Properties of blends of amorphous and semicrystalline <scp>PLAs</scp> containing multiwalled carbon nanotubes
Bibliographic record
Abstract
Abstract Blend nanocomposites of amorphous polylactide (aPLA) and semicrystalline PLA (scPLA)‐multiwalled carbon nanotubes (MWCNTs) were prepared by a twin‐screw extruder below the melting temperature of the scPLA. The maximum weight percent of MWCNTs in the blends was 0.9 wt.%. The extrudates were either pelletized immediately or after drawing at a drawing ratio of about 10. According to small amplitude oscillatory shear rheological analysis, the rheological properties of the aPLA/scPLA (85/15 wt.%) drawn sample were significantly increased compared to the undrawn samples. With the presence of MWCNTs, more crystallites could develop in the scPLA, and the electrical conductivity of the aPLA/scPLA nanocomposites was reduced due to the encapsulation of MWCNTs within the crystallites of scPLA. Increasing the temperature during compression moulding to 190°C, which is above the melting temperature of the scPLA, effectively removed this obstacle and the electrical conductivity was increased by a factor of up to 10 6 compared to the samples moulded at 150°C.
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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) | 0.001 | 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 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".