Inverse Design of Plasmonic Nanostructures Using Machine Learning for Optimized Prediction of Physical Parameters

Inverse Design of Plasmonic Nanostructures Using Machine Learning for Optimized Prediction of Physical Parameters

Plasmonic nanostructures have been widely studied for their unique optical properties, which are useful in sensing, photonics, and energy. However, the efficient design of these structures, considering the complex relationship between geometry, material, and optical response, remains a challenge. In...

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Bibliographic Details
Main Authors: Luana S. P. Maia, Darlan A. Barroso, Aêdo B. Silveira, Waleska F. Oliveira, André Galembeck, Carlos Alexandre R. Fernandes, Dayse G. C. Bandeira, Benoit Cluzel, Auzuir R. Alexandria, Glendo F. Guimarães
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Photonics
Subjects:
plasmonic
nanostructure
machine learning
inverse design
Online Access:https://www.mdpi.com/2304-6732/12/6/572
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