Helen Stewart1 Sanjoy Nandi1 Shuai Li1 Robert Elliman1

1, Australian National Univ, Canberra, Australian Capital Territory, Australia

Conductive bridge memory, in which the switching results from the electrochemical growth and dissolution of a metallic filament (typically Cu or Ag), has been shown to emulate basic neuromorphic computing functions, such as spike-timing dependent plasticity and short and long-term potentiation [1-2]. However, the integration of these devices in high-density neural networks requires low power consumption, with stable bipolar switching at currents of less than 10μA. This has proved to be a key challenge in the development of solid-state synaptic devices as operation in low current regimes has been shown to lead to large resistance fluctuations and reduced device performance [3]. A more detailed understanding of the filamentary resistive switching mechanisms is required for the realisation of functional devices.
The devices employed in this study consisted of insulator-metal (MIM) capacitor structures, comprising: Pt (25 nm)/Ag(30 nm) /HfO2 (20 nm)/Pt 50 nm. The evolution of switching behaviour was examined as a function of compliance current ranging from 1 μA to 5 mA. A transition from volatile to bipolar memory switching was observed for devices formed with compliance currents in the order of 100 μA. These results are shown to be consistent with a model in which low compliance currents lead to thin, unstable filaments, and high compliance currents lead to thicker, more stable filaments, with the transition from volatile to non-volatile behaviour determined by the relative thermal stability of the filament (i.e. the Rayleigh instability criteria).
The applicability of an analytical model of non-volatile switching presented in [4] is also extended to HfO2 based memory devices. This analytical model calculates the evolution of a tunnelling gap between the filament and active electrode during a triangular voltage sweep. A quantitative prediction of device variation between the high and low resistance states is important for the realisation power efficient spike-timing dependent plasticity. These findings provide an important insight into the influence of the electroforming process on switching behaviours and device stabilisation for emerging applications in solid state synapses.


[1] Li, Yi, et al. "Ultrafast synaptic events in a chalcogenide memristor." Scientific reports 3 (2013).
[2] S Yu et al. "An electronic synapse device based on metal oxide resistive switching memory for neuromorphic computation." IEEE Transactions on Electron Devices 58.8, pp 2729-2737 (2011).
[3] B Chen et al. "A novel operation scheme for oxide-based resistive-switching memory devices to achieve controlled switching behaviors." IEEE Electron Device Letters 32.3, pp 282-284 (2011).
[4] S Menzel, and R Waser. "Analytical analysis of the generic SET and RESET characteristics of electrochemical metallization memory cells." Nanoscale 5.22,pp 11003-11010 (2013)