Artificial Neural Synapses Based on Microfluidic Memristors Prepared by Capillary Tubes and Ionic Liquid

Neuromorphic simulation, i.e., the use of electronic devices to simulate the neural networks of the human brain, has attracted a lot of interest in the fields of data processing and memory. This work provides a new method for preparing a 1,3-dimethylimidazolium nitrate ([MMIm]­[NO₃]:H₂O) microfluidic memristor that is ultralow cost and technically uncomplicated. Such a fluidic device uses capillaries as memory tubes, which are structurally similar to interconnected neurons by simple solution treatment. When voltage is applied, the transmission of anions and cations in the tube corresponds to the release of neurotransmitters from the presynaptic membrane to the postsynaptic membrane. The change of synaptic weights (plasticity) also can be simulated by the gradual change of conductance of the fluid memristor. The learning process of microfluidic memristors is very obvious, and the habituation and recovery behaviors they exhibit are extremely similar to biological activities, representing its good use for simulating neural synapses.