Abstract
We implement a segmentation algorithm that allows identifi cation of individual particles and validate it by showing that the calculated particle size distribution (PSD) is in agreement with experimentally determined PSD obtained with laser diffraction. We study the microstructure of LiNi 1/3 Mn 1/3 Co 1/3 O 2 (NMC)-based cathodes, prepared with varying weight percent of carbon black and binder (2–5 wt%) and different compressions (0-2000 bar), and their electrochemical performance. Tomographic data (raw and processed with particles identifi ed and labeled) and the corresponding electrochemical data for 16 different cathodes is provided open source. [ 2 ] The microstructure datasets can be used to study electrode properties like porosity, tortuosity, electrode anisotropy, and homogeneity, or as realistic geometries for three dimensional (3D) electrochemical simulations. The electrochemical data is intended to aid in the verifi cation of simulation models. The large number of studied particles (approx. 7000-19000 per electrode) allows us to investigate spatially resolved PSD and shows that the vicinity of electrode boundaries is populated by smaller particles than the bulk electrode. In addition to insight into electrode morphology, we demonstrate that the technique is capable of resolving features on the sub-particle level such as particle fracture, which is observed here under high compression conditions. It is becoming increasingly clear that the development of next generation, higher performance lithium ion batteries (LIB) will require a concerted effort between experimentalists and simulation experts. In addition to the development of predictive tools for the selection of active materials, realization of LIBs with high C-rate capabilities and energy density will require the development of roadmaps for achieving favorable porous electrode microstructures. [ 3 , 4 ] However, due to the lack of publically
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