Ultra-low power IGZO optoelectronic synaptic transistors for neuromorphic computing

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 wellknown 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 ZrAlOx 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.