Citation: Yong-Peng Miao, Jing Lyu, Hai-Yang Yong, Sigen A, Yong-Sheng Gao, Wen-Xin Wang. Controlled Polymerization of Methyl Methacrylate and Styrene via Cu(0)-Mediated RDRP by Selecting the Optimal Reaction Conditions[J]. Chinese Journal of Polymer Science, ;2019, 37(6): 591-597. doi: 10.1007/s10118-019-2236-x shu

Controlled Polymerization of Methyl Methacrylate and Styrene via Cu(0)-Mediated RDRP by Selecting the Optimal Reaction Conditions

  • Corresponding author: Yong-Sheng Gao, yongsheng.gao@ucdconnect.ie Wen-Xin Wang, wenxin.wang@ucd.ie
  • Received Date: 26 November 2018
    Revised Date: 22 January 2019
    Accepted Date: 1 January 2018
    Available Online: 11 March 2019

  • Cu(0)-mediated reversible deactivation radical polymerization (Cu(0)-mediated RDRP) has been demonstrated as an excellent technique to control the polymerization of multiple vinyl monomers (e.g., acrylates, methacrylates, and styrene). However, the complexity of the reaction mechanism and multi-component system nature make it challenging to choose the appropriate conditions and consider the factors of achieving controllable polymerization when switching from one monomer to others with different reactivities. Herein, by polymerizing two examplary monomers: methyl methacrylate (MMA) and styrene via Cu(0)-mediated RDRP under different conditions, we have found that the reaction parameters (e.g., initiator, ligand, solvent, and deactivator) play a crucial role in regulating two equilibriums: (i) mutual conversion of different copper species which determines the relative concentration of Cu(I) and Cu(II), and (ii) polymerization equilibrium which is the combination of activation/deactivation, propagation and termination processes. We have demonstrated that by taking both the mutual conversion of different copper species and the polymerization equilibrium into account, the optimal reaction conditions could be selected, and the well-controlled Cu(0)-mediated RDRPs of methyl methacrylate and styrene were achieved with narrow molecular weight distributions and predicted molecular weight.
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