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An artificial synapse based on molecular junctions

Engineering and Technology

An artificial synapse based on molecular junctions

Y. Zhang, L. Liu, et al.

This groundbreaking research showcases a molecular electronic synapse that utilizes a self-assembled monolayer of peptide molecules. The work demonstrates the ability to modulate conductance dynamically, achieving remarkable accuracy in waveform recognition through innovative reservoir computing techniques. Conducted by Yuchun Zhang, Lin Liu, Bin Tu, Bin Cui, Jiahui Guo, Xing Zhao, Jingyu Wang, and Yong Yan, this study pushes the boundaries of molecular electronics.

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Playback language: English
Abstract
This paper demonstrates a molecular electronic synapse using a self-assembled monolayer (SAM) of peptide molecules sandwiched between an active Ag/AgOx electrode and a liquid EGaIn electrode. The conductance of the molecular junction is dynamically modulated by electrical biases, exhibiting both short-term plasticity (paired-pulse facilitation) and long-term plasticity (spike-timing-dependent plasticity). This dynamic response is attributed to chemical gating and coordination effects between Ag+ and peptide groups. The molecular synapse achieves 100% accuracy in waveform recognition using reservoir computing.
Publisher
Nature Communications
Published On
Jan 16, 2023
Authors
Yuchun Zhang, Lin Liu, Bin Tu, Bin Cui, Jiahui Guo, Xing Zhao, Jingyu Wang, Yong Yan
Tags
molecular electronics
self-assembled monolayer
conductance
waveform recognition
plasticity
reservoir computing
peptide molecules
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