Investigating Novel Electrolytes to Suppress Dendrite Growth in Li-Air Batteries

Monday, 25 May 2015: 14:20
Continental Room A (Hilton Chicago)
E. M. Ryan, J. Tan, T. Sokolinski (Boston University), and K. Ferris (Pacific Northwest National Laboratory)
This research focuses on improving the performance and durability of advanced lithium air (Li-air) battery technologies through computational modeling and materials informatics. In particular, the issue of dendrite growth at the anode-electrolyte interface was investigated through physical models and a materials informatics approach to identify novel electrolyte materials for Li-air batteries.

Dendrites form on the anode surface over multiple charge and discharge cycles, causing a decrease in performance and safety concerns due to short circuiting. Dendrite growth depends strongly on the reactive transport near the anode-electrolyte interface and heterogeneities on the anode surface. To reduce dendrite growth, we investigated increasing the mixing near the anode-electrolyte interface through novel electrolyte designs that directionally affect the transport properties of the electrolyte solution. The research was divided into two main tasks: physical modeling of dendrite growth and morphology, and development of a materials informatics approach for identifying novel electrolyte materials.

            Dendrite growth was investigated using the meso-scale smoothed particle hydrodynamics (SPH) method. SPH is a mesh-free technique that uses a Lagrangian framework to model the simulation domain as a discrete system of particles.  SPH particles are used as interpolation points to discretize and solve the governing partial differential equations of a system based on the SPH smoothing function. Due to its Lagrangian nature, SPH does not require explicit boundary tracking, which allows for simple implementation of complex geometries and moving boundaries, such as the dendrite formation at the anode-electrolyte interface.

A materials informatics approach was used in a discovery mode to identify promising material combinations for the electrolyte. Our research focused on developing the materials informatics framework for electrolyte solutions. The developed framework is general and is applicable to other materials systems for batteries and for other application areas. The informatics techniques have predictive capabilities based upon an electrolyte materials knowledge base, allowing us to evaluate materials based on their thermodynamic properties and the desired properties needed for a specific application.