Effective Electronic and Ionic Conductivities of Dense EV-Designed NMC-Based Positive Electrodes using Fourier Based Numerical Simulations on FIB/SEM Volumes

Experimental conductivity measurements, obtained on NMC532-based electrodes with markedly different porosities and made with percolating and non-percolating CB/PVdF phase, are compared with full-field numerical predictions. These ones are based on segmented nanotomography images and phase bulk properties and contain no tunable parameter. A good agreement between the calculated and measured transport properties is observed. 3D current density fields give insights on the microstructure impacts on the current density distribution. Ionic transport is dominated by low tortuosity micrometric channels. Results also highlight the presence of “dead areas” in porosity that are crossed by a very low ionic current showing that, at high rate, the effective porosity may reduce to the micrometric pore network. For electronic conductivity, the CB/PVdF mixture percolation threshold is evaluated at 6-7 % in volume. Even below this key value threshold, CB/PVdF aggregates significantly improve electronic conductivity by forming gateways between NMC clusters thus minimising the constriction resistances between them. The size of the representative volume element relative to electronic and ionic conductivities is also investigated.

[1]  C. Delacourt,et al.  The electrode tortuosity factor: why the conventional tortuosity factor is not well suited for quantifying transport in porous Li-ion battery electrodes and what to use instead , 2020, npj Computational Materials.

[2]  E. Maire,et al.  Multiscale Characterization of Composite Electrode Microstructures for High Density Lithium-ion Batteries Guided by the Specificities of Their Electronic and Ionic Transport Mechanisms , 2020, Journal of The Electrochemical Society.

[3]  Victor E. Brunini,et al.  Electrode Mesoscale as a Collection of Particles: Coupled Electrochemical and Mechanical Analysis of NMC Cathodes , 2020 .

[4]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[5]  U. Krewer,et al.  Joint structural and electrochemical modeling: Impact of porosity on lithium-ion battery performance , 2019, Electrochimica Acta.

[6]  E. Maire,et al.  Numerical Prediction of Multiscale Electronic Conductivity of Lithium-Ion Battery Positive Electrodes , 2019, Journal of The Electrochemical Society.

[7]  A. Kwade,et al.  Numerical simulation of the behavior of lithium-ion battery electrodes during the calendaring process via the discrete element method , 2019, Powder Technology.

[8]  B. Polzin,et al.  Quantifying Reaction and Rate Heterogeneity in Battery Electrodes in 3D through Operando X-ray Diffraction Computed Tomography. , 2019, ACS applied materials & interfaces.

[9]  F. Willot,et al.  Stochastic 3D Modeling of Three-Phase Microstructures for Predicting Transport Properties: A Case Study , 2019, Transport in Porous Media.

[10]  M. Schneider On the Barzilai‐Borwein basic scheme in FFT‐based computational homogenization , 2019, International Journal for Numerical Methods in Engineering.

[11]  D. Jeulin,et al.  Thermoelastic properties of microcracked polycrystals. Part I: Adequacy of Fourier-based methods for cracked elastic bodies , 2018, International Journal of Solids and Structures.

[12]  Andrew M. Colclasure,et al.  Resolving the discrepancy in tortuosity factor estimation for Li-Ion battery electrodes through micro-macro modeling and experiment , 2018 .

[13]  Marie Francine Lagadec,et al.  Topological and Network Analysis of Lithium Ion Battery Components: The Importance of Pore Space Connectivity for Cell Operation , 2018, 1806.00083.

[14]  Bernhard Tjaden,et al.  Tortuosity in electrochemical devices: a review of calculation approaches , 2018 .

[15]  K. Smith,et al.  Secondary-Phase Stochastics in Lithium-Ion Battery Electrodes. , 2018, ACS applied materials & interfaces.

[16]  Garima Shukla,et al.  Multiscale Simulation Platform Linking Lithium Ion Battery Electrode Fabrication Process with Performance at the Cell Level. , 2017, The journal of physical chemistry letters.

[17]  J. Vondrejc,et al.  Energy-based comparison between the Fourier-Galerkin method and the finite element method , 2017, J. Comput. Appl. Math..

