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AN IMPROVED NON-GAUSSIAN STATISTICAL THEORY OF RUBBER ELASTICITY FOR SHORT CHAINS

机译:短链橡胶弹性的改进非高斯统计理论

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The mechanical behavior of polymers has long been described by the non-Gaussian statistical model. Non-Gaussian models are generally based on the Kuhn-Griin (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.
机译:长期以来,非高斯统计模型描述了聚合物的机械性能。非高斯模型通常基于Kuhn-Griin(KG)分布函数,该函数本身是从复数Rayleigh精确傅里叶积分分布的一阶近似中得出的。 KG函数已在聚合物物理学领域获得了广泛的接受,以至于非高斯理论通常用于描述具有各种柔韧性比的链。但是,KG功能仅与具有40个以上段的长链相关。在此,我们提出了一种由非高斯链的瑞利分布函数得出的熵力的新的精确近似值。近似值提供了逆Langevin函数的改进版本,该函数相对于确切的熵力具有有限的误差值。对于少于40个段的中小型链,建议的函数比KG函数提供的分布函数估计要精确得多。

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