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Comparison of three‐dimensional analysis and stereological techniques for quantifying lithium‐ion battery electrode microstructures
Authors:OLUWADAMILOLA O. TAIWO  DONAL P. FINEGAN  DAVID S. EASTWOOD  JULIE L. FIFE  LEON D. BROWN  JAWWAD A. DARR  PETER D. LEE  DANIEL J.L. BRETT  PAUL R. SHEARING
Affiliation:1. The Electrochemical Innovation Lab, Department of Chemical Engineering, University College London, London, U.K.;2. Manchester X‐Ray Imaging Facility, School of Materials, University of Manchester, Manchester M13 9PL, U.K.;3. Swiss Light Source, Paul Scherrer Institut, Switzerland;4. Department of Chemistry, University College London, London, U.K.
Abstract:Lithium‐ion battery performance is intrinsically linked to electrode microstructure. Quantitative measurement of key structural parameters of lithium‐ion battery electrode microstructures will enable optimization as well as motivate systematic numerical studies for the improvement of battery performance. With the rapid development of 3‐D imaging techniques, quantitative assessment of 3‐D microstructures from 2‐D image sections by stereological methods appears outmoded; however, in spite of the proliferation of tomographic imaging techniques, it remains significantly easier to obtain two‐dimensional (2‐D) data sets. In this study, stereological prediction and three‐dimensional (3‐D) analysis techniques for quantitative assessment of key geometric parameters for characterizing battery electrode microstructures are examined and compared. Lithium‐ion battery electrodes were imaged using synchrotron‐based X‐ray tomographic microscopy. For each electrode sample investigated, stereological analysis was performed on reconstructed 2‐D image sections generated from tomographic imaging, whereas direct 3‐D analysis was performed on reconstructed image volumes. The analysis showed that geometric parameter estimation using 2‐D image sections is bound to be associated with ambiguity and that volume‐based 3‐D characterization of nonconvex, irregular and interconnected particles can be used to more accurately quantify spatially‐dependent parameters, such as tortuosity and pore‐phase connectivity.
Keywords:Image quantification  lithium‐ion battery  microstructural characterization  stereology  X‐ray tomography  3‐D image analysis
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