Effects of extruder screw configurations on thermal properties of glass fiber‐reinforced polyamide 6 composites throughout the direct long‐fiber‐reinforced thermoplastics process
Bibliographic record
Abstract
The direct long‐fiber‐reinforced thermoplastics (D‐LFT) process is a series of processes involving two twin‐screw extruders, a conveyer, and a compression molding machine. The second twin‐screw extruder is designed for mixing continuous fibers with polymer melt and plays an important role in the D‐LFT process. This study investigates effects of the screw configurations of the second extruder on thermal properties of glass fiber‐reinforced polyamide 6 (PA6) composites throughout the D‐LFT process. Two screw configurations, which generate low and high shear stress in composite melt (named the conveying and mixing screws, respectively), were used in the second twin‐screw extruder. Samples were taken from four different locations along the D‐LFT process and characterized using triple detection gel permeation chromatography (GPC), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC). The results suggested that the molecular weight of the PA6 matrix increased in the later stages of the D‐LFT process (i.e., after the second extruder) by branching of PA6 molecules. In addition, the mixing screw decreased the molecular weight of the PA6 matrix more than the conveying screw. However, such a decrease in molecular weight had little influence on the thermal stability and crystallization behavior of the composites. POLYM. COMPOS., 40:3500–3509, 2019. © 2019 Society of Plastics Engineers
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".