Characterization of deep sub-wavelength nanowells by imaging the photon state scattering spectra

Liu, Weiping, Liu, Xuefeng and Gao, Xiaohong W. ORCID logoORCID: (2021) Characterization of deep sub-wavelength nanowells by imaging the photon state scattering spectra. Optics Express, 29 (2) . pp. 1221-1231. ISSN 1094-4087 [Article] (doi:10.1364/OE.413942)

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Optical-matter interactions and photon scattering in a sub-wavelength space are of great interest in many applications, such as nanopore-based gene sequencing and molecule characterization. Previous studies show that spatial distribution features of the scattering photon states are highly sensitive to the dielectric and structural properties of the nanopore array and matter contained on or within them, as a result of the complex optical-matter interaction in a confined system. In this paper, we report a method for shape characterization of subwavelength nanowells using photon state spatial distribution spectra in the scattering near field. Far-field parametric images of the near-field optical scattering from sub-wavelength nanowell arrays on a SiN substrate were obtained experimentally. Finite-difference time-domain simulations were used to interpret the experimental results. The rich features of the parametric images originating from the interaction of the photons and the nanowells were analyzed to recover the size of the nanowells. Experiments on nanoholes modified with Shp2 proteins were also performed. Results show that the scattering distribution of modified nanoholes exhibits significant differences compared to empty nanoholes. This work highlights the potential of utilizing the photon status scattering of nanowells for molecular characterization or other virus detection applications.

Item Type: Article
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 33802
Notes on copyright: © 2021 Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.
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Depositing User: Xiaohong Gao
Date Deposited: 10 Sep 2021 08:53
Last Modified: 02 Nov 2022 11:41

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