Skip to main navigation Skip to search Skip to main content

Inverse design of plasmonic nanoantenna using generative adversarial network

  • Qiwen Bao
  • , Dasen Zhang
  • , Xianjin Liu
  • , Licheng Wang
  • , Junjun Xiao*
  • *Corresponding author for this work
  • Harbin Institute of Technology Shenzhen

Research output: Contribution to journalArticlepeer-review

Abstract

The local surface plasmon resonance (LSPR) effect has been widely used in various nanophotonic applications. However, because the LSPR effect is highly sensitive to the structure and geometry, it is desirable to efficiently search viable geometries for predefined local field enhancement spectrum. Herein we present a generative adversarial network-based LSPR nanoantenna design scheme. By encoding the antenna structure information into an red-green-blue (RGB) color image, the corresponding nanoantenna structure can be inverse-designed to achieve the required enhancement spectrum of the local field. The proposed scheme can accurately offer the multiple geometry layout for the customized specific spectrum in seconds, which could be beneficial for fast design and fabrication of plasmonic nanoantenna.

Original languageEnglish
Article number365204
JournalNanotechnology
Volume34
Issue number36
DOIs
StatePublished - 3 Sep 2023
Externally publishedYes

Keywords

  • deep learning
  • generative adversarial network
  • inverse design
  • plasmonic nanoantenna

Fingerprint

Dive into the research topics of 'Inverse design of plasmonic nanoantenna using generative adversarial network'. Together they form a unique fingerprint.

Cite this