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

Huanhuan Wei, Rongchao Shi, Lin Sun, Haiyang Yu, Jiangdong Gong, Chao Liu, Zhipeng Xu, Yao Ni, Jialiang Xu () and Wentao Xu ()
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Huanhuan Wei: Nankai University
Rongchao Shi: Nankai University
Lin Sun: Nankai University
Haiyang Yu: Nankai University
Jiangdong Gong: Nankai University
Chao Liu: Nankai University
Zhipeng Xu: Nankai University
Yao Ni: Nankai University
Jialiang Xu: Nankai University
Wentao Xu: Nankai University

Nature Communications, 2021, vol. 12, issue 1, 1-10

Abstract: Abstract A graphdiyne-based artificial synapse (GAS), exhibiting intrinsic short-term plasticity, has been proposed to mimic biological signal transmission behavior. The impulse response of the GAS has been reduced to several millivolts with competitive femtowatt-level consumption, exceeding the biological level by orders of magnitude. Most importantly, the GAS is capable of parallelly processing signals transmitted from multiple pre-neurons and therefore realizing dynamic logic and spatiotemporal rules. It is also found that the GAS is thermally stable (at 353 K) and environmentally stable (in a relative humidity up to 35%). Our artificial efferent nerve, connecting the GAS with artificial muscles, has been demonstrated to complete the information integration of pre-neurons and the information output of motor neurons, which is advantageous for coalescing multiple sensory feedbacks and reacting to events. Our synaptic element has potential applications in bioinspired peripheral nervous systems of soft electronics, neurorobotics, and biohybrid systems of brain–computer interfaces.

Date: 2021
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DOI: 10.1038/s41467-021-21319-9

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