Preparation and Characterisation of UV-Curable Flame Retardant Wood Coating Containing a Phosphorus Acrylate Monomer
Bibliographic record
Abstract
The application of a flame retardant coating is an effective solution to enhance the fire retardancy of wood flooring. However, finding the right balance between reducing the flame propagation and good overall coating properties while conserving wood appearance is complex. In order to answer this complex problem, transparent ultraviolet (UV)-curable flame retardant wood coatings were prepared from an acrylate oligomer, an acrylate monomer, and the addition of the tri(acryloyloxyethyl) phosphate (TAEP), a phosphorus-based monomer, at different concentrations in the formulation. The coatings’ photopolymerisation, optical transparency, hardness, water sorption and thermal stability were assessed. The fire behaviour and the adhesion of the coatings applied on the yellow birch panels were evaluated, respectively, using the cone calorimeter and pull-off tests. Scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS) analyses were performed on the collected burnt residues to obtain a better understanding of the flame retardancy mechanism. Our study reveals that phosphorus monomer addition improved the coating adhesion and the fire performance of the coated wood without impacting the photopolymerisation. The conversion percentage remained close to 70% with the TAEP addition. The pull-off strength reached 1.12 MPa for the coating with the highest P-monomer content, a value significantly different from the non-flame retarded coating. For the same coating formulation, the peak of heat release rate decreased by 13% and the mass percentage of the residues increased by 37% compared to the reference. However, the flame-retarded coatings displayed a higher hygroscopy. The action in the condensed phase of the phosphorus flame retardant is highlighted in this study.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".