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Gelation of RAFT polymer networks analyzed by rheology
Polymer ( IF 4.1 ) Pub Date : 2024-12-14 , DOI: 10.1016/j.polymer.2024.127956 Patrick Imrie, Jianyong Jin
Polymer ( IF 4.1 ) Pub Date : 2024-12-14 , DOI: 10.1016/j.polymer.2024.127956 Patrick Imrie, Jianyong Jin
Reversible addition-fragmentation chain-transfer (RAFT) polymerization is used to make polymer networks with improved homogeneity. Network formation is mostly inferred from the characterization of macro-indicators, such as vinyl bond conversion for kinetics data and swelling ratio for degree of crosslinking, which offer little information on micro-structure and homogeneity. To better probe the formation and structure of RAFT polymer networks during gelation, dynamic analysis was performed in situ using an advanced rheometer. In agreement with previous investigations, the time to gelation of the RAFT networks was prolonged in relation to free-radical polymerized (FRP) networks. It was found that the loss modulus (G″) of the RAFT networks was lower than that of FRP networks, indicating less friction from fewer microgel defects. The loss factor tan δ of the RAFT networks was quasi-steady, suggesting good retention of ideally elastic properties. In the vicinity of the gel point, the RAFT networks showed a prominent loss modulus (G″) local maximum phenomenon.
中文翻译:
流变学分析 RAFT 聚合物网络的凝胶化
可逆加成-碎裂-链转移 (RAFT) 聚合用于制造具有更高均匀性的聚合物网络。网络形成主要从宏观指标的表征中推断出来,例如动力学数据的乙烯基键转化率和交联度的溶胀比,这些指标提供的微观结构和均匀性信息很少。为了更好地探测凝胶化过程中 RAFT 聚合物网络的形成和结构,使用先进的流变仪进行了原位动态分析。与以前的研究一致,与自由基聚合 (FRP) 网络相比,RAFT 网络的凝胶化时间延长。结果发现,RAFT 网络的损耗模量 (G“) 低于 FRP 网络,表明微凝胶缺陷较少,摩擦较小。RAFT 网络的损失因子 tan δ 是准稳态的,表明很好地保留了理想的弹性特性。在凝胶点附近,RAFT 网络显示出明显的损耗模量 (G“) 局部最大值现象。
更新日期:2024-12-14
中文翻译:
流变学分析 RAFT 聚合物网络的凝胶化
可逆加成-碎裂-链转移 (RAFT) 聚合用于制造具有更高均匀性的聚合物网络。网络形成主要从宏观指标的表征中推断出来,例如动力学数据的乙烯基键转化率和交联度的溶胀比,这些指标提供的微观结构和均匀性信息很少。为了更好地探测凝胶化过程中 RAFT 聚合物网络的形成和结构,使用先进的流变仪进行了原位动态分析。与以前的研究一致,与自由基聚合 (FRP) 网络相比,RAFT 网络的凝胶化时间延长。结果发现,RAFT 网络的损耗模量 (G“) 低于 FRP 网络,表明微凝胶缺陷较少,摩擦较小。RAFT 网络的损失因子 tan δ 是准稳态的,表明很好地保留了理想的弹性特性。在凝胶点附近,RAFT 网络显示出明显的损耗模量 (G“) 局部最大值现象。