Tool for Tortuosity Estimation in Lithium Ion Battery Porous Electrodes

We present an open source software application “BruggemanEstimator” that allows a user to estimate the tortuosity of a porous electrode. BruggemanEstimator determines the Bruggeman exponent based on the Differential Effective Medium approximation and as input requires only two microscope images: one of the top and one of a cross section through an electrode. These images, which can be easily acquired with a scanning electron or optical microscope, are used to extract a sampling of active particle shapes as well as the orientation of the particles within the electrode. We validate the accuracy of BruggemanEstimator by comparing the estimated Bruggeman exponents to values calculated by performing numerical diffusion simulations on three-dimensional microstructures obtained from tomographic techniques. © The Author(s) 2014. Published by ECS. This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives 4.0 License (CC BY-NC-ND, http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is not changed in any way and is properly cited. For permission for commercial reuse, please email: oa@electrochem.org. [DOI: 10.1149/2.0111502jes] All rights reserved.

[1]  S. Torquato.  Random Heterogeneous Materials , 2002 .

[2]  Martin Ebner,et al.  Validity of the Bruggeman relation for porous electrodes , 2013 .

[3]  Johannes E. Schindelin,et al.  Fiji: an open-source platform for biological-image analysis , 2012, Nature Methods.

[4]  Moses Ender,et al.  Quantitative Characterization of LiFePO4 Cathodes Reconstructed by FIB/SEM Tomography , 2012 .

[5]  Michael Unser,et al.  A pyramid approach to subpixel registration based on intensity , 1998, IEEE Trans. Image Process..

[6]  F. Marone,et al.  X‐Ray Tomography of Porous, Transition Metal Oxide Based Lithium Ion Battery Electrodes , 2013 .

[7]  M. E. Muller,et al.  A Note on the Generation of Random Normal Deviates , 1958 .

[8]  Martin Ebner,et al.  Tortuosity Anisotropy in Lithium‐Ion Battery Electrodes , 2014 .

[9]  S. Torquato,et al.  Random Heterogeneous Materials: Microstructure and Macroscopic Properties , 2005 .

[10]  Nigel P. Brandon,et al.  Local Tortuosity Inhomogeneities in a Lithium Battery Composite Electrode , 2011 .

[11]  Yet-Ming Chiang,et al.  An Analytical Method to Determine Tortuosity in Rechargeable Battery Electrodes , 2012 .

[12]  Ralph E. White,et al.  Comparison between Computer Simulations and Experimental Data for High-Rate Discharges of Plastic Lithium-Ion Batteries , 2000 .

[13]  Peng Lu,et al.  Effects of Inhomogeneities—Nanoscale to Mesoscale—on the Durability of Li-Ion Batteries , 2013 .

[14]  M. Smoluchowski.  Zur kinetischen Theorie der Brownschen Molekularbewegung und der Suspensionen , 1906 .

[15]  A. Einstein.  Über die von der molekularkinetischen Theorie der Wärme geforderte Bewegung von in ruhenden Flüssigkeiten suspendierten Teilchen [AdP 17, 549 (1905)] , 2005, Annalen der Physik.

[16]  K. Zaghib,et al.  Quantifying tortuosity in porous Li-ion battery materials , 2009 .

[17]  D. A. G. Bruggeman.  Berechnung verschiedener physikalischer Konstanten von heterogenen Substanzen. I. Dielektrizitätskonstanten und Leitfähigkeiten der Mischkörper aus isotropen Substanzen , 1935 .

[18]  D. Wheeler,et al.  A Combination of X‐Ray Tomography and Carbon Binder Modeling: Reconstructing the Three Phases of LiCoO2 Li‐Ion Battery Cathodes , 2014 .

[19]  D. Wheeler,et al.  FIB/SEM-based calculation of tortuosity in a porous LiCoO2 cathode for a Li-ion battery , 2013 .

[20]  Norman Epstein,et al.  On tortuosity and the tortuosity factor in flow and diffusion through porous media , 1989 .