Influence of ammonium polyphosphate‐modified polypropylene on flammability characteristics of polypropylene keratin and chitosan sustainable composites
Bibliographic record
Abstract
Abstract The combination of keratin fibers (KF), obtained from poultry feathers, with chitosan (Ch) are employed in polypropylene (PP) composites to enhance the flame‐retardant (FR) properties. The combined effect of each additive and the use of functionalized PP with ammonium polyphosphate (PP‐gAPP) as a compatibilizer, compared with PP‐gMA, on composite FR properties was analyzed. This compatibilizer was prepared by melt reaction of maleic anhydride grafted PP (PP‐gMA) with ammonium polyphosphate (APP). The grafting of APP was characterized by FTIR, XRD, and NMR. PP/KF/Ch composites using PP‐gAPP as compatibilizer were characterized by TGA, mechanical properties, and fire‐retardant tests such as UL‐94 (HB), limiting oxygen index (LOI), and cone calorimeter evaluations. These tests demonstrated the enhancement in fire‐retardant characteristics obtained by using PP‐gAPP as a compatibilizer agent compared with PP‐gMA. The combination of the additives (KF and Ch) with PP‐gAPP as compatibilizer in PP, increases the modulus and tensile strength and significantly improves the LOI and reduces the peak heat release rate during cone calorimetry tests with better thermal stability and a noticeable reduction in horizontal burning rate. Most important, the results indicated that the combination of these additives produce similar flame retardancy than a reference sample with high magnesium hydroxide loading. These composites are a promising way to meet the growing demand for high‐performance materials with FR characteristics using bio‐fire retardant additives such as KF and Ch, in sustainable and environmentally friendly composites.
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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 | 0.001 | 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 | 0.000 | 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 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".