Polarity-triggered anti-Kasha system for high-contrast cell imaging and classification  

作　　者：Junyi Gong Peifa Wei Junkai Liu Yuncong Chen Zheng Zhao Weijun Zhao Huilin Xie Chao Ma Jacky W.Y.Lam Kam Sing Wong Ying Li Ben Zhong Tang 

机构地区：[1]Shenzhen Institute of Aggregate Science and Technology,School of Science and Engineering,The Chinese University of Hong Kong,Shenzhen,China [2]Department of Chemistry,Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction,Institute for Advanced Study,State Key Laboratory of Molecular Nanoscience,Division of Life Science and Department of Chemical and Biological Engineering,The Hong Kong University of Science and Technology,Clear Water Bay,Kowloon,China [3]Institutes of Physical Science and Information Technology,Anhui University,Hefei,China [4]Department of Physics,HKUST,Kowloon,China [5]Guangzhou Municipal and Guangdong Provincial Key Laboratory of Molecular Target and Clinical Pharmacology,The NMPA and State Key Laboratory of Respiratory Disease,Innovation Research Center for AIE Pharmaceutical Biology,School of Pharmaceutical Sciences and the Fifth Affiliated Hospital,Guangzhou Medical University,Guangzhou,China [6]Center for AIE Research,Shenzhen Key Laboratory of Polymer Science and Technology,Guangdong Research Center for Interfacial Engineering of Functional Materials,College of Material Science and Engineering,Shenzhen University,Shenzhen,China [7]Center for Aggregation-Induced Emission,SCUT-HKUST Joint Research Institute,State Key Laboratory of Luminescent Materials and Devices,South China University of Technology,Guangzhou,China [8]AIE Institute,Guangzhou Development District,Huangpu,China

出　　处：《Aggregate》2023年第2期216-226,共11页聚集体（英文）

基　　金：National Natural Science Foundation of China,Grant/Award Number:51903052;Shanghai Pujiang Project,Grant/Award Number:19PJ1400700;Zhejiang Provincial Natural Science Foundation of China,Grant/Award Number:LR17F050001;the National Science Foundation of China,Grant/Award Numbers:21788102,21805002,61735016,61975172;the Research Grants Council of Hong Kong,Grant/Award Numbers:16305518,16304819,N-HKUST609/19,A-HKUST605/16,C6009-17G;Innovation and Technology Commission,Grant/Award Numbers:ITC-CNERC14SC01,ITCPD/17-9;Science and Technology Plan of Shenzhen,Grant/Award Number:JCYJ20200109110608167。

摘　　要：Kasha’s rule,which states that all exciton emissions occur from the lowest excited state and are independent of excitation energy,makes high-energy excitons difficult to use and severely hinders the widespread applications of organic photoluminescent materials in the real world.For decades,scientists have tried to break this rule to unleash the power of high-energy excitons,but only minimal progress has been achieved,with no rational guiding principles provided,and few applications developed.So far,breaking Kasha’s rule has remained a purely academic concept.In this paper,we introduce a design principle for a purely organic anti-Kasha system and synthesise a series of compounds based on the design rule.As predicted,these compounds all display evident S_(2) emissions in dilute solutions.In addition,we introduce a highly accurate(over 90%)convolutional neural network as an assistant for the classification of cells using anti-Kasha luminogens,thereby providing a new application direction for anti-Kasha systems.

关 键 词：anti-Kasha cell classification excited-state dynamics FLUORESCENCE 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]