High-Temperature Chemical Oxidation Pathways in Lithium-ion Batteries: Mechanistic insights into Ethylene Carbonate Decomposition

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Authors: Leon Schmidt, Kie Hankins, Jorge Valenzuela García de León, René Windiks, Adrian Lindner, Ruth Witzel, Yuchen Qiu, Edwin Knobbe, Ulrike Krewer
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Abstract

Thermal events remain a safety challenge for lithium-ion batteries due to self-reinforcing exothermic reactions that occur at elevated temperatures. Higher states of charge have been shown to exacerbate the onset and severity of these events. This has been attributed to the release of lattice oxygen in cells containing Ni-rich layered oxide electrodes. The degradation reactions on the electrode/electrolyte interface triggered by this oxygen remain insufficiently understood. In this study, we investigate high-temperature degradation pathways of ethylene carbonate (EC)-based electrolytes in contact with Ni-rich positive electrode active materials up to 130 ◦C. By combining in-situ high-temperature online electrochemical mass spectrometry with post-mortem analyses, we identify and validate key degradation intermediates and products. Two distinct EC oxidation pathways are revealed: one activated at high voltages, and one initiated by trace water impurities. Theoretical calculations reveal the reactions are thermodynamically favorable and quantify their heat release. Both pathways produce significant heat and lead to gassing of CO$_2$ and H$_2$. These findings suggest a significant contribution of EC to thermal gas evolution and exothermicity under abuse conditions, thereby establishing a mechanistic link between electrolyte chemistry and thermal events. This integrated experimental-computational approach provides critical insights to guide improved electrolyte formulations and predictive thermal models.

Fields of Study & Subjects

Battery Modeling and Management Advancements in Battery Materials Advanced Battery Materials and Technologies

Publication details

Journal / source
RADAR4KIT
Publication date
1 January 2026
Language
EN
Document type
Dataset