橡胶短链弹性的改进非高斯统计理论

V. Morovati, R. Dargazany
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引用次数: 3

摘要

聚合物的力学行为早已被非高斯统计模型所描述。非高斯模型通常基于kuhn - grn (KG)分布函数,它本身是由复瑞利精确傅立叶积分分布的一阶近似导出的。KG函数在聚合物物理领域获得了广泛的认可,因此非高斯理论经常被用来描述具有不同柔度比的链。然而,KG功能仅与超过40个片段的长链相关。在此,我们提出了一种新的由非高斯链的瑞利分布函数得到的熵力的精确近似。该近似提供了一种改进的朗之万逆函数,该函数相对于确切的熵力具有有限的误差值。对于少于40段的中小型连锁店,所提出的函数提供了比KG函数更准确的分布函数估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Improved Non-Gaussian Statistical Theory of Rubber Elasticity for Short Chains
The mechanical behavior of polymers has long been described by the non-Gaussian statistical model. Non-Gaussian models are generally based on the Kuhn-Grün (KG) distribution function, which itself is derived from the first order approximation of the complex Rayleigh’s exact Fourier integral distribution. The KG function has gained such a broad acceptance in the field of polymer physics that the non-Gaussian theory is often used to describe chains with various flexibility ratios. However, KG function is shown to be only relevant for long chains, with more than 40 segments. Here, we propose a new accurate approximation of the entropic force resulted from Rayleigh distribution function of non-Gaussian chains. The approximation provides an improved version of inverse Langevin function which has a limited error value with respect to the exact entropic force. The proposed function provides a significantly more accurate estimation of the distribution function than KG functions for small and medium-sized chains with less than 40 segments.
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