An Experimental Proof that Resistance-Switching Memory Cells are not Memristors

It has been suggested that all resistive-switching memory cells are memristors. The latter are hypothetical, ideal devices whose resistance, as originally formulated, depends only on the net charge that traverses them. Recently, an unambiguous test has been proposed [J. Phys. D: Appl. Phys. {\bf 52}, 01LT01 (2019)] to determine whether a given physical system is indeed a memristor or not. Here, we experimentally apply such a test to both in-house fabricated Cu-SiO2 and commercially available electrochemical metallization cells. Our results unambiguously show that electrochemical metallization memory cells are not memristors. Since the particular resistance-switching memories employed in our study share similar features with many other memory cells, our findings refute the claim that all resistance-switching memories are memristors. They also cast doubts on the existence of ideal memristors as actual physical devices that can be fabricated experimentally. Our results then lead us to formulate two memristor impossibility conjectures regarding the impossibility of building a model of physical resistance-switching memories based on the memristor model

Physical Simulation of Si-Based Resistive Random-Access Memory Devices

We present a newly-developed three-dimensional (3D) physical simulator suitable for the study of resistive random-access memory (RRAM) devices. We explore the switching behavior of Si-rich silica (SiOx) RRAM structures, whose operation has been successfully demonstrated experimentally at ambient conditions [1]. The simulator couples self-consistently a simulation of oxygen ion and electron transport to a self-heating model and the `atomistic' simulator GARAND. The electro-thermal simulation model provides many advantages compared to the classical phenomenological models based on the resistor breaker network. The simulator is validated with respect to experimental data and captures successfully the memristive behavior of the simulated SiOx RRAMs, by reconstructing the conductive filament formation and destruction phenomena in the 3D space. The simulation framework is useful for exploring the little-known physics of SiOx RRAMs, and providing efficient designs, in terms of performance, variability and reliability, for both memory devices and circuits

Semiempirical Modeling of Reset Transitions in Unipolar Resistive-Switching based Memristors

We have measured the transition process from the high to low resistivity states, i.e., the reset process of resistive switching based memristors based on Ni/HfO2/Si-n+ structures, and have also developed an analytical model for their electrical characteristics. When the characteristic curves are plotted in the current-voltage (I-V) domain a high variability is observed. In spite of that, when the same curves are plotted in the charge-flux domain (Q-phi), they can be described by a simple model containing only three parameters: the charge (Qrst) and the flux (rst) at the reset point, and an exponent, n, relating the charge and the flux before the reset transition. The three parameters can be easily extracted from the Q-phi plots. There is a strong correlation between these three parameters, the origin of which is still under study

Memristors for the Curious Outsiders

We present both an overview and a perspective of recent experimental advances and proposed new approaches to performing computation using memristors. A memristor is a 2-terminal passive component with a dynamic resistance depending on an internal parameter. We provide an brief historical introduction, as well as an overview over the physical mechanism that lead to memristive behavior. This review is meant to guide nonpractitioners in the field of memristive circuits and their connection to machine learning and neural computation.Comment: Perpective paper for MDPI Technologies; 43 page