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[论文解读] Entropy maximization underlies topology and mechanical properties in dynamic covalent hydrogels

Lucien Cousin, Pietro Miotti|arXiv (Cornell University)|Mar 18, 2026
Hydrogels: synthesis, properties, applications被引用 0
一句话总结

论文表明动态共价网络重排以最大化网络熵,推迟凝胶化并产生更陡峭的模量上升;键交换可在不损失键的情况下重新配置力学。

ABSTRACT

Adding dynamic bonds in polymer networks enables reprocessing and recycling; however the full impact of reversible bonds on dynamic network mechanics remains unclear. We build model dynamic networks and observe substantial deviations from classic theory. We rationalize these findings by considering that bond exchange enables the networks to rearrange and adopt a topology with a higher entropy. This allows us to accurately predict the gel point and elasticity of the dynamic networks. Further, we show by controlling bond exchange that network rearrangement can dramatically alter the mechanical properties, even without loss of bonds.

研究动机与目标

  • 研究动态可逆键如何影响凝胶点与弹性,超越经典永久网络理论的理解。
  • 确定当键形成比例 p 变化时,网络熵是否驱动 DCvN 内部拓扑变化。
  • 量化键交换及由此产生的拓扑如何影响在接近及超过凝胶化时的力学性质。

提出的方法

  • 使用可逆 BORON-酸–二醇键连接的4臂PEG星形网格,合成模型动态共价网络。
  • 通过调整温度、浓度和竞争结合体,系统性地改变形成键的分数 p。
  • 通过剪切流变测量在不同条件下的凝胶点、平台模量 G_P 及弛豫时间 τ_M。
  • 通过图论框架,以基于熵的星形连通性与环的计数来表征网络拓扑。
  • 开发熵最大化模型以预测 P_i(每个星形上结合臂的分布)及由此产生的凝胶点。
  • 将环纳入模型并用耗散粒子动力学模拟与实验数据验证。
  • 提出基于虚拟网络(phantom-network)的弹性模型, incorporating 缺陷(环与悬挂链)以预测 G' 相对于 p 的变化。
Figure 1: Synthesis and mechanical characterization of dynamic covalent networks. a) General structure of the dynamic covalent networks formed by cross-linking 4-arm PEG stars end-functionalized with either a boronic acid or a diol. The formed networks incorporate reacted and unreacted bonds in vari
Figure 1: Synthesis and mechanical characterization of dynamic covalent networks. a) General structure of the dynamic covalent networks formed by cross-linking 4-arm PEG stars end-functionalized with either a boronic acid or a diol. The formed networks incorporate reacted and unreacted bonds in vari

实验结果

研究问题

  • RQ1动态共价网络中形成键的分数 p 如何影响凝胶点与弹性,超越经典理论?
  • RQ2通过连通性分布 P_i 与环,熵是否解释接近凝胶化时与仿射网络预测的偏离?
  • RQ3键交换动力学是否重构网络拓扑以最大化熵,以及这对凝胶化后力学性质有何影响?
  • RQ4能否用一个同时考虑环与悬挂链的统一模型来捕捉 DCvN 在凝胶化附近的观测弹性?

主要发现

  • 观测到的凝胶点 p_gel 较高(约 0.6)比 Flory–Stockmayer 的预测(约 0.33)高。
  • 归一化模量数据在以 p 绘制时无论通过何种方式改变 p 都坠入同一主曲线。
  • 包含环形成在内的熵最大化连通性比经典模型更能预测 p_gel 与 G' 随 p 的上升。
  • 即使不改变键数量,键交换也通过改变网络拓扑与弹性来影响模量,体现在使键变为动态后再重新固定时模量的变化。
  • 一个结合环与悬挂链的标度化虚拟网络模型能够捕捉凝胶点的延迟及凝胶化附近 G' 的更陡增。
  • 模拟结果支持熵最大化理论所预测的 P_i 分布与环的比例。
Figure 2: The maximization of network entropy in dynamic covalent networks leads to a different connectivity that explains the measured gel point. a) Measured gel point in the case of 4-arm and 8-arm stars compared with the predictions from the Flory–Stockmayer model and with our prediction, taking
Figure 2: The maximization of network entropy in dynamic covalent networks leads to a different connectivity that explains the measured gel point. a) Measured gel point in the case of 4-arm and 8-arm stars compared with the predictions from the Flory–Stockmayer model and with our prediction, taking

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