Nanoscale imaging of electrochemical and electrical properties in Li-ion battery materials

Abstract

The demand of Li-ion batteries is exponentially increasing in various applications from portable electronic devices to electric vehicles. Since electrochemical properties such as capacity and cycle characteristics of the Li-ion battery are directly related to the commercialization of various electronics, they have been studied by many scientists. As nanotechnology advances, the design of battery materials also becomes more complicated. Accordingly, development of analysis technique has also been required to observe the improved electrochemical properties at nanoscale. In this study, nanoscale imaging is applied to better understand the characteristics of solid-state electrolyte (SSE) and Si-based composite anode, which are promising materials for next-generation Li-ion batteries. Various methodologies to measure not only the surface morphology, but also electrochemical and electrical properties are introduced based on atomic force microscopy (AFM). The ways to suppress the artifacts in images are also explained. First, a quantitative method to calculate the concentration distribution and diffusivity of Li-ion inside the SSE is presented. This analysis methodology can help to solve the chronic problem of SSE with low ionic conductivity at the lattice structure and interface between electrode and SSE. Time-of-flight secondary ion mass spectroscopy (ToF-SIMS), X-ray photoelectron spectroscopy (XPS), and inductively coupled plasma optical emission spectroscopy (ICP-OES) are used to obtain the quantitative amount of Li-ion in SSE, and the dependence of electrochemical strain microscopy (ESM) signal on Li-ion concentration is analyzed. The ionic movements induced by a DC bias voltage and the concentration gradient are monitored to analyze the diffusion behavior of Li-ion inside the SSE. As a result, the change in diffusivity as a function of depth is derived, and the effect of ion concentration on diffusion behavior is discussed. Second, the artifact-free conductive AFM (C-AFM) is introduced to visualize the electron conduction channel in the Si-based composite anode. The origin of a typical artifact, capacitive current, is introduced with a way to remove the artifact signal. In this regard, various statistics that can show the reliability of AFM images are utilized. The capacitive current is dominantly detected at a position where the change in surface height is significant, thus securing a flat surface prior to applying the C-AFM is required. We compare the electrical conductivity of the Si-based composite anode before and after 130 cycles, and discuss the superior performance of the electrode including single-walled carbon nanotube (SWCNT). Especially, the degradation of electrical property of the carbon coating around the Si-based active material and nearby graphite were investigated. The third study is to investigate the pulverization behavior of the Si-based active material depending on the type of conductive additive. The surface potential measurement on the active material reveals that the electrode only having carbon black additive has uneven charging/discharging process. On the other hand, the electrode including SWCNTs as a conductive additive enables the uniform electron transfer to the active material, and provides the stable electrochemical reaction. It can finally lead to uniform volume change during cycling, which can alleviate the particle pulverization. Additionally, the requirements for reliable surface potential imaging are explored. The imaging methods in this study enable us to quantitatively diagnose the current status of the materials, and visualize specific properties with a nanoscale spatial resolution. It leads to predict the future properties of the material based on the degradation imaging, and finally will become the basis for the reverse engineering of the next-generation battery materials.