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Insights into the generation of laser-induced assembly of MoSe_(2) nanospheres 被引量:1
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作者 Gangshuo Liu zengxin huang +4 位作者 Chao Yan Shanshan Li Can Xu Lipei Song Dengfeng Kuang 《Nano Research》 SCIE EI CSCD 2022年第7期6686-6694,共9页
Laser-induced assembly is a promising technology for advancing micro/nano photonic devices.However,the dynamic process and the photothermal interaction in laser-induced assembly technique,as well as the role of laser ... Laser-induced assembly is a promising technology for advancing micro/nano photonic devices.However,the dynamic process and the photothermal interaction in laser-induced assembly technique,as well as the role of laser illumination pattern on the assembly structure have not been well investigated.In this paper,we prepare dark MoSe_(2) nanospheres with a facile solvothermal synthesis method and grow a concentric ring-shaped assembly with incident light following Fresnel circular-aperture diffraction.The impact of the illumination light filed on the structure of the assembly is investigated.The concentric ring-shaped assembly reveals focusing effect with about 4.87 times intensity amplification.Optical trap effect,photothermal effect,and tension effect are proved to synergistically enhance the trap stiffness and broaden trap region.This work gives an insight into the production of laser induced assembly,hence broadens the potential application of nanoparticles and assembly in micro-optics and photonic devices. 展开更多
关键词 laser-induced assembly MoSe_(2)nanospheres optical trap photothermal interaction
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Bidirectional cascaded deep neural networks with a pretrained autoencoder for dielectric metasurfaces 被引量:1
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作者 WEICHAO KONG JUN CHEN +1 位作者 zengxin huang DENGFENG KUANG 《Photonics Research》 SCIE EI CAS CSCD 2021年第8期1607-1615,共9页
Metasurfaces composed of meta-atoms provide promising platforms for manipulating amplitude,phase,and polarization of light.However,the traditional design methods of metasurfaces are time consuming and laborious.Here,w... Metasurfaces composed of meta-atoms provide promising platforms for manipulating amplitude,phase,and polarization of light.However,the traditional design methods of metasurfaces are time consuming and laborious.Here,we propose a bidirectional cascaded deep neural network with a pretrained autoencoder for rapid design of dielectric metasurfaces in the range of 450 nm to 850 nm.The forward model realizes a prediction of amplitude and phase responses with a mean absolute error of 0.03.Meanwhile,the backward model can retrieve patterns of meta-atoms in an inverse-design manner.The availability of this model is demonstrated by database establishment,model evaluation,and generalization testing.Furthermore,we try to reveal the mechanism behind the model in a visualization way.The proposed approach is beneficial to reduce the cost of computation burden and improve nanophotonic design efficiency for solving electromagnetic on-demand design issues automatically. 展开更多
关键词 NEURAL NETWORKS DIELECTRIC
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