Publication date: 15th April 2025
The emergence of nanofluidic memristors offers a promising platform for mimicking biological synapses, where signal transmission relies on ionic transport in aqueous environments [1,2,3]. In our previous studies, we demonstrated the realization of nanofluidic memristors through various mechanisms, including ion-wall interactions in conical nanochannels using ionic liquids [1], voltage-gated mechanical deformation of polymer films [4], dynamic ion enrichment and depletion in asymmetrically charged channels [5] in 2~23 fJ per spike per channel [6], and electrohydrodynamic modulation via voltage-induced liquid film thickening and thinning [7], which successfully replicated the hibernation-like behavior observed in animals [8].
In this work, I will present an advantage of fluidic memristors that can restore the resistance, thus enhancing their endurance. Resistance drift constrains the accuracy of memristor-based neuromorphic computing due to resistance switching from residual ions in the junction. We demonstrate nanofluidic memristors using voltage-activated ion filling in asymmetrically concentrated electrolyte solutions within Ångström channels, enabling resistance switching. Inspired by the brain’s waste clearance mechanism, we replicated this process to remove residual ions, restoring conductance after 2 × 104 cycles, paving the way for endurance enhancement. Furthermore, our devices exhibit hour-long memory retention and low energy consumption of 60 nJ·cm-2 for the membrane and ~ 0.2 fJ per voltage spike per channel. By optimizing frequency, voltage, concentration gradients, and pH, we emulate short-term synaptic plasticity for adaptive learning. Finally, we demonstrated the first nanofluidic neuromorphic chip with a 4 × 4 memristor array, capable of recognizing mathematical operators using a pre-trained nanofluidic memristor array. Our work demonstrated the potential of fluidic memristor-based neuromorphic computing chips with long retention, low energy consumption, and restorable resistance.
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