(Invited) Battphase – a Convergent, Non-Oscillatory, Efficient Algorithm and Code for Predicting Shape Changes in Lithium Metal Batteries Using Phase-Field Models

Monday, 10 October 2022: 08:40
Room 315 (The Hilton Atlanta)
T. Jang, L. Mishra (University of Texas at Austin), S. A. Roberts (Sandia National Laboratories), A. Subramaniam, M. Uppaluri (University of Texas at Austin), M. P. Gururajan (Indian Institute of Technology Bombay), J. G. Zhang (Pacific Northwest National Laboratory), and V. R. Subramanian (University of Texas at Austin)
Electrochemical models at different scales and varying levels of complexity have been used in the literature to study the evolution of the anode surface in lithium metal batteries. This includes continuum, mesoscale (phase-field approaches), and multiscale models.1-5 Thermodynamics-based equations have been used to study phase changes in lithium batteries using phase-field approaches. However, grid convergence studies and the effect of additional parameters needed to simulate these models are not well-documented in the literature. In this talk, using a motivating example of a moving boundary model in one- and two-dimensions, we show how one can properly formulate phase-field models using the immersed interface/domain approach, implement robust and efficient algorithms for the same and analyze the results (Figure 1). An open-access code with no restrictions is provided as well. The talk concludes with some thoughts on the computational efficiency of phase-field models for simulating dendritic growth.

Acknowledgements

The authors would like to express gratitude to Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Vehicle Technologies of the DOE through the Advanced Battery Material Research (BMR) Program (Battery500 consortium). This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government. Supported by the Laboratory Directed Research and Development program at Sandia National Laboratories, a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA-0003525. VS acknowledges interactions with Dr. Srikanth Vedantam from IIT Madras, India and Dr. Daniel Wheeler from National Institute of Standards and Technology for early discussions on phase-field and level-set methods. VS also acknowledges Richard Braatz from Massachusetts Institute of Technology for pointing out the poor results from standard algorithms because of the convective nature of the models.

References

1. Q. Wang, G. Zhang, Y. Li, Z. Hong, D. Wang and S. Shi, NPJ Comput. Mater., 6, 176 (2020).
2. Z. Hong and V. Viswanathan, ACS Energy Lett., 3, 1737 (2018).
3. L. Liang and L.-Q. Chen, Appl. Phys. Lett., 105, 263903 (2014).
4. D. A. Cogswell and M. Z. Bazant, ACS Nano, 6, 2215 (2012).
5. Y. Zeng and M. Z. Bazant, SIAM J. Appl. Math., 74, 980 (2014).