15 citations · 37 across the 3 of their papers we have counts for
6 papers
Deep Convolutional Neural Networks to Predict Mutual Coupling Effects in Metasurfaces
Sensong An, Bowen Zheng, Mikhail Y. Shalaginov +13
Metasurfaces have provided a novel and promising platform for the realization of compact and large-scale optical devices. The conventional metasurface design approach assumes perio…
A Freeform Dielectric Metasurface Modeling Approach Based on Deep Neural Networks
Sensong An, Bowen Zheng, Mikhail Y. Shalaginov +12
Metasurfaces have shown promising potentials in shaping optical wavefronts while remaining compact compared to bulky geometric optics devices. Design of meta-atoms, the fundamental…
Multifunctional Metasurface Design with a Generative Adversarial Network
Sensong An, Bowen Zheng, Hong Tang +7
Metasurfaces have enabled precise electromagnetic wave manipulation with strong potential to obtain unprecedented functionalities and multifunctional behavior in flat optical devic…
A Novel Modeling Approach for All-Dielectric Metasurfaces Using Deep Neural Networks
Sensong An, Clayton Fowler, Bowen Zheng +11
Metasurfaces have become a promising means for manipulating optical wavefronts in flat and high-performance optical devices. Conventional metasurface device design relies on trial-…
A Metamaterial-inspired Approach to RF Energy Harvesting
Clayton Fowler, Jiangfeng Zhou
We demonstrate an RF energy harvesting rectenna design based on a metamaterial perfect absorber (MPA). With the embedded Schottky diodes, the rectenna converts captured RF waves to…
A Highly Efficient Polarization-Independent Metamaterial-Based RF Energy-Harvesting Rectenna for Low-Power Applications
Clayton Fowler, Jiangfeng Zhou
A highly-efficient multi-resonant RF energy-harvesting rectenna based on a metamaterial perfect absorber featuring closely-spaced polarization-independent absorption modes is prese…