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 

作者机构：Shenzhen Institute of Aggregate Science and TechnologySchool of Science and EngineeringThe Chinese University of Hong KongShenzhenChina Department of ChemistryHong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and ReconstructionInstitute for Advanced StudyState Key Laboratory of Molecular NanoscienceDivision of Life Science and Department of Chemical and Biological EngineeringThe Hong Kong University of Science and TechnologyClear Water BayKowloonChina Institutes of Physical Science and Information TechnologyAnhui UniversityHefeiChina Department of PhysicsHKUSTKowloonChina Guangzhou Municipal and Guangdong Provincial Key Laboratory of Molecular Target and Clinical PharmacologyThe NMPA and State Key Laboratory of Respiratory DiseaseInnovation Research Center for AIE Pharmaceutical BiologySchool of Pharmaceutical Sciences and the Fifth Affiliated HospitalGuangzhou Medical UniversityGuangzhouChina Center for AIE ResearchShenzhen Key Laboratory of Polymer Science and TechnologyGuangdong Research Center for Interfacial Engineering of Functional MaterialsCollege of Material Science and EngineeringShenzhen UniversityShenzhenChina Center for Aggregation-Induced EmissionSCUT-HKUST Joint Research InstituteState Key Laboratory of Luminescent Materials and DevicesSouth China University of TechnologyGuangzhouChina AIE InstituteGuangzhou Development DistrictHuangpuChina 

出 版 物：《Aggregate》 (聚集体（英文）)

年 卷 期：2023年第4卷第2期

页      面：216-226页

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 081002[工学-信号与信息处理] 

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 

主　　题：anti-Kasha cell classification excited-state dynamics fluorescence 

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 *** 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 *** far,breaking Kasha’s rule has remained a purely academic *** this paper,we introduce a design principle for a purely organic anti-Kasha system and synthesise a series of compounds based on the design *** predicted,these compounds all display evident S_(2) emissions in dilute *** 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.