Fractal structures of PA6/POE blend nanocomposites and their dynamic properties
Bibliographic record
Abstract
We investigate the effect of minor phase rheological properties and compatibilizer on the phase morphology and graphene 3D structure in polyamide-6 (PA6)/polyolefin elastomer (POE) blends. It is revealed that in blends containing low viscosity (LV) POE, graphene is better dispersed facilitating its localization at the interface. In the blend containing high viscosity (HV) POE with poor graphene dispersion, large graphene aggregates are observed inside the POE phase with less interfacial coverage. Interestingly, graphene induces a co-continuous morphology and electrical and rheological percolation in both systems, although at a lower graphene content for the LV system. The LV system exhibits a more interconnected morphology, while in the HV system we observe a compact fractal-like POE structure with a lower degree of interconnectivity. Our morphological observation suggests that co-continuous morphology in the LV system is dominated by sheet formation, while in the HV system it is dominated by coalescence between moderately elongated domains. Fractal analysis of the graphene 3D network (based on the rheological characterization) is correlated with the higher degree of connectivity of the graphene 3D structure in the LV system. The 2D fractal dimension of the POE phase (host phase for graphene) is in line with the fractal dimension of the graphene flocs, indicating that the graphene flocs influence the blend morphology. The addition of compatibilizer to the HV system did not result in improved electrical properties.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 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".