Long-ionic-gated graphene synaptic transistor with enhanced memory, learning function and humidity perception

With the development of neuromorphic electronics, much effort has been devoted to expand perception, memory, and computing integration capabilities. In this paper, an ionic-based graphene synaptic transistor with long-gate structure has been investigated to mimic memory, learning function and perceive humidity. By harnessing the tunable in-plane-field transport of charge carriers in graphene and ions motion in ion-gel, this transistor mimics various synaptic functionalities, including inhibitory postsynaptic current, excitatory postsynaptic current, paired-pulse facilitation, long-term depression, and long-term potentiation. Under short pules stimuli, the long-gate structure provides our transistor with an inertial assisted re-accumulation, generating two excitatory postsynaptic current peaks and enhanced paired-pule facilitation up to ∼265%. Furthermore, the presence of the long-gate structure enables our transistor to exhibit excellent learning and simulate Ebbinghaus' memory. In addition, physical mechanic about its humidity perception has been analyzed and discussed. This study provides a unique platform for designing high-performance carbon-based artificial synapses enabling integrated functions of sensing, storage, and computation for the neuromorphic system.