Rheological, electrical, and dynamic thermomechanical properties: Comparison between multiwall and double-wall carbon nanotubes in polylactide and polyamide 11
Bibliographic record
Abstract
In this study, multiwall carbon nanotubes (MWCNTs) and double-wall carbon nanotubes (DWCNTs) have been dispersed in polylactide (PLA) and polyamide 11 (PA11) using an internal mixer. Rheological characterization confirmed the formation of carbon nanotube (CNT) networks in PLA and PA11 attributed to well-dispersed CNTs in the respective matrices. A lower rheological percolation threshold of PLA/MWCNT nanocomposites (less than 0.5 wt. %) compared to PA11/MWCNT nanocomposites (about 2 wt. %) confirmed the greater affinity of CNTs for PLA. The threshold for DWCNTs was below 0.5 wt. % in PLA and between 0.5 and 1 wt. % in PA11. PLA-based nanocomposites also showed higher electrical conductivity values compared to PA11-based nanocomposites. Nanocomposites containing DWCNTs exhibited higher electrical conductivities compared to those containing MWCNTs due to the higher aspect ratio of DWCNTs. Dynamic mechanical thermal analysis showed enhanced storage modulus values and reduced damping behavior with increasing content of CNTs for both polymers.
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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) | 0.000 | 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 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".