VMT) nanocomposites were successfully synthesized via in situ melt intercalation of cyclo(4, 4′‐oxybis(benzene)disulfide) oligomers (COBDS) into octadecylammonium‐exchanged VMT (organo‐VMT). The POBDS/VMT nanocomposites were melt fabricated in a two‐step process. First, the COBDS/VMT nanocomposite precursor was fabricated by melt delaminating organo‐VMT with COBDS at a temperature slightly higher than its melting point. Subsequently, exfoliated POBDS‐VMT nanocomposites can be prepared in situ via instant melt ring‐opening polymerization of the COBDS‐VMT nanocomposite precursor. The nanoscale dispersion of VMT layers within POBDS polymer was confirmed by X‐ray diffraction, scanning electron microscopy and transmission electron microscopy. High molecular weight POBDS polymer was formed in a few minutes at the same time as the nanocomposite formation. The results of dynamic mechanical analysis showed that the storage modulus and glass transition temperature of the nanocomposites are much higher than those of the POBDS matrix, even with a very small amount of VMT addition. This methodology provides a potential approach to synthesize high‐performance polymer/clay nanocomposites. Copyright © 2004 Society of Chemical Industry
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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".