Poly(ethyl methacrylate) Composite Coatings Containing Halogen-Free Inorganic Additives with Flame-Retardant Properties
Bibliographic record
Abstract
This investigation is motivated by the need for the development of polymer coatings containing inorganic flame-retardant materials (FRMs) and the replacement of toxic halogenated FRMs. A green strategy is reported for the fabrication of poly(ethyl methacrylate) (PEMA)-FRM composite coatings using a dip-coating method. The use of water-isopropanol co-solvent allows the replacement of regular toxic solvents for PEMA. The abilities to form concentrated solutions of high-molecular-mass PEMA and to disperse FRM particles in such solutions are the main factors in the fabrication of coatings using a dip-coating technique. Huntite, halloysite, and hydrotalcite are used as advanced FRMs for the fabrication of PEMA-FRM coatings. FTIR, XRD, SEM, and TGA data are used for the analysis of the microstructure and composition of PEMA-FRM coatings. PEMA and PEMA-FRM coatings provide corrosion protection of stainless steel. The ability to form laminates with different layers using a dip-coating method facilitates the fabrication of composite coatings with enhanced properties.
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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".