In order to accelerate the semiconductor device simulation, we propose to use a neural network to learn an approximate solution for desired bias conditions. With an initial solution (predicted by a trained neural network) sufficiently close to the final one, the computational cost to calculate several unnecessary solutions is significantly reduced. Specifically, a convolutional neural network for the metal–oxide–semiconductor field-effect transistor (MOSFET) is trained in a supervised manner to compute the initial solution. In particular, we propose to consider a device template for various devices and a compact expression of the solution based on the electrostatic potential. We empirically show that the proposed method accelerates the simulation significantly.

In this study, the state-of-the-art vertical gallium oxide MOSFET with the fin shaped source is numerically investigated. With the simulation environment, whose results for the electrical characteristics are in close agreement with the available experimental results, the impact of the fin shape is studied. It is found that a rectangular fin with a height of 1.0 μm and a width of 0.3 μm can give a low on-resistance per unit area and a low drain-induced barrier lowering (DIBL) simultaneously. Moreover, the tapered fins are simulated to estimate the sensitivity of the on-resistance, the DIBL, and the subthreshold slope.

A solution-processed FeO_x–GO hybrid based RRAM device with excellent self-rectifying characteristics (I_LRS/I_R > 10⁴) is presented.

AlGaN/GaN high-electron mobility transistor structures were utilized to fabricate metal-semiconductor- metal (MSM) two-dimensional electron gas (2DEG) varactors for application as a terahertz (THz) capacitive switch. By adopting an asymmetric MSM structure composed of nanoscale gates and micron-scale gates, the cutoff frequency of the MSM-2DEG varactors was dramatically improved, up to the THz range, by reducing series resistance. The balanced MSM-2DEG varactor, in which a nanoscale gate is sandwiched between two micron-scale gates exhibited a capacitance switching ratio (Cmax/Cmin) of 2.64, a cutoff frequency of 1.54 THz, and a figure of merit of 4.06 THz.

In this paper, the transient simulation of semiconductor devices using a deterministic Boltzmann equation solver is presented. Transient simulation capability is implemented in a deterministic Boltzmann equation solver for the 3-D momentum space based on the spherical harmonics expansion. The numerical simulation results with implicit time marching methods demonstrate that the transient simulation using a deterministic Boltzmann equation solver can be performed. The impact of the quasi-static approximation for the current density, which is widely adopted in the momentum-based equations, is tested for various devices such as homogeneous samples, an N⁺NN⁺ structure and an MOSFET.

High purity semi-insulating (HPSI) 4H-silicon carbide (SiC) was used to fabricate lateral and vertical photoconductive semiconductor switches (PCSSs). The lateral PCSSs were illuminated from the frontside (fPCSS) or the backside (bPCSS). The side-illuminated vertical PCSS (vPCSS) was designed to increase the light-matter interaction volume. A 532-nm pulsed laser with adjustable energy was utilized to excite the PCSSs. The turn-on time was found to be highly dependent on the optical illumination energy, and the full-width at half-maximum of the PCSSs output waveforms was related to the peak output voltage. The output electrical pulse from the vPCSS exhibited a shorter turn-on time and a larger pulsewidth than the two types of lateral PCSSs. The vPCSS outperformed the fPCSS and bPCSS in terms of minimum $\mathrm{\scriptscriptstyle ON}$ -state resistance and output pulse amplitude under the same optical illumination energy. The vPCSS, which utilizes a large effective contact area to collect photogenerated carriers, also had higher photon absorption efficiency by arranging the optical path at a right angle to the carrier transport. The vPCSS exhibited a minimum $\mathrm{\scriptscriptstyle ON}$ -state resistance of 0.34 $\Omega $ at optical illumination energy of 8 mJ.