A memphotoristor for high-efficiency temporal vision processing - Kumar, Mohit; Kim, Jisu; Seo, Hyungtak (Materials Today Physics, 2023)
A photodetector with history-dependent dynamical responses to optical inputs could offer an essential breakthrough in performing temporal vision processing and time-series prediction without the requirement for sophisticated circuitry and undesired high energy consumption. Till now, memristor dynamics and its effective modulation with photo illumination have been utilized to mimic bio-inspired vision processing. Despite significant effort, it is still challenging to process real-time analogue temporal optical information with high accuracy, which requires developing a photonic counterpart of the electric-triggered memristor. Here, we report on the development of a Ga2O3-based proof-of-concept memphotoristor, in which memristive dynamics were stimulated with ultraviolet photon flux rather than conventional voltage. Specifically, a distinct hysteresis loop opening appeared in the cyclic photocurrent-ultraviolet intensity curves, where the magnitude of the loop opening depends on the photon flux. Additionally, light-illumination-induced fading memory, nonlinearity, and temporal dynamics were successfully utilized to demonstrate in-sensor reservoir computation and time-series prediction with an accuracy of 98.86%. Our research will pave the way to developing a wide range of cutting-edge optoelectronics for various applications, such as photosensors, photonic memory storage, and neuromorphic vision sensing of objects in real time.
Keywords: Higher efficiency; In-gap state; In-sensor processing; Memphotoristor; Memristor; Photon flux; Real- time; Sensor processing; Time series prediction; Vision processing; In-gap states; In-sensor processing; Memphotoristor; Photodetector; Time-series prediction