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您的检索式：作者名="Kaixuan Ding"
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| 1 | Large Scale One-Pot Synthesis of Monodispersed Na_(3)(VOPO_(4))_(2)F Cathode for Na-Ion Batteries显示文摘Na-ion batteries(NIBs)have received significant interest as potential candidates for large-scale energy storage owing to the widespread distribution of sodium and superior low-temperature performance.However,their commercial application is usually hindered by the high production cost and inadequate performance for electrode materials,particularly for cathodes.Na_(3)(VOPO_(4))_(2)F(NVOPF)has been recognized as one of the most promising cathodes for high-energy NIBs owing to the high working voltage and energy density.Here,we report a facile highly efficient room-temperature solution protocol for large-scale synthesis of NVOPF cathode for NIBs.By simply regulating pH,NVOPF can be obtained,which delivered a discharge capacity of 120.2 mAh g^(-1) at 0.1 C and 72%capacity retention over 8000 cycles at 25 C.Besides,the kilogram-level NVOPF products have been synthesized,and 26650 cylindrical cells were fabricated,which exhibit excellent cycling stabilities,remarkable lowtemperature performance with comparable safety features.We hope our findings could provide insights on the industrial application of NVOPF in NIBs. | Qiangqiang Zhang Xing Shen Quan Zhou Kaixuan Li Feixiang Ding Yaxiang Lu Junmei Zhao Liquan Chen Yong-Sheng Hu | 2022 | Energy Material Advances2022，，1： | 2 |
| 2 | Scene images and text information‐based object location of robot grasping显示文摘With the rapid development of artificial intelligence(AI),the application of this technology in the medical field is becoming increasingly extensive,along with a gradual increase in the amount of intelligent equipment in hospitals.Service robots can save human resources and replace nursing staff to achieve some work.In view of the phenomenon of mobile service robots'grabbing and distribution of patients'drugs in hospitals,a real‐time object detection and positioning system based on image and text information is proposed,which realizes the precise positioning and tracking of the grabbing objects and completes the grasping of a specific object(medicine bottle).The lightweight object detection model NanoDet is used to learn the features of the grasping objects and the object category,and bounding boxes are regressed.Then,the images in the bounding boxes are enhanced to overcome unfavourable factors,such as a small object region.The text detection and recognition model PP‐OCR is used to detect and recognise the enhanced images and extract the text information.The object information provided by the two models is fused,and the text recognition result is matched with the object detection box to achieve the precise posi-tioning of the grasping object.The kernel correlation filter(KCF)tracking algorithm is introduced to achieve real‐time tracking of specific objects to precisely control the robot's grasping.Both deep learning models adopt lightweight networks to facilitate direct deployment.The experiments show that the proposed robot grasping detection system has high reliability,accuracy and real‐time performance. | Zhichao Liu Kaixuan Ding Qingyang Xu Yong Song Xianfeng Yuan Yibin Li | 2022 | IET Cyber-Systems and Robotics2022，4，2： | 0 |
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