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Your search keyword '"Jia, Jialu"' showing total 7 results
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7 results on '"Jia, Jialu"'

4. Fabrication of porous Ti3C2Tx MXene films by in situ foaming strategy for unparalleled high-rate energy storage.

Author

Shi, Yi, Lu, Xiaolong, Xu, Zhiwei, Wang, Qi, Guo, Huafei, Jia, Jialu, Fang, Bijun, Yuan, Ningyi, and Ding, Jianning

Subjects
ENERGY storage, SURFACE chemistry, FOAM, SUPERCAPACITOR electrodes, NANOSTRUCTURED materials, ELECTRIC capacity
Abstract

MXene film electrodes for supercapacitors, assembled with MXene nanosheets as structure units, inevitably suffer from self-restacking, which severely restrains ion transport kinetics and results in insufficient active site utilization and poor rate capability. Herein, an in situ foaming strategy employing the accumulated gas generated during the etching of sacrificial templates, combined with the confinement between the MXene film, has been proposed to fabricate pores between stacked MXene sheets and along the vertical direction of the film. The surface chemistry of the foamed film was further modified by alkali washing treatment to replace hydrophobic –F groups with hydrophilic –OH groups to improve electrolyte penetration and introduce more active sites. The resultant porous MXene film electrode exhibits a greatly improved specific capacitance (354.1 F g−1 at 5 mV s−1) and unparalleled rate capability (with a capacitance retention of 96.1% at 2000 mV s−1). This work demonstrates a facile but efficient method for the construction of porous MXene films, simultaneously providing insights into the promising applications of MXenes. [ABSTRACT FROM AUTHOR]

Published
2023
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6. A High-Computational Efficiency Human Detection and Flow Estimation Method Based on TOF Measurements

Author

Jiuchao Qian, Jiefeng Gao, Jia Jialu, Rendong Ying, Weihang Wang, Jun Wang, and Peilin Liu

Subjects
computational efficiency, Computer science, 02 engineering and technology, lcsh:Chemical technology, human detection, Biochemistry, Article, Pattern Recognition, Automated, Analytical Chemistry, Image (mathematics), Physical Phenomena, Imaging, Three-Dimensional, Artificial Intelligence, 0202 electrical engineering, electronic engineering, information engineering, Humans, lcsh:TP1-1185, Computer vision, Electrical and Electronic Engineering, Instrumentation, Monitoring, Physiologic, business.industry, TOF, Frame (networking), 020207 software engineering, Filter (signal processing), Atomic and Molecular Physics, and Optics, Feature (computer vision), flow estimation, 020201 artificial intelligence & image processing, Artificial intelligence, business, Focus (optics), Head, Algorithms
Abstract

State-of-the-art human detection methods focus on deep network architectures to achieve higher recognition performance, at the expense of huge computation. However, computational efficiency and real-time performance are also important evaluation indicators. This paper presents a fast real-time human detection and flow estimation method using depth images captured by a top-view TOF camera. The proposed algorithm mainly consists of head detection based on local pooling and searching, classification refinement based on human morphological features, and tracking assignment filter based on dynamic multi-dimensional feature. A depth image dataset record with more than 10k entries and departure events with detailed human location annotations is established. Taking full advantage of the distance information implied in the depth image, we achieve high-accuracy human detection and people counting with accuracy of 97.73% and significantly reduce the running time. Experiments demonstrate that our algorithm can run at 23.10 ms per frame on a CPU platform. In addition, the proposed robust approach is effective in complex situations such as fast walking, occlusion, crowded scenes, etc.

Published
2019
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7. Fabrication of porous Ti 3 C 2 T x MXene films by in situ foaming strategy for unparalleled high-rate energy storage.

Author

Shi Y, Lu X, Xu Z, Wang Q, Guo H, Jia J, Fang B, Yuan N, and Ding J

Abstract

MXene film electrodes for supercapacitors, assembled with MXene nanosheets as structure units, inevitably suffer from self-restacking, which severely restrains ion transport kinetics and results in insufficient active site utilization and poor rate capability. Herein, an in situ foaming strategy employing the accumulated gas generated during the etching of sacrificial templates, combined with the confinement between the MXene film, has been proposed to fabricate pores between stacked MXene sheets and along the vertical direction of the film. The surface chemistry of the foamed film was further modified by alkali washing treatment to replace hydrophobic -F groups with hydrophilic -OH groups to improve electrolyte penetration and introduce more active sites. The resultant porous MXene film electrode exhibits a greatly improved specific capacitance (354.1 F g -1 at 5 mV s -1 ) and unparalleled rate capability (with a capacitance retention of 96.1% at 2000 mV s -1 ). This work demonstrates a facile but efficient method for the construction of porous MXene films, simultaneously providing insights into the promising applications of MXenes.

Published
2022
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