Rubber-lignin-ammonium polyphosphate bio-composite foams: Fabrication, thermomechanical properties and flame retardancy
Bibliographic record
Abstract
Bio-composite foams based on Epoxidized Natural Rubber (ENR) filled with lignin (LG) and ammonium polyphosphate (APP) were fabricated via batch foaming. The addition of APP accelerated the foaming process at lower temperatures. Pre-mixing induced ionic and hydrogen bonding between the LG and the APP particles, which reduced crosslinking between LG and ENR. The resulting ENR bio-composite foams with LG/APP exhibited a significant increase in compressive strength (up to 700 %) and modulus (up to 600 %) compared to the ENR foam baseline. Furthermore, the LG/APP foams demonstrated lower thermal conductivity than both the ENR foam baseline and foams containing only LG or APP, attributed to optimal thermal conduction in the solid phase and convection within the pore cells. The combination of APP and LG produced synergistic effects, with phosphorus (from APP) and high carbon content (from LG) enhancing flame-retardant efficiency. This study highlights the potential of these sustainable bio-composite foams for applications requiring enhanced thermal insulation and flame retardancy attributes for insulation and other practical applications.
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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".