从衰减曲线求弛豫分布函数的数值方法及其在聚γ-苄基-谷氨酸浓溶液电双折射衰减过程中的应用

Kinko Tsuji, Hiroshi Watanabe, Koshiro Yoshioka
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引用次数: 11

摘要

在(1)中,我们描述了一种从衰减曲线确定松弛分布函数的数值方法。将分布函数展开为一系列适当的多项式,并用最小二乘法确定系数的最优值。为了检验它的适用性和局限性,我们将它应用于一些由不同类型的分布函数构成的人工衰减曲线。结果表明,该方法对连续分布比离散分布更适用。只要原始衰减数据是准确的,精确计算是非常有效的,而当原始衰减数据是粗糙的或包含一些噪声时,粗略计算是很好的。因此,粗略计算对于不存在误差的实验衰变数据的分析是可行的。在(II)中,我们将我们的方法应用于几种浓聚γ-苄基- l-谷氨酸溶液的电双折射衰减过程。有时由于基线选择不当,需要对实验数据进行修改。半对数图对修正是有效的。为了使我们的物理图像更清晰,引入了长度分布函数。得到了长度分布曲线的场强依赖性、时间依赖性和浓度依赖性。我们的方法对于研究分布函数随外部或内部条件变化的系统变化是强有力的。
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A numerical method of obtaining the relaxation distribution function from decay curves and its application to the decay process of electric birefringence of concentrated poly-γ-benzyl-l-glutamate solutions

In (I), we describe a numerical method for determining the relaxation distribution function from decay curves. The distribution function is expanded in a series of appropriate polynomials and the best values of the coefficients are determined by the method of least squares. In order to examine its applicability and limit, we apply it to some artificial decay curves constructed with different types of distribution functions. According to the results, our method is more adequate for the continuous distribution than for the discrete one. Accurate calculation is very effective so long as the original decay data are accurate, while rough calculation is good when the original decay data are rough or include some noise. Therefore, rough calculation is practical for analysis of experimental decay data which are not free from errors.

In (II), we apply our method to the decay process of electric birefringence of several concentrated poly-γ-benzyl-L-glutamate solutions. It is sometimes necessary to modify the experimental data because of improper selection of the base line. The semi-logarithmic plot is effective for modification. In order to make our physical image clearer, the length distribution function is introduced. Field strength dependence, time dependence and concentration dependence of the length distribution curve have been obtained. Our method is powerful for investigating a systematic change of the distribution function with changes of external or internal conditions.

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