Architecting Sub-2 nm Organosilica Nanohybrids for Far-field Super-resolution Imaging.
KAUST DepartmentAdvanced Membranes and Porous Materials Research Center
Chemical Science Program
Nanostructured Functional Materials (NFM) laboratory
Physical Science and Engineering (PSE) Division
Online Publication Date2019-10-30
Print Publication Date2020-01-07
Embargo End Date2020-10-31
Permanent link to this recordhttp://hdl.handle.net/10754/660132
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AbstractStimulated emission depletion (STED) microscopy enables ultrastructural imaging of biological samples with high spatiotemporal resolution. Herein, we report a new class of STED nanoprobes based on fluorescent organosilica nanohybrids featuring sub-2 nm physical dimension and near-unity quantum yield. Corroborated by theoretical calculations, we experimentally demonstrate that the detrimental spin-orbit coupling (SOC) effect of heavy-atom-rich organic fluorophores can be effectively mitigated through a silane-molecule-mediated hydrolysis-condensation/dehalogenation process, resulting in bright fluorescent organosilica nanohybrids integrating with multiple emitters in one hybrid nanodot. When harnessed as STED nanoprobes, these sub-2 nm fluorescent nanohybrids show intense photoluminescence, high biocompatibility, and satisfactory long-term photostability. By taking advantages of the low-power excitation (0.5 uW), prolonged singlet-state lifetime, and negligible depletion-induced re-excitation, these fluorescent STED nanohybrids present high depletion efficiency (> 96%), extremely low saturation intensity (PSat = 0.54 mW, ~0.188 MW/cm2), and eventually ultra-high lateral resolution of sub-20 nm (~Wavelength em/28). We believe that this approach may facilitate the expansion of the nanoprobe toolbox across imaging and biological disciplines.
CitationLiu, X., Liang, L., Yan, W., Qin, X., Peng, X., Han, F., … Qu, J. (2019). Architecting Sub-2 nm Organosilica Nanohybrids for Far-field Super-resolution Imaging. Angewandte Chemie International Edition. doi:10.1002/anie.201912404
SponsorsThis work is supported by the Singapore Ministry of Education (MOE2017-T2-2-110), Agency for Science, Technology and Research (A*STAR) (Grant NO. A1883c0011), National Research Foundation, Prime Minister’s Office, Singapore under its Competitive Research Program (Award No. NRF-CRP15-2015-03) and under the NRF Investigatorship programme (Award No. NRF-NRFI05-2019-0003), the National Key R&D Program of China (2017YFA0700500), the National Natural Science Foundation of China (21771135, 21701119, 61705137, 81727804, 61975127), the Science and Technology Project of Shenzhen (KQJSCX20180328093614762). The computational work for this article was supported by resources of the Hihg Performance Computing System at National University of Singapore. 10.1002/anie.201912404.