| AVS 62nd International Symposium & Exhibition | |
| Applied Surface Science | Thursday Sessions |
| Session AS+SS-ThA |
| Session: | Advances in 2D Chemical Mapping and Data Analysis |
| Presenter: | Alexander Pearse, University of Maryland, College Park |
| Authors: | A.J. Pearse, University of Maryland, College Park E. Gillette, University of Maryland, College Park S.B. Lee, University of Maryland, College Park G.W. Rubloff, University of Maryland, College Park |
| Correspondent: | Click to Email |
The rate at which a battery can deliver energy is ultimately dominated by the ability or inability to effectively transport both ions and electrons throughout the electrodes. When charge transport is a limiting factor, material utilization within the battery becomes spatially inhomogeneous, reducing performance. Additionally, the material and architectural requirements for optimizing transport for both ions and electrons are not always synergistic, which can lead to design challenges. The effects of architecture on device performance are generally characterized by externally measured scalar quantities, such as cell potential or current, but these quantities do not reveal where within the electrode any problem may lie. There is a growing need to develop models which can accurately predict spatially resolved dynamics within battery electrodes, as well as experimental techniques to verify them, particularly as nanoscience produces more and more sophisticated electrode designs.
Here we show that chemical state mapping with X-ray photoelectron spectroscopy (XPS) is a powerful tool for revealing transport-limit-induced dynamics within battery electrodes, and connect surface science with electrochemical modeling. We examine the specific problem of facile ion transport but limited electronic transport, which often occurs in high aspect ratio electrodes made of low conductivity semiconductors or insulators. While characterizing complex structures using XPS is normally very challenging, it is possible to gain much more useful and accurate information when a model device is designed from the ground up to exploit the strengths of XPS. By fabricating battery chips in which the anticipated gradients of material utilization (i.e. the spatially varying amount of lithium intercalated) are laid out laterally on a flat substrate, we can clearly map chemical changes in the electrode as a function of distance from a current collector. By using transition metal oxide (MxOy) cathode materials, we are able to track the state of charge through local quantification of the reaction Mn+ + e- -> M(n-1)+. Our data clearly reveal that as the applied current density increases, ion insertion activity is dramatically contracted towards the current collector, which leads to performance limitations at high rates. Importantly, we also use our spatially resolved data to validate the predictions of a sophisticated finite element multiphysics battery model. The visualization and understanding of design induced performance limits, as well as the validation of a predictive model, allow us to optimize the design of future high performance nanostructured battery electrodes.