Quantitative Relationships Between Pore Tortuosity, Pore Topology, and Solid Particle Morphology Using a Novel Discrete Particle Size Algorithm

To sustain the continuous high-rate charge current required for fast charging of electric vehicle batteries, the ionic effective diffusion coefficient of the electrodes must be high enough to avoid the electrode being transport limited. Tortuosity factor and porosity are the two microstructure parameters that control this effective diffusion coefficient. While different methods exist to experimentally measure or calculate the tortuosity factor, no generic relationship between tortuosity and microstructure presently exists that is applicable across a large variety of electrode microstructures and porosities. Indeed, most relationships are microstructure specific. In this work, generic relationships are established using only geometrically defined metrics that can thus be used to design thick electrodes suitable for fast charging. To achieve this objective, an original, discrete particle-size algorithm is introduced and used to identify and segment particles across a set of 19 various electrode microstructures (nickel-manganese-cobalt [NMC] and graphite) obtained from X-ray computed tomography (CT) to quantify parameters such as porosity, particle elongation, sinuosity, and constriction, which influence the effective diffusion coefficient. Compared to the widely used watershed method, the new algorithm shows less over-segmentation. Particle size obtained with different numerical methods is also compared. Lastly, microstructure-tortuosity relationship and particle size and morphology analysis methods are reviewed

Resolving the Discrepancy in Tortuosity Factor Estimation for Li-Ion Battery Electrodes through Micro-Macro Modeling and Experiment

Battery performance is strongly correlated with electrode microstructural properties. Of the relevant properties, the tortuosity factor of the electrolyte transport paths through microstructure pores is important as it limits battery maximum charge/discharge rate, particularly for energy-dense thick electrodes. Tortuosity factor however, is difficult to precisely measure, and thus its estimation has been debated frequently in the literature. Herein, three independent approaches have been applied to quantify the tortuosity factor of lithium-ion battery electrodes. The first approach is a microstructure model based on three-dimensional geometries from X-ray computed tomography (CT) and stochastic reconstructions enhanced with computationally generated carbon/binder domain (CBD), as CT is often unable to resolve the CBD. The second approach uses a macro-homogeneous model to fit electrochemical data at several rates, providing a separate estimation of the tortuosity factor. The third approach experimentally measures tortuosity factor via symmetric cells employing a blocking electrolyte. Comparisons have been made across the three approaches for 14 graphite and nickel-manganese-cobalt oxide electrodes. Analysis suggests that if the tortuosity factor were characterized based on the active material skeleton only, the actual tortuosities would be 1.35–1.81 times higher for calendered electrodes. Correlations are provided for varying porosity, CBD phase interfacial arrangement and solid particle morphology

Resolving the discrepancy in tortuosity factor estimation for Li-Ion battery electrodes through micro-macro modeling and experiment

Battery performance is strongly correlated with electrode microstructural properties. Of the relevant properties, the tortuosity factor of the electrolyte transport paths through microstructure pores is important as it limits battery maximum charge/discharge rate, particularly for energy-dense thick electrodes. Tortuosity factor however, is difficult to precisely measure, and thus its estimation has been debated frequently in the literature. Herein, three independent approaches have been applied to quantify the tortuosity factor of lithium-ion battery electrodes. The first approach is a microstructure model based on three-dimensional geometries from X-ray computed tomography (CT) and stochastic reconstructions enhanced with computationally generated carbon/binder domain (CBD), as CT is often unable to resolve the CBD. The second approach uses a macro-homogeneous model to fit electrochemical data at several rates, providing a separate estimation of the tortuosity factor. The third approach experimentally measures tortuosity factor via symmetric cells employing a blocking electrolyte. Comparisons have been made across the three approaches for 14 graphite and nickel-manganese-cobalt oxide electrodes. Analysis suggests that if the tortuosity factor were characterized based on the active material skeleton only, the actual tortuosities would be 1.35–1.81 times higher for calendered electrodes. Correlations are provided for varying porosity, CBD phase interfacial arrangement and solid particle morphology