  The brain's remarkable and efficient information processing capability is
driving research into brain-inspired (neuromorphic) computing paradigms.
Artificial aqueous ion channels are emerging as an exciting platform for
neuromorphic computing, representing a departure from conventional solid-state
devices by directly mimicking the brain's fluidic ion transport. Supported by a
quantitative theoretical model, we present easy to fabricate tapered
microchannels that embed a conducting network of fluidic nanochannels between a
colloidal structure. Due to transient salt concentration polarisation our
devices are volatile memristors (memory resistors) that are remarkably stable.
The voltage-driven net salt flux and accumulation, that underpin the
concentration polarisation, surprisingly combine into a diffusionlike quadratic
dependence of the memory retention time on the channel length, allowing channel
design for a specific timescale. We implement our device as a synaptic element
for neuromorphic reservoir computing. Individual channels distinguish various
time series, that together represent (handwritten) numbers, for subsequent
in-silico classification with a simple readout function. Our results represent
a significant step towards realising the promise of fluidic ion channels as a
platform to emulate the rich aqueous dynamics of the brain.
