A multi-criteria decision analysis on injection moulding of polymeric microcellular nanocomposite foams containing multi-walled carbon nanotubes
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Bibliographic record
Abstract
In this paper, polyamide 6 (PA6)/multi-walled carbon nanotubes (MWCNTs) nanocomposites were foamed using an injection moulding machine. Morphological properties were characterised using X-ray diffraction and scanning electron microscopy (SEM). The samples were produced based on the Taguchi L16 orthogonal array in different processing conditions and variant content of MWCNT. Specific tensile strength (STS) and Rockwell hardness, mean cell size and density were investigated and considered as different criteria for selecting the best sample. Criteria weighting and alternative ranking were performed using analytical hierarchy process and two methods of technique for order of preference by similarity to ideal solution and multi-objective optimisation on the basis of ratio analysis, respectively. The results of the X-ray diffraction test showed 0.85, 0.94 and 1 Å increase in the distance between MWCNT’s walls of nanocomposites containing 0.5, 1 and 1.5 wt-% of MWCNTs, respectively, and SEM test results indicated that an appropriate microcellular structure was achieved. Mechanical properties results show that STS and Rockwell hardness of samples were improved about 147 and 17% by adding 1 and 1.5 wt-% of MWCNTs, respectively. Also, the results of multi-criteria decision-making methods revealed that the alternative number 12 (A-12) is the best alternative. The processing conditions of this sample were: 1 wt-% of MWCNT, holding pressure (HP) time of 4 s and HP of 100 MPa.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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