Wang Junpeng, Lin Tzyy-Shyang, Gu Yuwei, Wang Rui, Olsen Bradley D, Johnson Jeremiah A
Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.
ACS Macro Lett. 2018 Feb 20;7(2):244-249. doi: 10.1021/acsmacrolett.8b00008. Epub 2018 Feb 6.
To predict and understand the properties of polymer networks, it is necessary to quantify network defects. Of the various possible network defects, loops are perhaps the most pervasive and yet difficult to directly measure. Network disassembly spectrometry (NDS) has previously enabled counting of the simplest loops-primary loops-but higher-order loops, e.g., secondary loops, have remained elusive. Here, we report that the introduction of a nondegradable tracer within the NDS framework enables the simultaneous measurement of primary and secondary loops in end-linked polymer networks for the first time. With this new "NDS2.0" method, the concentration dependences of the primary and secondary loop fractions are measured; the results agree well with a purely topological theory for network formation from phantom chains. In addition, semibatch monomer addition is shown to decrease both primary and secondary loops, though the latter to a much smaller extent. Finally, using the measured primary and secondary loop fractions, we were able to predict the shear storage modulus of end-linked polymer gels via real elastic network theory (RENT).
为了预测和理解聚合物网络的性质，有必要对网络缺陷进行量化。在各种可能的网络缺陷中，环可能是最普遍存在但又难以直接测量的。网络拆解光谱法（NDS）此前能够对最简单的环——初级环进行计数，但高阶环，如次级环，仍然难以捉摸。在此，我们报告称，在NDS框架内引入不可降解的示踪剂首次实现了对末端连接聚合物网络中初级环和次级环的同时测量。通过这种新的“NDS2.0”方法，测量了初级环和次级环分数的浓度依赖性；结果与由虚链形成网络的纯拓扑理论非常吻合。此外，半间歇单体添加显示会减少初级环和次级环，不过次级环减少的程度要小得多。最后，利用测得的初级环和次级环分数，我们能够通过真实弹性网络理论（RENT）预测末端连接聚合物凝胶的剪切储能模量。
