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Optical Nonlinearity Enabled Super-Resolved Multiplexing Microscopy

  • Lei Ding
  • , Chaohao Chen*
  • , Xuchen Shan
  • , Baolei Liu
  • , Dajing Wang
  • , Ziqing Du
  • , Guanshu Zhao
  • , Qian Peter Su
  • , Yang Yang
  • , Benjamin Halkon
  • , Toan Trong Tran
  • , Jiayan Liao
  • , Igor Aharonovich
  • , Min Zhang
  • , Faliang Cheng*
  • , Lan Fu*
  • , Xiaoxue Xu*
  • , Fan Wang*
  • *此作品的通讯作者
  • Dongguan University of Technology
  • University of Technology Sydney
  • Australian National University
  • Beihang University

科研成果: 期刊稿件文章同行评审

摘要

Optical multiplexing for nanoscale object recognition is of great significance within the intricate domains of biology, medicine, anti-counterfeiting, and microscopic imaging. Traditionally, the multiplexing dimensions of nanoscopy are limited to emission intensity, color, lifetime, and polarization. Here, a novel dimension, optical nonlinearity, is proposed for super-resolved multiplexing microscopy. This optical nonlinearity is attributable to the energy transitions between multiple energy levels of the doped lanthanide ions in upconversion nanoparticles (UCNPs), resulting in unique optical fingerprints for UCNPs with different compositions. A vortex beam is applied to transport the optical nonlinearity onto the imaging point-spread function (PSF), creating a robust super-resolved multiplexing imaging strategy for differentiating UCNPs with distinctive optical nonlinearities. The composition information of the nanoparticles can be retrieved with variations of the corresponding PSF in the obtained image. Four channels multiplexing super-resolved imaging with a single scanning, applying emission color and nonlinearity of two orthogonal imaging dimensions with a spatial resolution higher than 150 nm (1/6.5λ), are demonstrated. This work provides a new and orthogonal dimension – optical nonlinearity – to existing multiplexing dimensions, which shows great potential in bioimaging, anti-counterfeiting, microarray assays, deep tissue multiplexing detection, and high-density data storage.

源语言英语
文章编号2308844
期刊Advanced Materials
36
2
DOI
出版状态已出版 - 11 1月 2024

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