Surface diffusion-limited lifetime of silver and copper nanofilaments in resistive switching devices

Abstract

Silver/copper-filament-based resistive switching memory relies on the formation and disruption of a metallic conductive filament (CF) with relatively large surface-to-volume ratio. The nanoscale CF can spontaneously break after formation, with a lifetime ranging from few microseconds to several months, or even years. Controlling and predicting the CF lifetime enables device engineering for a wide range of applications, such as non-volatile memory for data storage, tunable short/long term memory for synaptic neuromorphic computing, and fast selection devices for crosspoint arrays. However, conflictive explanations for the CF retention process are being proposed. Here we show that the CF lifetime can be described by a universal surface-limited self-diffusion mechanism of disruption of the metallic CF. The surface diffusion process provides a new perspective of ion transport mechanism at the nanoscale, explaining the broad range of reported lifetimes, and paving the way for material engineering of resistive switching device for memory and computing applications.

Volatile Resistive Switching Memory Based on Ag Ion Drift/Diffusion—Part II: Compact Modeling

“…As a result, the transition to the ON-state for the volatile RRAM is similar to the set transition of the nonvolatile RRAM, while the spontaneous "reset" transition is missing in the previous nonvolatile RRAM models [15]- [18]. As pointed out in previous studies [9], [14], the CF relaxation process consists of two phases, namely CF diameter narrowing, which leads to the CF disconnection, and CF retraction, where the remaining fragments of the CF reduce their extension toward the top and bottom electrodes.…”

“…accessing individual elements in large cross-point arrays for high-density data storage [5]- [8], and sensor arrays for highresolution environment perception [1]. The relaxation time, namely, the lifetime of the ON-state or low resistance state (LRS), can be controlled by the filament size, hence the compliance current I C [9]. The controllable relaxation time provides further opportunities of application in neuromorphic computation systems, as the device can mimic the short/long term memory effect of biological synapses [10]- [12].…”

Bridging Biological and Artificial Neural Networks with Emerging Neuromorphic Devices: Fundamentals, Progress, and Challenges

“…For example, Chang et al showed experimentally that the retention loss in a RRAM memristor device bears striking resemblance to memory loss in biological systems. [98,[216][217][218] [176] Similarly, increasing the current compliance or the number of pulses applied to a CBRAM synapse, the conducting filaments will grow wider, thus the conductance state can be maintained for a longer period, which is a modulation from STSP to LTSP.…”

Parylene Based Memristive Devices with Multilevel Resistive Switching for Neuromorphic Applications

“…Note that although the question of the nature of RS in M/PPX/ITO structures is extremely interesting, its detailed analysis lies beyond the scope of this study. Here, based on the experimental data and on the related literature, we only make the following conclusion: the bipolar RS behavior of the investigated samples most likely originates from the formation/destruction of metal bridges (filaments) in the dielectric parylene layer due to migration of metal cations (Ag + , Cu + /Cu +2 , Al +3 or Ti +4 ) from the top electrode toward the bottom during the SET process under strong electric field [1,3,30,35,46]. In contrast, according to the molecular dynamics simulations performed by Ielmini et al [30], the conductive bridges can spontaneously break during the RESET switching as a result of atomic surface diffusion driven by the minimization of the system energy.…”