Long-Term Synaptic Plasticity Emulated in Modified Graphene Oxide Electrolyte Gated IZO-Based Thin-Film Transistors.

Emulating neural behaviors at the synaptic level is of great significance for building neuromorphic computational systems and realizing artificial intelligence. Here, oxide-based electric double-layer (EDL) thin-film transistors were fabricated using 3-triethoxysilylpropylamine modified graphene oxide (KH550-GO) electrolyte as the gate dielectrics. Resulting from the EDL effect and electrochemical doping between mobile protons and the indium-zinc-oxide channel layer, long-term synaptic plasticity was emulated in our devices. Synaptic functions including long-term memory, synaptic temporal integration, and dynamic filters were successfully reproduced. In particular, spike rate-dependent plasticity (SRDP), one of the basic learning rules of long-term plasticity in the neural network where the synaptic weight changes according to the rate of presynaptic spikes, was emulated in our devices. Our results may facilitate the development of neuromorphic computational systems.