Predicting the Impact of Parameter Uncertainty on Model-Guided Li-O ₂ Cathode Design

Despite their high theoretical capacity, actual performance in lithium-oxygen (Li-O 2 ) batteries is limited by sluggish transport and kinetic processes. Cathodes must provide ample surface area to host solid reduction products, but cathode design and electrolyte properties must also support species transport to access these surfaces. Numerous modeling studies therefore attempt to optimize cathode design by identifying microstructures to balance these two needs. However, model validation has historically relied on literature-sourced transport properties, which vary greatly between studies. In this work, we develop an open source, 1-D, continuum-scale Li-O 2 battery model to examine the impact of cathode and electrolyte properties on predicted Li-O 2 battery performance and design. Results demonstrate that O 2 diffusion and solubility have the greatest impact on optimal design. Varying O 2 diffusivity within the range of literature values surveyed led to maximum energy density variations of nearly 400%. These variations have a meaningful impact on the associated design conclusions: the optimal cathode porosity varied between 55 and 75%, depending on the O 2 diffusivity. Moreover, the impact of advanced micrsotructures, such as graded cathode porosity, varies greatly with changes in electrolyte transport parameter estimates. As such, fundamental studies are required to accurately measure key electrolyte properties to enable numerical simulation as a guide to Li-O 2 cathode design.