Summary: This paper introduces a new inorganic poly(phosphazene disulfide) material. With unique element composition and molecular structure, the polymer has noncombustible safety and preferable conductivity. When used as cathode material for rechargeable lithium batteries, the polymer's first discharge capacity is as high as 467.9 mAh · g?1, which can be retained at 409.9 mAh · g?1 after 60 repeated cycles. Therefore, it has a great application potential in the field of lithium batteries.
Replacement of the Cl atoms by S? S groups by refluxing Na2S2 and linear poly(dichloro‐phosphazene). 相似文献
This article analyzes the bias dependence of gate‐drain capacitance (Cgd) and gate‐source capacitance (Cgs) in the AlGaN/GaN high electron mobility transistors under a high drain‐to‐source voltage (Vds) from the perspective of channel shape variation, and further simplifies Cgd and Cgs to be gate‐to‐source voltage (Vgs) dependent only at high Vds. This method can significantly reduce the number of parameters to be fitted in Cgd and Cgs and therefore lower the difficulty of model development. The Angelov capacitance models are chosen for verifying the effectiveness of simplification. Good agreement between simulated and measured small‐signal S‐parameters, large‐signal power sweep, and power contours comprehensively proves the accuracy of this simplification method. 相似文献
Promoting the spatial resolution of hyperspectral sensors is expected to improve computer vision tasks. However, due to the physical limitations of imaging sensors, the hyperspectral image is often of low spatial resolution. In this paper, we propose a new hyperspectral image super-resolution method from a low-resolution (LR) hyperspectral image and a high resolution (HR) multispectral image of the same scene. The reconstruction of HR hyperspectral image is formulated as a joint estimation of the hyperspectral dictionary and the sparse codes based on the spatial-spectral sparsity of the hyperspectral image. The hyperspectral dictionary is learned from the LR hyperspectral image. The sparse codes with respect to the learned dictionary are estimated from LR hyperspectral image and the corresponding HR multispectral image. To improve the accuracy, both spectral dictionary learning and sparse coefficients estimation exploit the spatial correlation of the HR hyperspectral image. Experiments show that the proposed method outperforms several state-of-art hyperspectral image super-resolution methods in objective quality metrics and visual performance.