该研究团队使用网络分析工具对胶体结构进行了深入研究和表征。研究人员构建了具有不同吸引力水平的胶体的粒子级网络，并利用高斯混合模型识别出了多分散刚性分形团簇。这些团簇网络能够清晰地展示胶体凝胶的主要物理特征。然后，他们使用一个简单的质量-弹簧模型从这些团簇网络中定量地恢复了胶体凝胶的弹性。
研究这些凝胶网络的弹性表明，凝胶的弹性（一种动态特性）与其团簇网络的弹性（一种静态度量）直接相关。最后，研究人员利用弹性研究设计并实验验证了一个完全解析的胶体凝胶相图，该相图使用了远远超出相界线的单个粒子积分数，并具有清晰的固液相边界。
据悉，由于粒子-粒子相互作用形成的分枝空间跨越网络，胶体凝胶在固体的微小部分表现出类似固体的行为。这些网络使凝胶具有刚性，并且随着吸引力的增加，弹性也会增加。刚性的出现可以通过平均场方法来描述，但目前对于不同吸引力的凝胶中硬度如何变化的基本理解仍然有限。此外，基于系统变量恢复精确的凝胶相图是一项极具挑战性的任务。因此，了解胶体团簇的性质以及它们的连接方式对于产生刚性的机制是控制和设计具有理想性能凝胶的关键。
附：英文原文
Title: Network physics of attractive colloidal gels: Resilience, rigidity, and phase diagram
Author: Nabizadeh, Mohammad, Nasirian, Farzaneh, Li, Xinzhi, Saraswat, Yug, Waheibi, Rony, Hsiao, Lilian C., Bi, Dapeng, Ravandi, Babak, Jamali, Safa
Issue&Volume: 2024-1-9
Abstract: Colloidal gels exhibit solid-like behavior at vanishingly small fractions of solids, owing to ramified space-spanning networks that form due to particle–particle interactions. These networks give the gel its rigidity, and with stronger attractions the elasticity grows as well. The emergence of rigidity can be described through a mean field approach; nonetheless, fundamental understanding of how rigidity varies in gels of different attractions is lacking. Moreover, recovering an accurate gelation phase diagram based on the system’s variables has been an extremely challenging task. Understanding the nature of colloidal clusters, and how rigidity emerges from their connections is key to controlling and designing gels with desirable properties. Here, we employ network analysis tools to interrogate and characterize the colloidal structures. We construct a particle-level network, having all the spatial coordinates of colloids with different attraction levels, and also identify polydisperse rigid fractal clusters using a Gaussian mixture model, to form a coarse-grained cluster network that distinctly shows main physical features of the colloidal gels. A simple mass-spring model then is used to recover quantitatively the elasticity of colloidal gels from these cluster networks. Interrogating the resilience of these gel networks shows that the elasticity of a gel (a dynamic property) is directly correlated to its cluster network’s resilience (a static measure). Finally, we use the resilience investigations to devise [and experimentally validate] a fully resolved phase diagram for colloidal gelation, with a clear solid–liquid phase boundary using a single volume fraction of particles well beyond this phase boundary.
DOI: 10.1073/pnas.2316394121
Source: https://www.pnas.org/doi/abs/10.1073/pnas.2316394121