Ultra-low power IGZO optoelectronic synaptic transistors for neuromorphic computing

Abstract

Inspired by biological visual systems, optoelectronic synapses with image perception, memory retention, and preprocessing capabilities offer a promising pathway for developing high-performance artificial perceptual vision computing systems. Among these, oxide-based optoelectronic synaptic transistors are well-known for their enduring photoconductive properties and ease of integration, which hold substantial potential in this regard. In this study, we utilized indium gallium zinc oxide as a semiconductor layer and high-k ZrAlO_x as a gate dielectric layer to engineer low-power high-performance synaptic transistors with photonic memory. Crucial biological synaptic functions, including excitatory postsynaptic currents, paired-pulse facilitation, and the transition from short-term to long-term plasticity, were replicated via optical pulse modulation. This simulation was sustained even at an operating voltage as low as 0.0001 V, exhibiting a conspicuous photonic synaptic response with energy consumption as low as 0.0845 fJ per synaptic event. Furthermore, an optoelectronic synaptic device was employed to model “learn-forget-relearn” behavior similar to that exhibited by the human brain, as well as Morse code encoding. Finally, a 3 × 3 device array was constructed to demonstrate its advantages in image recognition and storage. This study provides an effective strategy for developing readily integrable, ultralow-power optoelectronic synapses with substantial potential in the domains of morphological visual systems, biomimetic robotics, and artificial intelligence.