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您的检索式：作者名="Lou Haoran"
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| 1 | Flexible ultraviolet photodetectors based on ZnO–SnO_2 heterojunction nanowire arrays显示文摘A ZnO–SnO_2 nanowires(NWs) array, as a metal oxide semiconductor, was successfully synthesized by a near-field electrospinning method for the applications as high performance ultraviolet photodetectors. Ultraviolet photodetectors based on a single nanowire exhibited excellent photoresponse properties to 300 nm ultraviolet light illumination including ultrahigh I_(on)/I_(off) ratios(up to 10~3), good stability and reproducibility because of the separation between photo-generated electron-hole pairs. Moreover, the NWs array shows an enhanced photosensing performance. Flexible photodetectors on the PI substrates with similar tendency properties were also fabricated. In addition, under various bending curvatures and cycles, the as-fabricated flexible photodetectors revealed mechanical flexibility and good stable electrical properties, showing that they have the potential for applications in future flexible photoelectron devices. | Zheng Lou Xiaoli Yang Haoran Chen Zhongzhu Liang | 2018 | Journal of Semiconductors2018，39，2： | 5 |
| 2 | Growth of aligned SnS nanowire arrays for near infrared photodetectors显示文摘Aligned SnS nanowires arrays were grown via a simple chemical vapor deposition method.As-synthesized SnS nanowires are single crystals grown along the[111]direction.The single SnS nanowire based device showed excellent response to near infrared lights with good responsivity of 267.9 A/W,high external quantum efficiency of 3.12×10^4%and fast response time.Photodetectors were built on the aligned SnS nanowire arrays,exhibiting a light on/off ratio of 3.6,and the response and decay time of 4.5 and 0.7 s,respectively,to 1064 nm light illumination. | Guozhen Shen Haoran Chen Zheng Lou | 2020 | Journal of Semiconductors2020，41，4： | 2 |
| 3 | Vehicle-following system based on deep reinforcement learning in marine scene显示文摘In order to solve the problems that the feature data type are not rich enough in the data collection process about the vehicle-following task in marine scene which results in a long model convergence time and high training difficulty,a two-stage vehicle-following system was proposed.Firstly,semantic segmentation model predicts the number of pixels of the followed target,then the number of pixels of the followed target is mapped to the position feature.Secondly,deep reinforcement learning algorithm enables the control equipment to make decision action,to ensure that two moving objects remain within the safe distance.The experimental results show that the two-stage vehicle-following system has a 40%faster convergence rate than the model without position feature,and the following stability is significantly improved by adding the position feature. | Zhang Xin Lou Haoran Jiang Li Xiao Qianhao Cai Zhuwen | 2022 | The Journal of China Universities of Posts and Telecommunications2022，29，5： | 0 |
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