Methods for Tomographic Segmentation in Pseudo-Cylindrical Coordinates for Bobbin-Type Batteries
Dominick P Guida1, Alyssa M Stavola1, Andrew Chihpin Chuang2
1Department of Chemical Engineering, Northeastern University, 360 Huntington Avenue, Boston, Massachusetts 02115, United States of America.
ACS Measurement Science Au
|October 25, 2023
Summary
This study introduces a new method to analyze battery structures using X-ray computed tomography (CT) data. It converts Cartesian coordinates to pseudo-cylindrical ones, improving the understanding of radial dependencies in batteries like alkaline Zn-MnO2.
Area of Science:
- Materials Science
- Electrochemistry
- Imaging Science
Background:
- High-resolution X-ray computed tomography (CT) is crucial for analyzing sealed battery samples.
- Cartesian coordinates in CT data are unsuitable for studying radial dependencies in bobbin-type batteries.
- Alkaline zinc-manganese dioxide (Zn-MnO2) batteries are prevalent in the primary battery market.
Purpose of the Study:
- To develop a method for approximating Cartesian CT data into pseudo-cylindrical coordinates.
- To enable correlation between computational battery models and CT data by aligning radial volume fractions.
- To improve the analysis of radial material dependencies in bobbin-type batteries.
Main Methods:
- A novel pseudo-cylindrical coordinate transformation is applied to CT data from Zn-MnO2 AA battery anodes.
- Pseudo-radius is defined as the relative distance from the central current pin to the separator within the anode.
- The method is demonstrated and validated using 10 AA battery anodes.
Main Results:
- The pseudo-cylindrical method yields averaged one-dimensional material profiles.
- These profiles show improved quantitative matching to individual anode slices compared to other averaging methods.
- The method effectively corrects for asymmetries in bobbin-type battery components.
Conclusions:
- The developed pseudo-cylindrical coordinate method enhances the analysis of CT data for bobbin-type batteries.
- This approach facilitates better comparison between experimental CT data and computational battery models.
- Accurate radial analysis is vital for optimizing battery performance and design.


