Reactive and Additive Modifications of Styrenic Polymers with Phosphorus-Containing Compounds and Their Effects on Fire Retardance
Bibliographic record
Abstract
Polystyrene, despite its high flammability, is widely used as a thermal insulation material for buildings, for food packaging, in electrical and automotive industries, etc. A number of modification routes have been explored to improve the fire retardance and boost the thermal stability of commercially important styrene-based polymeric products. The earlier strategies mostly involved the use of halogenated fire retardants. Nowadays, these compounds are considered to be persistent pollutants that are hazardous to public and environmental health. Many well-known halogen-based fire retardants, regardless of their chemical structures and modes of action, have been withdrawn from built environments in the European Union, USA, and Canada. This had triggered a growing research interest in, and an industrial demand for, halogen-free alternatives, which not only will reduce the flammability but also address toxicity and bioaccumulation issues. Among the possible options, phosphorus-containing compounds have received greater attention due to their excellent fire-retarding efficiencies and environmentally friendly attributes. Numerous reports were also published on reactive and additive modifications of polystyrene in different forms, particularly in the last decade; hence, the current article aims to provide a critical review of these publications. The authors mainly intend to focus on the chemistries of phosphorous compounds, with the P atom being in different chemical environments, used either as reactive, or additive, fire retardants in styrene-based materials. The chemical pathways and possible mechanisms behind the fire retardance are discussed in this review.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".