Inverse Design of Reflective Polarizers using Generative Machine Learning
Автор: Parinaz Naseri
Загружено: 2022-03-30
Просмотров: 612
EuCAP2022, Madrid, Spain, March 2022
Generative machine learning is redefining how we design advanced metasurfaces.
Metasurfaces are key for next-generation wireless communication, but optimizing their designs for performance and manufacturability is a major challenge.
Traditionally, designing triple-band reflective polarizing metasurfaces required extensive expert knowledge and slow, trial-and-error processes—especially for achieving bandwidth, polarization, and angular stability constraints.
Our team used generative adversarial networks (GANs) to automate and accelerate this process, efficiently exploring vast design spaces and delivering unique, high-performing polarizers that meet strict requirements. We even validated this approach with successful simulation, fabrication, and measurement results.
Machine learning is truly unlocking new possibilities in metasurface design.
P.S. Would you trust AI to invent the next generation of wireless tech? Share your thoughts!
#MachineLearning #Metasurfaces #InverseDesign #GenerativeAI #WirelessCommunication #ResearchInnovation
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