| 1 | by a cascade optical field modulation strategy facilitating selective multispectral narrow-band near-infrared photodetection显示文摘Since selective detection of multiple narrow spectral bands in the near-infrared(NIR)region still poses a fundamental challenge,we have,in this work,developed NIR photodetectors(PDs)using photon upconversion nanocrystals(UCNCs)combined with perovskite films.To conquer the relatively high pumping threshold of UCNCs,we designed a novel cascade optical field modulation strategy to boost upconversion luminescence(UCL)by cascading the superlensing effect of dielectric microlens arrays and the plasmonic effect of gold nanorods,which readily leads to a UCL enhancement by more than four orders of magnitude under weak light irradiation.By accommodating multiple optically active lanthanide ions in a core-shell-shell hierarchical architecture,developed PDs on top of this structure can detect three well-separated narrow bands in the NIR region,i.e.,those centered at 808,980,and 1540 nm.Due to the large UCL enhancement,the obtained PDs demonstrate extremely high responsivities of 30.73,23.15,and 12.20 AW^(−1) and detectivities of 5.36,3.45,and 1.91×10^(11) Jones for 808,980,and 1540 nm light detection,respectively,together with short response times in the range of 80-120 ms.Moreover,we demonstrate for the first time that the response to the excitation modulation frequency of a PD can be employed to discriminate the incident light wavelength.We believe that our work provides novel insight for developing NIR PDs and that it can spur the development of other applications using upconversion nanotechnology. | Yanan Ji Wen Xu Nan Ding Haitao Yang Hongwei Song Qingyun Liu Hans Agren Jerker Widengren Haichun Liu | 2020 | Light(Science & Applications)2020，9，1： | 6 |
| 5 | An Efficient Webpage Classification Algorithm Based on LSH显示文摘With the explosive growth of Internet information, it is more and more important to fetch real-time and related information. And it puts forward higher requirement on the speed of webpage classification which is one of common methods to retrieve and manage information. To get a more efficient classifier, this paper proposes a webpage classification method based on locality sensitive hash function. In which, three innovative modules including building feature dictionary, mapping feature vectors to fingerprints using Localitysensitive hashing, and extending webpage features are contained. The compare results show that the proposed algorithm has better performance in lower time than the naive bayes one. | Junjun Liu Haichun Sun Zhijun Ding | 2015 | 国际计算机前沿大会会议论文集2015，，1： | 0 |
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