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• W2783170020 abstract "While large dispersions in electrochemical performance have been reported for lithium oxygen batteries in the literature, they have not been investigated in any depth. The variability in the results is often assumed to arise from differences in cell design, electrode structure, handling and cell preparation at different times. An accurate theoretical framework turns out to be needed to get a better insight into the mechanisms underneath and to interpret experimental results. Here, we develop and use a pore network model to simulate the electrochemical performance of three-dimensionally resolved lithium–oxygen cathode mesostructures obtained from TXM nanocomputed tomography. We apply this model to the 3D reconstructed object of a Super P carbon electrode and calculate discharge curves, using identical conditions, for four different zones in the electrode and their reversed configurations. The resulting galvanostatic discharge curves show some dispersion, (both in terms of capacity and overpotential) which we attribute to the way pores are connected with each other. Based on these results, we propose that the stochastic nature of pores interconnectivity and the microscopic arrangement of pores can lead, at least partially, to the variations in electrochemical results observed experimentally." @default.
• W2783170020 created "2018-01-26" @default.
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• W2783170020 date "2018-02-03" @default.
• W2783170020 modified "2023-10-09" @default.
• W2783170020 title "Stochasticity of Pores Interconnectivity in Li–O₂ Batteries and its Impact on the Variations in Electrochemical Performance" @default.
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• W2783170020 doi "https://doi.org/10.1021/acs.jpclett.7b03315" @default.
• W2783170020 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/29341616" @default.
• W2783170020 hasPublicationYear "2018" @default.
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