A Light‐Stimulus Flexible Synaptic Transistor Based on Ion‐Gel Side‐Gated Graphene for Neuromorphic Computing. Issue 11 (7th September 2022) - Liu, Shilin; He, Xiaoying; Su, Jiale; Cao, Bowen; Rao, Lan; Li, Chong; Yang, Xiaohong; Xin, Xiangjun
Abstract : Optogenetic technology is to express the channel proteins that can be act on light for realizing the activity of neurons activated and inhibited. Here, inspired by optogenetics, a flexible side‐gate artificial synaptic transistor based on ion gel and graphene is demonstrated, where the long‐term remembering or forgetting could be activated by the 450 nm light stimulus. Taking advantage of in‐plane‐field tunable carrier transport in graphene and the high ionic motion of ion gels, various synaptic functions under flatting or bending conditions by electric stimuli are successfully mimicked, including inhibition postsynaptic current, excitatory postsynaptic current, and paired‐pulse facilitation. A light‐induced forgetting or remembering is demonstrated by long‐term synaptic plasticity under 20 s and 10 Hz positive or negative gate pulse stimulus in the dark and 4 min recovery with light illumination. Moreover, the light stimulus promotes the associative learning and remembering function, which is demonstrated by Pavlov's dog experiment with electrical pulses and light stimulus. Such light‐assisted learning and memory function on synaptic plasticity can be attributed to the photogenerated electrons trapping effects in our device. The authors' results provide a feasible strategy for realizing flexible light–electrical‐stimulus synaptic transistors and developing the low‐energy flexible neuromorphic optoelectronic hardware platform. Abstract : A side‐gate fully flexible light–electrical‐stimulus artificial synaptic transistor based on ion gel and graphene is demonstrated for realizing long‐term properties and associative learning. Experimental results indicate that 450 nm light stimulation can either inhibit or enhance the long‐term properties of the proposed device. The authors' results provide a potential way to realize flexible optoelectronic hybrid integrated neuromorphic devices.