Nitrogen/phosphorus synergistic flame retardant-filled flexible polyurethane foams: microstructure, compressive stress, sound absorption, and combustion resistance
Bibliographic record
Abstract
Compared with a rigid polyurethane foam, a flexible polyurethane foam (FPUF) has more diversified applications including filtration, sound absorption, vibration-proofing, decoration, packaging, and heat insulation. However, its most potential hazard is flammability. Therefore, in this study, we focused on improving its flame retardation and then tested its sound absorption with the addition of nitrogen/phosphorus synergistic flame retardants. The influence of phosphorus-based flame retardants (TCPP, TDCP, and V6) and a nitrogen/phosphorus synergistic flame retardant (melamine-TDCP) on its microstructure, compressive stress, sound absorption, thermal stability, and flame retardation was systematically explored. The presence of phosphorus flame retardants improved the sound absorption but considerably decreased the mechanical properties. The melamine-TDCP compound flame retardant delivered smaller cells and thus increased the compression property of the resulting foam. Moreover, with a higher content of melamine, the initial mass-loss temperature also increased. In particular, on using TDCP and 5 wt% of melamine as flame retardants, the compressive stress increased by 3.4 times, the average sound absorption coefficient was 0.45, and LOI reached 25.5, which met the requirements of industrial flame retardant/sound absorbent materials. This resultant flame retardant/sound absorbent flexible polyurethane foam can serve as a mattress and furniture pad material, vehicle seat cushion material, and liner for laminated composites in the future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".