Unified picture on temperature dependence of lithium dendrite growth via phase-field simulation

(Press-News.org) They published their work on Sep. 12 in Energy Material Advances.

 

"The great electrochemical phase-field simulation efforts devoted to exploring the dendrite growth mechanism under the temperature field recently," said paper author Shi, School of Materials Science and Engineering, Shanghai University. "The uniformity of temperature distribution inside batteries has a substantial impact on the stability of Li electrodeposition and dissolution, and the mechanism underlying the temperature-dependent Li dendrite growth remains controversial."

 

Shi said that various simulation methods are utilized to investigate Li dendrites across different scales, encompassing density functional theory, molecular dynamics, kinetic Monte Carlo, and phase-field approach.

 

"Phase field simulation has emerged as a pivotal tool for comprehending temperature-dependent Li dendrite growth dynamics and multiple physical fields, and excels in addressing intricate morphological evolution and coupling of multiple physical fields. In our previous work, we have proposed specific strategies to suppress dendritic growth by adjusting separator pore size/thickness/surface coating particles via phase field simulation. Besides, we incorporated the dependent relationship among diffusion coefficient, exchange current density, applied electric potential, electrolyte concentration and temperature into the electrochemical phase-field model to capture their synergistic effects on electrodeposition morphologies. This phase-field simulation is closer to the practical electrodeposition process and provides rational guidance for designing high safety lithium-based batteries (Chin.Chem.Lett.,2022,33:3287; Chin.Chem.Lett.,2023,34:107993; Materials,2022,15:7912; Acta Phys. Sin.,2020,69:226401; npj Comput. Mater., 2020, 176; Computation, Modeling and Simulation in Electrochemical Energy Storage, ISBN: 9787122426888)." Shi explained.

 

"However, this simulation method still has some problems. The reliance of this model on experimental data limits its applicability to other battery systems" Shi said. At the same time, we investigated the effect of initial temperature on Li dendrite morphology through temperature-dependent ionic diffusion coefficient, reaction coefficient, and conductivity, but did not couple the temperature field. Interestingly, we couple the temperature field to investigate the effect of initial temperature on Li dendrite morphology, and give a unified picture for the seemingly contradictory dendrite-promoting, dendrite-inhibiting, and dual effects of increased temperature in different electrolyte types.

 

"Maybe it is necessary to comprehensively considering the temperature-dependent Li+ diffusion coefficient, electrochemical reaction coefficient, and initial temperature distribution in phase-field model," Shi said. In 2018, an electrochemical phase-field model combining heat transfer only was first established by using the temperature-dependent Li+ diffusion coefficient and found that both internal self-heating and elevated uniform initial temperature can inhibit the dendrite growth. Recently, fitted an accurate thermal-coupled model by formulating the experimental temperature-dependent conductivities of electrode and electrolyte, surface tension, reaction, and diffusion coefficients, and found that the dendrite formation is promoted by elevating temperature.

 

"Diverse strategies to regulate Li dendrite growth have been developed, including modifications to a specific battery component and applications of external fields such as pressure, magnetic field, acoustic wave, light field, electric field, and temperature field," Shi said. "In this paper, we establish a mechanism diagram correlating the activation–energy ratio, uniform initial temperature, and maximum dendrite height, which unifies the seemingly contradictory simulation results."

 

"We surmised that, based on nonuniform initial temperature distribution of Lithium dendrite, a positive temperature gradient along the discharging current facilitates uniform Li+ deposition and local hotspot should be avoided," Shi said.

 

The researchers find that for nonuniform initial temperature, simulation results show that a positive temperature gradient along the discharging current facilitates uniform Li+ deposition and local hotspot should be avoided. Shi said, "the findings of this study provide valuable insights for future advancements in temperature regulation to control dendrite growth."

 

"Lithium metal anodes are regarded as highly promising anode materials for Li-based batteries, but the inevitable dendrite growth on the Li anode results in low Coulombic efficiency and other problems," Shi said. "To further promote the practical application of lithium metal batteries, we need to understand the growth mechanism of lithium dendrites precisely."

 

Shi is also Materials Genome Institute, Shanghai University. Zhang, Clean Combustion Research Center (CCRC), Physical Sciences and Engineering Division (PSE), King Abdullah University of Science and Technology (KAUST). Other contributors include Yajie Li and Wei Zhao, School of Materials Science and Engineering, Shanghai University.

 

National Natural Science Foundation of China (52102280 and U2030206), the Shanghai Municipal Science and Technology Commission (no. 19DZ2252600), and the Scientific Research Project of Zhijiang Laboratory (2021PE0AC02).

 

 

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Reference
Authors: YAJIE LI, WEI ZHAO, GENG ZHANG , AND SIQI SHI


Title of original paper: Unified Picture on Temperature Dependence of Lithium Dendrite Growth via Phase-Field Simulation


Journal: Energy Material Advances


DOI: 10.34133/energymatadv.0053


Affiliations: 1School of Materials Science and Engineering, Shanghai University, Shanghai 200444, China. 2Clean Combustion Research Center (CCRC), Physical Sciences and Engineering Division (PSE), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia. 3Materials Genome Institute, Shanghai University, Shanghai 200444, China.


About the Author: Siqi Shi is a professor and PhD supervision at the School of Materials Science and Engineering & the Institute of Materials Genome Engineering, Shanghai University. He is the recipient of the National Excellent Youth Science Foundation in 2016. His current research focuses on the calculation and design of electrochemical energy storage materials, material databases, and machine learning, committed to promoting the research and development of artificial intelligence enabling materials. He has published more than 180 research papers in Journals such as Nat Catalog, Chem Rev, Prog Mater Sci, Natl Sci Rev, and Adv Mate. He also created an electrochemical energy storage material calculation and data platform with independent intellectual property rights. He is in charge of 12 projects supported by the National Natural Science Foundation of China or the National Key Research and Development Plan. Currently, he serves as a branch director of the Solid State Ionics of the Chinese Silicate Society, and a branch committee member of the Computational Materials Science, Chinese Society for Materials Research.

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