(Invited) 3D Pore-Scale Transport Model Incorporating Realistic Cathode Morphology and Intermediate Reactions in Lithium-Air Batteries

Abstract

The lithium-air (Li-air) battery, with its usable energy density close to 1,700Wh/kg1, has captured worldwide attention as a promising battery solution for electric vehicles. However, a major hurdle facing the development of Li-air battery systems is their poor round-trip efficiency owing to the formation of electrically insulating lithium peroxide (Li2O2) at the cathode surface. Computational modeling has proven to be an indispensable tool in the analysis of battery systems, however, all existing simulations thus far treat the electrode/Li2O2 matrix as a homogenous continuum and utilize simply-shaped electrode morphologies, such as spheres and rods, to construct volume-averaged expressions (see Fig. 1a) for porosity and surface area and are insufficient to probe the effect of precise electrode microstructures and Li2O2 growth2,3. Utilizing a pore-scale transport-resolved model of the Li-air battery, the complex electrode and Li2O2morphologies can be directly incorporated and their effects on the system-level performance can be evaluated. In this work, we present a pore-scale transport resolved model (see Fig. 1b) of the Li-air battery that fully accounts for the electrode microstructure and peroxide growth4. This approach requires no empirical correlations regarding the electrode morphology. 3D reconstructed images of real carbon fiber cathode (Fig. 2) are used as geometric inputs to the model. Results obtained from our pore-scale model agree well with experiments and the validated model is then used to predict the galvanostatic discharge behavior of a Li-air cell for a variety of electrode morphologies and design parameters. Fig. 3 shows the cell voltage versus specific capacity curves for nanofiber electrodes of varying mean pore spacing from our 3D pore-scale model. The cell discharge capacity is limited by the spacing between nanostructures, which may lead to pore blocking and hence the reduction of active surface area. To capture the different growth morphologies two potential peroxide forming reactions, based on an intermediate oxygen reduction reaction where O2 reduces to becomes superoxide (O2 -), are incorporated as shown in Fig. 1c. Superoxide may form at the surface of the electrode and then follow one of two possible paths; reaction at the electrode surface to form lithium peroxide or diffusion into the bulk liquid to nucleate lithium peroxide in the electrolyte5. Lithium peroxide created at the electrode/electrolyte surface will produce a thin film growth morphology while peroxide particles generated further away in the electrolyte contributes to the formation of larger particle shaped or toroidal shaped growth. The competition between the different reactions can be explicitly accounted for in the pore-scale modeling framework. A discrete element method is used to simulate the nucleation and movement of lithium peroxide. Through extensive 3D simulations, we systematically examine the effect of drawing current, ORR rate coefficients, oxygen solubility, mean pore size and distribution on Li2O2growth and cell performance as to better understand the underlying physics of capacity fading during cycling. The methodology presented here can be applied to other electrochemical systems that include an insoluble product formation as a result of the reaction process and will be a valuable tool for rational design of electrode microstructures for improved cell performance.