Near- and far-field wave shaping for optofluidic particle manipulation
Near- and far-field wave shaping for optofluidic particle manipulation
Optofluidic particle manipulation provides a powerful and versatile technological platform for on-chip sensing. Embedded planar nanophotonic devices can shape electromagnetic fields in fluidic channels, allowing for a high level of control over particles. This thesis reports my research contribution to designing optofluidic nanostructures for several different kinds of on-chip particle manipulation that are detailed as below. I have numerically demonstrated plasmonic nanoparticle routers that can guide and route nanospheres in a microfluidic channel. I have analyzed the power flow and the corresponding optical force on the nanosphere, and have derived the Maxwell stress tensor utilized in the finite element analysis solver. I also identified the relationship between the relative refractive index of the nanospheres and the magnitude of the generated optical force. The results suggest a new method for next-generation plasmo-fluidic sensing. I have designed dielectric metalenses with phase profiles that can be coherently controlled. The Mie scattering field from the meta-atoms of the metalens can be tailored dynamically, in which the output Bessel beam sweeps in a range from –1.37° to 1.36°. I have further analyzed particle routing in a continuous flow. I have numerically demonstrated a metalens microfluidic microsphere sorting based on fluorescent color. The sorting originates from the metalens’ ability to focus fluorescent light back onto the target sphere, creating self-induced optical tweezers. Because the embedded metalens doublet eliminates the need for any additional sorting mechanism, the technique can be referred to as FEACS (Fluorescence-Enabled
University of Southampton
Yin, Shengqi
363a868e-95cb-4354-b52f-0d4f9fcd3e70
June 2023
Yin, Shengqi
363a868e-95cb-4354-b52f-0d4f9fcd3e70
Fang, Xu
96b4b212-496b-4d68-82a4-06df70f94a86
Green, Nicolas
d9b47269-c426-41fd-a41d-5f4579faa581
Yin, Shengqi
(2023)
Near- and far-field wave shaping for optofluidic particle manipulation.
University of Southampton, Doctoral Thesis, 194pp.
Record type:
Thesis
(Doctoral)
Abstract
Optofluidic particle manipulation provides a powerful and versatile technological platform for on-chip sensing. Embedded planar nanophotonic devices can shape electromagnetic fields in fluidic channels, allowing for a high level of control over particles. This thesis reports my research contribution to designing optofluidic nanostructures for several different kinds of on-chip particle manipulation that are detailed as below. I have numerically demonstrated plasmonic nanoparticle routers that can guide and route nanospheres in a microfluidic channel. I have analyzed the power flow and the corresponding optical force on the nanosphere, and have derived the Maxwell stress tensor utilized in the finite element analysis solver. I also identified the relationship between the relative refractive index of the nanospheres and the magnitude of the generated optical force. The results suggest a new method for next-generation plasmo-fluidic sensing. I have designed dielectric metalenses with phase profiles that can be coherently controlled. The Mie scattering field from the meta-atoms of the metalens can be tailored dynamically, in which the output Bessel beam sweeps in a range from –1.37° to 1.36°. I have further analyzed particle routing in a continuous flow. I have numerically demonstrated a metalens microfluidic microsphere sorting based on fluorescent color. The sorting originates from the metalens’ ability to focus fluorescent light back onto the target sphere, creating self-induced optical tweezers. Because the embedded metalens doublet eliminates the need for any additional sorting mechanism, the technique can be referred to as FEACS (Fluorescence-Enabled
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Published date: June 2023
Identifiers
Local EPrints ID: 476226
URI: http://eprints.soton.ac.uk/id/eprint/476226
PURE UUID: 37d43831-e7cb-4067-934c-61e390455e82
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Date deposited: 14 Apr 2023 16:47
Last modified: 08 Aug 2024 01:49
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Contributors
Author:
Shengqi Yin
Thesis advisor:
Xu Fang
Thesis advisor:
Nicolas Green
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