Compact Two-State-Variable Second-Order Memristor Model

Abstract

A key requirement for using memristors in functional circuits is a predictive physical model to capture the resistive switching behavior, which shall be compact enough to be implemented using a circuit simulator. Although a number of memristor models have been developed, most of these models (i.e., first-order memristor models) have utilized only a one-state-variable. However, such simplification is not adequate for accurate modeling because multiple mechanisms are involved in resistive switching. Here, a two-state-variable based second-order memristor model is presented, which considers the axial drift of the charged vacancies in an applied electric field and the radial vacancy motion caused by the thermophoresis and diffusion. In particular, this model emulates the details of the intrinsic short-term dynamics, such as decay and temporal heat summation, and therefore, it accurately predicts the resistive switching characteristics for both DC and AC input signals.

Applications and Impacts of Nanoscale Thermal Transport in Electronics Packaging

“…Hence, there is a tremendous opportunity to understand nanoscale thermal transport within these devices to improve their performance in application. Techniques such as manipulating the development of the oxygen-deficient filament by preferential thermophoresis using low thermal conductivity membranes between electrodes [432], passive or second-order thermal activation of several filaments [433], initial oxygen vacancy concentration [433,434], multiple combinations of oxide layers and scavenging layers can be potential avenues to improve device performance as neuromorphic computing research matures.…”

Scaling Effect on Silicon Nitride Memristor with Highly Doped Si Substrate

“…3D Xpoint PRAM connected to an ovonic threshold switch was already on market, which plays an intermediate role between NAND and DRAM as a storage class memory (SCM) . The RRAM‐based crosspoint array also shows great potential for implementation in SCM and embedded applications because of its outstanding performance such as fast switching operation, low‐power consumption, multilevel capability, high endurance, and high scalability in conventional complementary metal–oxide–semiconductor (CMOS) processing technologies . Compared to PRAM, which shows disadvantages in terms of a thick GeSbTe layer and the absence of chemical vapor deposition (CVD) capability for good performance, RRAM is more stable in high temperature processes, and it can be deposited by CVD to form thin layer (≈5 nm) materials which are especially suitable for fabricating three‐dimensional vertical structures .…”

Cycling‐Induced Degradation of Organic–Inorganic Perovskite‐Based Resistive Switching Memory

“…Because the degradation rate changed considerably after the negative set, we only consider experimental data from before that event. We observed that | I reset | increased from ≈28 to ≈42 mA, which suggests that the increase of the CF size with the number of cycles was caused by joule heating, which is regarded as the driving force in reset transition . On the basis of the steady‐state Fourier equation, the calculated T reset increased from ≈500 to ≈750 K in Figure a .…”