Abstract

The goal of this work is to further understand the relationships between porous electrode microstructure and mass transport properties. This understanding allows us to predict and improve cell performance from fundamental principles. The investigated battery systems are the widely used rechargeable Li-ion battery and the non-rechargeable alkaline battery. This work includes three main contributions in the battery field listed below.

Direct Measurement of Effective Electronic Transport in Porous Li-ion Electrodes. An accurate assessment of the electronic conductivity of electrodes is necessary for understanding and optimizing battery performance. The bulk electronic conductivity of porous LiCoO2-based cathodes was measured as a function of porosity, pressure, carbon fraction, and the presence of an electrolyte. The measurements were performed by delamination of thin-film electrodes from their aluminum current collectors and by use of a four-line probe.

Imaging and Correlating Microstructure To Conductivity. Transport properties of porous electrodes are strongly related to microstructure. An experimental 3D microstructure is needed not only for computation of direct transport properties, but also for a detailed electrode microstructure characterization. This work utilized X-ray tomography and focused ion beam (FIB)/scanning electron microscopy (SEM) to obtain the 3D structures of alkaline battery cathodes. FIB/SEM has the advantage of detecting carbon additives; thus, it was the main tomography tool employed. Additionally, protocols and techniques for acquiring, processing and segmenting series of FIB/SEM images were developed as part of this work. FIB/SEM images were also used to correlate electrodes' microstructure to their respective conductivities for both Li-ion and alkaline batteries.

Electrode Microstructure Metrics and the 3D Stochastic Grid Model. A detailed characterization of microstructure was conducted in this work, including characterization of the volume fraction, nearest neighbor probability, domain size distribution, shape factor, and Fourier transform coefficient. These metrics are compared between 2D FIB/SEM, 3D FIB/SEM and X-ray structures. Among those metrics, the first three metrics are used as a basis for SG model parameterization. The 3D stochastic grid (SG) model is based on Monte Carlo techniques, in which a small set of fundamental inter-domain parameters are used to generate structures. This allows us to predict electrode microstructure and its effects on both electronic and ionic properties.

Degree

PhD

College and Department

Ira A. Fulton College of Engineering and Technology; Chemical Engineering

Rights

http://lib.byu.edu/about/copyright/

Date Submitted

2015-03-01

Document Type

Dissertation

Handle

http://hdl.lib.byu.edu/1877/etd7702

Keywords

Li-ion battery, alkaline battery, electronic conductivity, microstructure, FIB/SEM, stochastic grid model

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