Universality, the Barton, Namikawa, and Nakajima relation, and scaling for dispersive ionic materials

TL;DR

This paper demonstrates that the Kohlrausch beta1 parameter for ionic materials is universally close to 1/3, leading to a fixed 'U' model that explains dispersion and scaling behavior across temperature and concentration variations.

Contribution

It establishes the fixed value of beta1 at 1/3 for the K1 model, introducing the universal 'U' model and confirming the Barton-Nakajima-Namikawa relation with p=1.65.

Findings

Beta1 parameter is universally close to 1/3 in ionic materials.

The 'U' model with fixed beta1 fits diverse data sets across conditions.

Scaling parameters are derived from composite nonlinear fits.

Abstract

Many frequency-response analyses of experimental data for homogeneous glasses and single-crystals involving mobile ions of a single type indicate that estimates of the stretched-exponential beta1 shape parameter of the Kohlrausch K1 fitting model are close to 1/3 and are virtually independent of both temperature and ionic concentration. This model, which usually yields better fits than others, is indirectly associated with temporal-domain stretched-exponential response having the same beta1 parameter value. Here it is shown that for the above conditions several different analyses yield the important and unique value of exactly 1/3 for the beta1 of the K1 model. It is therefore appropriate to fix the beta1 parameter of this model at the constant value of 1/3, then defined as the U model. It fits data sets exhibiting conductive-system dispersion that vary with both temperature and concentration just as well as those with beta1 free to vary, and it leads to a correspondingly universal value of the Barton-Nakajima-Namikawa (BNN) parameter p of 1.65. Composite-model complex-nonlinear-least-squares fitting, including the dispersive U-model,the effects of the bulk dipolar-electronic dielectric constant, and of electrode polarization when significant, also leads to estimates of two hopping parameters that yield optimum scaling of experimental data that involve temperature and concentration variation.