Silicon nitride-on-SOI grating couplers are specifically designed for the O- and C-bands, utilizing CUMEC's advanced process platform. Through simulation, we have achieved an impressive maximum coupling efficiency of -1.4 dB and -1.8 dB to standard single-mode fiber for the O- and C-bands respectively, accompanied by a remarkable 1-dB bandwidth of 70 nm and 78 nm. Furthermore, we have conducted an analysis on fabrication variation tolerance.
We design a type of broadband Silicon Nitride (SiN) power splitters with various split ratios using shortcuts to adiabaticity (STA) technique to ensure the compactness and performance of the device. The decoupled system states are employed in the double-waveguides system to guarantee the approximate adiabatic evolution and the desired split ratios are implemented by manipulating the boundary conditions. The devices show broadband response for a wide wavelength range from 1260 to 1360 nm and have excellent robustness against fabrication errors in our simulations.
Efficient optical coupling between standard single mode fibers and nanophotonic waveguides has been recognized as a major practical challenge since the early years of photonics. In this work, a low-loss and wide band edge coupler based on subwavelength gratings (SWG) for standard single mode fibers is proposed and demonstrated on 220 nm SOI platform. The edge coupler has a minimum feature size of 130 nm and a 630-m length, which was fabricated in CUMEC’s 200 mm CMOS production facilities. The best coupling losses are 1.60 and 1.95 dB for TE and TMin1500-1600 nm wavelength range, respectively, achieving a minimum PDL of 0.2 dB at 1500 nm. Moreover, by taking advantage of SiN-on-Si integrated process and wafer bonding process, the edge coupler exhibits high process and package reliability, making it attractive for the commercial application.
This article presents a graph-driven placement framework for Si photonic circuits. In this framework, a netlist exported from the schematic diagram is transferred into an adjacency matrix, and further parameterized to an undirected graph. By this method, optical devices and waveguides are quantified as nodes and edges, respectively. Non-Euclidean data structures between nodes can be extracted which includes parallel relations, sequential relations and connecting patterns, by matching those patterns with pre-defined database, certain layout strategies formulated by human experts can be properly applied. By extracting the geometric information and the preset spacing requirements of each device in the Process Design Kit library, the layout strategy requirements of each component can be assigned, so as to determine the geometric position. This work designed the graph-driven placement framework, tested the identification accuracy for connection pattern, and applied the framework in practical chip designs including artificial intelligent and Wavelength Division Multiplexing circuits.
An original design approach for inverted tapers based on effective mode area (EMA) control is proposed. It has been demonstrated that the inverted taper with constant loss as a function of position along the taper is most efficient. First, a general equation which can satisfy this constant loss condition is derived between EMA and the position within the taper. EMA can be controlled by adjusting the waveguide width. Introducing the relationship between EMA and waveguide width into this equation, an optimal profile for the inverted taper is obtained. The design approach is illustrated by applying it to an ideal SOI inverted taper. The conversion loss of the designed inverted taper can be reduced by 60% and 78% compared to parabolic and linear inverted tapers, respectively, when the taper length is 300 μm.
A kind of waveguide geometry extraction method based on optical measurements was proposed. By designing two Mach-Zehnder interferometers (MZIs) with different arm lengths, the width and height of the physical geometry of fabricated waveguides could be accurately extracted with the help of MZIs’ optical measured spectrum results. The extracted results on the CUMEC multi-project wafer service (MPW) showed that the mean width and height of the fabricated waveguide were 463.46 nm and 213.58 nm, respectively, while their standard deviation values were 3.82nmand 2.13 nm, respectively.
The thermo-optic phase shifters (TOPS) have been widely used in the applications of sensing, lidar and neural network on the SOI platform. We present a comparison of TOPS based on TiN metal, silicide and N-type doped silicon, which were fabricated by the CUMEC SOI process on the same SOI die. The average switching power (Pπ) of these TOPS are19.12 mW, 21.75 mW and 21.96 mW, respectively. In addition, the switching time of these three types of TOPS have been tested under 10 KHz square wave, the rise and drop time are 5.90 μs and 8.97 μs, 12.90μs and 4.00 μs, 12.80μs and 2.60μs, respectively. Moreover, the minimum possible distance between adjacent TOPS was also examined, which is beneficial to the application of the TOPS in large-scale compact network.
We report high-performance waveguide-integrated germanium photodetectors. The responsivity above 0.95A/W and dark current of 2.9nA were demonstrated with the bias voltage of -1V and input optical wavelength of 1310nm. The 3-dB bandwidth above 67GHz demonstrated due to radio-frequency (RF) resonance effect. The RF resonance is explained by the transfer function of parasitic circuit based on the equivalent circuit model of photodetector. In addition, clear open eye diagrams at 50Gb/s are also shown.
This paper proposes a GaN-based light-emitting diode based on an n-i-p terminal quantum barrier structure that is easy to implement in epitaxy, which can enhance electron confinement and improve hole injection efficiency. Existing GaNbased light-emitting diodes, due to the electron blocking layer (EBL) formed by inserting a wide band gap AlGaN material between the active region and the p-type hole injection layer, cannot effectively confine electrons, and also suppresses multiple quantum wells (MQWs) and Hole injection in the p-type region caused by the polarization field in the EBL. In order to improve the performance of GaN-based LEDs, better suppress electron leakage in the active region and increase the hole injection efficiency in the p-type region, a new design of the terminal quantum barrier was carried out, specifically n-GaN n-GaN (1×1018cm-3)-i-GaN-p-GaN (5×1018cm-3) terminal quantum barrier structure, the thickness of the n, i and p layers in the barrier structure are 4 nm, 5 nm and 4 nm, respectively. This paper uses simulation method to verify the terminal quantum barrier structure. The electrical and optical performance of the GaNbased MQW LED with conventional structure and the LED based on the n-i-p terminal quantum barrier structure were compared, including physical indicators such as output optical power, threshold voltage, and hole injection concentration. The simulation results show that, compared with the traditional structure, the LED with the nip terminal quantum barrier structure has higher output light power and lower threshold voltage, and significantly increases the hole concentration in the active area, which is more effective in suppressing Electronic leaks. The analysis results show that the strong reverse electrostatic field in the nip terminal quantum barrier structure can effectively enhance the electron confinement in the active region, suppress electron leakage and improve the p-type hole injection efficiency. In summary, it is shown that the nip terminal quantum barrier structure can be Effectively improve the performance of LEDs, showing better performance than conventional devices.
We introduced a Python-based design framework for manufacture-friendly optical ANN. It provides the cross-level interoperability between the photonic circuit chip layout and the neural networks infrastructure to enable the optical ANN with better tolerance to the device-by-device or chip-by-chip deviation. It allows a wide range of abstract on levels to describe the behavior of optical ANN: from the lowest-level functionality of manipulating the properties and arrangement of individual phase shifters on a photonic circuit chip, to the highest-level features of designing optical ANN via PyTorchlike development-library as well as its optimization with the well-established machine learning algorithms such as backpropagation. On all the levels, the physical design of the photonic circuit chip can be integrated and synchronized with the construction of the neural networks accounting the influences of the fabrication-deviation with the assistance of IPKISS, a Python-based tool for photonic circuit design. As a demonstration, we use our framework to design the LeNet-5 networks, which can be executed on the photonic circuit chip with non-uniformed grating coupling efficiency. Our LeNet-5 networks achieves the precision around 97.5% for MNIST task.
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