Electrochemical techniques for characterizing LiNixMnyCo1−x−yO2 battery electrodes. (1st November 2020)

• Record Type: Journal Article
• Authors: Varini, Maria; Ko, Jing Ying; Klett, Matilda; Ekström, Henrik; Lindbergh, Göran
• Is Part Of: Electrochimica acta. Volume 359(2020)
• Publication Date: 2020-11-01
• Subjects: Li-ion battery -- LiNi1/3Mn1/3Co1/3O2 -- Electrochemical characterization; Electrochemistry -- Periodicals; Electrochemistry, Industrial -- Periodicals; 541.37
• DOI: 10.1016/j.electacta.2020.136887
• Languages: English
• ISSNs: 0013-4686

Abstract

Abstract: LiNi1/3 Mn1/3 Co1/3 O2 (NMC111) is a state-of-the-art, commercially established positive electrode for Li-ion batteries. Identifying its performance limitations would support the development of better-performing batteries, as well as the design of novel electrode materials, such as Ni-rich LiNi x Mn y Co 1 − x − y O2 . These limitations can be identified through electrochemical characterization, and several techniques are available for the purpose. However, they are rarely considered in the framework of the same study, making it difficult to understand which technique to choose for investigating a specific aspect of the electrode. In the present work, we perform a comparison of NMC111's response towards Galvanostatic Cycling, Galvanostatic Intermittent Titration, Electrochemical Impedance Spectroscopy and Cyclic Voltammetry at different temperatures, and degrees of lithiation. Particular focus is put on the different thermodynamic and dynamic properties that can be extracted from each technique, either qualitatively or quantitatively. In this way, an overall characterization of NMC111 at Beginning of Life is provided, and used for discussing specific cases in which NMC111's electrochemical response is altered by the operating conditions: specifically, we here consider first-cycle formation, and ageing under high voltage operation. We discuss the suitability and limitations of each technique in addressing specific changes in the electrode, for a better understanding of its performances that could support the development of physics-based predictive models for Li-ion battery performance and lifetime.