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The rapid voltage and capacity fade of the otherwise promising Ni-rich layered LiNiMnCoO (NMC811) cathode are the primary obstacles to its successful commercialization in lithium-ion batteries (LIBs). Here, electrochemical electron paramagnetic resonance (EPR) spectroscopy is employed to gain insight into the cation redox behavior of the NMC811 cathode during the cell charge/discharge process. Different oxidation states of Ni ions are detected by variations in the signal of the EPR spectra. studies of NMC811 at different SOC levels also confirm changes in the local Mn-Ni environment. A comparison of studies on fresh and cycled NMC811 electrodes demonstrates that the fundamental redox processes remain unchanged upon cycling of the material. Finally, dissolved Mn and Co ions from the bulk are found using EPR characterization of the cycled cathode and separator. The dissolution of these metal ions can accelerate the degradation of the entire battery.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12035850 | PMC |
http://dx.doi.org/10.1021/acs.jpcc.5c00275 | DOI Listing |
Small Methods
October 2022
Electrochemical Innovation Lab, Department of Chemical Engineering, University College London, London, WC1E 7JE, UK.
X-ray computed tomography (X-ray CT) is a non-destructive characterization technique that in recent years has been adopted to study the microstructure of battery electrodes. However, the often manual and laborious data analysis process hinders the extraction of useful metrics that can ultimately inform the mechanisms behind cycle life degradation. This work presents a novel approach that combines two convolutional neural networks to first locate and segment each particle in a nano-CT LiNiMnCoO (NMC) electrode dataset, and successively classifies each particle according to the presence of flaws or cracks within its internal structure.
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