Circularrr Aops: Nanophotonic Inverse Design Data for Plasmonic Switches

Giving access to supplementary materials for a nanophotonics research paper focused on inverse design and plasmonic switches, updated in March 2024 by author ehsan20e20e. It includes data and code for training artificial neural networks using TensorFlow, Keras, and MATLAB to optimize photonic structures.

Use Cases

• Training neural networks to predict the optical response of plasmonic switches
• Implementing inverse design algorithms using the provided TensorFlow and Keras code
• Reproducing simulation results described in the associated Scientific Reports publication

Strengths

• Associated with a peer-reviewed publication in Scientific Reports
• Includes cross-platform support for MATLAB and Python/Keras
• Focuses on the niche domain of plasmonic-switch inverse design

Limitations

• Unknown record count and file size
• Lack of explicit column definitions in the metadata
• Highly specialized for nanophotonics research

Provenance

Source

ehsan20e20e via GitHub

Collection Method

synthetic

Freshness

Last updated March 10, 2024.