Bibliographic Details
| Title: |
An Analytical Method to Determine Tortuosity in Rechargeable Battery Electrodes. |
| Authors: |
Vijayaraghavan, Bharath1, Ely, David R.1, Yet-Ming Chiang2, García-García, Ramiro3, García, R. Edwin1 redwing@purdue.edu |
| Source: |
Journal of The Electrochemical Society. 2012, Vol. 159 Issue 5, pA548-A552. 5p. |
| Subjects: |
Lithium ions, Neutron diffraction crystallography, Ion selective electrodes, Thermal diffusivity, Porosity |
| Abstract: |
In high energy density, low porosity, lithium-ion battery electrodes, the underlying microstructural tortuosity controls the macroscopic charge capacity, average lithium-ion diffusivity, and macroscopic resistivity of the cell, particularly at high discharge rates and power densities. In this paper, an analytical framework is presented to extend widely used empirical tortuosity relations such as the Bruggemann relation to incorporate the effects of the mesoscale tortuosity through analytical integration along the width of the electrode (in the limit of high porosities), and integration along a statistically representative tortuous path (in the limit of low porosities). The framework presented herein enables to establish analytical tortuosity-porosity relations that combine the constitutive properties of the individual components. As an example application, the macroscopic tortuosity-porosity relation of a mixture of two porous particle systems of widely different length scales and well-known individual tortuosity constitutive equations, one displaying mesoscale porosity (the carbon black-electrolyte mixture) and a second one displaying microporosity (the electrochemically active phase), are combined into a self-consistent macroscopic tortuosity expression that is in agreement with recently reported empirical measures of tortuosity. [ABSTRACT FROM AUTHOR] |
|
Copyright of Journal of The Electrochemical Society is the property of IOP Publishing and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Engineering Source |