Version 1
: Received: 24 July 2024 / Approved: 25 July 2024 / Online: 25 July 2024 (12:09:35 CEST)
How to cite:
Peklar, R.; Mikac, U.; Serša, I. Simulation of Dendrite Growth with a Diffusion-Limited Aggregation Model Validated by MRI of a Lithium Symmetric Cell During Charging. Preprints2024, 2024072038. https://doi.org/10.20944/preprints202407.2038.v1
Peklar, R.; Mikac, U.; Serša, I. Simulation of Dendrite Growth with a Diffusion-Limited Aggregation Model Validated by MRI of a Lithium Symmetric Cell During Charging. Preprints 2024, 2024072038. https://doi.org/10.20944/preprints202407.2038.v1
Peklar, R.; Mikac, U.; Serša, I. Simulation of Dendrite Growth with a Diffusion-Limited Aggregation Model Validated by MRI of a Lithium Symmetric Cell During Charging. Preprints2024, 2024072038. https://doi.org/10.20944/preprints202407.2038.v1
APA Style
Peklar, R., Mikac, U., & Serša, I. (2024). Simulation of Dendrite Growth with a Diffusion-Limited Aggregation Model Validated by MRI of a Lithium Symmetric Cell During Charging. Preprints. https://doi.org/10.20944/preprints202407.2038.v1
Chicago/Turabian Style
Peklar, R., Urša Mikac and Igor Serša. 2024 "Simulation of Dendrite Growth with a Diffusion-Limited Aggregation Model Validated by MRI of a Lithium Symmetric Cell During Charging" Preprints. https://doi.org/10.20944/preprints202407.2038.v1
Abstract
Lithium-metal batteries offer high energy density, but are challenged by dendrite growth, which can lead to short circuits and battery failure. Various models with varying degrees of accuracy and computational cost have been developed to understand and predict dendrite growth. In this study, a simple simulation model to predict macroscale dendrite growth on lithium metal electrodes is presented. The model uses a 3D single-particle diffusion-limited aggregation (DLA) algorithm, biased by the electric field, to simulate dendrite growth. The model was validated using 3D MRI of dendrite growth in a lithium symmetric cell. It was used to simulate deposition between consecutive measured dendrite structures. The model also introduces an important parameter, namely the biasing factor c, which determines the balance between diffusion and electric field effects. This parameter was calibrated using the overlap and displacement of deposition sites metrics, achieving optimal results at c = 0.7. The model predictions were in good agreement with experimental data confirmed by fractal dimension analysis. This model provides a useful tool for predicting and studying dendrite formation in lithium and other metal batteries.
Keywords
lithium metal batteries; dendrite growth; numerical simulation; diffusion-limited aggregation; electric field biasing; MRI; battery safety
Subject
Chemistry and Materials Science, Electrochemistry
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
