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The focus of this paper is to understand the impact of the material properties of GaN, exploited using a vertical device, in power switching by estimating switching loss. The study was performed with a cascoded current aperture vertical electron transistor (CAVET). The normally OFF device was simulated and analyzed using a Silvaco ATLAS 2-D drift diffusion model integrated to SPICE-based circuit simulator. Besides evaluating the performance space and, hence, potential application space for GaN CAVETs, this paper presents significant accomplishment in establishing a device to circuit model, thereby, offering a reliable method of evaluating GaN-based power transistors. The accuracy of the model was established through the excellent agreement of simulated data with the data sheet specs of a commercial cascoded GaN high electron mobility transistor. The model was successfully applied to compare SiC MOSFETs with GaN CAVETs. A cascoded GaN CAVET has $2\times $ faster switching time, $3\times $ lower switching loss compared with standard commercial SiC MOSFET, owing to the higher electron mobility in GaN. Operating at frequencies of megahertz with low power loss, a GaN CAVET will, therefore, lead to smaller converter size and higher system efficiency. [ABSTRACT FROM PUBLISHER]

The accurate calculation of switching voltage (${V}_{s}$) is necessary for the reliable and low-power operation of monolithic 3-D (M3D) CMOS-nanoelectromechanical (NEM) hybrid reconfigurable logic circuits because ${V}_{s}$ corresponds to the operating voltage (${V}_{\text {dd}}$) of NEM memory switches. In this paper, based on the Euler–Bernoulli equation, the physics-based analytical model is proposed to determine ${V}_{s}$. The accuracy of the proposed model is verified by both the finite-element analysis and experimental results. Our proposed model shows >3% error compared with experimental data. Also, the design guidelines of NEM memory switches are presented in terms of minimum ${V}_{s}$ (${V}_{s\_{}{m}}$) and device dimensions. [ABSTRACT FROM AUTHOR]

This paper analyzes write errors in spin-torque switching due to thermal fluctuations in a system with perpendicular magnetic anisotropy. Prior analytical and numerical methods are summarized; a physics-based general 2-D Fokker–Planck equation (FPE) is solved numerically. Due to its computational efficiency and broad applicability to all switching regimes and system symmetries, the 2-D FPE has been used to study the relation between write error slope and material parameters as well as some emerging switching schemes. [ABSTRACT FROM PUBLISHER]

Magnetic tunnel junctions (MTJs) composed of ferromagnetic layers with perpendicular magnetic anisotropy (PMA) are of great interest for achieving high-density nonvolatile memory and logic chips owing to its scalability potential together with high thermal stability. Recent progress has demonstrated a capacity for high-speed performance and low power consumption through current-induced magnetization switching. In this paper, we present a compact model of the CoFeB/MgO PMA MTJ, a system exhibiting the best tunnel magnetoresistance ratio and switching performance. It integrates the physical models of static, dynamic, and stochastic behaviors; many experimental parameters are directly included to improve the agreement of simulation with experimental measurements. Mixed simulation based on the 65-nm technology node of a magnetic flip-flop validates its relevance and efficiency for MTJ/CMOS memory and logic chip design. [ABSTRACT FROM AUTHOR]

The need for reliable models that take into account the nonlinear kinetics of dopants is nowadays of paramount importance, particularly with the physical dimensions of electron devices shrinking to the deep nanoscale range and the development of emerging nanoionic systems such as the memristor. In this paper, we present a novel nonlinear dopant drift model that resolves the boundary issues existing in previously reported models that can be easily adjusted to match the dynamics of distinct memristive elements. With the aid of this model, we examine switching mechanisms, current–voltage characteristics, and the collective ion transport in two terminal memristive devices, providing new insights on memristive behavior. [ABSTRACT FROM PUBLISHER]