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键重排与网络弹性。

Bond scrambling and network elasticity.

作者信息

Ciferri Alberto

机构信息

Institute for Macromolecular Science-CNR, 16149 Genoa, Italy.

出版信息

Chemistry. 2009 Jul 13;15(28):6920-5. doi: 10.1002/chem.200802746.

DOI:10.1002/chem.200802746
PMID:19499558
Abstract

Dynamic networks (DNs) recently reported in the literature are based on cross-linked supramolecular chains or on covalent chains with reversible bonds. As originally pointed out by Lehn, these networks should be regarded as dynamic materials exhibiting adaptive features due to continuous scrambling of their bonds and sequences. Results in the recent literature reveal that these networks undergo reversible long-range deformation resembling that of rubber networks. The present analysis of this process in terms of the theory of composite networks is based on the expectation that the scrambling process should allow rupture of bonds in the undeformed state and their reformation in the stretched state. Accordingly, a permanent set of the resting length of DNs should generally be expected and set materials should retain long-range elasticity relative to the set state. However, only a limited set is shown by DNs, implying that a strong memory of the initial network topology assists elastic recovery of the original dimensions. The analysis of reported experimental data further reveals that the stress-strain dependence of dynamic networks accurately follows the classical rubber elasticity theory. In this respect, DNs show better rubber behavior than typical covalent networks. Consistently with theoretical predictions, this surprising finding suggests that bond scrambling relieves local strain constraints on the fluctuations of networks junctions and favors the recovery of the initial network topology. Scrambling therefore allows compliance under stress and enhanced recovery when stress is released. Unprecedented applications of these advanced materials thus become foreseeable.

摘要

文献中最近报道的动态网络(DNs)基于交联超分子链或具有可逆键的共价链。正如莱恩最初所指出的,这些网络应被视为动态材料,由于其键和序列的持续重排而呈现出适应性特征。近期文献中的结果表明,这些网络会经历类似于橡胶网络的可逆远程变形。目前根据复合网络理论对这一过程的分析基于这样的预期:重排过程应允许在未变形状态下键的断裂以及在拉伸状态下键的重新形成。因此,通常应预期动态网络的静止长度会有一个永久变形,并且设定后的材料相对于设定状态应保持远程弹性。然而,动态网络仅显示出有限的变形,这意味着对初始网络拓扑结构的强烈记忆有助于原始尺寸的弹性恢复。对已报道实验数据的分析进一步表明,动态网络的应力 - 应变依赖性准确地遵循经典橡胶弹性理论。在这方面,动态网络比典型的共价网络表现出更好的橡胶性能。与理论预测一致,这一惊人发现表明键的重排减轻了网络节点波动的局部应变约束,并有利于初始网络拓扑结构的恢复。因此,重排使得材料在应力作用下具有柔顺性,并在应力释放时增强恢复能力。因此,这些先进材料的前所未有的应用变得可预见。

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