Multi-Dimensional Characterization of Battery Materials

Ralf F. Ziesche, Thomas M.M. Heenan, Pooja Kumari, Jarrod Williams, Weiqun Li, Matthew E. Curd, Timothy L. Burnett, Ian Robinson, Dan J.L. Brett, Matthias J. Ehrhardt, Paul D. Quinn, Layla B. Mehdi, Philip J. Withers, Melanie M. Britton, Nigel D. Browning, Paul R. Shearing

Research output: Contribution to journalReview articlepeer-review

14 Citations (SciVal)

Abstract

Demand for low carbon energy storage has highlighted the importance of imaging techniques for the characterization of electrode microstructures to determine key parameters associated with battery manufacture, operation, degradation, and failure both for next generation lithium and other novel battery systems. Here, recent progress and literature highlights from magnetic resonance, neutron, X-ray, focused ion beam, scanning and transmission electron microscopy are summarized. Two major trends are identified: First, the use of multi-modal microscopy in a correlative fashion, providing contrast modes spanning length- and time-scales, and second, the application of machine learning to guide data collection and analysis, recognizing the role of these tools in evaluating large data streams from increasingly sophisticated imaging experiments.

Original languageEnglish
Article number2300103
Number of pages20
JournalAdvanced Energy Materials
Volume13
Issue number23
Early online date1 May 2023
DOIs
Publication statusPublished - 16 Jun 2023

Keywords

  • correlative microscopy
  • in situ imaging
  • Li-ion batteries
  • microscopy
  • multi-dimensional characterization
  • time-resolved

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • General Materials Science

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