Opto-Electronic Advances最新文献

Physics-informed deep learning for fringe pattern analysis 为条纹图案分析提供物理信息的深度学习

IF 14.1 1区物理与天体物理

Opto-Electronic Advances Pub Date : 2024-01-01 DOI: 10.29026/oea.2024.230034

Wei Yin, Yuxuan Che, Xinsheng Li, Mingyu Li, Yan Hu, Shijie Feng, E. Lam, Qian Chen, C. Zuo

引用次数: 1

Highly efficient vectorial field manipulation using a transmitted tri-layer metasurface in the terahertz band 在太赫兹波段使用传输三层超表面的高效矢量场操作

IF 14.1 1区物理与天体物理

Opto-Electronic Advances Pub Date : 2023-01-01 DOI: 10.29026/oea.2023.220012

Huan Zhao, Xin-Ke Wang, Shutian Liu, Yan Zhang

引用次数: 6

Switching of K-Q intervalley trions fine structure and their dynamics in n-doped monolayer WS2 氮掺杂单层WS2中K-Q介子精细结构的开关及其动力学

IF 14.1 1区物理与天体物理

Opto-Electronic Advances Pub Date : 2023-01-01 DOI: 10.29026/oea.2023.220034

Jiajie Pei, Xue Liu, A. G. del Águila, Di Bao, Sheng Liu, M. Amara, Weijie Zhao, Feng Zhang, Congya You, Yongzhen Zhang, Kenji Watanabe, T. Taniguchi, Han Zhang, Qihua Xiong

引用次数: 0

Janus aramid nanofiber aerogel incorporating plasmonic nanoparticles for high-efficiency interfacial solar steam generation 结合等离子体纳米粒子的Janus芳纶纳米纤维气凝胶用于高效率的界面太阳能蒸汽产生

IF 14.1 1区物理与天体物理

Opto-Electronic Advances Pub Date : 2023-01-01 DOI: 10.29026/oea.2023.220061

Hui Zhang, Lei Feng, Fengyue Wang, Mingze Liu, Y. Zhang, Jia Zhu, Yan-qing Lu, Ting Xu

引用次数: 0

4K-DMDNet: diffraction model-driven network for 4K computer-generated holography 4K- dmdnet:用于4K计算机生成全息的衍射模型驱动网络

IF 14.1 1区物理与天体物理

Opto-Electronic Advances Pub Date : 2023-01-01 DOI: 10.29026/oea.2023.220135

Kexuan Liu, Jiachen Wu, Zehao He, Liang Cao

{"title":"4K-DMDNet: diffraction model-driven network for 4K computer-generated holography","authors":"Kexuan Liu, Jiachen Wu, Zehao He, Liang Cao","doi":"10.29026/oea.2023.220135","DOIUrl":"https://doi.org/10.29026/oea.2023.220135","url":null,"abstract":"Deep learning offers a novel opportunity to achieve both high-quality and high-speed computer-generated holography (CGH). Current data-driven deep learning algorithms face the challenge that the labeled training datasets limit the training performance and generalization. The model-driven deep learning introduces the diffraction model into the neural network. It eliminates the need for the labeled training dataset and has been extensively applied to hologram generation. However, the existing model-driven deep learning algorithms face the problem of insufficient constraints. In this study, we propose a model-driven neural network capable of high-fidelity 4K computer-generated hologram generation, called 4K Diffraction Model-driven Network (4K-DMDNet). The constraint of the reconstructed images in the frequency domain is strengthened. And a network structure that combines the residual method and sub-pixel convolution method is built, which effectively enhances the fitting ability of the network for inverse problems. The generalization of the 4K-DMDNet is demonstrated with binary, grayscale and 3D images. High-quality full-color optical reconstructions of the 4K holograms have been achieved at the wavelengths of 450 nm, 520 nm, and 638 nm.","PeriodicalId":19611,"journal":{"name":"Opto-Electronic Advances","volume":"1 1","pages":""},"PeriodicalIF":14.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69522178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

All-fiber ellipsometer for nanoscale dielectric coatings 纳米介质涂层全光纤椭偏仪

IF 14.1 1区物理与天体物理

Opto-Electronic Advances Pub Date : 2023-01-01 DOI: 10.29026/oea.2023.230048

J. Imas, I. Matías, I. del Villar, A. Ozcáriz, C. Zamarreño, J. Albert

引用次数: 0

A bioinspired flexible optical sensor for force and orientation sensing 一种用于力和方向传感的仿生柔性光学传感器

IF 14.1 1区物理与天体物理

Opto-Electronic Advances Pub Date : 2023-01-01 DOI: 10.29026/oea.2023.230051

Lei Zhang, Liming Tong

引用次数: 0

Novel all-fiber-optic technology for control and multi-color probing of neural circuits in freely-moving animals 用于自由运动动物神经回路控制和多色探测的新型全光纤技术

IF 14.1 1区物理与天体物理

Opto-Electronic Advances Pub Date : 2023-01-01 DOI: 10.29026/oea.2023.230086

Xing Li

引用次数: 0

ZnO nanowires based degradable high-performance photodetectors for eco-friendly green electronics 基于ZnO纳米线的可降解高性能光电探测器，用于环保绿色电子产品

IF 14.1 1区物理与天体物理

Opto-Electronic Advances Pub Date : 2023-01-01 DOI: 10.29026/oea.2023.220020

Bhavaniprasad Yalagala, A. Dahiya, R. Dahiya

{"title":"ZnO nanowires based degradable high-performance photodetectors for eco-friendly green electronics","authors":"Bhavaniprasad Yalagala, A. Dahiya, R. Dahiya","doi":"10.29026/oea.2023.220020","DOIUrl":"https://doi.org/10.29026/oea.2023.220020","url":null,"abstract":"Disposable devices designed for single and/or multiple reliable measurements over a short duration have attracted con-siderable interest recently. However, these devices often use non-recyclable and non-biodegradable materials and wasteful fabrication methods. Herein, we present ZnO nanowires (NWs) based degradable high-performance UV photodetectors (PDs) on flexible chitosan substrate. Systematic investigations reveal the presented device exhibits excellent photo response, including high responsivity (55 A/W), superior specific detectivity (4x10 14 jones), and the highest gain (8.5x10 10 ) among the reported state of the art biodegradable PDs. Further, the presented PDs display excellent mechanical flexibility under wide range of bending conditions and thermal stability in the measured temperature range (5–50 °C). The biodegradability studies performed on the device, in both deionized (DI) water (pH≈6) and PBS solution (pH=7.4), show fast degradability in DI water (20 mins) as compared to PBS (48 h). These results show the potential the presented approach holds for green and cost-effective fabrication of wearable, and disposable sensing systems with reduced adverse environmental impact.","PeriodicalId":19611,"journal":{"name":"Opto-Electronic Advances","volume":"1 1","pages":""},"PeriodicalIF":14.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69520514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Table-top optical parametric chirped pulse amplifiers: past and present 台式光学参数啁啾脉冲放大器:过去和现在

IF 14.1 1区物理与天体物理

Opto-Electronic Advances Pub Date : 2023-01-01 DOI: 10.29026/oea.2023.220046

A. Dubietis, A. Matijošius

引用次数: 6