Achieving high-energy and high-power density Lithium-ion batteries (LIBs) with fast charge behavior is critical for the future of electric vehicle applications. Conventional LIBs have planar anode and cathode electrode stacks that can be optimized for energy or power, but not both simultaneously due to fundamental ion transport limitations with increasing electrode thickness. Three-dimensional (3D) electrode architectures^1,2 can remove these performance trade-offs through engineered ion-transport in thick electrodes. However, scalable manufacturing methods for patterning these architectures over large areas at meaningful time scales is still limited. As a path to solving this challenge, we leverage both modeling and experiments to investigate the feasibility of deploying acoustophoresis to assemble and pattern 3D battery electrodes. Acoustophoresis employs acoustic standing waves to focus particles and enables near micron-scale control over particle placement in a fluid medium at time scales < 1 second. Prior research has shown the potential for rapid assembly of particles with this approach,^3,4 making acoustic-based processing a promising methodology for manufacturing 3D electrodes over large areas. In this talk, we expand a previously developed model⁴ that solves differential equations of acoustic forces to track particle trajectories and define how the acoustic forces are influenced by slurry viscosity, particle loading, and particle morphology. Our initial experiments with different material systems, including LiNi_0.6Mn_0.2Co_0.2O₂ (NMC-622), help validate our model and process conditions to as a path towards acoustophoretic fabrication of 3D electrode architectures.

References

1. C. L. Cobb and S. E. Solberg, J. Electrochem. Soc., 164, A1339–A1341 (2017).
2. C. L. Cobb and M. Blanco, Journal of Power Sources, 249, 357–366 (2014).
3. D. S. Melchert et al., Materials & Design, 109512 (2021).
4. R. R. Collino et al., Materials Research Letters, 6, 191–198 (2018).

Acknowledgements

This material is based upon work supported by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) under the Advanced Manufacturing Office (AMO) Award Number DE-EE0009112. The views expressed herein do not necessarily represent the views of the U.S. Department of Energy or the United States Government.