[18]  B. Lestriez,et al.  Electronic and Ionic Dynamics Coupled at Solid–Liquid Electrolyte Interfaces in Porous Nanocomposites of Carbon Black, Poly(vinylidene fluoride), and γ-Alumina , 2017 .

[19]  Thierry Douillard,et al.  Multiscale Morphological and Electrical Characterization of Charge Transport Limitations to the Power Performance of Positive Electrode Blends for Lithium‐Ion Batteries , 2017 .

[20]  M. Schneider,et al.  FFT‐based homogenization for microstructures discretized by linear hexahedral elements , 2017 .

[21]  Matti Schneider,et al.  An FFT-based fast gradient method for elastic and inelastic unit cell homogenization problems , 2017 .

[22]  Gen Inoue,et al.  Numerical and experimental evaluation of the relationship between porous electrode structure and effective conductivity of ions and electrons in lithium-ion batteries , 2017 .

[23]  Z. Ogumi,et al.  Visualization of Inhomogeneous Reaction Distribution in the Model LiCoO2 Composite Electrode of Lithium Ion Batteries , 2017 .

[24]  A. Latz,et al.  Thick electrodes for Li-ion batteries: A model based analysis , 2016 .

[25]  Xianghui Xiao,et al.  Three-dimensional finite element study on stress generation in synchrotron X-ray tomography reconstructed nickel-manganese-cobalt based half cell , 2016 .

[26]  B. Lestriez,et al.  Interest in broadband dielectric spectroscopy to study the electronic transport in materials for lithium batteries , 2016 .

[27]  Julien Yvonnet,et al.  Multiscale modeling of microstructure–property relations , 2016 .

[28]  Dominique Jeulin,et al.  Morphological modeling of three-phase microstructures of anode layers using SEM images , 2017 .

[29]  T. Masese,et al.  Ionic Conduction in Lithium Ion Battery Composite Electrode Governs Cross-sectional Reaction Distribution , 2016, Scientific Reports.

[30]  N. Besnard Etude des propriétés de transport des charges aux différentes échelles d'une électrode de batterie lithium-ion et de leurs influences sur les performances en puissance pour l'application véhicule électrique , 2016 .

[31]  Victor E. Brunini,et al.  Mechanical and electrochemical response of a LiCoO2 cathode using reconstructed microstructures , 2016 .

[32]  M. Geers,et al.  A finite element perspective on nonlinear FFT‐based micromechanical simulations , 2016, 1601.05970.

[33]  M. Wagemaker,et al.  Direct Observation of Li‐Ion Transport in Electrodes under Nonequilibrium Conditions Using Neutron Depth Profiling , 2015 .

[34]  D. Wheeler,et al.  Three‐Phase Multiscale Modeling of a LiCoO2 Cathode: Combining the Advantages of FIB–SEM Imaging and X‐Ray Tomography , 2015 .

[35]  K. Schladitz,et al.  Multiscale simulation process and application to additives in porous composite battery electrodes , 2015 .

[36]  Tsuyoshi Sasaki,et al.  Impedance Spectroscopy Characterization of Porous Electrodes under Different Electrode Thickness Using a Symmetric Cell for High-Performance Lithium-Ion Batteries , 2015 .

[37]  Z. Ogumi,et al.  X-ray absorption fine structure imaging of inhomogeneous electrode reaction in LiFePO 4 lithium-ion battery cathode , 2014 .

[38]  V. Schmidt,et al.  Quantitative relationships between microstructure and effective transport properties based on virtual materials testing , 2014 .

[39]  Andrew L. Hector,et al.  Direct Observation of Active Material Concentration Gradients and Crystallinity Breakdown in LiFePO4 Electrodes During Charge/Discharge Cycling of Lithium Batteries , 2014, The journal of physical chemistry. C, Nanomaterials and interfaces.

[40]  A. Boulineau,et al.  Multiscale phase mapping of LiFePO4-based electrodes by transmission electron microscopy and electron forward scattering diffraction. , 2013, ACS nano.

[41]  D. Guyomard,et al.  Multiscale electronic transport in Li(1+x)Ni(1/3-u)Co(1/3-v)Mn(1/3-w)O2: a broadband dielectric study from 40 Hz to 10 GHz. , 2013, Physical chemistry chemical physics : PCCP.

