Microstructure Reconstruction of Battery Polymer Separators by Fusing 2D and 3D Image Data for Transport Property Analysis

Hongyi Xu, Francois Usseglio-Viretta, Steven Kench, Samuel Cooper, Donal Finegan

Research output: Contribution to journalArticlepeer-review

25 Scopus Citations

Abstract

A new approach to generate high-fidelity 3D microstructure reconstructions by leveraging resolution and sample volume characteristics from 2D and 3D microscopy methods is presented. This approach is employed to model the microstructure of a highly orthotropic polypropylene separator used in lithium-ion batteries, which have challenging multi-scale features of fibrils (<100 nm) and lamellae (>100 nm) to resolve in 3D. Phase contrast nano X-ray computed tomographic data are used to reconstruct the lamellae phase, while 2D scanning electron microscopy data are used to characterize sub-100 nm microstructure features such as the thin fibrils that are beyond the effective resolution of X-ray computed tomography. Fibril geometries are reconstructed stochastically based on the 2D higher resolution data, and integrated with the lamellae geometries in 3D space. Transport property analyses are performed to investigate the bias of microstructure models without considering the fibrils. A sensitivity study is also conducted to facilitate understanding of the relationship between microstructure characteristics and transport properties.

Original languageAmerican English
Article number229101
Number of pages9
JournalJournal of Power Sources
Volume480
DOIs
StatePublished - 31 Dec 2020

Bibliographical note

Publisher Copyright:
© 2020 Elsevier B.V.

NREL Publication Number

  • NREL/JA-5700-77860

Keywords

  • Data fusion
  • Microstructure
  • RVE
  • Separator
  • Stochastic reconstruction
  • Transport property

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