Seminar of the Division of Biomedical Physicochemistry
09:00, 24-05-10
Microsoft Teams
Upconversion and Down-shifting Emissions toward Deep Learning Fluorescence Imaging and Information Storage
Professor Lining Sun, Ph.D.
Department of Chemistry, Shanghai University, Shanghai, China
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The seminar will be held remotely using Microsoft Teams. People in the intibs.pl domain can join the Seminarium OFB team using the code: 7aoxdkd. Other persons are asked to contact us at
Abstract:
Lanthanide-doped nanoparticles have been considered as one of the most promising luminescent materials due to their excellent properties. Moreover, benefiting from a unique electronic structure, lanthanides have discrete energy levels and exhibit practical wavelength conversion via down-shifting and upconversion processes. Hence, their emissions cover the spectral regions from UV to NIR.
Here, my talk is mainly devoted to the combination of multi-modal emissions and deep learning. (1) Taking advantage of the Vis/NIR-II multi-modal emissions of UCNPs and deep learning, we successfully demonstrated the storage and decoding of visible light information in pork tissue.[1] (2) We demonstrated the multimode emissions of lanthanide nanocrystals are cooperated with deep learning, where the advantages of narrow emission peak of visible fluorescence and deep tissue penetration of NIR-II fluorescence are combined to offer a unique deep learning fluorescence bioimaging.[2] (3) Lanthanide-doped metal-organic frameworks (Ln-MOFs) have versatile luminescence properties, however it is challenging to achieve lanthanide-based upconversion luminescence in Ln-MOFs. Here, 1,3,5-benzenetricarboxylic acid (BTC) and Yb3+ ions were used to generate crystalline Yb-BTC MOF 1D-microrods with upconversion luminescence at 497 nm under NIR excitation via cooperative luminescence. Additionally, Er3+, Ho3+, Tb3+, and Eu3+ ions were doped into the Yb-BTC MOF and their upconversion luminescence and energy transfer mechanisms were studied. The effects of different dopants on the efficiency of cooperative luminescence were established and will provide guidance for the exploitation of Ln-MOFs exhibiting upconversion.[3]
References
[1] Y. Song, M. Lu, G. A. Mandl, Y. Xie, G. Sun, J. Chen, X. Liu, J. A. Capobianco, L. N. Sun, Energy Migration Control of Multimodal Emissions in an Er3+-Doped Nanostructure for Information Encryption and Deep-Learning Decoding, Angew. Chem. Int. Ed. 2021, 60, 23790. [2] Y. Song, M. Lu, Y. Xie, G. Sun, J. Chen, H. Zhang, X. Liu, F. Zhang, L.N. Sun. Deep Learning Fluorescence Imaging of Visible to NIR-II Based on Modulated Multimode Emissions Lanthanide Nanocrystals. Adv. Funct. Mater. 2022, 32, 2206802. [3] Y. Xie, G. Sun, G. A. Mandl, S. L. Maurizio, J. Chen, J. A. Capobianco, L.N. Sun. Upconversion Luminescence through Cooperative and Energy-Transfer Mechanisms in Yb3+-Metal-Organic Frameworks, Angew. Chem. Int. Ed. 2023, 62, e202216269.