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Published December 20, 2012 | Published
Journal Article Open

Suppression of Dendrite Formation via Pulse Charging in Rechargeable Lithium Metal Batteries

Abstract

We introduce a coarse-grained simulation model for the reductive deposition of lithium cations in secondary lithium metal batteries. The model accounts for the heterogeneous and nonequilibrium nature of the electrodeposition dynamics, and it enables simulation of the long timescales and lengthscales associated with metal dendrite formation. We investigate the effects of applied overpotential and material properties on early-stage dendrite formation, as well as the molecular mechanisms that govern this process. The model confirms that dendrite formation propensity increases with the applied electrode overpotential, and it demonstrates that application of the electrode overpotential in time-dependent pulses leads to dramatic suppression of dendrite formation while reducing the accumulated electrode on-time by as much as 96%. Moreover, the model predicts that time dependence of the applied electrode overpotential can lead to positive, negative, or zero correlation between cation diffusivity in the solid–electrolyte interphase (SEI) and dendrite formation propensity. Analysis of the simulation trajectories reveals that dendrite formation emerges from a competition between the timescales for cation diffusion and reduction at the anode/SEI interface, with lower applied overpotentials and shorter electrode pulse durations shifting this competition in favor of lower dendrite formation propensity. This work provides a molecular basis for understanding and designing pulsing waveforms that mitigate dendrite formation while minimally affecting battery charging times.

Additional Information

© 2012 American Chemical Society. Received: September 19, 2012; Revised: November 13, 2012; Published: November 19, 2012. This work is supported in part by the U.S. Office of Naval Research (USONR) under Grant No. N00014-10-1-0884. Additionally, T.F.M. acknowledges support from a Camille and Henry Dreyfus Foundation New Faculty Award and an Alfred P. Sloan Foundation Research Fellowship. Computational resources were provided by the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, and by the National Science Foundation under Grant No. CHE-1040558. Finally, the authors thank Jason Goodpaster for helpful discussions at early stages of this work.

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