Unusual Rheological Behavior of Liquid Polybutadiene Rubber/Clay Nanocomposite Gels: The Role of Polymer−Clay Interaction, Clay Exfoliation, and Clay Orientation and Disorientation
Bibliographic record
Abstract
The rheological properties of liquid polybutadiene rubber/organo-clay nanocomposite gels were investigated by rheological experiments, focusing on the effects of clay exfoliation and orientation−disorientation as well as polymer−clay interaction and temperature. Both irreversible and reversible viscosity transitions were observed in the temperature range from 26 to 136 °C in steady shear experiments on as-prepared and exfoliated samples. These transitions depend strongly on the end groups, molecular weight of the liquid rubber, and the shear field. The irreversible transition is attributed to the exfoliation of the clay, and the reversible transition can be understood as a shear-induced orientation−disorientation transition of the clay sheets. Polymer−clay interaction is confirmed to be a key controlling factor of the orientation−disorientation transition, whereas the shear field plays a critical role to induce such a transition. To our knowledge, this is the first rheological observation of the in-situ exfoliation process and the shear-induced orientation−disorientation transition of layered silicate in polymer/organo-clay nanocomposites. A tentative model was suggested on the basis of the clay exfoliation and orientation−disorientation transition, and the model is used to explain the observed unique rheological behavior.
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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".