Helmholtz Institute Ulm, Applied Electrochemistry, Helmholtzstr. 11, 89081, Ulm, Germany.
Karlsruhe Institute of Technology, Institute of Physical Chemistry, Fritz-Haber-Weg 2, 76131, Karlsruhe, Germany.
Sci Data. 2023 Jan 19;10(1):43. doi: 10.1038/s41597-023-01936-3.
Electrolytes are considered crucial for the performance of batteries, and therefore indispensable for future energy storage research. This paper presents data that describes the effect of the electrolyte composition on the ionic conductivity. In particular, the data focuses on electrolytes composed of ethylene carbonate (EC), propylene carbonate (PC), ethyl methyl carbonate (EMC), and lithium hexafluorophosphate (LiPF). The mass ratio of EC to PC was varied, while keeping the mass ratio of (EC + PC) and EMC at fixed values of 3:7 and 1:1. The conducting salt concentration was also varied during the study. Conductivity data was obtained from electrochemical impedance spectroscopy (EIS) measurements at various temperatures. Based on the thus obtained temperature series, the activation energy for ionic conduction was determined during the analysis. The data is presented here in a machine-readable format and includes a Python package for analyzing temperature series of electrolyte conductivity according to the Arrhenius equation and EIS data. The data may be useful e.g. for the training of machine learning models or for reference prior to experiments.
电解质被认为对电池的性能至关重要，因此是未来储能研究不可或缺的。本文介绍了描述电解质组成对离子电导率影响的数据。特别是，这些数据集中在由碳酸乙烯酯 (EC)、碳酸丙烯酯 (PC)、碳酸甲乙酯 (EMC) 和六氟磷酸锂 (LiPF) 组成的电解质上。在研究过程中，改变了 EC 与 PC 的质量比，同时保持 (EC + PC) 和 EMC 的质量比固定在 3:7 和 1:1。导电盐浓度也在研究过程中发生了变化。通过电化学阻抗谱 (EIS) 在不同温度下的测量得到了电导率数据。基于由此获得的温度系列，在分析过程中确定了离子传导的活化能。这里以机器可读的格式呈现数据，包括一个根据阿伦尼乌斯方程和 EIS 数据分析电解质电导率温度系列的 Python 包。这些数据可用于例如训练机器学习模型或在实验前参考。
