Development of Biodegradable Flame-Retardant Bamboo Charcoal Composites, Part II: Thermal Degradation, Gas Phase, and Elemental Analyses
Bibliographic record
Abstract
Bamboo charcoal (BC) and aluminum hypophosphite (AHP) singly and in combination were investigated as flame-retardant fillers for polylactic acid (PLA). A set of BC/PLA/AHP composites were prepared by melt-blending and tested for thermal and flame-retardancy properties in Part I. Here, in Part II, the results for differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), Fourier transform infrared (FTIR), thermogravimetry-Fourier transform infrared spectrometry (TG-FTIR), X-ray diffraction (XRD), and X-ray photoelectron analysis (XPS) are presented. The fillers either singly or together promoted earlier initial thermal degradation of the surface of BC/PLA/AHP composites, with a carbon residue rate up to 40.3%, providing a protective layer of char. Additionally, BC promotes heterogeneous nucleation of PLA, while AHP improves the mechanical properties and machinability. Gaseous combustion products CO, aromatic compounds, and carbonyl groups were significantly suppressed in only the BC-PLA composite, but not pure PLA or the BC/PLA/AHP system. The flame-retardant effects of AHP and BC-AHP co-addition combine effective gas-phase and condensed-phase surface phenomena that provide a heat and oxygen barrier, protecting the inner matrix. While it generated much CO2 and smoke during combustion, it is not yet clear whether BC addition on its own contributes any significant gas phase protection for PLA.
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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 | 0.000 |
| 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 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".