Exploring the effect of lignin as a filler on the mechanical properties and anisotropic nature of Glass/Polypropylene LFTs manufactured via direct compounded compression moulding (LFT-D)
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Bibliographic record
Abstract
ABSTRACT Glass Long Fibre Thermoplastics (LFTs) are becoming increasingly popular as lightweight, high-performance recyclable materials. This trend has also led to greater interest in the use of biomaterials, such as bio-fillers like lignin, to help reduce the carbon footprint of these petroleum-based polymer composites. This study investigated the influence of lignin bio-filler on the mechanical properties of glass-reinforced polypropylene (glass/PP) LFTs. Three lignin weight percentages (0%, 14%, and 21%) were evaluated while maintaining 30% glass fibre content. Tensile and shear tests were conducted on samples from both charge and flow regions of compression-moulded plaques, considering 0°, +45°, -45° and 90° material directions. Fracture surface analysis was conducted by utilising a Scanning Electron Microscope (SEM) to understand the failure mechanisms and structural behaviour under mechanical stress. The results indicated a decrease of up to 36% in tensile strength with increasing lignin content in the 0° direction, which was particularly significant at a lignin content of 21%. The 0° direction consistently exhibited higher tensile strength in the range of 70 MPa to 100 MPa than the 90° material directions followed by +45°, -45°. Shear strength remained largely unaffected for 14% lignin content, with an approximately 10% drop for 21% lignin content samples. SEM analysis revealed distinct failure mechanisms across the different material directions (0°, +45°, -45°, and 90°). This study provides essential material characterisation, enabling more accurate numerical and analytical modelling of these materials with a lightweight, low-cost filler.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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