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Efficacy analysis of new copper complex for visible light (455, 530 nm) radical/cationic photopolymerization: The synergic effects and catalytic cycle

The kinetics and the conversion features of two 3-component systems (A/B/N), based on the proposed new kinetic schemes of Mokbel and Mau et al, in which a visible LED is used to excite a copper complex to its excited triplet state (G*). The coupling of G* with iodonium salt and ethyl 4-(dimethylamin...

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Detalles Bibliográficos
Autores principales: Lin, Jui-Teng, Lalevee, Jacques, Cheng, Da-Chuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9321381/
https://www.ncbi.nlm.nih.gov/pubmed/35881581
http://dx.doi.org/10.1371/journal.pone.0270679
Descripción
Sumario:The kinetics and the conversion features of two 3-component systems (A/B/N), based on the proposed new kinetic schemes of Mokbel and Mau et al, in which a visible LED is used to excite a copper complex to its excited triplet state (G*). The coupling of G* with iodonium salt and ethyl 4-(dimethylamino)benzoate (EDB) produces both free radical polymerization (FRP) of acrylates and the free radical promoted cationic polymerization (CP) of epoxides using various new copper complex as the initiator. Higher FRP and CP conversion can be achieved by co-additive of [B] and N, via the dual function of (i) regeneration [A], and (ii) generation of extra radicals. The interpenetrated polymer network (IPN) capable of initiating both FRP and CP in a blend of TMPTA and EPOX. The synergic effects due to CP include: (i) CP can increase viscosity limiting the diffusional oxygen replenishment; (ii) the cation also acts as a diluting agent for the IPN network, and (iii) the exothermic property of the CP. The catalytic cycle, synergic effects, and the oxygen inhibition are theoretically confirmed to support the experimental hypothesis. The measured results of Mokbel and Mau et al are well analyzed and matching the predicted features of our modeling.