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Reprogrammable Spatiotemporally Modulated Graphene-Based Functional Metasurfaces

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Digital Metasurfaces have recently offered tremendous opportunities in real-time manipulation of terahertz (THz) waves in programmable ways to reach special applications that cannot be achieved using conventional architectures. Unlike the… Click to show full abstract

Digital Metasurfaces have recently offered tremendous opportunities in real-time manipulation of terahertz (THz) waves in programmable ways to reach special applications that cannot be achieved using conventional architectures. Unlike the previous demonstrations at this spectrum, which only exploit spatial modulation, in this paper, we propose a spatiotemporally modulated graphene-based digital metasurface (STGDM) to carry out different missions in both space and frequency domains. Applying proper time-variant Fermi level controlling signals turns a 2-bit phase-only meta-atom into a powerful sub-wavelength scatterer with the ability to modulate both phases and amplitudes with arbitrary high quantization levels at center or harmonic frequencies. Several illustrative examples have been presented to demonstrate the excellent capability of our STGDM to dynamically realize different THz scattering behaviors, including beam deflection, vortex beam generation, spatial power dividing, harmonic focusing, and airy beam generation with a single digital interface. The employed space-time coding strategy reveals an additional knob for lifting some fundamental limitations of the previous graphene-based metasurfaces to achieve functionalities requiring both phase and amplitude modulations. Meanwhile, by facilitating the structural design to obtain high quantization levels, the proposed STGDM may be a reliable component in highly-efficient THz imaging and information systems.

Keywords: modulated graphene; based functional; graphene; spatiotemporally modulated; graphene based; reprogrammable spatiotemporally

Journal Title: IEEE Journal on Emerging and Selected Topics in Circuits and Systems
Year Published: 2020

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