Title: Graphene-Boron Nitride Heterostructure Based Optoelectronic Devices for On-Chip Optical Interconnects
Description: Graphene has emerged as an appealing material for a variety of optoelectronic applications due to its unique electrical and optical characteristics. In this thesis, I will present recent advances in integrating graphene and graphene-boron nitride (BN) heterostructures with confined optical architectures, e.g. planar photonic crystal (PPC) nanocavities and silicon channel waveguides, to make this otherwise weakly absorbing material optically opaque. Based on these integrations, I will further demonstrate the resulting chip-integrated optoelectronic devices for optical interconnects. After transferring a layer of graphene onto PPC nanocavities, spectral selectivity at the resonance frequency and orders-of-magnitude enhancement of optical coupling with graphene have been observed in infrared spectrum. By applying electrostatic potential to graphene, electro-optic modulation of the cavity reflection is possible with contrast in excess of 10 dB. And furthermore, a novel and complex modulator device structure based on the cavity-coupled and BN-encapsulated dual-layer graphene capacitor is demonstrated to operate at a speed of 1.2 GHz.

On the other hand, an enhanced broad-spectrum light-graphene interaction coupled with silicon channel waveguides is also demonstrated with ∼0.1 dB/μm transmission attenuation due to graphene absorption. A waveguide-integrated graphene photodetector is fabricated and shown 0.1 A/W photoresponsivity and 20 GHz operation speed. An improved version of a similar photodetector using graphene-BN heterostructure exhibits 0.36 A/W photoresponsivity and 42 GHz response speed. The integration of graphene and graphene-BN heterostructures with nanophotonic architectures promises a new generation of compact, energy-efficient, high-speed optoelectronic device concepts for on-chip optical communications that are not yet feasible or very difficult to realize using traditional bulk semiconductors.