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| 1 | Realizing transmitted metasurface cloak by a tandem neural network显示文摘Being invisible at will has been a long-standing dream for centuries, epitomized by numerous legends;humans have never stopped their exploration steps to realize this dream. Recent years have witnessed a breakthrough in this search due to the advent of transformation optics, metamaterials, and metasurfaces. However, the previous metasurface cloaks typically work in a reflection manner that relies on a high-reflection background, thus limiting the applications. Here, we propose an easy yet viable approach to realize the transmitted metasurface cloak, just composed of two planar metasurfaces to hide an object inside, such as a cat. To tackle the hard-to-converge issue caused by the nonuniqueness phenomenon, we deploy a tandem neural network(T-NN) to efficiently streamline the inverse design. Once pretrained, the T-NN can work for a customer-desired electromagnetic response in one single forward computation, saving a great amount of time. Our work opens a new avenue to realize a transparent invisibility cloak, and the tandem-NN can also inspire the inverse design of other metamaterials and photonics. | ZHENG ZHEN CHAO QIAN YUETIAN JIA ZHIXIANG FAN RAN HAO TONG CAI BIN ZHENG HONGSHENG CHEN ERPING LI | 2021 | Photonics Research2021，9，5： | 1 |
| 2 | A knowledge-inherited learning for intelligent metasurface design and assembly显示文摘Recent breakthroughs in deep learning have ushered in an essential tool for optics and photonics,recurring in various applications of material design,system optimization,and automation control.Deep learning-enabled on-demand metasurface design has been the subject of extensive expansion,as it can alleviate the time-consuming,low-efficiency,and experience-orientated shortcomings in conventional numerical simulations and physics-based methods.However,collecting samples and training neural networks are fundamentally confined to predefined individual metamaterials and tend to fail for large problem sizes.Inspired by object-oriented C++programming,we propose a knowledge-inherited paradigm for multi-object and shape-unbound metasurface inverse design.Each inherited neural network carries knowledge from the'parent'metasurface and then is freely assembled to construct the'offspring'metasurface;such a process is as simple as building a container-type house.We benchmark the paradigm by the free design of aperiodic and periodic metasurfaces,with accuracies that reach 86.7%.Furthermore,we present an intelligent origami metasurface to facilitate compatible and lightweight satellite communication facilities.Our work opens up a new avenue for automatic metasurface design and leverages the assemblability to broaden the adaptability of intelligent metadevices. | Yuetian Jia Chao Qian Zhixiang Fan Tong Cai Er-Ping Li Hongsheng Chen | 2023 | Light(Science & Applications)2023，12，4： | 0 |
| 3 | A new aggregation-induced emission-based fluorescent probe for effective detection of Hg^(2+)and its multiple applications显示文摘Detection of mercury ions(Hg^(2+))in actual samples is of significant importance due to the toxicity of Hg^(2+)to human health.In this work,a simple tetraphenylethene(TPE)derived fluorescent probe TPE-Hg based on aggregation-induced emission(AIE)mechanism was synthesized.TPE-Hg can visually recognize Hg^(2+)in THF/HEPES(1:9,v/v,HEPES 20 mmol/L,pH 7.3)system with rapid response,strong anti-interference ability,large Stokes shift(203 nm),and low detection limit(7.548×10^(-7)mol/L).The results show that Hg^(2+)triggered elimination of TPE-Hg lead to releasing of an AIE-active compound 2 is responsible to the sensing mechanism.TPE-Hg is applicable to detect Hg^(2+)in actual water samples and image Hg^(2+)in living MCF-7 cells.In addition,TPE-Hg is suitable to assay the Hg^(2+)level in seafood and tea samples,and it is alsoapplicable intest strips. | Yongxin Pan Yuetian Guo Ying Li Lijun Tang Xiaomei Yan | 2023 | Chinese Chemical Letters2023，34，12： | 0 |
| 4 | Mining Compressed Frequent Subtrees Set显示文摘The number of frequent subtrees usually grows expo-nentially with the tree size because of combinatorial explosion. As a result, there are too many frequent subtrees for users to manage and use. To solve this problem, we generalize a compressed frame based on δ-cluster to the problem of compressing frequent-subtree sets, and propose an algorithm RPTlocal which can mine com-pressed frequent subtrees set directly. This algorithm sacrifices the theoretical bounds but still has good compression quality. By pruning the search space and generating frequent subtrees directly, this algorithm is also efficient. Experiment result shows that the representative subtrees mining by RPTlocal is almost two orders of magnitude less than the whole collection of the closed subtrees, and is more efficient than CMtreeMiner, the algorithm for mining both closed and Maximal frequent subtrees. | ZHAO Chuanshen WANG Xianyong SUN Zhihui LI Yuetian | 2009 | Wuhan University Journal of Natural Sciences2009，14，1： | 0 |
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