Synergistic Enhancement of Flame Retardancy Behavior of Glass-Fiber Reinforced Polylactide Composites through Using Phosphorus-Based Flame Retardants and Chain Modifiers
Bibliographic record
Abstract
Flame retardancy properties of neat PLA can be improved with different phosphorus-based flame retardants (FRs), however, developing flame retardant PLA-based engineering composites with maintained mechanical performance is still a challenge. This study proposes symbiosis approaches to enhance the flame retardancy behavior of polylactide (PLA) composites with 20 wt% short glass fibers (GF). This was first implemented by exploring the effects of various phosphorus-based FRs up to 5 wt% in neat PLA samples. Among the used phosphorus-based FRs, the use of only 3 wt% of diphosphoric acid-based FR (P/N), melamine coated ammonium polyphosphate (APPcoated), and APP with melamine synergist (APP/Mel) resulted in achieving the V0 value in a vertical burning test in the neat PLA samples. In addition to their superior efficiency in improving the flame retardancy of neat PLA, P/N had the least negative effect on the final mechanical performance of PLA samples. When incorporated in PLA composites with 20 wt% GF, however, even with the use of 30 wt% P/N, the V0 value could not be obtained due to the candlewick effect. To resolve this issue, the synergistic effect of P/N and aromatic polycarbodiimide (PCDI) cross-linker or Joncryl epoxy-based chain-extender (CE) on the flame retardancy characteristics of composites was examined. Due to the further chain modification, which also enhances the melt strength of PLA, the dripping of composites in the vertical burning test terminated and the V0 value could be reached when using only 1 wt% PCDI or CE. According to the scanning electron microscopic analysis, the use of noted chain modifiers further homogenized the distribution and refined the particle size of P/N within the PLA matrix. Hence this could synergistically contribute to the enhancements of the fire resistance performance of the PLA composites. Such incorporation of P/N and chain modifiers further leads to the enhancement of the mechanical performance of PLA composites and hence the resultant product can be proposed as a promising durable bioplastic engineering product where fire risk exists.
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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) | 0.003 | 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".