Threshold-Variation-Tolerant Coupling-Gate α-IGZO Synaptic Transistor for More Reliably Controllable Hardware Neuromorphic System

Abstract

Hardware-oriented neuromorphic computing is gaining great deal of interest for highly parallel data processing and superb energy efficiency, as the candidate for replacement of conventional von Neumann computing. In this work, a novel synaptic transistor constructing the neuromorphic system is proposed, fabricated, and characterized. Amorphous indium-gallium-zinc-oxide ( $\alpha $ -IGZO) and Al2O3 are introduced as the channel and gate dielectric materials, respectively. Along with the high functionality and low-temperature processing viability, geometric peculiarity featuring extended gate structure improves the performances of the proposed transistor as synaptic component in the neuromorphic system. The insight into the substantial effect of optimal device structure design on energy efficiency is highlighted.

Keywords

• Hardware-oriented neuromorphic computing
• parallel data processing
• energy efficiency
• synaptic transistor
• amorphous indium-gallium-zinc-oxide
• extended gate