Multifunctional human visual pathway-replicated hardware based on 2D materials

Zhuiri Peng, Lei Tong, Wenhao Shi, Langlang Xu, Xinyu Huang, Zheng Li, Xiangxiang Yu, Xiaohan Meng, Xiao He, Shengjie Lv, Gaochen Yang, Hao Hao, Tian Jiang (), Xiangshui Miao () and Lei Ye ()
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Zhuiri Peng: Huazhong University of Science and Technology
Lei Tong: The Chinese University of Hong Kong
Wenhao Shi: Huazhong University of Science and Technology
Langlang Xu: Huazhong University of Science and Technology
Xinyu Huang: Huazhong University of Science and Technology
Zheng Li: Huazhong University of Science and Technology
Xiangxiang Yu: Huazhong University of Science and Technology
Xiaohan Meng: Huazhong University of Science and Technology
Xiao He: Huazhong University of Science and Technology
Shengjie Lv: Huazhong University of Science and Technology
Gaochen Yang: Huazhong University of Science and Technology
Hao Hao: National University of Defense Technology
Tian Jiang: National University of Defense Technology
Xiangshui Miao: Huazhong University of Science and Technology
Lei Ye: Huazhong University of Science and Technology

Nature Communications, 2024, vol. 15, issue 1, 1-9

Abstract: Abstract Artificial visual system empowered by 2D materials-based hardware simulates the functionalities of the human visual system, leading the forefront of artificial intelligence vision. However, retina-mimicked hardware that has not yet fully emulated the neural circuits of visual pathways is restricted from realizing more complex and special functions. In this work, we proposed a human visual pathway-replicated hardware that consists of crossbar arrays with split floating gate 2D tungsten diselenide (WSe2) unit devices that simulate the retina and visual cortex, and related connective peripheral circuits that replicate connectomics between the retina and visual cortex. This hardware experimentally displays advanced multi-functions of red–green color-blindness processing, low-power shape recognition, and self-driven motion tracking, promoting the development of machine vision, driverless technology, brain–computer interfaces, and intelligent robotics.

Date: 2024
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DOI: 10.1038/s41467-024-52982-3

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