Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Application of deep learning to direct and inverse problems in plasmonic coloring

Not Accessible

Your library or personal account may give you access

Abstract

Laser pulses can color noble metals by inducing nanoparticles on their surface. We apply deep learning to solve the direct and inverse problems which link nanoparticle distributions and laser parameters to the produced colour.

© 2019 The Author(s)

PDF Article
More Like This
Deep Learning for Engineering Optical Scattering from Plasmonic Nanostructures

Joshua Baxter, Julien Desautels, Antonio Calà Lesina, Pierre Berini, and Lora Ramunno
JW2D.4 Flat Optics: Components to Systems (FLATOPTICS) 2021

Deep Learning for Design and Retrieval of Plasmonic Nanostructures

Michael Mrejen, Itzik Malkiel, Achiya Nagler, Uri Arieli, Lior Wolf, and Haim Suchowski
FTu4C.3 CLEO: QELS_Fundamental Science (CLEO:FS) 2019

Inverse Design of Photonic Crystal Nanobeam Cavity Structure via Deep Neural Network

Jianjun Hao, Lei Zheng, Daquan Yang, and Yijun Guo
M4A.296 Asia Communications and Photonics Conference (ACP) 2019

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All Rights Reserved