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Fast Diagnosis of Failure Mechanisms and Lifetime Prediction of Li Metal Batteries
Author(s) -
Gao Ningshengjie,
Abboud Alexander W.,
Mattei Gerard S.,
Li Zhuo,
Corrao Adam A.,
Fang Chengcheng,
Liaw Boryann,
Meng Ying Shirley,
Khalifah Peter G.,
Dufek Eric J.,
Li Bin
Publication year - 2021
Publication title -
small methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.66
H-Index - 46
ISSN - 2366-9608
DOI - 10.1002/smtd.202000807
Subject(s) - anode , electrolyte , faraday efficiency , battery (electricity) , materials science , lithium metal , electrical impedance , lithium (medication) , capacity loss , fault (geology) , voltage , metal , computer science , reliability engineering , electrode , chemistry , electrical engineering , engineering , metallurgy , thermodynamics , power (physics) , medicine , physics , endocrinology , seismology , geology
Lithium (Li) metal serving as an anode has the potential to double or triple stored energies in rechargeable Li batteries. However, they typically have short cycling lifetimes due to parasitic reactions between the Li metal and electrolyte. It is critically required to develop early fault‐detection methods for different failure mechanisms and quick lifetime‐prediction methods to ensure rapid development. Prior efforts to determine the dominant failure mechanisms have typically required destructive cell disassembly. In this study, non‐destructive diagnostic method based on rest voltages and coulombic efficiency are used to easily distinguish the different failure mechanisms—from loss of Li inventory, electrolyte depletion, and increased cell impedance—which are deeply understood and well validated by experiments and modeling. Using this new diagnostic method, the maximum lifetime of a Li metal cell can be quickly predicted from tests of corresponding anode‐free cells, which is important for the screenings of electrolytes, anode stabilization, optimization of operating conditions, and rational battery design.