Since the discovery of the laser, optical nonlinearities have been at the core of efficient light conversion sources. Typically, thick transparent crystals or quasi-phase matched waveguides are utilized in conjunction with phase-matching techniques to select a single parametric process. In recent years, due to the rapid developments in artificially structured materials, optical frequency mixing has been achieved at the nanoscale in subwavelength resonators arrayed as metasurfaces. Phase matching becomes relaxed for these wavelength-scale structures, and all allowed nonlinear processes can, in principle, occur on an equal footing. This could promote harmonic generation via a cascaded (consisting of several frequency mixing steps) process. However, so far, all reported work on dielectric metasurfaces have assumed frequency mixing from a direct (single step) nonlinear process. In this work, we prove the existence of cascaded second-order optical nonlinearities by analyzing the second- and third-wave mixing from a highly nonlinear metasurface in conjunction with polarization selection rules and crystal symmetries. We find that the third-wave mixing signal from a cascaded process can be of comparable strength to that from conventional third-harmonic generation and that surface nonlinearities are the dominant mechanism that contributes to cascaded second-order nonlinearities in our metasurface.
In this work, we prove the existence of cascaded second-order nonlinearities in a dielectric metasurface by analyzing the second and third wave mixing signal in conjunction with crystal symmetry and polarization selection rules.
In this work, we investigate the critical coupling of a single gold disk antenna with a focused beam by evaluating its absorption and scattering using spectral interferometry microcopy.
In this work, we investigate the linear optical response of a dielectric metasurface made of vertically-oriented germanium ellipses deposited on walls of a micron-scale cubic silicon nitride unit cell support matrix.
Hot-electron generation has been a topic of intense research for decades for numerous applications ranging from photodetection and photochemistry to biosensing. Recently, the technique of hot-electron generation using non-radiative decay of surface plasmons excited by metallic nanoantennas, or meta-atoms, in a metasurface has attracted attention. These metasurfaces can be designed with thicknesses on the order of the hot-electron diffusion length. The plasmonic resonances of these ultrathin metasurfaces can be tailored by changing the shape and size of the meta-atoms. One of the fundamental mechanisms leading to generation of hot-electrons in such systems is optical absorption, therefore, optimization of absorption is a key step in enhancing the performance of any metasurface based hot-electron device. Here we utilized an artificial intelligence-based approach, the genetic algorithm, to optimize absorption spectra of plasmonic metasurfaces. Using genetic algorithm optimization strategies, we designed a polarization insensitive plasmonic metasurface with 90% absorption at 1550 nm that does not require an optically thick ground plane. We fabricated and optically characterized the metasurface and our experimental results agree with simulations. Finally, we present a convolutional neural network that can predict the absorption spectra of metasurfaces never seen by the network, thereby eliminating the need for computationally expensive simulations. Our results suggest a new direction for optimizing hot-electron based photodetectors and sensors.
Hot-electron generation has been a topic of intense research for decades for numerous applications ranging from photodetection and photochemistry to biosensing. Recently, the technique of hot-electron generation using non-radiative decay of surface plasmons excited by metallic nanoantennas, or meta-atoms, in a metasurface has attracted attention. These metasurfaces can be designed with thicknesses on the order of the hot-electron diffusion length. The plasmonic resonances of these ultrathin metasurfaces can be tailored by changing the shape and size of the meta-atoms. One of the fundamental mechanisms leading to generation of hot-electrons in such systems is optical absorption, therefore, optimization of absorption is a key step in enhancing the performance of any metasurface based hot-electron device. Here we utilized an artificial intelligence-based approach, the genetic algorithm, to optimize absorption spectra of plasmonic metasurfaces. Using genetic algorithm optimization strategies, we designed a polarization insensitive plasmonic metasurface with 90% absorption at 1550 nm that does not require an optically thick ground plane. We fabricated and optically characterized the metasurface and our experimental results agree with simulations. Finally, we present a convolutional neural network that can predict the absorption spectra of metasurfaces never seen by the network, thereby eliminating the need for computationally expensive simulations. Our results suggest a new direction for optimizing hot-electron based photodetectors and sensors.
Conference Proceedings - Lasers and Electro-Optics Society Annual Meeting-LEOS
Sarma, Raktim; Xu, Jiaming; De Ceglia, Domenico; Nookala, Nishant; Carletti, Luca; Campione, Salvatore; Klem, John; Gennaro, Sylvain D.; Sinclair, Michael B.; Belkin, Mikhail A.; Brener, Igal
We demonstrate an extremely nonlinear all-dielectric metasurface that employs intersubband polaritons to achieve a second-harmonic conversion coefficient of 3 mW/W2, and second-harmonic power conversion efficiency of 0.045% at a modest pump intensity of 6.7 kW/cm2.
In this work, we identify the role of higher order antenna’s modes on a metasurface’s Pancharatnam – Berry phase by investigating second harmonic light scattering from two metasurfaces exhibiting dipolar and quadrupolar radiation.