神经形态工程学
光电探测器
光子学
材料科学
计算机科学
光电流
动态范围
光电子学
油藏计算
紫外线
电子工程
光学
人工智能
物理
计算机视觉
人工神经网络
工程类
循环神经网络
作者
Mohit Kumar,Jisu Kim,Hyungtak Seo
标识
DOI:10.1016/j.mtphys.2023.101176
摘要
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.
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