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Published on: June 23, 2018
On-chip graphene photodetectors with a nonvolatile p-i-n homojunction
Ruijuan Tian1,2, Yong Zhang3, Yingke Ji1
1Key Laboratory of Light Field Manipulation and Information Acquisition, and Shaanxi Key Laboratory of Optical Information Technology, School of Physical Science and Technology, Northwestern Polytechnical University, Xi'an, China.
Abstract:
Graphene's unique photothermoelectric (PTE) effect, combined with its compatibility for on-chip fabrication, promises its development in chip-integrated photodetectors with ultralow dark-current and ultrafast speed. Previous designs of on-chip graphene photodetectors required external electrical biases or gate voltages to separate photocarriers, leading to increased power consumption and complex circuitry. Here, we demonstrate a nonvolatile graphene p-i-n homojunction constructed on a silicon photonic crystal waveguide, which facilitates PTE-based photodetection without the need for electrical bias or gate voltages. By designing an air-slotted photonic crystal waveguide as two individual silicon back gates and employing ferroelectric dielectrics with remnant polarization fields, the nonvolatile p-i-n homojunction with a clear gradient of Seebeck coefficient is electrically configured. Hot carriers in the graphene channel generated from the absorption of waveguide evanescent field are separated by the nonvolatile p-i-n homojunction effectively to yield considerable photocurrents. With zero-bias and zero-gate voltage, the nonvolatile graphene p-i-n homojunction photodetector integrated on the optical waveguide exhibits high and flat responsivity of 193 mA W-1 over the broadband wavelength range of 1560-1630 nm and an ultrafast dynamics bandwidth of 17 GHz measured in the limits of our instruments. With the high-performance on-chip photodetection, the nonvolatile graphene homojunction directly constructed on silicon photonic circuits promises the extended on-chip functions of the optoelectronic synapse, in-memory sensing and computing, and neuromorphic computing.
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