Thermoplastic vulcanizate nanocomposites based on polyethylene/reclaimed rubber: A correlation between carbon nanotube dispersion state and electrical percolation threshold
Bibliographic record
Abstract
ABSTRACT A three‐step melt blending process was utilized to produce linear low‐density polyethylene (LLDPE)/reclaimed rubber (RR)/carbon nanotube (CNT) nanocomposites in the presence of maleic anhydride grafted polyethylene as a compatibilizer. The effect of LLDPE/RR ratio and CNT content on the morphological, thermal, mechanical, and rheological behavior of these dynamically vulcanized LLDPE/RR nanocomposites were investigated. The morphological study showed that the RR was dispersed in the LLDPE matrix, and CNT addition led to an improved morphology as smaller RR sizes inside LLDPE were observed. The mechanical results revealed that increasing the RR content decreased the hardness, modulus of elasticity, and elongation at break while CNT improved the tensile properties and other mechanical properties. The differential scanning calorimeter analysis showed that the CNT improved the LLDPE crystallization by acting as nucleation agents. Dynamic mechanical analysis showed higher storage modulus and lower loss factor as compared to the neat blend due to mobility restrictions of the polymer chains induced by the presence of CNT. For the conditions studied, the electrical percolation threshold was found to occur at a very low CNT concentration (about 1 wt %) compared to the literature because of the specific structure produced leading to CNT residing in the LLDPE matrix and at the interface between both polymeric phases. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136 , 47795.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".