Broadband Neuromorphic Phototransistors Based on Oxygen Vacancy Modulation in Indium-Gallium-Zinc Oxide Films

Abstract

Optoelectronic neuromorphic devices have gained considerable attention as promising platforms for next-generation sensors and artificial vision systems owing to their ability to mimic biological visual functions. A key challenge, however, lies in achieving broadband photodetection, particularly extending into the near-infrared (NIR) region, without relying on complex heterostructures that limit process simplicity, scalability, and stability. Here, we present a simple and effective approach to realize broadband photosensing and synaptic functionalities by engineering oxygen vacancies in indium–gallium-zinc oxide (IGZO) thin films. By tuning the oxygen vacancy content, IGZO-based synaptic phototransistors achieved broadband detection across the visible (blue, green, red) to NIR (850 nm) range. Particularly, defect engineering markedly enhanced photosensitivity in the NIR region, from 9.17 to 244.8 A W–1. Furthermore, the devices successfully emulated essential synaptic behaviors including short-term memory, long-term memory, and paired-pulse facilitation using NIR light stimulation. An artificial neural network trained with conductance modulation data achieved a classification accuracy of 90.38% on the MNIST handwritten digit data set. These results establish oxygen-vacancy-engineered IGZO phototransistors as a robust and scalable platform for broadband, low-power, and compact neuromorphic vision systems.