A limitation map of performance for porous electrodes in lithium-ion batteries

Hamed, Hamid; Henderick, Lowie; Choobar, Behnam Ghalami; D’Haen, Jan; Detavernier, Christophe; Hardy, An; Safari, Mohammadhosein

doi:10.1016/j.isci.2021.103496

Cited by 7 publications

(3 citation statements)

References 64 publications

(73 reference statements)

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“…21 The non-ohmic resistance originates from a combination of various phenomena including the charge-transfer at electrode/electrolyte interface and charge transport within the electrolyte as well as the solid-state diffusion of lithium within the active-material particles of the anode and cathode. 22,23 Particularly, the charge-transfer resistance is very sensitive to the slope of OCV ( U SOC ∂ ∂…”

Section: Resultsmentioning

confidence: 99%

Experimental Investigation of a 64 Ah Lithium-Ion Pouch Cell

Hamed,

Choobar,

Hamtaei

et al. 2024

J. Electrochem. Soc.

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This study presents a meticulous investigation and characterization of a 64 Ah commercial lithium-ion pouch cell. Notably, an exhaustive analysis of the cell’s open-circuit voltage and kinetics attributes is conducted, with particular emphasis on the temperature-dependent dynamics. Subsequently, a teardown experiment is performed, offering an incisive insight into the macro-geometrical properties underpinning the cell’s architecture. Further details about the microstructural features and formulation inherent to the cathode and anode are revealed after image processing of the electrodes’ cross sections. The details of cell balancing and cycling window of the electrodes in the pouch cell are determined and discussed based on the open-circuit-voltage measurements of the individual electrodes and a simple optimization algorithm. The methodologies presented in this work are insightful on the characterization and model parametrization of the high-capacity commercial lithium-ion cells.

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Section: Resultsmentioning

confidence: 99%

Experimental Investigation of a 64 Ah Lithium-Ion Pouch Cell

Hamed,

Choobar,

Hamtaei

et al. 2024

J. Electrochem. Soc.

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“…[ 19 ] A summary of the governing equations and the main parameters of the model are summarized in Table S3 and S4, Supporting Information, respectively. In the model‐based polarization analysis, [ 21 ] the share of each physical/chemical phenomenon in the cell polarization is quantified by enabling or disabling its limiting role in the model. Here, disabling a physical phenomenon means excluding its rate‐limiting impact on the electrode performance via increasing its representative coefficient (e.g., rate constant) from the experimentally measured or optimally refined value to a relative infinity.…”

Section: Resultsmentioning

confidence: 99%

Interrelationships among Adjustable Design Parameters and Rate Performance of Porous Electrodes in Lithium‐Ion Batteries

et al. 2023

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A combination of experiments and physics-based modeling is used to highlight the complex interaction among the adjustable design parameters of porous electrodes in determining the capacity and rate performance of lithium-ion batteries (LIBs). A series of 52 LiMn 2 O 4 electrodes are prepared with loading and porosity in the range of 10 to 30 mg cm À2 and 0.2 to 0.5, respectively, and cycled at different C-rates in front of Li. A detailed polarization analysis of the 96 discharge profiles points to the absence of any ubiquitous sharp and universal correlation between the lumped macroscopic indexes such as the electrode thickness and the battery performance. The results call for a careful attention to the nonlinear response of the LIBs to the design variations and the significance of big data analysis to reveal the peculiar interrelationships between the battery performance and the detailed features of the electrodes such as the configuration and spatial distribution of the (in)active particles.

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“…In fact, the insightful and mechanistic understanding on the reaction kinetics related to the high‐level microstructures, particularly the S‐level of ME@AM and the T‐level, is attracting increasing interest today. Development of computational models promotes the interpretation of detailed and multiscale transport mechanisms, [ 143 ] while the emerging characterization tools such as X‐ray nanocomputed tomography (CT) has been used to probe the high‐level structural information of the electrodes even during the electrochemical reaction. [ 144 ] However, the high‐level structure/interface evolution during electrode fabrication is poorly understood, but is significant for the final device performance.…”

Section: Discussionmentioning

confidence: 99%

Rethinking the Electrode Multiscale Microstructures: A Review on Structuring Strategies toward Battery Manufacturing Genome

Zhou

Huang³

et al. 2023

Advanced Energy Materials

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The success of liquid/solid‐state batteries is fundamentally determined by the electrode microstructures, which is particularly true for high‐energy‐density electrodes with either thick configuration or high‐capacity active materials. Unfortunately, high‐energy‐density electrodes usually suffer from fast performance degradation due to various challenging issues in microstructures. Therefore, a better understanding of electrode microstructures and the strategies toward optimizing them are in urgent need by the research community and battery industries. In this review, the authors attempt to rethink and comprehensively understand the multiscale microstructures for particularly thick electrodes and to summarize the corresponding structuring strategies. Specifically, in analogy to proteins, the multiscale electrode microstructures are classified into the primary structures of rigid building blocks, the secondary structures of active material microenvironment, and the tertiary structures of electrode architectures. Meanwhile, the design principles and structuring strategies at different levels of microstructures are detailed with consideration given to efficiency, energy consumption, eco‐friendliness, and scalability. Finally, a concept of a battery manufacturing genome based on structuring strategy profile (similar to amino acid profile) is proposed as the forthcoming opportunity for the future connection of machine learning with battery microstructure optimization, which may promote the development of next‐generation on‐demand batteries.

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A limitation map of performance for porous electrodes in lithium-ion batteries

Cited by 7 publications

References 64 publications

Experimental Investigation of a 64 Ah Lithium-Ion Pouch Cell

Experimental Investigation of a 64 Ah Lithium-Ion Pouch Cell

Interrelationships among Adjustable Design Parameters and Rate Performance of Porous Electrodes in Lithium‐Ion Batteries

Rethinking the Electrode Multiscale Microstructures: A Review on Structuring Strategies toward Battery Manufacturing Genome

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