Reinforcement Learning Enabled Nanophotonic Devices
A reinforcement learning algorithm is used to design photonic devices. The method creates metagratings and grating couplers that efficiently control both the direction and polarization of light. Further, a reinforcement learning approach is used to design in‐plane integrated photonic devices. This approach paves the way for advanced photonic components
Zi Wang +4 more
wiley +1 more source
Meta-optics redefines microdisplay: monolithic color LCoS without polarization dependency. [PDF]
Ou X +11 more
europepmc +1 more source
A highly efficient triple band metasurface enabled absorber for 5G/6G millimeter wave applications
Fatima Younis +5 more
openalex +1 more source
Manipulating the ultranarrow linewidth spectral features of quasi bound states in the continuum is challenging. A metasurface supporting linear‐to‐linear cross‐polarization coupling efficiency surpassing 25% is proposed to address the issue. Less than 100 nm linewidth is achieved, enabling the device to be applied to wavelength‐selective polarization ...
Shuhao Wu +5 more
wiley +1 more source
Near-field probing of the local density of optical states enhanced by bound states in the continuum in nonlocal metasurfaces. [PDF]
Ji J +6 more
europepmc +1 more source
Analysis, design, and fabrication of a high-gain low-profile metasurface antenna using direct feeding of Sievenpiper's HIS. [PDF]
Ghaneizadeh A +3 more
europepmc +1 more source
Long-metallic-strip array with parasitic rings: an efficient metasurface for dual-broadband electromagnetic window at large angles. [PDF]
Li T +9 more
europepmc +1 more source
Single-MicroRNA Detection on High-Selectivity Metasurface Fluorescence Biosensors. [PDF]
Iwanaga M.
europepmc +1 more source
Large-gap cascaded Moiré metasurfaces enabling switchable bright-field and phase-contrast imaging compatible with coherent and incoherent light. [PDF]
Li Y +6 more
europepmc +1 more source

