Two-terminal Resistive-switching Memories based on Liquid AgNO3 as Artificial Synapses

Abstract

The brain presents impressive characteristics, like memory retention and learning capabilities at low energy consumption, making it the most efficient computational entity known. A promising candidate for the task of mimicking the brain is a new generation of devices showing resistive switching, a process that resembles the synaptic behavior, namely the liquid-based resistive-switching memory (LRSM). Here we present a two-terminal structure that works based on a solution of silver nitrate (AgNO3) and a silver (Ag) electrode. Furthermore, since the goal is to mimic the behavior of synapses, the dynamical properties of resistive switching, endurance and data retention were studied. Low operation power was further achieved (<0.5 V, 0.1 mA). Finally, taking advantage of the liquid medium, in which the synaptic behavior occurs, a flexible device was built using microchannels in Polydimethylsiloxane (PDMS) that allowed for the harvesting of the silver nitrate and the insertion of a silver and copper electrode.