Relaxation Time of Multipore Nanofluidic Memristors for Neuromorphic Applications

Memristors have been positioned at the forefront of the purposes for carrying out neuromorphic computation. Their tunable conductance properties enable the imitation of synaptic behavior. Nanofluidic memristors made of multipore membranes have shown their memristic properties and are candidate devices for liquid neuromorphic systems. Such properties are visible through an inductive hysteresis in the current-voltage sweeps, which is then confirmed by the inductive characteristics in impedance spectroscopy measurements. The dynamic behavior of memristors is largely determined by a voltage-dependent relaxation time. Here, we obtain the kinetic relaxation time of a multipore nanofluidic memristor via its impedance spectra, modeling it and deriving a general equation for this time as a function of the applied voltage, fully correlated with the system's internal parameters. We show that the behavior of this characteristic of memristors is comparable to that of natural neural systems. Hence, we open a way to study the mimic of neuron characteristics by searching for memristors with the same kinetic times.