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20 August 2020 Intelligent inverse design for nanophotonic structures using deep learning
Sunae So, Junsuk Rho
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Proceedings Volume 11469, Emerging Topics in Artificial Intelligence 2020; 1146914 (2020) https://doi.org/10.1117/12.2568211
Event: SPIE Nanoscience + Engineering, 2020, Online Only
Abstract
In this study, we present an intelligent inverse design method of nanophotonic structures using a data-driven approach of deep learning [1-3]. We demonstrate attempts to increase the degree of freedom of design possibility, by designing arbitrary shapes of nanophotonic structures [2] and by designing types of materials and design parameters at the same time [3]. Recently, deep learning has shown its capability to provide appropriate nanophotonic designs for given desired optical functionalities. So far, however, these approaches have been applied to design only few structural parameters for the pre-defined nanophotonic systems. Here, we show two inverse design of nanophotonic structures using deep learning. Our methods increase the degree of freedom by designing nanophotonic structures in the form of binary images and designing types of materials and structural parameters simultaneously.
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Sunae So and Junsuk Rho "Intelligent inverse design for nanophotonic structures using deep learning", Proc. SPIE 11469, Emerging Topics in Artificial Intelligence 2020, 1146914 (20 August 2020); https://doi.org/10.1117/12.2568211
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KEYWORDS
Nanophotonics
Structural design
Binary data
Interfaces
Nanoparticles
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