Sustainable Fire-Resistant Materials: Recycled Polyethylene Composites with Non-Halogenated Intumescent Flame Retardants for Construction Applications
Why this work is in the frame
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Bibliographic record
Abstract
This study explores the development of sustainable fire-resistant composites using a blend of recycled linear low-density polyethylene (rLLDPE) and low-density polyethylene (rLDPE) for construction applications. The incorporation of non-halogenated intumescent flame retardants (IFRs), specifically ammonium polyphosphate (APP) and melamine polyphosphate (MPP), was shown to enhance the flame retardance, thermal stability, and mechanical performance of these recycled polymer blends. IFRs were introduced at 5 wt.% and 10 wt.% concentrations, and their effects were evaluated using limiting oxygen index (LOI) testing and thermogravimetric analysis (TGA). Results showed that 10 wt.% APP and a combination of 5 wt.% APP with 5 wt.% MPP increased LOI values from 18.5% (neat polymer blend) to 21.2% and 22.4%, respectively, demonstrating improved fire resistance. Enhanced char formation, facilitated by IFRs, contributes to superior thermal stability and fire protection. TGA results confirmed higher char yields, with the rLLDPE/rLDPE/MPP5/APP5 composition exhibiting the highest residue (3.00%), indicating a synergistic effect between APP and MPP. Rheological and mechanical analysis showed that APP had more impact on viscoelastic behavior, while the combination of IFRs provided balanced mechanical properties despite a slight reduction in tensile strength. This research highlights the potential of recycled polyethylene composites in promoting circular economy principles by developing sustainable, fire-resistant materials for the construction industry, reducing plastic waste, and enhancing the safety of recycled polymer-based applications.
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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 | 0.001 | 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 | 0.001 | 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) | 0.000 | 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