Valeriia Sedova,1 Florie Ogor,2 Joёl Rovera,2 Odysseas Tsilipakos,3 Lisa Lemberg,4 Kevin Heggarty,2 Andreas Erdmannhttps://orcid.org/0000-0001-9150-587X1
1Fraunhofer-Institut für Integrierte Systeme und Bauelementetechnologie IISB (Germany) 2IMT Atlantique Bretagne-Pays de la Loire (France) 3Foundation for Research and Technology-Hellas (Greece) 4Heidelberg Instruments Mikrotechnik GmbH (Germany)
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
Metasurfaces have become a key focus in research and are applied in numerous fields because of their exceptional capability to control electromagnetic waves across microwave to optical frequencies. These artificial sheet materials have the advantages of lightweight and ability to control wave propagation both on the surface and in the surrounding free space. The complexity of fabricating metasurfaces via two-photon lithography (TPL) is addressed through sophisticated modeling. Critical to the success of TPL is the ability to predict the effects of the fabrication process on the final product. This paper introduces three distinct modeling approaches that vary in complexity and predictive capabilities. We evaluate the performance and limitations of a simple threshold model, a compact model and a full model of polymerization. Through application examples, we demonstrate how these models can guide the fabrication of metasurfaces.
Conference Presentation
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
The alert did not successfully save. Please try again later.
Valeriia Sedova, Florie Ogor, Joёl Rovera, Odysseas Tsilipakos, Lisa Lemberg, Kevin Heggarty, Andreas Erdmann, "Advances in modeling and optimization for two-photon lithography," Proc. SPIE 13023, Computational Optics 2024, 1302309 (17 June 2024); https://doi.org/10.1117/12.3017407