Abstract
Lithium dendrite growth due to uneven electrodeposition usually leads to the potential hazard of internal short circuit and shorter lifetime of lithium-based batteries. Extensive efforts have been devoted to explore the effects of single or two factors on dendrite growth, involving the diffusion coefficient, exchange current density, electrolyte concentration, temperature, and applied voltage. However, these factors interrelate during battery operation, signifying that a understanding of how they jointly influence the electrodeposition is of paramount importance for the effective suppression of dendrites. Here, we incorporate the dependent relationships among key factors into the phase-field model to capture their synergistic effects on electrodeposition. All the simulations are implemented in our self-written MATLAB code under a unified modeling framework. Following this, five groups of experimentally common dendrite patterns are reproduced and the corresponding electrodeposition driving forces are identified. Unexpectedly, we find that with the decrease of the ratio of exchange current density (or applied voltage) to diffusion coefficient, the electrodeposition morphology changes from needle-like dendrites to columnar dendrites and to uniform deposition. The present phase-field simulation tends to depict the practical electrodeposition process, providing important insights into synergistic regulation to suppress dendrite growth.
Original language | English (US) |
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Pages (from-to) | 107993 |
Journal | CHINESE CHEMICAL LETTERS |
Volume | 34 |
Issue number | 2 |
DOIs | |
State | Published - Dec 27 2022 |
Bibliographical note
KAUST Repository Item: Exported on 2023-06-02Acknowledgements: This work was supported by the National Natural Science Foundation of China (Nos. 52102280, U2030206, 11874254, 51622207), Shanghai Pujiang Program (No. 2019PJD016), Foundation of China Academy of Engineering Physics-Key Laboratory of Neutron Physics (No. 2019BB07), and Scientific Research Project of Zhijiang Laboratory (No. 2021PE0AC02). It was also supported by funding from King Abdullah University of Science and Technology (KAUST).