Notice bibliographique
Résumé
Protective wood coatings for aircraft interiors are essential to serve specific functions such as protecting the wood surface and providing high-gloss aesthetically appealing surfaces. Such coatings must also withstand cracking, provide sufficient hardness, adhesion to the wood, and fire-retardant properties. Additionally, the application of bio-sourced feedstock and the reduction of volatile organic compounds are important factors in the interior coatings. Recent advances in radical polymerization techniques allow the synthesis of such polymers with multiple functions, desirable macromolecular structures, and low dispersities, the last of which leads to low solution viscosities and easier coating application. We used nitroxide mediated polymerization (NMP) as it only requires heat and alkoxyamine to initiate and control the polymerization. It does not require extensive post-polymerization treatments, making it a facile approach for many industrial applications. In this thesis, we focused on methacrylic monomers with suitable functional groups for the development of coating formulations. We used commercially bio-based feedstock in the coating, as much as possible. To develop the coating formulation, we used isobornyl methacrylate (IBOMA, from pine sap) and C13 methacrylate (C13MA, from vegetable oils) along with other functional monomers. We started with the copolymerization of IBOMA and C13MA and achieved polymers with relatively low dispersities. We also used hydroxyethyl methacrylate (HEMA) to improve the adhesion to the wood substrates.Other components of developing the new coating were the incorporation of fire-resistant additives and cross-linkable monomers. We first used methacrylate-functionalized polyhedral oligomeric silsesquioxane (POSSMA) to copolymerize with C13MA to improve the thermal stability of the coatings. Interestingly, POSSMA-rich copolymers revealed improved thermal stabilities. However, the low ceiling temperature of POSSMA prevented achieving high molecular weight polymers. Thus, we sought an alternative technique, using POSS nanoparticles and used IBOMA and (2-acetoacetoxy) ethyl methacrylate (AAEMA). AAEMA was utilized to react with a bio-based diamine for subsequent cross-linking based on dynamic transamination network. Such cross-linked networks, called vitrimers, impart recyclability features to thermosetting polymers. We added amine-functionalized POSS at different loadings to achieve recyclable nanocomposite thermosets with enhanced thermal and mechanical properties. The vitrimers and nanocomposites showed reprocessability up to 3 cycles without substantial decrease in the mechanical properties. Additionally, the cross-linked coating revealed improved impact resistance and adhesion to the wood compared to the uncross-linked coating. Moreover, high POSS loadings up to 20 wt% could enhance the flame retardancy behavior of the coatings. We explored two other approaches to impart flame retardancy to the polymers based on using phosphorus compounds. The first method involved the incorporation of strongly acidic and cross-linkable HEMAP monomer (comprising 70% ethylene glycol methacrylate phosphate (EGMP) and 30% methyl methacrylate (MMA)). We demonstrated that NMP fails in the polymerization of HEMAP but reversible addition fragmentation transfer polymerization of HEMAP was achievable. Copolymerization of HEMAP with IBOMA and MMA notably improved the char residue and decomposition behavior. Later, we synthesized hybrid nanoparticles of organophosphorus-titanium-silicon (PTS) to serve as additives to simultaneously enhance thermal and mechanical properties. We developed copolymers of glycidyl methacrylate and C13MA cross-linked by a bio-based diamine and reinforced by PTS. Incorporation of PTS not only improved the decomposition behavior but also increased the mechanical properties, indicating a promising flame-retardant additive in coating resins
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».