Unraveling the roles of switching and relaxation times in volatile electrochemical memristors to mimic neuromorphic dynamical features

Computing through ensembles of interacting dynamical elements is the next frontier of the diverse field of neuromorphic computing. Spiking neural networks are one of the possible examples. Computation through dynamics and through time requires the development of novel technologies for devices with rich dynamics. Among the various candidates, the most promising ones are volatile electrochemical memristive systems that switch from high to low resistance state by voltage application and self-recover the high resistance state after a tunable relaxation time. Such devices can perform a wide variety of computational primitives. However, a clear comprehensive picture of their possible dynamics and their physical interpretation is still missing. In the present manuscript, prototypical electrochemical silver/silicon oxide/ platinum (Ag/SiOx /Pt) memristive devices are characterized to identify dynamical aspects, like integrative effects and stochastic switching. Integrative effects are evidenced both in high and low resistance states, associated to wake-up phase and cumulative switching. All the dynamical aspects are related to characteristic switching times and relaxation times, and with reference to the electrochemical and physical processes involved in device operation. The various dynamical aspects are linked to short-term memory effects and basic temporal processing functions based on paired-pulse effects that are relevant for neuromorphic applications