This paper provides a comprehensive review of recent progress in GaN-based gas sensors with a focus on their dynamic-related responses, mechanisms and applications, which are important for sensing performance, efficiency, and signal processing.

With the slowdown of Moore’s law, many emerging electronic devices and computing architectures have been proposed to sustain the performance advancement of computing. Among them, the Ising machine is a non-von-Neumann solver that has received wide attention in recent years. It is capable of solving intractable combinatorial optimization (CO) problems, which are difficult to be solve using conventional digital computers. In fact, many CO problems can be mapped to finding the corresponding ground states of Ising model. At present, Ising machine prototypes based on different physical principles, such as emerging memristive oscillators, have been demonstrated, among which the Ising Hamiltonian solver based on the coupled oscillator network simultaneously holds the advantages of room-temperature operation, compact footprint, low power consumption, and fast speed to solution. This paper comprehensively surveys the recent developments in this important field, including the types of oscillators, the implementation principle of the Ising model, and the solver’s performance. Finally, methods to further improve the performance have also been suggested.

This work adopts interface charge engineering to fabricate normally off metal–insulator–semiconductor high electron mobility transistors (MIS-HEMTs) on an in situ SiNx/AlGaN/GaN platform using an in situ O3 treatment performed in the atomic layer deposition system. The combination of in situ SiNx passivation and an O3-treated Al2O3/AlGaN gate interface allows the device to provide an excellent breakdown voltage of 1498 V at a low specific on-resistance of 2.02 mΩ cm2. The threshold voltage is increased by 2 V by significantly compensating the net polarization charges by more than five times with O3 treatment as well as reducing the interface traps and improving the high-temperature gate stability. Furthermore, a physical model of fixed charges at the Al2O3/AlGaN interface is established based on dielectric thickness-dependent linear fitting and numerical calculations. The matched device performance and simulated energy band bending elucidate the O3-treated fixed-charge modulation mechanism, providing a practical method for producing normally off GaN MIS-HEMTs.

Visual sensors, including 3D light detection and ranging, neuromorphic dynamic vision sensor, and conventional frame cameras, are increasingly integrated into edge-side intelligent machines. However, their data are heterogeneous, causing complexity in system development. Moreover, conventional digital hardware is constrained by von Neumann bottleneck and the physical limit of transistor scaling. The computational demands of training ever-growing models further exacerbate these challenges. We propose a hardware-software co-designed random resistive memory-based deep extreme point learning machine. Data-wise, the multi-sensory data are unified as point set and processed universally. Software-wise, most weights are exempted from training. Hardware-wise, nanoscale resistive memory enables collocation of memory and processing, and leverages the inherent programming stochasticity for generating random weights. The co-design system is validated on 3D segmentation (ShapeNet), event recognition (DVS128 Gesture), and image classification (Fashion-MNIST) tasks, achieving accuracy comparable to conventional systems while delivering 6.78 × /21.04 × /15.79 × energy efficiency improvements and 70.12%/89.46%/85.61% training cost reductions.

In this work, we present the novel application of SiN_x stress-engineering techniques for the suppression of short-channel effects in AlGaN/GaN high-electron-mobility transistors (HEMTs), accompanied by a comprehensive analysis of the underlying mechanisms. The compressive stress SiN_x passivation significantly enhances the barrier height at the heterojunction beneath the gate, maintaining it above the quasi-Fermi level even as V_ds rises to 20 V. As a result, in GaN devices with a gate length of 160 nm, the devices with compressive stress SiN_x passivation exhibit significantly lower drain-induced barrier lowering (DIBL) factors of 2.25 mV/V, 2.56 mV/V, 4.71 mV/V, and 3.84 mV/V corresponding to drain bias voltages of 5 V, 10 V, 15 V, and 20 V, respectively. Furthermore, as V_ds increases, there is an insignificant degradation in transconductance, subthreshold swing, leakage current, or output conductance. In contrast, the devices with stress-free passivation show relatively higher DIBL factors (greater than 20 mV/V) and substantial degradation in pinch-off performance and output characteristics. These results demonstrate that the SiN_x stress-engineering technique is an attractive technique to facilitate high-performance and high-reliability GaN-based HEMTs for radio frequency (RF) electronics applications.

In this work, high threshold voltage and breakdown voltage E-mode GaN HEMTs using an Al:HfOx-based charge trapping layer (CTL) are presented. The developed GaN HEMTs exhibit a wide threshold modulation range of ΔVTH ∼ 17.8 V, which enables the achievement of enhancement-mode (E-mode) operation after initialization process owing to the high charge storage capacity of the Al:HfOx layer. The E-mode GaN HEMTs exhibit a high positive VTH of 8.4 V, a high IDS,max of 466 mA/mm, a low RON of 10.49 Ω mm, and a high on/off ratio of ∼109. Moreover, the off-state breakdown voltage reaches up to 1100 V, which is primarily attributed to in situ O3 pretreatment effectively suppressing and blocking leakage current. Furthermore, thanks to the VTH of GaN HEMTs being tunable by initialization voltage using the proposed CTL scheme, we prove that the direct-coupled FET logic-integrated GaN inverters can operate under a variety of conditions (β = 10–40 and VDD = 3–15 V) with commendable output swing and noise margins. These results present a promising approach toward realizing the monolithic integration of GaN devices for power IC applications.