Fully Light‐Controlled Memory and Neuromorphic Computation in Layered Black Phosphorus
Taimur Ahmed, M. Tahir, Mei Xian Low, Yanyun Ren, Sherif Abdulkader Tawfik, Edwin Mayes, Sruthi Kuriakose, Shahid Nawaz, Michelle J. S. Spencer, Hua Chen, Madhu Bhaskaran, Sharath Sriram, Sumeet Walia
Abstract
Imprinting vision as memory is a core attribute of human cognitive learning. Fundamental to artificial intelligence systems are bioinspired neuromorphic vision components for the visible and invisible segments of the electromagnetic spectrum. Realization of a single imaging unit with a combination of in-built memory and signal processing capability is imperative to deploy efficient brain-like vision systems. However, the lack of a platform that can be fully controlled by light without the need to apply alternating polarity electric signals has hampered this technological advance. Here, a neuromorphic imaging element based on a fully light-modulated 2D semiconductor in a simple reconfigurable phototransistor structure is presented. This standalone device exhibits inherent characteristics that enable neuromorphic image pre-processing and recognition. Fundamentally, the unique photoresponse induced by oxidation-related defects in 2D black phosphorus (BP) is exploited to achieve visual memory, wavelength-selective multibit programming, and erasing functions, which allow in-pixel image pre-processing. Furthermore, all-optically driven neuromorphic computation is demonstrated by machine learning to classify numbers and recognize images with an accuracy of over 90%. The devices provide a promising approach toward neurorobotics, human-machine interaction technologies, and scalable bionic systems with visual data storage/buffering and processing.