Development of a processing and properties map of carbon nanotube-reinforced thermoplastic fibres
Bibliographic record
Abstract
The main objective of this research is to develop a processing map to determine the optimal nanotube content leading to the maximum elastic modulus according to the allowable viscosity limit in melt spinning. In this work, multi-walled carbon nanotubes (MWNT) and polyamide 12 (Rilsan® PA 12) were studied. The characterization of PA 12 with MWNT contents of 0 wt%, 0.1 wt%, 0.5 wt%, 1.0 wt%, 2.0 wt% and 5.0 wt% was performed through differential calorimetry (DSC) and thermo-gravimetric analysis (TGA). Scanning electron microscopy (SEM) was used to assess the dispersion state of the nanotubes and relate those observations to the characterization results. The shear viscosity was investigated to identify optimal values for the production of fibres by melt spinning. MWNT contents below 5.0 wt% were selected to produce fibres according to the preliminary viscosity measurements, but further investigation of elongational and capillary viscosity will be needed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".