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您的检索式：作者名="Minwei Jiang"
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| 1 | Synthesis and electrochemical performance of La-doped Li_3V_(2-x)La_x(PO_4)_3 cathode materials for lithium batteries显示文摘La-doped Li3V2-xLax(PO4)3 (x=0.01,0.02,and 0.03) cathode materials for lithium ion batteries were synthesized by the microwave-assisted carbothermal reduction method (MW-CTR).The structures and properties of the prepared samples were investigated by X-ray diffraction (XRD) and electrochemical measurements.The results showed that all the three Li3V2-xLax(PO4)3 samples had the same monoclinic structures and sharper diffraction peaks of the crystal plane compared with those of the undoped Li3V2(PO4)3.The initial charge/discharge specific capacity,coulomb efficiency,and discharge decay rate of all the three Li3V2-xLax(PO4)3 samples were superior to those of the undoped Li3V2(PO4)3 sample,and the Li3V1.98La0.02(PO4)3 sample exhibited the best features among the three La-doped Li3V2-xLax(PO4)3 samples.Electrochemical impedance spectroscopy (EIS) demonstrated that the Li3V1.98La0.02(PO4)3 sample had a lower charge transfer resistance and a higher Li ion diffusion coefficient compared with the undoped Li3V2(PO4)3 sample. | JIANG Boquan HU Shufen WANG Minwei OUYANG Xiaoping GONG Zhenyu | 2011 | Rare Metals2011，30，2： | 2 |
| 2 | Diffractive Deep Neural Networks at Visible Wavelengths显示文摘Optical deep learning based on diffractive optical elements offers unique advantages for parallel processing,computational speed,and power efficiency.One landmark method is the diffractive deep neural network(D^(2) NN)based on three-dimensional printing technology operated in the terahertz spectral range.Since the terahertz bandwidth involves limited interparticle coupling and material losses,this paper extends D^(2) NN to visible wavelengths.A general theory including a revised formula is proposed to solve any contradictions between wavelength,neuron size,and fabrication limitations.A novel visible light D^(2) NN classifier is used to recognize unchanged targets(handwritten digits ranging from 0 to 9)and targets that have been changed(i.e.,targets that have been covered or altered)at a visible wavelength of 632.8 nm.The obtained experimental classification accuracy(84%)and numerical classification accuracy(91.57%)quantify the match between the theoretical design and fabricated system performance.The presented framework can be used to apply a D^(2) NN to various practical applications and design other new applications. | Hang Chen Jianan Feng Minwei Jiang Yiqun Wang Jie Lin Jiubin Tan Peng Jin | 2021 | Engineering2021，7，10： | 0 |
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