Phase-Field Simulation and Machine Learning Study of the Effects of Elastic and Plastic Properties of Electrodes and Solid Polymer Electrolytes on the Suppression of Li Dendrite Growth,ACS Applied Materials & Interfaces

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Phase-Field Simulation and Machine Learning Study of the Effects of Elastic and Plastic Properties of Electrodes and Solid Polymer Electrolytes on the Suppression of Li Dendrite Growth
ACS Applied Materials & Interfaces ( IF 8.3 ) Pub Date : 2022-06-27 , DOI: 10.1021/acsami.2c03000
Yao Ren ₁ , Kena Zhang ₁ , Yue Zhou ₂ , Ye Cao ₁

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Lithium (Li) dendrite growth in Li batteries is a long-standing problem, which causes critical safety concerns and severely limits the advancement of rechargeable Li batteries. Replacing a conventional liquid electrolyte with a solid electrolyte of high mechanical strength and rigidity has become a potential approach to inhibiting the Li dendrite growth. However, there still lacks an accurate understanding of the role of the mechanical properties of the metal electrode and the solid electrolyte in the Li dendrite growth. In this work, we develop a phase-field model coupled with the elastoplastic deformation to investigate the Li dendrite growth and its inhibition in the cell. Different mechanical properties, including the elastic modulus and the initial yield strength of both the metal electrode and the solid electrolyte, are explored to understand their independent roles in the inhibition of Li dendrite growth. High-throughput phase-field simulations are performed to establish a database of relationships between the aforementioned mechanical properties and the Li dendrite morphology, based on which a compressed-sensing machine learning model is trained to derive interpretable analytical correlations between the key material parameters and the dendrite morphology, as described by the dendrite length and area ratio. It is revealed that the Li dendrite can be effectively inhibited by electrolytes of high elastic moduli and initial yield strengths. Meanwhile, the role of the yield strength of the Li metal is also critical when the yield strength of the electrolyte becomes low. This work provides a fundamental understanding of the dendrite inhibition by mechanical suppression and demonstrates a computational data-driven methodology to potentially guide the electrode and electrolyte material selection for better inhibition of the dendrite growth.

中文翻译：

电极和固体聚合物电解质的弹性和塑性性能对抑制锂枝晶生长的影响的相场模拟和机器学习研究

锂电池中的锂 (Li) 枝晶生长是一个长期存在的问题，它引起了严重的安全问题并严重限制了可充电锂电池的发展。用具有高机械强度和刚度的固体电解质代替传统的液体电解质已成为抑制锂枝晶生长的潜在方法。然而，对于金属电极和固体电解质的力学性能在锂枝晶生长中的作用，仍缺乏准确的认识。在这项工作中，我们开发了一个与弹塑性变形相结合的相场模型，以研究锂枝晶的生长及其在细胞中的抑制作用。不同的机械性能，包括金属电极和固体电解质的弹性模量和初始屈服强度，探索了解它们在抑制锂枝晶生长中的独立作用。进行高通量相场模拟以建立上述力学性能与锂枝晶形态之间的关系数据库，在此基础上训练压缩传感机器学习模型，以得出关键材料参数与锂枝晶形态之间可解释的分析相关性。枝晶形态，如枝晶长度和面积比所描述的。结果表明，高弹性模量和初始屈服强度的电解质可以有效地抑制锂枝晶。同时，当电解质的屈服强度变低时，锂金属的屈服强度的作用也很关键。

更新日期：2022-06-27

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