Incorporating dynamic covalent linkages into thermosets can endow previously unrecyclable materials with new functionality and reprocessing options. Recent work has shown that the properties of the resulting covalent adaptable networks (CANs) are highly dependent on network topology, specifically the phenomenon of percolation, when permanent linkages form a connected skeleton that spans the material. Here, we use a model glassy disulfide based CAN to assess the merits of mean-field percolation theory as a tool to describe the network topology of CANs. After challenging the theory with both experimental data and a coarse-grained molecular dynamics simulation, we find that the mean-field approach is surprisingly accurate, despite its simplifying assumptions. The theory is particularly well suited to the unique context of mixed-composition CANs and provides practical guidance on how to design for reprocessability.

中文翻译：

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模型共价自适应网络中的网络拓扑和渗流


将动态共价键掺入热固性塑料中，可以赋予以前不可回收的材料新的功能和再加工选项。最近的研究表明，所得共价适应性网络 （CAN） 的特性高度依赖于网络拓扑，特别是渗流现象，当永久连接形成跨越材料的连接骨架时。在这里，我们使用基于玻璃二硫化物的模型 CAN 来评估平均场渗流理论的优点，作为描述 CAN 网络拓扑的工具。在用实验数据和粗粒度分子动力学模拟挑战该理论后，我们发现平均场方法尽管假设简单，但出奇地准确。该理论特别适合混合成分 CAN 的独特环境，并为如何设计可再加工性提供了实用指导。