Polymers Branch, US Army Research Laboratory, Aberdeen Proving Ground, MD 21005
Proc Natl Acad Sci U S A. 2020 Jul 7;117(27):15394-15396. doi: 10.1073/pnas.2006305117. Epub 2020 Jun 22.
The chordless cycle sizes of spatially embedded networks are demonstrated to follow an exponential growth law similar to random graphs if the number of nodes [Formula: see text] is below a critical value [Formula: see text] For covalent polymer networks, increasing the network size, as measured by the number of cross-link nodes, beyond [Formula: see text] results in a crossover to a new regime in which the characteristic size of the chordless cycles [Formula: see text] no longer increases. From this result, the onset and intensity of finite-size effects can be predicted from measurement of [Formula: see text] in large networks. Although such information is largely inaccessible with experiments, the agreement of simulation results from molecular dynamics, Metropolis Monte Carlo, and kinetic Monte Carlo suggests the crossover is a fundamental physical feature which is insensitive to the details of the network generation. These results show random graphs as a promising model to capture structural differences in confined physical networks.
空间嵌入网络的无弦循环大小被证明遵循指数增长规律,如果节点数量[公式:见正文]低于临界值[公式:见正文],则类似于随机图。对于共价聚合物网络,通过增加交联节点数量来增加网络大小,超过[公式:见正文]会导致交叉到一个新的区域,其中无弦循环的特征大小[公式:见正文]不再增加。从这个结果可以预测有限大小效应的开始和强度,可以从大网络中测量[公式:见正文]来预测。尽管这种信息在很大程度上无法通过实验获得,但分子动力学、Metropolis 蒙特卡罗和动力学蒙特卡罗的模拟结果的一致性表明,这种交叉是一种基本的物理特征,不受网络生成细节的影响。这些结果表明随机图是一种很有前途的模型,可以捕捉受限物理网络中的结构差异。