Investigating the Effects of Transport and Mixing on Dendrite Growth in High Energy Density Lithium Batteries

High Energy density lithium (Li) batteries are promising advanced energy technologies for applications in the automotive and portable power markets. Advanced Li batteries have several design and operational challenges to overcome before becoming commercially viable. One of these challenges is the formation of dendrites on the anode surface of the Li-air battery over multiple charge and discharge cycles. Dendrite formation decreases cell performance and causes safety concerns due to short circuiting. In this research computational methods are adopted to investigate the physics of dendrite formation in Li-air batteries and to develop strategies to suppress dendrite growth.

The effects of convection and anisotropic transport properties in the electrolyte on the morphology and growth rate of dendrites are investigated using a two-dimensional (2D) smoothed particle hydrodynamics (SPH) model. SPH is a mesh-free Lagrangian computational fluid dynamics method, which allows for easy implementation of complex physics at the dendrite surface.

Anisotropic diffusion is modeled to study the effects of mixing near the anode-electrolyte interface on dendrite growth. The simulation results suggest that high anisotropy in the electrolyte promotes a robust, compact dendrite structure versus isotropic diffusion cases. Convection effects are also considered to study the electro-osmosis effect on dendrite growth. Circulating flows are included in the model to simulate electro-osmotic flows near the anode-electrolyte interface. The simulation results reveal that the convection effect will increase the mixing near the dendrite and lead to significant changes in dendrite morphology.

The results of these computational studies are being used to develop mitigation strategies for dendrite growth in Li-air batteries. These strategies include the use of novel electrolyte solutions and hybrid electrolyte designs, which allow for the tuning of transport properties through the electrolyte. The computational models are being used to investigate these designs and optimize material properties to increase battery performance and lifetime.