Causes of binder damage in porous battery electrodes and strategies to prevent it

Foster, Jamie M.; Huang, Xiosong; Jiang, Meng; Chapman, S. Jonathan; Protas, Bartosz; Richardson, Giles

doi:10.1016/j.jpowsour.2017.03.035

Cited by 53 publications

(34 citation statements)

References 37 publications

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“…Despite these advances in 3D imaging and high-resolution mesoscale simulation, most imaging techniques are incapable of distinguishing the conductive binder domain (CBD, which is composed of polyvinylidene fluoride (PVDF) binder and conductive carbon black (CB)) from the void/electrolyte phase. Recent studies have begun to make advancements in resolving the CBD [11,14,17,19,[33][34][35], yet these data are insufficient for mesoscale simulation, either due to resolution or image size. While some have attempted to physically predict the CBD phase [36,37], modelers typically use stochastic or algorithmic approaches to incorporate CBD into image-based mesoscale simulations [19,20,[38][39][40][41][42].…”

Section: Introductionmentioning

confidence: 99%

Mesoscale Effects of Composition and Calendering in Lithium-Ion Battery Composite Electrodes

Trembacki

Noble

Ferraro

et al. 2020

Journal of Electrochemical Energy Conversion and Storage

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Macrohomogeneous battery models are widely used to predict battery performance, necessarily relying on effective electrode properties, such as specific surface area, tortuosity, and electrical conductivity. While these properties are typically estimated using ideal effective medium theories, in practice they exhibit highly non-ideal behaviors arising from their complex mesostructures. In this paper, we computationally reconstruct electrodes from X-ray computed tomography of 16 nickel–manganese–cobalt-oxide electrodes, manufactured using various material recipes and calendering pressures. Due to imaging limitations, a synthetic conductive binder domain (CBD) consisting of binder and conductive carbon is added to the reconstructions using a binder bridge algorithm. Reconstructed particle surface areas are significantly smaller than standard approximations predicted, as the majority of the particle surface area is covered by CBD, affecting electrochemical reaction availability. Finite element effective property simulations are performed on 320 large electrode subdomains to analyze trends and heterogeneity across the electrodes. Significant anisotropy of up to 27% in tortuosity and 47% in effective conductivity is observed. Electrical conductivity increases up to 7.5× with particle lithiation. We compare the results to traditional Bruggeman approximations and offer improved alternatives for use in cell-scale modeling, with Bruggeman exponents ranging from 1.62 to 1.72 rather than the theoretical value of 1.5. We also conclude that the CBD phase alone, rather than the entire solid phase, should be used to estimate effective electronic conductivity. This study provides insight into mesoscale transport phenomena and results in improved effective property approximations founded on realistic, image-based morphologies.

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Section: Introductionmentioning

confidence: 99%

Mesoscale Effects of Composition and Calendering in Lithium-Ion Battery Composite Electrodes

Trembacki

Noble

Ferraro

et al. 2020

Journal of Electrochemical Energy Conversion and Storage

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“…A physical explanation for this binder delamination is provided in[36,37].https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0956792521000292 Downloaded from https://www.cambridge.org/core.…”

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confidence: 99%

Charge transport modelling of Lithium-ion batteries

et al. 2021

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This paper presents the current state of mathematical modelling of the electrochemical behaviour of lithium-ion batteries (LIBs) as they are charged and discharged. It reviews the models developed by Newman and co-workers, both in the cases of dilute and moderately concentrated electrolytes and indicates the modelling assumptions required for their development. Particular attention is paid to the interface conditions imposed between the electrolyte and the active electrode material; necessary conditions are derived for one of these, the Butler–Volmer relation, in order to ensure physically realistic solutions. Insight into the origin of the differences between various models found in the literature is revealed by considering formulations obtained by using different measures of the electric potential. Materials commonly used for electrodes in LIBs are considered and the various mathematical models used to describe lithium transport in them discussed. The problem of upscaling from models of behaviour at the single electrode particle scale to the cell scale is addressed using homogenisation techniques resulting in the pseudo-2D model commonly used to describe charge transport and discharge behaviour in lithium-ion cells. Numerical solution to this model is discussed and illustrative results for a common device are computed.

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“…These surrounding materials put a mechanical constraint on the expansion and contraction of the particles. To study the effect of the binders, the particles are encapsulated by a thin layer of a binder, then the outer surface of the binder is exposed to electrolyte 8,41 . Figure 6A shows the maximum principal stress inside the anode particles as a function of discharge time.…”

Section: Resultsmentioning

confidence: 99%

“…To study the effect of the binders, the particles are encapsulated by a thin layer of a binder, then the outer surface of the binder is exposed to electrolyte. 8,41 Figure 6A shows the maximum principal stress inside the anode particles as a function of discharge time. Although the curves look similar to those without the binder layer, shown in Figure 2C, the level of the maximum principal stress is increased in the presence of the binder.…”

Section: Effect Of Bindermentioning

confidence: 99%

“…Since it is difficult to measure the stress level of the electrode particles by experiment due to the complex structure and small scales involved, theoretical studies are often carried out to understand chemo-mechanical behavior in the active materials. For example, on the single particle level, the effects of particle size, 2 anisotropy of the active material, 3 charge/discharge rates [4][5][6] and binder encapsulation [7][8][9] have all been investigated. To expand the scale of the investigation from the particle level to the cell level, pseudo two-dimensional (P2D) models 10 have been widely used due to their benefits in computational cost.…”

Section: Introductionmentioning

confidence: 99%

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Simultaneous effect of particle size and location on stress development in the electrodes of lithium‐ion batteries

2020

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In this study, stress generation at the electrode in Li-ion batteries was studied using a two-dimensional cell-scale model that includes multiple active particles during galvanostatic discharge. Numerical simulations were performed using an electrochemical-mechanical coupled model to elucidate the simultaneous effects of particle size and location, lithium intercalation kinetics and binder constraints on the stress. The simulation results showed that when different sizes of particle are considered in the electrode, the small particles were discharged more than the large particles, resulting in higher level of stress in the smaller particles. In addition, the closer the particles were located to the separator, the larger the stresses that were developed in those particles. Therefore, a layered structure, where the particle size gradually increases as the distance from the particles to the separator decreases, can alleviate stress on the electrode. When binder constraints were considered for the electrode particles, the stress was increased at the anode and alleviated at the cathode upon discharge. This indicates that the effect of mechanical constraints on stress generation in the particles differs in the lithiation and delithiation process.

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Causes of binder damage in porous battery electrodes and strategies to prevent it

Cited by 53 publications

References 37 publications

Mesoscale Effects of Composition and Calendering in Lithium-Ion Battery Composite Electrodes

Mesoscale Effects of Composition and Calendering in Lithium-Ion Battery Composite Electrodes

Charge transport modelling of Lithium-ion batteries

Simultaneous effect of particle size and location on stress development in the electrodes of lithium‐ion batteries

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