A four parameter model for the solid-electrolyte interphase to predict battery aging during operation

Kolzenberg, Lars von; Stadler, Jochen; Fath, Johannes Philipp; Ecker, Madeleine; Horstmann, Birger; Latz, Arnulf

doi:10.1016/j.jpowsour.2022.231560

Cited by 13 publications

(4 citation statements)

References 55 publications

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“…This will be an essential aspect to consider, and quantify, for future studies on packs or single cells. Recent models (Dubarry et al, 2019;Dubarry and Beck, 2022;von Kolzenberg et al, 2022) are starting to provide information on this impact. Early work showcases an impact resembling kinetic limitations on the NE (RDF GIC on Figure 7).…”

Section: Other Considerationsmentioning

confidence: 99%

Best practices for incremental capacity analysis

Dubarry

Anseán

2022

Front. Energy Res.

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This publication will present best practices for incremental capacity analysis, a technique whose popularity is growing year by year because of its ability to identify battery degradation modes for diagnosis and prognosis. While not complicated in principles, the analysis can often feel overwhelming for newcomers because of contradictory information introduced by ill-analyzed datasets. This work aims to summarize and centralize good practices to provide a strong baseline to start a proper analysis. We will provide general comments on the technique and how to avoid the main pitfalls. We will also discuss the best starting points for the most common battery chemistries such as layered oxides, iron phosphate, spinel or blends for positive electrodes and graphite, silicon oxide, or lithium titanate for negative electrodes. Finally, a set of complete synthetic degradation maps for the most common commercially available chemistries will be provided and discussed to serve as guide for future studies.

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Section: Other Considerationsmentioning

confidence: 99%

Best practices for incremental capacity analysis

Dubarry

Anseán

2022

Front. Energy Res.

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“…Note that while the possibility of a large-scale and porous SEI layer has been previously discussed in some of the SEI growth models, cryo-EM allowed direct observation of this previously proposed SEI structure. 26 , 40 , 41 , 42 Interestingly, instead of both layers forming on the same particle, the compact and extended SEI layers are observed on separate particles. Cryo-EM characterizations of both layers further indicate that the lack of inorganic crystalline SEI particles in extended SEI might be the reason for its poor passivation.…”

Section: Introductionmentioning

confidence: 98%

“…Extended SEI is critical to the battery’s performance as such large-scale SEI growth greatly contributes to the Li inventory loss during cycling and is detrimental to the lithium-ion transport. 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 However, these structures have been previously overlooked because they can be easily removed by the washing and drying sample preparation steps common in other characterization techniques. Cryo-EM is able to preserve the native state of these extended SEI structures by vitrifying the solid-liquid interfacial structures, thus allowing researchers to better probe the nanoscale features at the interface.…”

Section: Introductionmentioning

confidence: 99%

Expanding the cryogenic electron microscopy toolbox to reveal diverse classes of battery solid electrolyte interphase

Mecklenberg¹,

Yuan²,

Wang³

et al. 2022

iScience

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“…Under storage conditions, the literature reports two important observations. The first one is the dependence of capacity loss on the state-of-charge (SOC) [36,37,38,39], and the second one is the square-root behavior in time [40,41,42,43].…”

Section: Introductionmentioning

confidence: 99%