title: Scanning superlens microscopy for non-invasive large field-of-view visible light nanoscale imaging.
abstract: Nanoscale correlation of structural information acquisition with specific-molecule identification provides new insight for studying rare subcellular events. To achieve this correlation, scanning electron microscopy has been combined with super-resolution fluorescent microscopy, despite its destructivity when acquiring biological structure information. Here we propose time-efficient non-invasive microsphere-based scanning superlens microscopy that enables the large-area observation of live-cell morphology or sub-membrane structures with sub-diffraction-limited resolution and is demonstrated by observing biological and non-biological objects. This microscopy operates in both non-invasive and contact modes with ∼200 times the acquisition efficiency of atomic force microscopy, which is achieved by replacing the point of an atomic force microscope tip with an imaging area of microspheres and stitching the areas recorded during scanning, enabling sub-diffraction-limited resolution. Our method marks a possible path to non-invasive cell imaging and simultaneous tracking of specific molecules with nanoscale resolution, facilitating the study of subcellular events over a total cell period.
authors.affiliation: State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.|University of Chinese Academy of Sciences, Beijing 100049, China.
authors.forename: Feifei
authors.initials: F
authors.lastname: Wang
authors.affiliation: State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.
authors.forename: Lianqing
authors.initials: L
authors.lastname: Liu
authors.affiliation: State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.
authors.forename: Haibo
authors.initials: H
authors.lastname: Yu
authors.affiliation: State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.|University of Chinese Academy of Sciences, Beijing 100049, China.
authors.forename: Yangdong
authors.initials: Y
authors.lastname: Wen
authors.affiliation: State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.
authors.forename: Peng
authors.initials: P
authors.lastname: Yu
authors.affiliation: State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.
authors.forename: Zhu
authors.initials: Z
authors.lastname: Liu
authors.affiliation: State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.
authors.forename: Yuechao
authors.initials: Y
authors.lastname: Wang
authors.affiliation: State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.|Department of Mechanical and Biomedical Engineering, City University of Hong Kong, Kowloon Tong 999077, Hong Kong.
authors.forename: Wen Jung
authors.initials: WJ
authors.lastname: Li