Polyamide 6–wheat straw composites: Effects of additives on physical and mechanical properties of the composite
Bibliographic record
Abstract
Abstract Polyamide 6 was modified with lithium chloride (LiCl) salt and N‐butyl benzenesulfonamide (N‐BBSA) plasticizer (additives). The modification was done in order to develop an environmentally friendly composite, composed of wheat straw (WS). A 15 wt% of ground WS was compounded with Polyamide 6 along with the additives. Addition of LiCl decreased the melting point of the matrix, allowing for a lower compounding temperature. However, a pseudo‐crosslinking formation upon addition of salt limited the polymer chain movement and restricted the processing temperature. LiCl addition increased the tensile and flexural modulus of the composite, but decreased the tensile and flexural strength. Decrease in the strength was found to be related to the increase in the residence time of material during extrusion causing severe WS thermal degradation. Addition of N‐BBSA eased the processing due to lubrication effect, however, when used in excess, lowered the flexural modulus and strength. Addition of WS to Polyamide 6 increased the modulus of the matrix. Matrix tensile modulus and flexural modulus were enhanced by 27%; however, a decrease in strength of the matrix was obtained. Addition of WS, LiCl, and plasticizer lowered the impact properties of Polyamide 6. It was concluded that combination of 2 wt% LiCl and of 2 wt% N‐BBSA gives the best mechanical properties. POLYM. COMPOS., 2012. © 2012 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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".