Graphene-based near-field optical microscopy: high-resolution imaging using reconfigurable gratings

Multifunctional metasails for self-stabilized beam-riding and optical communication

The photonic propulsion of lightsails can be used to accelerate spacecraft to relativistic velocities, providing a feasible route for the exploration of interstellar space in the human lifetime. Breakthrough Starshot is an initiative aiming to launch lightsail-driven spacecrafts accelerated to a relativistic velocity of 0.2c via radiation pressure of a high-power laser beam in order to probe the habitable zone of Alpha Centauri, located 4.2 light years away from the Earth, and transmit back the scientific data collected in the flyby mission to an Earth-based receiver. The success of such a mission requires the lightsail to provide maximal acceleration while featuring beam-riding stability under the illumination of an intense laser beam during the launch phase. Moreover, the large-area lightsail can be harnessed to improve the margin in the photon-starved downlink channel throughout the communication phase by maximizing the gain of the transmitter despite extending the acceleration period and reducing the stability margin due to the elimination of a portion of the propulsion segments. Owing to the potential of metasurfaces to serve as low-weight versatile multifunctional photonic components, metasurface-based lightsails or metasails are deemed to be ideal candidates to simultaneously address the requirements of photonic propulsion and optical communication in laser-driven deep-space probes. Here, we demonstrate the design of a multifunctional metasail for providing high acceleration and enabling the self-stabilized beam-riding of a spacecraft with a detached payload from the sail while maximizing the transmission gain in the downlink optical communication. The metasail consists of two interleaved sub-arrays of dielectric unit cells operating based on the Pancharatnam-Berry geometric phase, optimized to meet the propulsion and communication requirements, respectively. The beam-riding stability of the sail is analyzed through simulation of the motion trajectory during the acceleration phase, while taking into account the effect of the relativistic Doppler shift, and the downlink communication performance is enabled by providing the required conjugate phase by the metasail elements, resulting in beam collimation. The obtained results verify the multifunctionality of the platform and point toward the promise of metasails for extended mission applications.

Super-Resolution Imaging with Graphene

Super-resolution optical imaging is a consistent research hotspot for promoting studies in nanotechnology and biotechnology due to its capability of overcoming the diffraction limit, which is an intrinsic obstacle in pursuing higher resolution for conventional microscopy techniques. In the past few decades, a great number of techniques in this research domain have been theoretically proposed and experimentally demonstrated. Graphene, a special two-dimensional material, has become the most meritorious candidate and attracted incredible attention in high-resolution imaging domain due to its distinctive properties. In this article, the working principle of graphene-assisted imaging devices is summarized, and recent advances of super-resolution optical imaging based on graphene are reviewed for both near-field and far-field applications.

Robust visibility of graphene monolayer on patterned plasmonic substrates

Single and few-layer graphene flakes, while visible on a dielectric surface with customized thickness, cannot be optically imaged when exfoliated directly on semiconductors or metal substrates with arbitrary thickness. In this paper, we show that such graphene flakes become visible through a conventional microscope on a substrate patterned with a submicron sized, hexagonally packed array of gold disks. The interaction of the metal pattern with the incident light generates surface plasmon polaritons (SPPs) and results in enhanced reflectivity for certain angles and wavelengths. In the areas where graphene flakes are present, the interaction of the SPP with incident radiation is altered and consequently decreases the reflectivity in this region and increases the contrast, which accounts for the visibility of the graphene flakes on such substrates. We validate the observed contrast in visibility utilizing an in-house developed modified form of rigorous coupled wave analysis algorithm to appropriately incorporate the optical properties of two-dimensional materials. We present a parametric study of the contrast of graphene flakes on the patterned substrate to demonstrate the robustness of the visibility.

Adaptive Genetic Algorithm for Optical Metasurfaces Design

As optical metasurfaces become progressively ubiquitous, the expectations from them are becoming increasingly complex. The limited number of structural parameters in the conventional metasurface building blocks, and existing phase engineering rules do not completely support the growth rate of metasurface applications. In this paper, we present digitized-binary elements, as alternative high-dimensional building blocks, to accommodate the needs of complex-tailorable-multifunctional applications. To design these complicated platforms, we demonstrate adaptive genetic algorithm (AGA), as a powerful evolutionary optimizer, capable of handling such demanding design expectations. We solve four complex problems of high current interest to the optics community, namely, a binary-pattern plasmonic reflectarray with high tolerance to fabrication imperfections and high reflection efficiency for beam-steering purposes, a dual-beam aperiodic leaky-wave antenna, which diffracts TE and TM excitation waveguides modes to arbitrarily chosen directions, a compact birefringent all-dielectric metasurface with finer pixel resolution compared to canonical nano-antennas, and a visible-transparent infrared emitting/absorbing metasurface that shows high promise for solar-cell cooling applications, to showcase the advantages of the combination of binary-pattern metasurfaces and the AGA technique. Each of these novel applications encounters computational and fabrication challenges under conventional design methods, and is chosen carefully to highlight one of the unique advantages of the AGA technique. Finally, we show that large surplus datasets produced as by-products of the evolutionary optimizers can be employed as ingredients of the new-age computational algorithms, such as, machine learning and deep leaning. In doing so, we open a new gateway of predicting the solution to a problem in the fastest possible way based on statistical analysis of the datasets rather than researching the whole solution space.