Artificial intelligence-assisted chiral nanophotonic designs

• Published in: Opto-Electronic Advances Vol. 6; no. 10; p. 230057
• Main Authors: Zhang, Xuanru, Cui, Tie Jun
• Format: Journal Article
• Language: English
• Published: School of Information Science and Engineering,Southeast University,Nanjing 210096,China 01.01.2023; State Key Laboratory of Millimeter Waves,Southeast University,Nanjing 210096,China; Institute of Electromagnetic Space,Southeast University,Nanjing 210096,China; Institue of Optics and Electronics, Chinese Academy of Sciences
• ISSN: 2096-4579
• DOI: 10.29026/oea.2023.230057

Chiral nanostructures can enhance the weak inherent chiral effects of biomolecules and highlight the important roles in chiral detection. However, the design of the chiral nanostructures is challenged by extensive theoretical simulations and explorative experiments. Recently, Zheyu Fang’s group proposed a chiral nanostructure design method based on reinforcement learning, which can find out metallic chiral nanostructures with a sharp peak in circular dichroism spectra and enhance the chiral detection signals. This work envisions the powerful roles of artificial intelligence in nanophotonic designs.