E-Glass/Polypropylene Pultruded Nanocomposite: Manufacture, Characterisation, Thermal and Mechanical Properties
Bibliographic record
Abstract
The manufacture of continuous fibre-reinforced nanocomposites, E-glass reinforced in a polypropylene (PP) matrix with and without nanoclay, by pultrusion is discussed. Thermal and mechanical characterisation of nanocomposites has been performed and compared with traditional microcomposites. Also, the nanocomposites were characterised by Transmission Electron Microscopy (TEM) and Optical Micrography (OPM). Compressive strength of pultruded polypropylene nanocomposites was improved by improving the yield strength of the surrounding matrix in shear and reducing fibre misalignment in the composite through optimisation of manufacturing process variables. TGA and DSC results show that nanoclay improves thermal stability without any deviation in glass transition temperature and melt temperature. Initially, polypropylene and nanoclay were melt intercalated using a single-screw extruder and the pultruded nanocomposite was fabricated using extruded pre-impregnated (pre-preg) tapes. Compression tests were performed as mandated by ASTM guidelines. OPM was used to examine the failure surfaces. TEM revealed an intercalated morphology. Significant improvements were achieved in compressive strength and compressive modulus with relatively low nanoclay loadings. Mechanical tests were performed for baseline pultruded PP nanocomposite with 0 wt% nanoclay and modified pultruded PP nanocomposite with 3 wt% nanoclay. The tests showed significant improvements in compressive strength (~122%) and shear strength (~60%) in modified pultruded PP nanocomposites in comparison with baseline properties. Uni-axial tensile tests showed a minor increase in tensile strength (~3.4%). Multi-scale simulations of nanoclay/polymer interface behaviour are currently in progress in order to understand the strength enhancement mechanism.
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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) | 0.000 | 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 | 0.001 |
| 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".