Quantification of the Deep Discharge Induced Asymmetric Copper Deposition in Lithium‐Ion Cells by Operando Synchrotron X‐Ray Tomography
Shahabeddin Dayani,
Henning Markötter,
Jonas Krug von Nidda
et al.
Abstract:Lithium‐ion cells connected in series are prone to an electrical safety risk called overdischarge. This paper presents a comprehensive investigation of the overdischarge phenomenon in lithium‐ion cells using operando nondestructive imaging. The study focuses on understanding the behavior of copper dissolution and deposition during overdischarge, which can lead to irreversible capacity loss and internal short‐circuits. By utilizing synchrotron X‐ray computed tomography (SXCT), the concentration of dissolved and… Show more
“…Discharge below the end-of-discharge voltage can result in Cu dissolution from the anode current collecting foil. 163,164,[199][200][201][202][203] Cu dissolution to Cu 2+ or Cu + gets thermodynamically allowed when the anode potential increases above 3.38 V or 3.56 V vs Li/Li + , respectively. 164 Furthermore, Flügel et al showed for seven types of commercial cells, that the additional discharge from the end-ofdischarge voltage to 0 V leads only to minor decreases of cell energy corresponding to negative SOCs of −3% to −9%.…”
Section: Workflows For Detection Of LI Depositionsmentioning
Lithium deposition on anode surfaces can lead to fast capacity degradation and decreased safety properties of Li-ion cells. To avoid the critical aging mechanism of lithium deposition, its detection is essential. We present workflows for the efficient detection of Li deposition on electrode and cell level. The workflows are based on a variety of complementary advanced physico-chemical methods which were validated against each other for both graphite and graphite/Si electrodes: Electrochemical analysis, scanning electron microscopy, glow discharge-optical emission spectroscopy and neutron depth profiling, ex situ optical microscopy, in situ optical microscopy of cross-sectioned full cells, measurements in 3-electrode full cells, as well as 3D microstructurally resolved simulations. General considerations for workflows for analysis of battery cells and materials are discussed. The efficiency can be increased by parallel or serial execution of methods, stop criteria, and design of experiments planning. An important point in case of investigation of Li depositions are rest times during which Li can re-intercalate into the anode or react with electrolyte. Three workflows are presented to solve the questions on the occurrence of lithium deposition in an aged cell, the positions of lithium deposition in a cell, and operating conditions which avoid lithium depositions in a cell.
“…Discharge below the end-of-discharge voltage can result in Cu dissolution from the anode current collecting foil. 163,164,[199][200][201][202][203] Cu dissolution to Cu 2+ or Cu + gets thermodynamically allowed when the anode potential increases above 3.38 V or 3.56 V vs Li/Li + , respectively. 164 Furthermore, Flügel et al showed for seven types of commercial cells, that the additional discharge from the end-ofdischarge voltage to 0 V leads only to minor decreases of cell energy corresponding to negative SOCs of −3% to −9%.…”
Section: Workflows For Detection Of LI Depositionsmentioning
Lithium deposition on anode surfaces can lead to fast capacity degradation and decreased safety properties of Li-ion cells. To avoid the critical aging mechanism of lithium deposition, its detection is essential. We present workflows for the efficient detection of Li deposition on electrode and cell level. The workflows are based on a variety of complementary advanced physico-chemical methods which were validated against each other for both graphite and graphite/Si electrodes: Electrochemical analysis, scanning electron microscopy, glow discharge-optical emission spectroscopy and neutron depth profiling, ex situ optical microscopy, in situ optical microscopy of cross-sectioned full cells, measurements in 3-electrode full cells, as well as 3D microstructurally resolved simulations. General considerations for workflows for analysis of battery cells and materials are discussed. The efficiency can be increased by parallel or serial execution of methods, stop criteria, and design of experiments planning. An important point in case of investigation of Li depositions are rest times during which Li can re-intercalate into the anode or react with electrolyte. Three workflows are presented to solve the questions on the occurrence of lithium deposition in an aged cell, the positions of lithium deposition in a cell, and operating conditions which avoid lithium depositions in a cell.
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