Neutron Depth Profiling: Following the Lithium Distribution in Rechargeable Batteries

The sustainable energy transition relies on energy storage technology. Crucial to meet the ever increasing energy storage demand is profound understanding of the governing processes. Yet, due to the inherent difficulty to study light ions with conventional techniques, limited methodology is available for operando monitoring of lithium ion batteries. A non-invasive and versatile alternative is Neutron Depth Profiling(NDP). This technique provides information on the spatial and temporal lithium concentration during (dis)charge. In this work NDP is used to shed light on key challenges for lithium ion batteries. The results provide detailed understanding of electrode parameters such as tortuosity and Li-ion transport. This allows to reduce the battery internal resistance or increase charging current, thereby reducing charge times. Post lithium ion battery technology relies on a reversible lithium-metal anode, this would enable batteries based on the conversion reaction of lithium with oxygen or sulfur. Furthermore, a lithium metal anode can double pack level energy density when employing current cathodes. Using NDP, we can monitor the lithium concentration profile as the material is plated. This allows to study the dependency with respect to current density, electrolyte composition and cycling history. Moreover NDP allows to follow lithium independent of oxidation state. Hence enabling to monitor battery failure originating from lithium polysulfide dissolution in the liquid electrolyte. The findings as presented rationalize electrode design towards high energy-dense, safe and low-cost Li-S batteries. The thesis concludes with a revolutionary concept based on a gas filled gridpix time projection chamber. A gridpix detector allows a 3D particle trace reconstruction. Hence a 3D spatial isotope specific, lithium-6, distribution is obtained. This technique would cater for a whole new range of topics to study.