Preparation and properties of epoxy nanocomposites. Part 2: The effect of dispersion and intercalation/exfoliation of organoclay on mechanical properties
Bibliographic record
Abstract
Abstract The effect of the dispersion and intercalation/exfoliation of organoclay on the mechanical properties of epoxy nanocomposites was studied. The epoxy resin was EPON828 and the hardener was Jeffamine D‐230. The organoclay Cloisite 30B was used. Nanocomposites were prepared by different mixing devices that can generate different shear forces, such as a mechanical stirrer, a microfluidizer, and a homogenizer. The results indicate that the modulus increases almost linearly with the clay loading and also is improved with the quality of microdispersion, although the latter plays a less important role. On the other hand, only good dispersion can improve the strength, while poor dispersion results in loss of strength. The strength levels off above 4 wt% organoclay loading. It can be concluded that finer and more uniform dispersion increases the clay surface area available for interaction with the matrix and reduces stress concentration in the large aggregates that initiate the failure under stress. It is also observed that the presence of C30B does not significantly affect the glass transition ( T g ) of the epoxy systems regardless of the level of clay dispersion and clay loading. Dynamic mechanic analysis (DMA) shows the positive effect of dispersion and intercalation/exfoliation on the storage modulus of epoxy nanocomposites (ENCs). POLYM. ENG. SCI., 2012. © 2011 Society of Plastics Engineers
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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 | 0.000 | 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 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".