Engineering and Technology

Mimicking efferent nerves using a graphdiyne-based artificial synapse with multiple ion diffusion dynamics

H. Wei, R. Shi, et al.

Discover the groundbreaking work of Huanhuan Wei, Rongchao Shi, Lin Sun, Haiyang Yu, Jiangdong Gong, Chao Liu, Zhipeng Xu, Yao Ni, Jialiang Xu, and Wentao Xu as they unveil a novel graphdiyne-based artificial synapse (GAS) that not only mimics biological signal transmission but also achieves exceptional energy efficiency. This breakthrough opens up exciting possibilities in soft electronics, neurorobotics, and brain-computer interfaces.

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Abstract

This paper proposes a graphdiyne-based artificial synapse (GAS) that mimics biological signal transmission. The GAS exhibits short-term plasticity, a low impulse response (millivolts), and femtowatt-level energy consumption. It can process signals from multiple pre-neurons, enabling dynamic logic and spatiotemporal rules. The GAS demonstrates thermal and environmental stability and is successfully integrated with artificial muscles to create an artificial efferent nerve, showcasing information integration and output, making it suitable for applications in soft electronics, neurorobotics, and brain-computer interfaces.

Publisher

NATURE COMMUNICATIONS

Published On

Mar 17, 2021

Authors

Huanhuan Wei, Rongchao Shi, Lin Sun, Haiyang Yu, Jiangdong Gong, Chao Liu, Zhipeng Xu, Yao Ni, Jialiang Xu, Wentao Xu

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