The device performance determines the application scenario of photodetectors, and how to design the photodetector is thus the key to improve the performance. In this paper, the effect of channel size parameters on the performances of the graphene/MoS2 heterojunction photodetector is investigated based on the photogating effect. The experimental results show that reducing the channel size between the electrodes or increasing the contact size between the material and electrode can increase the photocurrent and reduce the response time. Compared to normal devices, this optimized device has a photocurrent increase of nearly five times and a response time reduction of nearly four times. This work provides a new idea for the design and fabrication of high-performance optoelectronic device.
As a typical atomically thin two-dimensional (2D) crystal, graphene-based photodetector has attracted tremendous attention in recent years due to excellent photoelectric performance of graphene. However, due to the unstable chemical properties of graphene, the guidance is lacking in the design of composites with other materials. The stability and repeatability of the device are also restricted by the material properties. Here, we have established a graphene simulation model and obtained the electrical characteristics of graphene which are consistent with the experimental results by using the method of equivalent design. We simulate the detection capability of graphene-silicon composite photodetector and graphene-germanium photodetector under different doping conditions for visible light (532nm) and near infrared wave (1550nm) respectively. The current-voltage characteristics of the heterojunction are obtained. Through this model, the proposed bottom gate adjustment mechanism makes the carrier transport of graphene/silicon-on-insulator (GSOI) photodetector adjustable. By adjusting the carrier concentration and distribution in the graphene channel and silicon through the bottom gate voltage, an enhanced built-in potential is obtained, which increases the device responsivity by 5-10 times to 106 A/W. This model can be used to simulate the carrier distribution and current density when different gate voltages are applied, and the modulation law of this model is in good agreement with the experimental results. This work will be beneficial to the mechanism analysis and performance optimization of the graphene composite structure photodetector, which has important guiding significance for the experiment.
Graphene-Si heterojunction devices have been widely studied in the field of photoelectric detection, solar cells and sensors areas. However, optical modulation devices based on graphene-Si heterojunction have been rarely reported. Herein, we analyze the photoelectric performance of the graphene-Si heterojunction at different laser powers. The Fermi level of the graphene can be tuned as the photo-excited holes in Si diffuse into the graphene. For the hybrid Si-graphene waveguide modulator, the maximum modulation efficiency of 279.3 dB/cm is achieved at 1550 nm by using finite element analysis method. We hope that the study of the graphene-Si heterojunction can provide a way for application in hybrid graphene-Si waveguide modulators.
The noise immunity of spectral detection is analyzed theoretically for the kind of chip spectrometer based on the combine of integrated filter matrix and sparse recovery. With the sparse representation algorithm, the mathematic model of the detection noise and condition number of filter matrix is built for the Gaussian shaped incident spectrum. In the simulations, the filter matrix with different condition number is produced by changing the cavity length with the fabry perot (FP) interference model. An exponential relationship between the spectrum recovery variance and the condition number is obtained, which is consistent with the built theory model. The result reveals that when the condition number of filter matrix is 103 level, the noise tolerance of chip spectrometer will be as large as 10% when the variance is about 5 ×10-3 in the sparse recovery.
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