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The ternary cathode material LiNi0.83Co0.12Mn0.05O2 (NCM) has excellent properties, such as superior energy density, low cost, and high voltage platform. Recently, it becomes one of the research hotspots of lithium-ion batteries (LIBs). However, NCM has insufficient cycle stability and cannot meet the demand for the high-rate capability, which limits its application in energy storage equipment. The precursor of NCM was modified with (Ni0.4Co0.2Mn0.4)1−xZrx(OH)2 by the co-precipitation. After high-temperature sintering, the diffusion of Zr4+ has significant impacts on the stability and capability for NCM. The doped sample exhibits a capacity retention rate of 79.5% at 1 C after 200 cycles and also delivers excellent rate performance, and the average specific discharge capacity is 189.4 mAh g−1 (2 C) and 180.6 mAh g−1 (5 C), respectively. [ABSTRACT FROM AUTHOR]

Instance segmentation requires both pixel-level classification accuracy and high-level semantic features at the target instance level, which is very challenging, and the cascade structure can effectively improve both of these problems. To make full use of the relationship between detection and segmentation, this paper proposes a joint multi-tasking cascade structure, which is not simply to cascade the two tasks of detection and segmentation, but to unitedly put them into multi-stage processing, and especially to integrate the information at different stages of the mask branch. The entire structure can effectively utilize the superior characteristics of each stage in the matter of detection and segmentation, thus improving the quality of mask prediction. The feature fusion process is introduced in the full convolution networks (FCN) branch, and the high-level and low-level features are effectively fused to enhance the contextual information of the picture semantic features. The experiments demonstrate the better results on the COCO dataset. [ABSTRACT FROM AUTHOR]