Julian Feinauer

Quantifying microstructural dynamics and electrochemical activity of graphite and silicon-graphite lithium ion battery anodes

Despite numerous studies presenting advances in tomographic imaging and analysis of lithium ion batteries, graphite-based anodes have received little attention. Weak X-ray attenuation of graphite and, as a result, poor contrast between graphite and the other carbon-based components in an electrode pore space renders data analysis challenging. Here we demonstrate operando tomography of weakly attenuating electrodes during electrochemical (de)lithiation. We use propagation-based phase contrast tomography to facilitate the differentiation between weakly attenuating materials and apply digital volume correlation to capture the dynamics of the electrodes during operation. After validating that we can quantify the local electrochemical activity and microstructural changes throughout graphite electrodes, we apply our technique to graphite-silicon composite electrodes. We show that microstructural changes that occur during (de)lithiation of a pure graphite electrode are of the same order of magnitude as spatial inhomogeneities within it, while strain in composite electrodes is locally pronounced and introduces significant microstructural changes.

Preparation and Characterization of Li-Ion Graphite Anodes Using Synchrotron Tomography

We present an approach for multi-layer preparation to perform microstructure analysis of a Li-ion cell anode active material using synchrotron tomography. All necessary steps, from the disassembly of differently-housed cells (pouch and cylindrical), via selection of interesting layer regions, to the separation of the graphite-compound and current collector, are described in detail. The proposed stacking method improves the efficiency of synchrotron tomography by measuring up to ten layers in parallel, without the loss of image resolution nor quality, resulting in a maximization of acquired data. Additionally, we perform an analysis of the obtained 3D volumes by calculating microstructural characteristics, like porosity, tortuosity and specific surface area. Due to a large amount of measurable layers within one stacked sample, differences between aged and pristine material (e.g., significant differences in tortuosity and specific surface area, while porosity remains constant), as well as the homogeneity of the material within one cell could be recognized.

A New Method for Quantitative Marking of Deposited Lithium by Chemical Treatment on Graphite Anodes in Lithium-Ion Cells

A novel approach for the marking of deposited lithium on graphite anodes from large automotive lithium-ion cells (≥6 Ah) is presented. Graphite anode samples were extracted from two different formats (cylindrical and pouch cells) of pristine and differently aged lithium-ion cells. The samples present a variety of anodes with various states of lithium deposition (also known as plating). A chemical modification was performed to metallic lithium deposited on the anode surface due to previous plating with isopropanol (IPA). After this procedure an oxygenated species was detected by scanning electron microscopy (SEM), which later was confirmed as Li2 CO3 by Fourier transform infrared spectroscopy (FTIR) and X-ray powder diffraction (XRPD). A valuation of the covered area by Li2 CO3 was carried out with an image analysis using energy-dispersive X-ray spectroscopy (EDX) and quantitative Rietveld refinement.

Analysis, Modeling and Simulation of Tomographic Image Data for the 3D Microstructure of Electrode Material in Lithium-Ion Batteries

Abstract This article describes stochastic 3D structure models for electrodes of lithium-ion batteries, which can be used for model-based optimization of the electrode morphology. First, a single particle model is presented which can be used to parametrically describe individual particles from 3D tomographic image data. By fitting parametrical distributions it is therefore also possible to simulate (statistically similar) particles. Hereafter, different approaches for the arrangement of individual particles in the observation window are presented, so that system-based properties of different electrode types can be approximately matched (e. g. the connectivity of the particle system as well as the structure of the pore space). Finally, algorithms for the automatic recognition of particle cracks in tomographic image data are presented which can be used to integrate ageing effects into the models.

MULTIBAT: Unified workflow for fast electrochemical 3D simulations of lithium-ion cells combining virtual stochastic microstructures, electrochemical degradation models and model order reduction

We present a simulation workflow for efficient investigations of the interplay between 3D lithium-ion electrode microstructures and electrochemical performance, with emphasis on lithium plating. Our approach addresses several challenges. First, the 3D microstructures of porous electrodes are generated by a parametric stochastic model, in order to significantly reduce the necessity of tomographic imaging. Secondly, we integrate a consistent microscopic, 3D spatially-resolved physical model for the electrochemical behavior of the lithium-ion cells taking lithium plating and stripping into account. This highly non-linear mathematical model is solved numerically on the complex 3D microstructures to compute the transient cell behavior. Due to the complexity of the model and the considerable size of realistic microstructures even a single charging cycle of the battery requires several hours computing time. This renders large scale parameter studies extremely time consuming. Hence, we develop a mathematical model order reduction scheme. We demonstrate how these aspects are integrated into one unified workflow, which is a step towards computer aided engineering for the development of more efficient lithium-ion cells.

3D Microstructure Modeling and Simulation of Materials in Lithium-ion Battery Cells

The microstructure of lithium-ion battery electrodes has a major influence on the performance and durability of lithium-ion batteries. In this paper, an overview of a general framework for the simulation of battery electrode microstructures is presented. A multistep approach is used for the generation of such particle-based materials. First, a ‘host lattice’ for the coarse structure of the material and the placement of particles is generated. Then, several application-specific rules, which, e.g., influence connectivity are implemented. Finally, the particles are simulated using Gaussian random fields on the sphere. To show the broad applicability of this approach, three different applications of the general framework are discussed, which allow to model the microstructure of anodes of energy and power cells as well as of cathodes of energy cells. Finally, the validation of such models as well as applications together with electrochemical transport simulation are presented.