Fully Light‐Controlled Memory and Neuromorphic Computation in Layered Black Phosphorus

AbstractImprinting 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.

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Details

Published: Nov 17, 2020
Vol/Issue: 33(10)
License: View

Authors

T

Taimur Ahmed

Functional Materials and Microsystems Research Group and the Micro Nano Research Facility RMIT University Melbourne VIC 3001 Australia

M

Muhammad Tahir

Department of Physics Colorado State University Fort Collins CO 80523 USA

M

Mei Xian Low

Functional Materials and Microsystems Research Group and the Micro Nano Research Facility RMIT University Melbourne VIC 3001 Australia

Y

Yanyun Ren

Center for Advanced Optoelectronic Functional Materials Research and Key Laboratory for UV Light‐Emitting Materials and Technology Northeast Normal University Ministry of Education Changchun 130024 China

S

Sherif Abdulkader Tawfik

School of Science RMIT University Melbourne VIC 3001 Australia

E

Edwin L. H. Mayes

School of Science RMIT University Melbourne VIC 3001 Australia

S

Sruthi Kuriakose

Functional Materials and Microsystems Research Group and the Micro Nano Research Facility RMIT University Melbourne VIC 3001 Australia

S

Shahid Nawaz

Department of Physics University of California Berkeley CA 94720 USA

M

Michelle J. S. Spencer

School of Science RMIT University Melbourne VIC 3001 Australia

H

Hua Chen

Department of Physics Colorado State University Fort Collins CO 80523 USA; School of Advanced Materials Discovery (SAMD) Colorado State University Fort Collins CO 80523 USA

M

Madhu Bhaskaran

Functional Materials and Microsystems Research Group and the Micro Nano Research Facility RMIT University Melbourne VIC 3001 Australia; ARC Centre of Excellence for Transformative Meta‐Optical Systems RMIT University Melbourne VIC 3001 Australia

S

Sharath Sriram

Functional Materials and Microsystems Research Group and the Micro Nano Research Facility RMIT University Melbourne VIC 3001 Australia; ARC Centre of Excellence for Transformative Meta‐Optical Systems RMIT University Melbourne VIC 3001 Australia

S

Sumeet Walia

Functional Materials and Microsystems Research Group and the Micro Nano Research Facility RMIT University Melbourne VIC 3001 Australia; School of Engineering RMIT University Melbourne VIC 3001 Australia

Funding

Australian National Fabrication Facility

Cite This Article

Taimur Ahmed, Muhammad Tahir, Mei Xian Low, et al. (2020). Fully Light‐Controlled Memory and Neuromorphic Computation in Layered Black Phosphorus. Advanced Materials, 33(10). https://doi.org/10.1002/adma.202004207

Fully Light‐Controlled Memory and Neuromorphic Computation in Layered Black Phosphorus

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