Investigation of Silicon-Based Anodes for Li-Ion Batteries Using X-Rays and Neutron 3D/4D Imaging Techniques
Authors: Lübke Erik , Helfen Lukas , Brunner Roland , Vorauer Thomas , Drnec Jakub , Koller Stefan , Lyonnard Sandrine 
Published: July 2022

Silicon-based anode materials are one of the most promising approaches to further increase the energy density of lithium-ion batteries. However, current materials are limited by poor cycling stability and rapid capacity fading, mainly caused by the massive volume expansion of Si during lithiation and subsequent strain on the material composite. [1] Furthermore, this electrode swelling also results in continuous solid electrolyte interface (SEI) growth, which hinders the migration of Lithium and leads to permanent capacity loss. [2] [3]

To optimize these materials, analytical techniques able to probe the local 3D morphology and Li content are necessary. By applying methods such as neutron computed tomography (NCT), X-Ray computed tomography (XCT) and synchrotron scattering micro-tomography (SMT) structural ageing and changes in the distribution of lithium in the various components can be characterized and quantified for different charging states and recharge cycle numbers.

This study investigates an anode material based on a dual phase alloy system of amorphous Silicon (a-Si) with crystalline iron silicide (c-FeSi2) and graphite. [4] [5] Li-ion battery coin cells containing this silicon-graphite composite anode material were industrially produced and aged by performing 1, 300, and 700 charge-discharge cycles, corresponding to remaining capacities of 100, 70 and 50 %, respectively. NCT and XCT scans were acquired at the NeXT instrument of the ILL in Grenoble (France) [6], and SMT measurements performed at ID31 of the neighboring ESRF. These datasets were reconstructed and evaluated using specially developed data processing pipelines. By performing multi-modal registration, the NCT and XCT scans were aligned and segmented to combine the complementary datasets and create a 4D model of the Li-ion battery coin cells.

Figure 1 shows a sample of the combined NCT (cyan) and XCT datasets (red). Cropped horizontal slices of Li-Ion battery coin cells are depicted side by side with the main components labelled. Comparing one of the highly cycled cells with 50% remaining capacity (top) with the reference cell without electrolyte (bottom), trapped Lithium can be observed in the anode layers, visible as cyan colored blotchy areas in the otherwise dark component. The pixel size is approximately 5 µm.

The change of lithium distribution in the components between different cycle numbers and charge states in the attenuation-based tomography techniques of NCT / XCT is quantified by modelling expected attenuation parameters to the observed values. The diffraction-based tomography method of SMT was modeled using expected lattice parameters. From this information, trapped Lithium can be identified and changes in the distribution are analyzed to point out possible degradation and failure mechanisms.

We acknowledge financial support from the European Union’s Horizon 2020 research and Innovation program No. 875514 (ECO2LIB) as well as No. 847439 (InnovaXN) under the Marie Skłodowska-Curie grant agreement.

[1] S. Tardif et al, https://doi.org/10.1021/acsnano.7b05796

[2] T. Vorauer et al, https://doi.org/10.1038/s42004-020-00386-x

[3] P. Kumar et al, https://doi.org/10.1002/smll.201906812

[4] C. Berhaut et al, https://doi.org/10.1021/acsnano.9b05055

[5] C. Berhaut et al, https://doi.org/10.1016/j.ensm.2020.04.008

[6] A. Tengattini et al, https://doi.org/10.1016/j.nima.2020.163939

Figure 1