Wang Rui, Lin Tzyy-Shyang, Johnson Jeremiah A, Olsen Bradley D
Department of Chemical Engineering and ‡Department of Chemistry, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.
Department of Chemical Engineering and Department of Chemistry, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.
ACS Macro Lett. 2017 Dec 19;6(12):1414-1419. doi: 10.1021/acsmacrolett.7b00586. Epub 2017 Dec 5.
Accurate prediction of the gel point for real polymer networks is a long-standing challenge in polymer chemistry and physics that is extremely important for applications of gels and elastomers. Here, kinetic Monte Carlo simulation is applied to simultaneously describe network topology and growth kinetics. By accounting for topological defects in the polymer networks, the simulation can quantitatively predict experimental gel point measurements without any fitting parameters. Gel point suppression becomes more severe as the primary loop fraction in the networks increases. A topological homomorphism theory mapping defects onto effective junctions is developed to qualitatively explain the origins of this effect, which accurately captures the gel point suppression in the low loop limit where cooperative effects between topological defects are small.
准确预测实际聚合物网络的凝胶点是聚合物化学和物理学中长期存在的挑战，这对于凝胶和弹性体的应用极为重要。在此，应用动力学蒙特卡罗模拟来同时描述网络拓扑和生长动力学。通过考虑聚合物网络中的拓扑缺陷，该模拟无需任何拟合参数即可定量预测实验凝胶点测量结果。随着网络中初级环分数的增加，凝胶点抑制变得更加严重。开发了一种将缺陷映射到有效连接点的拓扑同态理论，以定性解释这种效应的起源，该理论准确地捕捉了在拓扑缺陷之间协同效应较小的低环极限下的凝胶点抑制。
