Photonics Research, Volume. 12, Issue 5, 959(2024)

Optical trapping-enhanced probes designed by a deep learning approach

Miao Peng1,2、†, Guangzong Xiao1,3、†,*, Xinlin Chen1,3, Te Du4, Tengfang Kuang1,3, Xiang Han1,3, Wei Xiong1,3, Gangyi Zhu5, Junbo Yang4, Zhongqi Tan1,3, Kaiyong Yang1,3, and Hui Luo1,3
Author Affiliations
  • 1College of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha 410073, China
  • 2College of Electronic Information and Physics, Central South University of Forestry and Technology, Changsha 410004, China
  • 3Nanhu Laser Laboratory, National University of Defense Technology, Changsha 410021, China
  • 4Center of Material Science, National University of Defense Technology, Changsha 410073, China
  • 5College of Communication and Information Technology, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
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    Figures & Tables(12)
    (a) The schematic of the trapped SSN nanoparticle, which is made of Si (magenta) and Si3N4 (blue), with its long axis aligned to the optical axis (z-axis) of the trapping beam (red). The cross section in the x−y plane is a square of width W, and the aspect ratio AR is the ratio of height H to width W. (b) The effective refractive indices and birefringence of the SSN nanoparticles as a function of ρ. (c) Top-view and (d) side-view of SEM images of SSN nanoparticles with ρ=0.2, W=450 nm, and AR=2.
    The relationship between the axial stiffness kz of SSN nanoparticles and the width W, aspect ratio AR under different ρ values. (a) ρ=0.1, (b) ρ=0.2, (c) ρ=0.3, (d) ρ=0.4, (e) ρ=0.5, (f) ρ=0.6, (g) ρ=0.7, (h) ρ=0.8, (i) ρ=0.9. The black pixels in the maps indicate the nanoparticle sizes that cannot be trapped in 3D due to excessive scattering forces.
    Architecture of the DL network based on the NN-PSO algorithm, where the input is the size parameters and the output is the kz.
    The kz optimization process for ρ=0.2 (a) and 0.3 (b), respectively. The arrow indicates the route to find the optimal solution. The circle numbers indicate the number of the grid to be calculated in that route, and the blue dot indicates the optimal solution.
    The x- (a), y- (b), and z- (c) axis power spectral density curves for two types of particles (SSN and TiO2) measured in water.
    The fabrication process of SSN nanoparticles. (The legend is the color coding for different materials.)
    Characterization of SSN nanoparticles. (a) and (b) SEM images of the sample shown In step (8). (d) Height of the unit cell as measured by AFM.
    To determine the exact dissolution time of the Cr sacrificial layer. (a) 47 s, (b) 80 s, (c) 120 s, (d) 180 s, (e) 7 min. (f) A small drop of DI water is dropped on the surface of the samples.
    The trapping efficiency as a function of the radius of the amorphous TiO2 microsphere. The blue and red curves are the axial (Qz) and lateral (Qx) trapping efficiency, respectively.
    The relationship between torques and the angular displacement for two shapes of SSN nanoparticles. ρ=0.2, τx (a), τy (b), τz (c); ρ=0.3, τx (d), τy (e), and τz (f). The blue and red curves represent cylindrical and rectangular SSN nanoparticles, respectively.
    Relationship between rotation angle γ and kz when ρ is 0.2 and 0.3, respectively.
    • Table 1. Trapping Parameters of Two Kinds of Particles in Water

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      Table 1. Trapping Parameters of Two Kinds of Particles in Water

      TypesCorner Frequency fc (Hz)Optical Trap Stiffness k (pNμm1mW1)
      fcxfcyfczkxkykz
      SSN117913048500.750.830.54
      TiO26757291740.430.460.11
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    Miao Peng, Guangzong Xiao, Xinlin Chen, Te Du, Tengfang Kuang, Xiang Han, Wei Xiong, Gangyi Zhu, Junbo Yang, Zhongqi Tan, Kaiyong Yang, Hui Luo, "Optical trapping-enhanced probes designed by a deep learning approach," Photonics Res. 12, 959 (2024)

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    Paper Information

    Category: Nanophotonics and Photonic Crystals

    Received: Jan. 3, 2024

    Accepted: Mar. 8, 2024

    Published Online: May. 6, 2024

    The Author Email: Guangzong Xiao (xiaoguangzong@nudt.edu.cn)

    DOI:10.1364/PRJ.517547

    CSTR:32188.14.PRJ.517547

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