4.8 Review

Lithium Batteries and the Solid Electrolyte Interphase (SEI)-Progress and Outlook

Journal

ADVANCED ENERGY MATERIALS
Volume 13, Issue 10, Pages -

Publisher

WILEY-V C H VERLAG GMBH
DOI: 10.1002/aenm.202203307

Keywords

Helmholtz double layer; lithium metal batteries; lithium-ion batteries; solid electrolyte interphases; Stern Helmholtz layer

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Interfacial dynamics in chemical systems have important implications for the optimization of electrochemical energy storage materials and devices. Understanding fundamental electrochemistry at interfaces can also shed light on relevant phenomena in various systems. This review focuses on the solid electrolyte interphase (SEI) in lithium-ion batteries, summarizing its formation, composition, dynamic structure, and reaction mechanisms. Additionally, the influence of electrolyte and electrode materials on SEI structure and properties is discussed, along with state-of-the-art approaches to characterizing the SEI.
Interfacial dynamics within chemical systems such as electron and ion transport processes have relevance in the rational optimization of electrochemical energy storage materials and devices. Evolving the understanding of fundamental electrochemistry at interfaces would also help in the understanding of relevant phenomena in biological, microbial, pharmaceutical, electronic, and photonic systems. In lithium-ion batteries, the electrochemical instability of the electrolyte and its ensuing reactive decomposition proceeds at the anode surface within the Helmholtz double layer resulting in a buildup of the reductive products, forming the solid electrolyte interphase (SEI). This review summarizes relevant aspects of the SEI including formation, composition, dynamic structure, and reaction mechanisms, focusing primarily on the graphite anode with insights into the lithium metal anode. Furthermore, the influence of the electrolyte and electrode materials on SEI structure and properties is discussed. An update is also presented on state-of-the-art approaches to quantitatively characterize the structure and changing properties of the SEI. Lastly, a framework evaluating the standing problems and future research directions including feasible computational, machine learning, and experimental approaches are outlined.

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