Shannon entropy analysis of the stretched exponential process : application to various shear induced multilamellar vesicles system

TL;DR

This study uses Shannon entropy to analyze the non-uniformity of relaxation processes in shear-induced multilamellar vesicles, revealing how shear type and frequency affect the process's statistical homogeneity and entropy.

Contribution

It introduces Shannon entropy as a novel tool to quantify non-uniformity in stretched exponential relaxation processes under shear conditions.

Findings

Shannon entropy peaks at β=1, indicating a single exponential process.

Sine shear shows frequency-dependent Shannon entropy.

Higher shear intensity correlates with increased Shannon entropy, reflecting less constrained diffusion.

Abstract

The stretched exponential function, $\exp[-(t/\tau_{K})^{\beta}]$, describes various relaxation processes while it has been suggested that the power exponent, $\beta$ is derived from the non-uniformity of the process. In this paper, we attempted to estimate this non-uniformity by introducing Shannon entropy. Shannon entropy evaluates the average information contents of the distribution function, which reflects statistical homogeneity. We investigated the relaxation process of shear induced multilamellar system, which is described with the stretched exponential function. Three types of shear (constant, square, sine) at different frequencies are attempted in order to determine their effects on the relaxation process. We found that the Shannon entropy to which the first moment was introduced is maximized at $\beta~=~1$ : a single exponential. The Shannon entropy of sine shear experiments exhibited the frequency dependence. Thus it is interpreted that the increase of the intensity of shearing and the thermodynamic entropy are reflected on the Shannon entropy. We discussed the meaning of the maximum Shannon entropy in terms of various points of view, it was found that it corresponds to the diffusion process free from the restriction such as geometrical constraints. The constraints and the non-uniformity of process were successfully estimated by Shannon entropy. This study gives a new insight of entropy in general.