Multivariate analysis and extraction of parameters in resistive RAMs using the Quantum Point Contact model

Abstract

A multivariate analysis of the parameters that characterize the reset process in RRAMs has been performed. The different correlations obtained can help to shed light on the current components that contribute in the Low Resistance State (LRS) of the technology considered. In addition, a screening method for the Quantum Point Contact (QPC) current component is presented. For this purpose the second derivative of the current has been obtained using a novel numerical method which allows determining the QPC model parameters. Once the procedure is completed, a whole RS series of thousands of curves is studied by means of a genetic algorithm. The extracted QPC parameter distributions are characterized in depth to get information about the filamentary pathways associated with LRS in the low voltage conduction regime.

Resistive Switching in Graphene Oxide

“…Despite this model may be only appropriate for partially reduced GO, this work commits memristance in GO to the creation of a percolation path of highly reduced GO by the energy accumulated in the device. This theory agrees with the prospective estimation of the energy scale of the phenomenon given in Romero et al (2019), and it is also supported by Times series Statistical Analysis (Rodriguez et al, 2019): the results thrown from the analysis of successive set and reset processes show that the autocorrelation and partial autocorrelation levels match those typically found in resistive switching due to a well-defined conductive path between the electrodes that it is interrupted at a Quantum Point Contact (Roldan et al, 2018).…”

Resistive Switching and Charge Transport in Laser-Fabricated Graphene Oxide Memristors: A Time Series and Quantum Point Contact Modeling Approach

“…Therefore, the physics lying behind their operation has only had its surface scratched [18]. In this work, we intend to tackle this issue making use of well-established numerical techniques previously developed for more “conventional” memristors that are developed with 3D stacks of transitions metal oxides [13,15,22,23]. Therefore, in this manuscript, we specifically deal with the characterization and analysis of resistive switching processes and charge conduction in laser-fabricated graphene oxide (GO) memristors [18] from a statistical perspective.…”

“…From the statistical viewpoint, information can be extracted that is related to the correlation of successive RS cycles and the inherent stochasticity of RS memristors operation. The quantum properties of conduction along the conductive filaments that short the electrodes have been scrutinized by means of the Quantum Point Contact (QPC) model as described in [15,22].…”

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

“…For a complete review about conductance quantization effects in RS devices see Refs. [23][24][25][26][27][28][29][30][31]. From the electrical viewpoint, (6) can be envisaged as two opposite biased diodes (see Fig.…”