A recurrence model capturing interface traps for non-zero bandgap GFETs towards dynamic mimicking of synaptic plasticity

Abstract This paper primarily focusses on developing an analytical model with a non-zero bandgap of boron (B)/nitrogen (N) substitution doped graphene field-effect transistors (GFETs) to mimic the synaptic behaviour. The trap charges at the channel and gate-insulator interface are utilized to induce the hysteresis conduction mechanism, which is further exploited to accomplish synaptic plasticity. The proposed recurrence, that is the time-dependent trap drain current model, accurately captures the physical insights of trap charges using an equivalent metal–insulator–graphene model. An interesting feature of the proposed model is that it is compatible with both the doped (B/N) and the undoped GFETs. The model is also investigated to generate the hysteresis characteristics of the GFET that are further utilized to simulate the synaptic behaviour. Another fact that must be noticed is the existence of complete OFF regions for doped B/N GFETs, unlike the undoped case, which manifest undesirable ambipolar behaviour. The synapse made up of B/N-doped GFETs predicts an optimistic learning and memory mechanism, termed as spike time-dependent plasticity (STDP). The STDP characteristics of B/N doped synaptic GFETs have been enhanced by more than 18 × compared to artificial synapses made of undoped GFETs. Hence, the hysteresis behaviour along with the non-zero bandgap of B/N substitution doped GFETs makes them highly favourable for the dynamic mimicking of synaptic plasticity to be efficiently biologically plausible.