Zhang XR, Cui TJ. Artificial intelligence-assisted chiral nanophotonic designs. Opto-Electron Adv 6, 230057 (2023). doi: 10.29026/oea.2023.230057
Citation: Zhang XR, Cui TJ. Artificial intelligence-assisted chiral nanophotonic designs. Opto-Electron Adv 6, 230057 (2023). doi: 10.29026/oea.2023.230057

News & Views Open Access

Artificial intelligence-assisted chiral nanophotonic designs

More Information
  • Chiral nanostructures can enhance the weak inherent chiral effects of biomolecules and highlight the important roles in chiral detection. However, the design of the chiral nanostructures is challenged by extensive theoretical simulations and explorative experiments. Recently, Zheyu Fang’s group proposed a chiral nanostructure design method based on reinforcement learning, which can find out metallic chiral nanostructures with a sharp peak in circular dichroism spectra and enhance the chiral detection signals. This work envisions the powerful roles of artificial intelligence in nanophotonic designs.
  • 加载中
  • [1] Barron LD. Molecular Light Scattering and Optical Activity 2nd ed (Cambridge University Press, Cambridge, 2009).

    Google Scholar

    [2] Droulias S, Bougas L. Chiral sensing with achiral anisotropic metasurfaces. Phys Rev B 104, 075412 (2021). doi: 10.1103/PhysRevB.104.075412

    CrossRef Google Scholar

    [3] Zhao Y, Askarpour AN, Sun LY, Shi JW, Li XQ et al. Chirality detection of enantiomers using twisted optical metamaterials. Nat Commun 8, 14180 (2017). doi: 10.1038/ncomms14180

    CrossRef Google Scholar

    [4] Brullot W, Vanbel MK, Swusten T, Verbiest T. Resolving enantiomers using the optical angular momentum of twisted light. Sci Adv 2, e1501349 (2016). doi: 10.1126/sciadv.1501349

    CrossRef Google Scholar

    [5] Zhang XR, Cui TJ. Single-particle dichroism using orbital angular momentum in a microwave plasmonic resonator. ACS Photonics 7, 3291–3297 (2020). doi: 10.1021/acsphotonics.0c01139

    CrossRef Google Scholar

    [6] Zhang XR, Zhao X, Cui TJ. Microwave vortex transceiver system with continuous tunability using identical plasmonic resonators. Adv Opt Mater 10, 2201543 (2022). doi: 10.1002/adom.202201543

    CrossRef Google Scholar

    [7] Zhang Q, Liu C, Wan X, Zhang L, Liu S et al. Machine-learning designs of anisotropic digital coding metasurfaces. Adv Theory Simul 2, 1800132 (2019). doi: 10.1002/adts.201800132

    CrossRef Google Scholar

    [8] Jiang JQ, Fan JA. Global optimization of dielectric metasurfaces using a physics-driven neural network. Nano Lett 19, 5366–5372 (2019). doi: 10.1021/acs.nanolett.9b01857

    CrossRef Google Scholar

    [9] Melati D, Grinberg Y, Dezfouli MK, Janz S, Cheben P et al. Mapping the global design space of nanophotonic components using machine learning pattern recognition. Nat Commun 10, 4775 (2019). doi: 10.1038/s41467-019-12698-1

    CrossRef Google Scholar

    [10] Khatib O, Ren SM, Malof J, Padilla WJ. Deep learning the electromagnetic properties of metamaterials—a comprehensive review. Adv Funct Mater 31, 2101748 (2021). doi: 10.1002/adfm.202101748

    CrossRef Google Scholar

    [11] Liu ZH, Liu XH, Xiao ZY, Lu CC, Wang HQ et al. Integrated nanophotonic wavelength router based on an intelligent algorithm. Optica 6, 1367–1373 (2019). doi: 10.1364/OPTICA.6.001367

    CrossRef Google Scholar

    [12] Liu C, Yu WM, Ma Q, Li LL, Cui TJ. Intelligent coding metasurface holograms by physics-assisted unsupervised generative adversarial network. Photonics Res 9, B159–B167 (2021). doi: 10.1364/PRJ.416287

    CrossRef Google Scholar

    [13] Chen YX, Zhang FY, Dang ZB, He X, Luo CX et al. Chiral detection of biomolecules based on reinforcement learning. Opto-Electron Sci 2, 220019 (2023). doi: 10.29026/oes.2023.220019

    CrossRef Google Scholar

  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Figures(1)

Article Metrics

Article views(2403) PDF downloads(791) Cited by(0)

Access History

Other Articles By Authors

Article Contents

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint