Melt Mixing of Polycarbonate with Multi‐Walled Carbon Nanotubes in Miniature Mixers
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Bibliographic record
Abstract
Abstract Summary: MWNT mixtures with PC were prepared in three different miniature mixers at 265 °C and 50 rpm for 6 min by the master batch dilution method. One mixer is a 4.5 cm 3 DACA microcompounder (DACA Instruments) consisting of two conical co‐rotating screws with a bypass, allowing the material to circulate for defined periods. The other two miniature mixers are custom‐built in our lab: the 2.2 cm 3 APAM and the 3 cm 3 MBM. The volume resistivity for the nanocomposites obtained from the APAM and the MBM showed a similar trend for different MWNT compositions. The electrical percolation concentration for the nanocomposites prepared in the APAM and the MBM is between 0.50 wt.‐% (or 0.34 vol.‐%) and 0.75 wt.‐% (or 0.52 vol.‐%) MWNT, and it is between 0.75 wt.‐% (or 0.52 vol.‐%) and 1.00 wt.‐% (or 0.69 vol.‐%) for the DACA microcompounder. Rheological characterization indicates that the microstructure of PC/MWNT composites prepared from the miniature mixers changes at a concentration of 0.38 wt.‐% for the APAM and the MBM and 0.50 wt.‐% for the DACA where an interconnected network is formed. TEM micrographs show that there are some small aggregates in the nanocomposites obtained from the APAM, fewer aggregates from the MBM, and least from the DACA. AFM analysis suggests that the length of nanotubes is reduced from 0.57 µm to 0.38–0.42 µm after they were melt mixed in the three mixers. Effect of MWNT content on volume resistivity of PC/MWNT obtained from different microcompounders. magnified image Effect of MWNT content on volume resistivity of PC/MWNT obtained from different microcompounders.
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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) | 0.000 | 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 it