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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 summary is machine-generated.

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.

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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.