Morphology and dynamic mechanical properties of styrene–butadiene rubber/silica/organoclay nanocomposites manufactured by a latex method
Bibliographic record
Abstract
Abstract In this study, the styrene–butadiene rubber (SBR)/ N , N ‐dimethyldodecylamine‐montmorillonite nanocomposite was prepared with a latex method by applying DDA to Na + ‐MMT as a modifier. The dispersion of silica and the dynamic viscoelastic properties of the SBR/silica (60 phr) compound were studied by replacing 7 phr of the silica with organoclay. By the analysis of transmission electron microscopy images and the Payne effect, the dispersion of silica in the SBR/silica (53 phr)/DDA‐MMT (7 phr) compound was further improved as compared to the SBR/silica (60 phr) compound that used only silica as a filler. The Payne effect curve of the SBR/silica/DDA‐MMT compound was close to the curve of the SBR/silica (53 phr) compound. This indicates that organically modified silicate did not form filler–filler networks with silica. Also, the SBR/DDA‐MMT compound filled with silica showed the highest values of T g and tan δ at 0°C. This result was attributed to the shift of the tan δ curve to the right because of the relatively higher degree of crosslink. Consequently, the SBR/silica/organoclay nanocomposite showed the best skid resistance due to the increase of T g , and the best rolling resistance due to the reduced filler–filler networks. High 100% and 300% modulus values were also achieved. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 teacher head, 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".