Login / Signup

Synthesis and Crystallization of Waterborne Thiol-ene Polymers: Toward Innovative Oxygen Barrier Coatings.

Justine ElgoyhenValentina PirelaAlejandro J MüllerRadmila Tomosvka
Published in: ACS applied polymer materials (2023)
The synthesis of waterborne thiol-ene polymer dispersions is challenging due to the high reactivity of thiol monomers and the premature thiol-ene polymerization that leads to high irreproducibility. By turning this challenge into an advantage, a synthesis approach of high solid content film-forming waterborne poly(thioether) prepolymers is reported based on initiator-free step growth sonopolymerization. Copolymerization of bifunctional thiol and ene monomers diallyl terephthalate, glycol dimercaptoacetate, glycol dimercaptopropionate, and 2,2-(ethylenedioxy)diethanethiol gave rise to linear poly(thioether) functional chains with molar mass ranging between 7 and 23 kDa when synthesized at 30% solid content and between 1 and 9 kDa at increased solid content of 50%. To further increase the polymers' molar mass, an additional photopolymerization step was performed in the presence of a water-soluble photoinitiator, i.e., lithium phenyl-2,4,6-trimethylbenzoylphosphinate, leading to high molar mass chains of up to 200 kDa, the highest reported so far for step grown poly(thioethers). The polymer dispersions presented good film-forming ability at room temperature, yielding semicrystalline films with a high potential for barrier coating applications. Nevertheless, affected by the polymer chemical repeating structure, which includes an aromatic ring, these thiol-ene chains can only crystallize very slowly from the molten state. Herein, for the first time, we present the successful implementation of a self-nucleation (SN) procedure for these types of poly(thioethers), which effectively accelerates their crystallization kinetics.
Keyphrases
  • room temperature
  • water soluble
  • heat shock protein
  • risk assessment
  • reduced graphene oxide
  • minimally invasive
  • amino acid
  • neural network