Modeling and characterization of stochastic resistive switching in single AgS nanowires.

Chalcogenide resistive switches (RS), such as AgS, change resistance due to the growth of metallic filaments between electrodes along the electric field gradient. Therefore, they are candidates for neuromorphic and volatile memory applications. This work analyzed the RS of individual AgS nanowires (NWs) and extended the basic RS model to reproduce experimental observations. The work models resistivity of the device as a percolation of the conductive filaments. It also addressed continuous fluctuations of the resistivity with a stochastic change in volume fractions of the filaments in the device. As a result, these fluctuations cause unpredictable patterns in current-voltage characteristics and include a spontaneous change in resistance of the device during the linear sweep that conventional memristor models with constant resistivity cannot represent. The parameters of the presented stochastic model of a single AgS NW were fitted to the experimental data and reproduced key features of RS in the physical devices. Moreover, the model suggested a non-core shell structure of the AgS NWs. The outcome of this work is aimed to aid in simulating large self-assembled memristive networks and help to extend existing RS models.