On the universality of the I–V switching characteristics in non-volatile and volatile resistive switching oxides

Abstract

In this paper, we want to review the correlation between filamentary (width) switching and the (SET) I–V characteristics by discussing the existing models.

Fundamentals and SPICE Implementation of the Dynamic Memdiode Model for Bipolar Resistive Switching Devices

“…During this phase the current also grows as a function of VC but following approximately the load line of the circuit (slope~1/R I ), and next at an almost constant voltage called the transition voltage V T (blue line in Fig. 6) [36]. This second phase corresponds to the accumulation of ions/defects in the constriction (or alternatively to its lateral expansion) with the consequent progressive resistance reduction.…”

“…This property is used to represent the so-called snapback (SB: positive bias) and snapforward (SF: negative bias) effects in the RS I-V loop. These effects are typically present in VCMs [36]. In this work, we introduce explicitly the memory state  in the characteristic times as:…”

Non-Uniform Spline Quasi-Interpolation to Extract the Series Resistance in Resistive Switching Memristors for Compact Modeling Purposes

“…We present here a mathematical technique to improve the extraction of the series resistance in RRAMs [16][17][18]. The series resistance is an essential parameter that needs to be obtained to represent the device correctly at the circuit level.…”

Impact of Oxygen Non‐Stoichiometry on Near‐Ambient Temperature Ionic Mobility in Polaronic Mixed‐Ionic‐Electronic Conducting Thin Films

“…[21,22] While this mechanism was regarded as an aging effect, determining the lifetime of capacitors or gate dielectrics, progress in nanometric processing methods has enabled the design of novel devices that take advantage of the mobile ionic species, with versatile functionalities that cannot be achieved solely by electronic effects. New memory devices based on ionic defect motion have emerged, for example, in the fields of electronics (e.g., memristors), [12,[23][24][25][26][27][28][29] magnetics (e.g., magnetoionics), [30][31][32] optics (e.g., electrochromic devices), [33][34][35][36] and ferroelectrics, [37][38][39] often matching the performance of their electronic counterparts, at lower energy consumption and smaller device footprint. Moreover, these new devices are considered as promising candidates for progressing beyond traditional computational architectures.…”