Real-time 3D imaging of microstructure growth in battery cells using indirect MRI

• Published in: Proceedings of the National Academy of Sciences - PNAS 2016-09, Vol.113 (39), p.10779-10784
• Main Authors: Ilott, Andrew J., Mohammadi, Mohaddese, Chang, Hee Jung, Grey, Clare P., Jerschow, Alexej
• Format: Article
• Language: English
• Subjects: Batteries; charge transport; defects; Electrolytes; Electromagnetism; ENERGY STORAGE; energy storage (including batteries and capacitors); Lithium; materials and chemistry by design; MATERIALS SCIENCE; NMR; Nuclear magnetic resonance; Physical Sciences; Radio frequency; synthesis (novel materials); Three dimensional imaging
• ISSN: 0027-8424; 1091-6490
• DOI: 10.1073/pnas.1607903113

Lithium metal is a promising anode material for Li-ion batteries due to its high theoretical specific capacity and low potential. The growth of dendrites is a major barrier to the development of high capacity, rechargeable Li batteries with lithium metal anodes, and hence, significant efforts have been undertaken to develop new electrolytes and separator materials that can prevent this process or promote smooth deposits at the anode. Central to these goals, and to the task of understanding the conditions that initiate and propagate dendrite growth, is the development of analytical and nondestructive techniques that can be applied in situ to functioning batteries. MRI has recently been demonstrated to provide noninvasive imaging methodology that can detect and localize microstructure buildup. However, until now, monitoring dendrite growth by MRI has been limited to observing the relatively insensitive metal nucleus directly, thus restricting the temporal and spatial resolution and requiring special hardware and acquisition modes. Here, we present an alternative approach to detect a broad class of metallic dendrite growth via the dendrites’ indirect effects on the surrounding electrolyte, allowing for the application of fast 3D ¹H MRI experiments with high resolution. We use these experiments to reconstruct 3D images of growing Li dendrites from MRI, revealing details about the growth rate and fractal behavior. Radiofrequency and static magnetic field calculations are used alongside the images to quantify the amount of the growing structures.