Chiral detection of biomolecules based on reinforcement learning  

作　　者：Yuxiang Chen Fengyu Zhang Zhibo Dang Xiao He Chunxiong Luo Zhengchang Liu Pu Peng Yuchen Dai Yijing Huang Yu Li Zheyu Fang 

机构地区：[1]School of Physics,Peking University,Beijing 100871,China [2]The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics,School of Physics&Center for Quantitative Biology,Academy for Advanced Interdisciplinary Studies,Peking University,Beijing 100871,China [3]Academy for Advanced Interdisciplinary Studies,Peking University,Beijing 100871,China [4]Wenzhou Institute,University of Chinese Academy of Sciences,Wenzhou 325001,China

出　　处：《Opto-Electronic Science》2023年第1期1-10,共10页光电科学（英文）

基　　金：This work is supported by the National Science Foundation of China(Grant Nos.12027807,62225501,and 11974002);National Key Research and Development Program of China(Grant No.2020YFA0211300,2020YFA0906900,and 2021YFF1200500);PKU-Baidu Fund Project(Grant No.2020BD023),and High-performance Computing Platform of Peking University.

摘　　要：Chirality plays an important role in biological processes,and enantiomers often possess similar physical properties and different physiologic functions.In recent years,chiral detection of enantiomers become a popular topic.Plasmonic metasurfaces enhance weak inherent chiral effects of biomolecules,so they are used in chiral detection.Artificial intelligence algorithm makes a lot of contribution to many aspects of nanophotonics.Here,we propose a nanostructure design method based on reinforcement learning and devise chiral nanostructures to distinguish enantiomers.The algorithm finds out the metallic nanostructures with a sharp peak in circular dichroism spectra and emphasizes the frequency shifts caused by nearfield interaction of nanostructures and biomolecules.Our work inspires universal and efficient machine-learning methods for nanophotonic design.

关 键 词：chiral detection metasurface deep learning CATHODOLUMINESCENCE 

分 类 号：O62[理学—有机化学]