Ultra-Low Percolation Threshold Induced by Thermal Treatments in Co-Continuous Blend-Based PP/PS/MWCNTs Nanocomposites
Bibliographic record
Abstract
The effect of the crystallization of polypropylene (PP) forming an immiscible polymer blend with polystyrene (PS) containing conductive multi-wall carbon nanotubes (MWCNTs) on its electrical conductivity and electrical percolation threshold (PT) was investigated in this work. PP/PS/MWCNTs composites with a co-continuous morphology and a concentration of MWCNTs ranging from 0 to 2 wt.% were obtained. The PT was greatly reduced by a two-step approach. First, a 50% reduction in the PT was achieved by using the effect of double percolation in the blend system compared to PP/MWCNTs. Second, with the additional thermal treatments, referred to as slow-cooling treatment (with the cooling rate 0.5 °C/min), and isothermal treatment (at 135 °C for 15 min), ultra-low PT values were achieved for the PP/PS/MWCNTs system. A 0.06 wt.% of MWCNTs was attained upon the use of the slow-cooling treatment and 0.08 wt.% of MWCNTs upon the isothermal treatment. This reduction is attributed to PP crystals' volume exclusion, with no alteration in the blend morphology.
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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) | 0.001 | 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".