The role of interface on the toughening and failure mechanisms of thermoplastic nanocomposites reinforced with nanofibrillated rubber
Bibliographic record
Abstract
a nanofiber-pair atomistic scheme, and the obtained results were subsequently incorporated into the pull-out and uniaxial test simulations. The results indicate that the compatibilizer grafting results in enhanced interfacial shear strength by introducing extra chemical interactions at the interface. In particular, it was found that the compatibilizer restricts the formation and coalescence of nanovoids, resulting in enhanced toughening effects. Together, we have shown that the presence of a small amount of well-dispersed rubber nanofibrillar network whose surfaces are grafted with maleic anhydride compatibilizer can dramatically increase the toughness and alter the failure mechanisms of the nanocomposites without any deterioration in the stiffness, which is also consistent with the recent experimental observations in our lab. The interfacial failure mechanism was also investigated by monitoring the changes in the atomic concentration profiles, mean square displacement and fractional free volume. The results obtained may serve as a promising alternative for the continuum-based modeling and analysis of interfaces.
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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) | 0.002 | 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".