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锡基薄膜电极充放锂过程力学性能的原位测量 |
In-situ measurement of mechanical properties of tin-based film electrode in lithium insertion/removal process |
投稿时间:2023-04-18 修订日期:2023-07-03 |
DOI: |
中文关键词: Cu6Sn5薄膜电极 多光束光学传感器 原位曲率测量 TPE算法 |
英文关键词:Cu6Sn5 film electrode Multi-beam optical sensor In-situ curvature measurement Tree-structured Parzen Estimator |
基金项目:国家自然科学基金项目(No.12072179 和No.11672168)、之江实验室科研攻关项目(No.2021PEOAC02) |
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中文摘要: |
电池电极的力学性能对于电池的循环寿命至关重要,电极材料的杨氏模量和活性离子在电极中的偏摩尔体积是影响力学性能的关键因素。本文通过采用磁控溅射的方式在基底上进行Cu6Sn5薄膜的制备,随后通过搭建的原位曲率测量系统,并结合电化学测试方法,采用多光束光学传感器对充放锂过程中的Cu6Sn5负极薄膜材料进行原位曲率测量。测量结果表明,从第二周电化学循环过程开始曲率呈现周期性变化,且弹性变形主要出现在放电(嵌锂)过程中,塑性变形主要出现在充电(脱锂)过程中。由于线弹性过程中Cu6Sn5的杨氏模量和锂在Cu6Sn5中偏摩尔体积的不确定性,本文将这两个参数作为贝叶斯优化中的超参数,并通过限定超参数的取值范围,利用贝叶斯优化中的树状结构Parzen估计算法计算超参数的最优值,最终得到了Cu6Sn5的杨氏模量和锂的偏摩尔体积分别为140.149GPa和2.787cm3/mol。本文的工作为Cu6Sn5薄膜电极的理论建模研究奠定了基础,所采用的方法为其他电极电池力学和电化学耦合行为的研究提供参考。 |
英文摘要: |
The mechanical properties of battery electrodes are crucial for the cycling lifespan of batteries. Meanwhile, the Young's modulus of electrode and partial molar volume of lithium electrode are key factors that affect the mechanical properties of battery electrodes. The present work mainly focuses on the mechanical properties of lithium-ion batteries with the Cu6Sn5 film electrode, in which the Young's modulus of Cu6Sn5 and the partial molar volume of lithium electrode are unclear yet. We combine the experiments and the algorithm of machine learning to obtain the two parameters. We prepared the Cu6Sn5 film on the Si substrate by Magnetron sputtering. After that, we used multi-beam optical sensor to measure the in-situ curvature of Cu6Sn5 films of negative electrode during the charge-discharge process through the established in-situ curvature measurement system and electrochemical testing methods. The measurement results indicate that the curvature exhibits periodic changes starting from the second cycle of electrochemical cycling, and the elastic deformation mainly occurs during the discharge (lithium insertion) process, while the plastic deformation mainly occurs during the charging (lithium removal) process. The partial molar volume of lithium and the Young's modulus of Cu6Sn5 in the linear elastic process are taken as hyperparameters and the optimal value of hyperparameter is obtained by limiting the value range of hyperparameter within TPE algorithm of Bayesian optimization. As a result, the Young's modulus of Cu6Sn5 and the partial molar volume of lithium are 140.149 GPa and 2.787 cm3/mol respectively. The work lays the foundation for the theoretical modeling research of Cu6Sn5 film electrodes and provides a framework for the study of the mechanical and electrochemical coupling behavior of other batteries. |
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