Exploiting Dynamic Nonlinearity in Upconversion Nanoparticles for Super-Resolution Imaging

Chaohao Chen; Lei Ding; Baolei Liu; Ziqing Du; Yongtao Liu; Xiangjun Di; Xuchen Shan; Chenxiao Lin; Min Zhang; Xiaoxue Xu; Xiaolan Zhong; Jianfeng Wang; Lingqian Chang; Benjamin Halkon; Xin Chen; Faliang Cheng; Fan Wang

doi:10.1021/acs.nanolett.2c02269

Exploiting Dynamic Nonlinearity in Upconversion Nanoparticles for Super-Resolution Imaging

Nano Lett. 2022 Sep 14;22(17):7136-7143. doi: 10.1021/acs.nanolett.2c02269. Epub 2022 Aug 26.

Authors

Chaohao Chen^{1

2}, Lei Ding³, Baolei Liu⁴, Ziqing Du³, Yongtao Liu⁵, Xiangjun Di³, Xuchen Shan⁴, Chenxiao Lin⁶, Min Zhang¹, Xiaoxue Xu⁷, Xiaolan Zhong⁴, Jianfeng Wang⁴, Lingqian Chang⁸, Benjamin Halkon⁹, Xin Chen², Faliang Cheng¹, Fan Wang^{4

10}

Affiliations

¹ Guangdong Engineering and Technology Research Center for Advanced Nanomaterials, School of Environment and Civil Engineering, Dongguan University of Technology, Dongguan 523808, China.
² Department of Chemical Engineering, Shaanxi Key Laboratory of Energy Chemical Process Intensification, Institute of Polymer Science in Chemical Engineering, School of Chemical Engineering and Technology, Xi'an Jiaotong University, Xi'an 710049, China.
³ School of Mathematical and Physical Sciences, Faculty of Science, University of Technology Sydney, Ultimo, New South Wales 2007, Australia.
⁴ School of Physics, Beihang University, Beijing 100191, China.
⁵ Smart Computational Imaging Laboratory, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, China.
⁶ Department for Electrochemical Energy Storage, Helmholtz-Zentrum Berlin für Materialien und Energie, Hahn-Meitner-Platz, Berlin 14109, Germany.
⁷ School of Biomedical Engineering, Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, New South Wales 2007, Australia.
⁸ Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China.
⁹ Centre for Audio, Acoustics & Vibration, Faculty of Engineering & IT, University of Technology Sydney, Ultimo, New South Wales 2007, Australia.
¹⁰ School of Electrical and Data Engineering, Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, New South Wales 2007, Australia.

PMID: 36018249
DOI: 10.1021/acs.nanolett.2c02269

Abstract

Single-beam super-resolution microscopy, also known as superlinear microscopy, exploits the nonlinear response of fluorescent probes in confocal microscopy. The technique requires no complex purpose-built system, light field modulation, or beam shaping. Here, we present a strategy to enhance this technique's spatial resolution by modulating excitation intensity during image acquisition. This modulation induces dynamic optical nonlinearity in upconversion nanoparticles (UCNPs), resulting in variations of nonlinear fluorescence response in the obtained images. The higher orders of fluorescence response can be extracted with a proposed weighted finite difference imaging algorithm from raw fluorescence images to generate an image with higher resolution than superlinear microscopy images. We apply this approach to resolve single nanoparticles in a large area, improving the resolution to 132 nm. This work suggests a new scope for the development of dynamic nonlinear fluorescent probes in super-resolution nanoscopy.

Keywords: Upconversion nanoparticles; nonlinear optical response; super-resolution imaging.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Fluorescent Dyes*
Microscopy, Confocal / methods
Nanoparticles*

Substances

Fluorescent Dyes