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By Sarah Fields
July 2019

Lithium-ion batteries can come in the form of laminated lithium-ion batteries for mobile electronic devices, cylindrical batteries for industrial power tools, and other cylindrical batteries for energy storage systems. The R&D division of Murata Manufacturing Co., Ltd., is using multiphysics simulation to examine batteries using lithium metal as a negative electrode material.

Dendrites, needle-like growths, are a fierce antagonist to efficient lithium-ion battery functioning. Dendrites form when a current is applied to a lithium metal electrode and can cause unwanted side reactions that result in short circuiting, drastically limiting the life of the battery.

Mitigating dendrite formation is an active area of research for the entire battery industry. Most researchers approach the problem of safety hazards and life span due to dendrite formation by changing the chemistry in some way. However, gains in this area have been painstakingly slow, prompting some researchers to take an alternative path.

When examining batteries that use lithium metal as a negative electrode material, Jusuke Shimura, a R&D engineer at Murata, looked to investigate the effect of changing the charging current pattern on dendrite formation.

This approach is gaining traction in the battery and energy storage world as the industry ramps up to meet the needs of an era of electrification and renewable energy.

Using Multiphysics to Minimize Dendrites

Lithium dendrite occurs when current is applied to the lithium metal electrode, resulting in a short circuit. “In order to commercialize lithium-ion batteries with lithium metal electrodes, this problem must be solved,” says Shimura.

The key to his approach was identifying a current pattern for charging that would minimize the growth of lithium dendrites. This approach works because at the off time between pulses, the concentration gradient at the electrode interface decreases, minimizing dendrite buildup. Also, introducing reverse pulses in the current pattern plays an important role by repeatedly dissolving formed dendrites.

To capture the electrochemical effects over his geometry, Shimura enlisted the battery modeling capabilities of COMSOL Multiphysics®. He used a combination of experimental evidence and simulation to determine the best charging pattern. Many researchers have been exploring this challenge from a chemical and material perspective. To make strides in this area, Shimura wanted to establish a baseline understanding of his physical system experimentally. It was important for him to understand the shape of dendrite formation over time. To accomplish this, he created an X-ray CT-compatible laminated cell that contains a contrast agent in its electrolyte membrane, and visually measured the formation of dendrites over time (Figure 1).

“I created a laminated cell that could be imaged with X-ray computed tomography, so that I would know where the dendrites are forming. Then, I used COMSOL® to find the best pulse pattern of charging to limit dendrite growth based on the shape and the size of the formed dendrites,” explains Shimura.

With the data from the X-ray computed tomography, Shimura created a model of a lithium metal cell and analyzed the effect of changing the current pattern. The results showed how much lithium metal precipitated onto the dendrite (Figure 2).

Using multiphysics modeling, Shimura evaluated various current patterns to determine the current pattern with the slowest rate of dendrite formation (Figure 3). This method allowed him to examine which has more lithium deposition — the electrode surface with planar diffusion (bottom part of Figure 3) or the dendrite with spherical-like diffusion (left part of Figure 3) through one cycle of the pulse pattern.

He ultimately found that a repetition of reverse pulse for 20 seconds, off-time for 10 seconds, forward pulse for 20 seconds, and off-time for 10 seconds resulted in the least dendrite growth (Figure 4).

“通过使用这种模式，枝晶的生长速度不到原来的三分之一。这一改进仅仅是通过改变充电模式实现的，其化学成分仍保持不变，”Shimura 解释说。

Shimura 的仿真工作流程为：首先以实验确定枝晶的大小，然后，使用 COMSOL 多物理场仿真软件的电池建模功能，通 过浓度相关的 Butler-Volmer 方程模拟电极反应，并使用耦合的扩散-迁移方程模拟电解质内的锂离子传输。

开发面向未来的电池

借助仿真分析，Shimura 找到了为锂离子电池充电的最佳脉冲模式。与施加直流电相比，这种方法使电池寿命延长了三倍。“在 COMSOL 多物理场仿真软件的帮助下，基于第一性原理，我们通过仿真验证优化的充电模式，可以改善电池的使用寿命。”Shimura 说道。

展望未来，Shimura 认为在他们的研究持续快速发展的过程中，多物理场仿真将继续发挥积极作用。他总结道：“我们会继续使用 COMSOL 多物理场仿真软件优化电池的充电模式，推动整个电池市场的发展。”