Visible light-driven indium-gallium-zinc-oxide optoelectronic synaptic transistor with defect engineering for neuromorphic computing system and artificial intelligence

Abstract

There has been considerable interest in the development of optoelectronic synaptic transistors with synaptic functions and neural computations. These neuromorphic devices exhibit high-efficiency energy consumption and fast operation by imitating biological neural computation methods. Here, a simple defect engineering method for oxide semiconductors is proposed so that indium-gallium-zinc-oxide (IGZO) optoelectronic synaptic transistors can have synaptic behavior even in the long-wavelength-visible-light region, in which it is difficult to stimulate the conventional oxide semiconductor. Two additional defective layers (the defective interface layer and light absorption layer) are controlled to generate defects that improve the synaptic function and visible-light ab-sorption. The IGZO optoelectronic synaptic transistor with defect engineering shows the peak of photo-induced postsynaptic current (PSC) of 17.04 nA and maximum gain of 24.67 with 25 optical pulses and a 198% paired -pulse facilitation (PPF) index under red-light illumination at a 635-nm wavelength. Furthermore, learning and forgetting were mimicked by optical and electrical signals, as demonstrated in a "Pavlov's dog" experiment. These results demonstrate that IGZO optoelectronic synaptic transistors can be used in various optical applica-tions driven by a wide range of visible light, such as artificial eyes or intelligent display products.