Ziesche, R.F.; Heenan, T.M.M.; Kumari, P.; Williams, J.; Li, W.; Curd, M.E.; Burnett, T.L.; Robinson, I.; Brett, D.J.L.; Ehrhardt, M.J.; Quinn, P.D.; Mehdi, L.B.; Withers, P.J.; Britton, M.M.; Browning, N.D.; Shearing, P.R.: Multi-Dimensional Characterization of Battery Materials. Advanced Energy Materials 13 (2023), p. 2300103/1-20
10.1002/aenm.202300103
Open Access Version
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.