Silicon photonic-based refractive index sensors are of great value in the detection of gases, biological and chemical substances. Among them, microring resonators are the most promising due to their compact size and narrow Lorentzian-shaped spectrum. The electric field in a subwavelength grating waveguide (SWG) is essentially confined in the low-refractive index dielectric, favoring enhanced analyte-photon interactions, which represents higher sensitivity. However, it is very challenging to further significantly improve the sensitivity of SWG ring resonator refractive index sensors. Here, a hybrid waveguide blocks double slot subwavelength grating microring resonator (HDSSWG-MRR) refractive index sensor operating in a water refractive index environment is proposed. By designing a new waveguide structure, a sensitivity of up to 1005 nm/RIU has been achieved, which is 182 nm/RIU higher than the currently highest sensitivity silicon photonic micro ring refractive index sensor. Meanwhile, utilizing a unique waveguide structure, a Q of 22,429 was achieved and a low limit of detection of 6.86 × 10⁻⁵ RIU was calculated.

A four-port grating coupler with etched square holes is pro-posed and demonstrated for surface-normal and polarization independent coupling. Benefiting from the perfectly vertical coupling and 1×4 power splitting/combing scheme, efficient polarization independent operation was achieved. The cou-pling efficiency was further improved by grating apodization. According to the simulations, the proposed two-dimensional (2D) apodized grating coupler can achieve a coupling efficiency (CE) of 64.5% (-1.9dB), a low upward back-reflection of 8.5% (-11dB) and polarization-dependent loss (PDL) lower than 0.04dB across the wavelength range of 1520-1620nm. A CE of 56.3% (-2.5dB) was experimentally measured, with PDL be-low 0.4dB within the C-band and lower than 0.7dB within the L-band. Waveguide delay lines were used to compensate the waveguide channel phase differences at the output port.

In this work, a bidirectional grating coupler for perfectly vertical coupling is proposed. The coupling efficiency is enhanced using a silicon nitride (Si₃N₄) layer above a uniform grating. In the presence of Si₃N₄ layer, the back-reflected optical power into the fiber is diminished and coupling into the waveguide is increased. Genetic algorithm (GA) is used to optimize the grating and Si₃N₄ layer simultaneously. The optimal design obtained from GA shows that the average in-plane coupling efficiency is enhanced from about 57.5% (−2.5 dB) to 68.5% (−1.65 dB), meanwhile the average back-reflection in the C band is reduced from 17.6% (−7.5 dB) to 7.4% (−11.3 dB). With the help of a backside metal mirror, the average coupling efficiency and peak coupling efficiency are further increased to 87% (−0.6 dB) and 89.4% (−0.49 dB). The minimum feature size of the designed device is 266 nm, which makes our design easy to fabricate through 193 nm deep-UV lithography and lowers the fabrication cost. In addition, the coupler proposed here shows a wide-band character with a 1-dB bandwidth of 64 nm and 3-dB bandwidth of 96 nm. Such a grating coupler design can provide an efficient and cost-effective solution for vertical fiber-to-chip optical coupling of a Wavelength Division Multiplexing (WDM) application.

Optical receivers with potentially high operation bandwidth and low cost have received considerable interest due to rapidly growing data traffic and potential Tb/s optical interconnect requirements. Experimental realization of 65 GHz optical signal detection and 262 GHz intrinsic operation speed reveals the significance role of graphene photodetectors (PDs) in optical interconnect domains. In this work, a novel complementary metal oxide semiconductor post‐backend process has been developed for integrating graphene PDs onto silicon integrated circuit chips. A prototype monolithic optoelectronic integrated optical receiver has been successfully demonstrated for the first time. Moreover, this is a firstly reported broadband optical receiver benefiting from natural broadband light absorption features of graphene material. This work is a perfect exhibition of the concept of monolithic optoelectronic integration and will pave way to monolithically integrated graphene optoelectronic devices with silicon ICs for three‐dimensional optoelectronic integrated circuit chips.

The GaN-based heterostructures and related HEMTs (High Electron Mobility Transistors) were investigated by 1MeV neutrons at fluences up to 10¹⁵ cm⁻², yielding an increase of the densities of screw dislocations and edge dislocations for GaN-based heterostructures. It gave the result that neutron irradiation-induced structural defects into GaN-based materials, and the irradiation-induced dislocations would propagate to the material surface causing surface morphology deterioration. However, the GaN-based material strain was robust to neutrons, and the more initial dislocations, the easier to generate irradiation defects and thus, more strongly affecting the electrical property degradations of materials and devices. Meanwhile, the reduction of the two-dimensional electron gas (2DEG) concentration (n_s) caused by irradiation-induced defects led to the reducing the drain current. Moreover, the significant degradation of the reverse gate leakage current at fluences ranging from 10¹⁴ to 10¹⁵ cm⁻² could be attributed to the irradiation-induced deep defects. The neutron induced damage was more difficult to anneal recovery than other particles, due to the neutron irradiation-induced deep levels and defect complexes such as defect clusters.

In the photovoltaic (PV) field, the outdoor evaluation of a PV system is quite complex, due to the variations of temperature and irradiance. In fact, the diagnosis of the PV modules is extremely required in order to maintain the optimum performance. In this paper, an artificial neural network (ANN) is proposed to build and train the model, and evaluate the PV module performance by mean bias error, mean square error and the regression analysis. We take temperature, irradiance and a specific voltage for input, and a specific current value for output, repeat several times in order to obtain an I-V curve. The main feature lies to the data-driven black-box method, with the ignorance of any analytical equations and hence the conventional five parameters (serial resistance, shunt resistance, non-ideal factor, reverse saturation current, and photon current). The ANN is able to predict the I-V curves of the Si PV module at arbitrary irradiance and temperature. Finally, the proposed algorithm has proved to be valid in terms of comparison with the testing dataset.