Investigation of flame retardancy properties of polypropylene-colemanite and intumescent flame retardant additive blends
Bibliographic record
Abstract
Polypropylene (PP) represents a considerable proportion of polyolefins (PO) used in different industrial applications such as automobile components, textiles, packaging, insulation, medical devices, various housewares and household appliances due to its efficient cost, desirable mechanical, thermal and electrical properties, easy processability and recyclability. Because of its carbonaceous structure, PP is a highly flammable material with a LOI value of 18 that presents serious fire hazard. In this research, Intumescent flame retardant (IFR) and colemanite were added to polypropylene to compose 30% of the total mass of the polymeric compounds and the synergistic effect of colemanite with intumescent flame retardant (IFR) additive in PP was investigated by limiting oxygen index (LOI), glow wire test (GWT), UL-94 test and mechanical properties measurements. The LOI, UL 94 and glow wire test results showed that colemanite had a significant effect on flame retardancy and LOI value which can reach to 37.6 % with loading level of 2 wt.% colemanite at the total amount of flame retardant additives kept constant at 30 wt.%. Additionally, the PP/IFR compounds passed UL 94 V0 rating and both 750 °C and 850 °C glow wire tests and with 2-8 wt.% colemanite loading. According to TGA analyses, the results indicated that colemanite improved the thermal stability of PP/IFR compounds and also promoted the formation of char layer. When colemanite mineral added to polypropylene without IFR system, it has no effect on flame retardancy properties of polypropylene. When all properties have been taken into consideration, colemanite can be used up to 6 wt% in IFR.
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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) | 0.001 | 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".