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Research Data if the Publication "Analyzing and improving conductive networks in commercial high-energy Ni-rich cathodes"

Lindner, Adrian 1; Menesklou, Wolfgang 1; Krewer, Ulrike ORCID iD icon 1; Both, Svenja 2,3; Hein, Simon 2,3; Danner, Timo 2,3; Latz, Arnulf 2,3
1 Institut für Angewandte Materialien – Elektrochemische Technologien (IAM-ET1), Karlsruher Institut für Technologie (KIT)
2 Helmholtz-Institut Ulm (HIU), Karlsruher Institut für Technologie (KIT)
3 Deutsches Zentrum für Luft- und Raumfahrt (DLR)

Abstract:

Nickel-rich stoichiometries such as NMC811 have gained increasing relevance for lithium-ion-batteries in recent years due to their high specific capacity and reduced use of critical resources. However, low intrinsic electronic conductivity of NMC active materials makes the use of carbon-based additives necessary. Volume fraction and distribution of the carbon-binder-domain (CBD) have a significant impact on the electrode performance. This work combines high-resolution tomography and microstructure-resolved simulations to characterize the three-dimensional transport networks of a commercial NMC811 cathode. FIB-SEM tomography reveals that low CBD volume fractions with suboptimal distribution cause a non-percolating conductive network in the microstructure and thus unfavourably low electronic conductivity. Increasing the CBD content through virtual electrode design enables percolation and enhances electronic conductivity fundamentally. Simulations on both the real and virtually designed structures demonstrate how percolating CBD networks lead to a significantly improved energy density.


Zugehörige Institution(en) am KIT Institut für Angewandte Materialien – Elektrochemische Technologien (IAM-ET1)
Publikationstyp Forschungsdaten
Publikationsdatum 17.12.2024
Erstellungsdatum 25.07.2024
Identifikator DOI: 10.35097/hsHzwAgynDovbKTU
KITopen-ID: 1000172805
Lizenz Creative Commons Namensnennung – Weitergabe unter gleichen Bedingungen 4.0 International
Liesmich

Full research data is provided for figures 2c, 3, 5, S2, S3 and S4. Large 3D datasets are available upon request. Discharge curves (experimental and simulation) are provided with cell potential, time and areal discharge capacity.

Art der Forschungsdaten Dataset
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