Thermal and Nanoindentation Behaviours of Layered Silicate Reinforced Recycled GF-12 Nanocomposites
Bibliographic record
Abstract
<p class="1Body">This work is an attempt to improve the thermal and nanoindentation behaviours of recycled Glass-Filled Polyamide-12 (GF-12) by adding layered Silicate (Nanoclay) as a reinforced filler. Differential Scanning Calorimetry (DSC) and Nanoindentation tests were conducted to study the effect of various loading levels (0-7 wt. %) of Nano-layered silicate on the thermal and nanohardness behaviours of GF-12 and its nanocomposites. Wide Angle X-ray Diffraction (WAXD) was employed to characterise the nanostructure of material and determine the intercalation/exfoliation for layered silicate in a GF-12 matrix. This study reveals that the layer silicate has a positive effect on the hardness results. Nanoindentation results showed remarkable improvement when layered silicate was added to recycled GF-12. The Glass transition (T<sub>g</sub>) and crystallization (T<sub>c</sub>) temperatures showed a slight improvement over the base polymer by the incorporation of layered silicate. Moreover, the enhancement of crystallization was obvious with the addition of clay loading, which functioned as a nucleating agent that could increase the rate of crystallization.</p>
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How this classification was reachedexpand
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 | 0.007 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".