[42]  F. Willot,et al.  Fourier‐based schemes with modified Green operator for computing the electrical response of heterogeneous media with accurate local fields , 2013, 1307.1015.

[43]  Xiangyun Song,et al.  Cooperation between Active Material, Polymeric Binder and Conductive Carbon Additive in Lithium Ion Battery Cathode , 2012 .

[44]  Dominique Guyomard,et al.  Multiscale electronic transport mechanism and true conductivities in amorphous carbon–LiFePO4 nanocomposites , 2012 .

[45]  D. Stephenson,et al.  Modeling 3D Microstructure and Ion Transport in Porous Li-Ion Battery Electrodes , 2011 .

[46]  Paul W. J. Glover,et al.  A generalized Archie’s law for n phases , 2010 .

[47]  Thomas J. Richardson,et al.  Visualization of Charge Distribution in a Lithium Battery Electrode , 2010 .

[48]  B. Lestriez,et al.  A Multiscale Description of the Electronic Transport within the Hierarchical Architecture of a Composite Electrode for Lithium Batteries , 2009 .

[49]  Charles W. Monroe,et al.  Direct in situ measurements of Li transport in Li-ion battery negative electrodes , 2009 .

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

[51]  Ann Marie Sastry,et al.  Selection of Conductive Additives in Li-Ion Battery Cathodes A Numerical Study , 2007 .

[52]  D. Guyomard,et al.  Critical Role of Polymeric Binders on the Electronic Transport Properties of Composites Electrode , 2006 .

[53]  N. Baffier,et al.  Dielectric and conductivity spectroscopy of Li1−xNi1+xO2 in the range of 10–1010 Hz: polaron hopping , 2002 .

[54]  Graeme W. Milton,et al.  A fast numerical scheme for computing the response of composites using grid refinement , 1999 .

[55]  M. Doyle,et al.  Modeling of Galvanostatic Charge and Discharge of the Lithium/Polymer/Insertion Cell , 1993 .

[56]  D. Wheeler,et al.  Quantifying Tortuosity of Porous Li-Ion Battery Electrodes: Comparing Polarization-Interrupt and Blocking-Electrolyte Methods , 2018 .

[57]  David R. Noble,et al.  Editors' Choice—Mesoscale Analysis of Conductive Binder Domain Morphology in Lithium-Ion Battery Electrodes , 2018 .

[58]  V. Battaglia,et al.  Comparing Macroscale and Microscale Simulations of Porous Battery Electrodes , 2017 .

[59]  Hajime Arai,et al.  Factors determining the packing-limitation of active materials in the composite electrode of lithium-ion batteries , 2016 .

[60]  S. Roberts,et al.  Conductivity degradation of polyvinylidene fluoride composite binder during cycling: Measurements and simulations for lithium-ion batteries , 2016 .

[61]  Hubert A. Gasteiger,et al.  Tortuosity Determination of Battery Electrodes and Separators by Impedance Spectroscopy , 2016 .

[62]  P. Soudan,et al.  An In Situ Multiscale Study of Ion and Electron Motion in a Lithium‐Ion Battery Composite Electrode , 2015 .

[63]  Roland Zengerle,et al.  Three-dimensional electrochemical Li-ion battery modelling featuring a focused ion-beam/scanning electron microscopy based three-phase reconstruction of a LiCoO2 cathode , 2014 .

[64]  Steen B. Schougaard,et al.  Effective Transport Properties of Porous Electrochemical Materials — A Homogenization Approach , 2014 .

[65]  D. Stephenson,et al.  Direct Measurements of Effective Ionic Transport in Porous Li-Ion Electrodes , 2013 .

[66]  Stefan Pischinger,et al.  Percolation–tunneling modeling for the study of the electric conductivity in LiFePO4 based Li-ion battery cathodes , 2011 .

[67]  M. Doyle,et al.  Simulation and Optimization of the Dual Lithium Ion Insertion Cell , 1994 .

[68]  M. Wühr,et al.  The Influence of Water on the Cycleability of Lithium in 2‐Methyltetrahydrofuran‐Based Electrolytes , 1993 .

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

[70]  E. Kröner Statistical continuum mechanics , 1971 .