Neuromorphic Reservoir Computing with Memristive Nanofluidic Diodes

Memristive systems show conductance states modulated by past electrical stimuli acting as artificial synapses. Most neuromorphic computing systems are based on solid-state memristive devices that use physical environments and electrical carriers different from the ionic solutions characteristic of biochemical and bioengineering applications. Here, we use membranes with multiple nanopores showing different conductance states in an aqueous electrolyte as a model for reservoir computing (RC). To this end, the different membrane conductances obtained with distinct sequences of voltage pulses in the millisecond range are used for the identification of 10-digit inputs in the case of both correct and corrupted inputs. Using the current rectification of the nanofluidic conical diodes, we explore two additional options: (i) the use of the current and its sign instead of the conductance in the digit identification and (ii) the use of an antiparallel arrangement of two membranes instead of the single-membrane unit.