Stochastic 3D Reconstruction of Cracked Polycrystalline NMC Particles Using 2D SEM Data: Article No. 232

Research output: Contribution to journalArticlepeer-review

Abstract

Li-ion battery performance is strongly influenced by the 3D microstructure of its cathode particles. Cracks within these particles develop during calendaring and cycling, reducing connectivity but increasing reactive surface, making their impact on battery performance complex. Understanding these contradictory effects requires a quantitative link between particle morphology and battery performance. However, informative 3D imaging techniques are time-consuming, costly and rarely available, such that analyses often have to rely on 2D image data. This paper presents a novel stereological approach for generating virtual 3D cathode particles exhibiting crack networks that are statistically equivalent to those observed in 2D sections of experimentally measured particles. Consequently, 2D image data suffices for deriving a full 3D characterization of cracked cathodes particles. Such virtually generated 3D particles could serve as geometry input for spatially resolved electro-chemo-mechanical simulations to enhance our understanding of structure-property relationships of cathodes in Li-ion batteries.
Original languageAmerican English
Number of pages16
Journal n p j Computational Materials
Volume11
DOIs
StatePublished - 2025

NLR Publication Number

  • NREL/JA-5700-92588

Keywords

  • active material
  • cathode
  • crack morphology
  • lithium-ion battery
  • NMC particle
  • stereological 3D reconstruction
  • stochastic crack network model

Fingerprint

Dive into the research topics of 'Stochastic 3D Reconstruction of Cracked Polycrystalline NMC Particles Using 2D SEM Data: Article No. 232'. Together they form a unique fingerprint.

Cite this