In this paper, we report a two-dimensional (2D) simulation for InGaAs/InAlAs separate absorption, grading, charge, and multiplication avalanche photodiodes (SAGCM APDs) and study the effect of the charge layer and multiplication layer on the operating voltage ranges of APD. We find that with the increase of the thicknesses as well as the doping concentrations of the charge layer and the multiplication layer, the punchthrough voltage increases; with the increase of the doping concentrations of two layers and the thickness of the charge layer, the breakdown voltage decreases; with the increase of the thickness of the multiplication layer, the breakdown voltage first rapidly declines and then slightly rises.

With an appropriate high anneal temperature under H₂ atmosphere, GaN quantum dots (QDs) have been fabricated via GaN thermal decomposition in metal organic chemical vapor deposition (MOCVD). Based on the characterization of atomic force microscopy (AFM), the obtained GaN QDs show good size distribution and have a low density of 2.4 × 10⁸ cm^-2. X-ray photoelectron spectroscopy (XPS) analysis demonstrates that the GaN QDs were formed without Ga droplets by thermal decomposition of GaN.

The long-wave infrared (LWIR) quantum-well photodetector (QWIP) operates at low temperatures, but is prone to focal plane temperature changes when imaging in complex thermal environments. This causes dark current changes and generates low-frequency temporal dark current noise. To address this, a dark current noise correction method based on dark pixels is proposed. First, dark pixels were constructed in a QWIP system and the response components of imaging pixels and dark pixels were analyzed. Next, the feature data of dark pixels and imaging pixels were collected and preprocessed, after which a recurrent neural network (RNN) was used to fit the dark current response model. Target data were collected and input into the dark current response model to obtain dark level correction values and correct the original data. Finally, after calculation and correction, temporal noise was reduced by 49.02% on average. The proposed method uses the characteristics of dark pixels to reduce dark current temporal noise, which is difficult using conventional radiation calibrations; this is helpful in promoting the application of QWIPs in LWIR remote sensing.

Indium arsenide (InAs)-based fin field-effect transistors (FinFETs) are emerging as potential alternatives to traditional Si technologies due to their exceptional carrier mobility and high saturation velocity, which are crucial for advancing Moore’s law. Recent developments in operating principles, processing methods, and architectural designs have enabled the aggressive scaling of InAs-based FinFETs and their successful integration with Si wafers, bringing their key performances comparable to that of Si-based counterparts. However, several obstacles prevent their widespread adoption, including difficulties in creating uniform fin structures, optimizing metal contacts, and controlling interface defects. This review explores the recent innovations in the processing techniques and architectural designs of InAs-based FinFETs, with a focus on overcoming scaling and integration challenges. In addition, it proposes new technological approaches to address the limitations, supporting the continued evolution of InAs-based technology.

The performance of long-wave infrared (LWIR) quantum well (QWIP) detection systems is seriously affected by the dark current of the detectors. Tiny variations in the focal-plane temperature of the devices cause fluctuations in the dark current, which in turn generate temporal noise. It is difficult to measure the dark current accurately after the detector assembly is packaged. To address the above problems, a QWIP dark current measurement method based on focal-plane temperature is proposed, as well as a method to reduce dark current noise. First, the response model of the LWIR QWIP detection system was established, and the dark current model was introduced. Then, the detection system components were introduced, chiller calibration experiments were carried out, and the dark current values of the QWIP at different temperatures were measured by combining the system design and parameters. Next, the dark current noise correction method was proposed, the target data were collected, and experiments were carried out to correct them. Finally, after the calculation, the temporal noise was reduced by 57.69% after the correction, which is proof of a significant effect. This method can obtain the real-time dark current value by collecting the focal-plane temperature data, and reduce the dark current temporal noise (difficult to eliminate using conventional methods), which is beneficial for promoting the application of QWIPs in LWIR remote sensing detection.