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

机译:一种改进的短链橡胶弹性的非高斯统计理论

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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-Grun (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,聚合物的力学行为已经由非高斯统计模型描述。非高斯模型通常基于Kuhn-Grun(kg)分布函数,其自身来自复合瑞利的精确傅里叶集成积分的第一阶近似。 KG函数在聚合物物理领域获得了这种广泛的接受,即非高斯理论通常用于描述具有各种灵活比的链条。然而,kg函数被显示为与长链相关的,具有超过40个段。在这里,我们提出了由非高斯链条的瑞利分布函数引起的熵力的新精确近似。近似提供了一种改进的逆Langevin函数的版本,其相对于精确的熵力具有有限的误差值。所提出的功能提供了比具有少于40个段的小和中型链的分布函数明显更准确地估计。

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